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Simple Summary: Pelvic radiotherapy is used to treat a range of cancers. Radiotherapy can damage surrounding, non-cancerous tissue and organs, causing long-term problems, including bowel symptoms such as bleeding, pain, and incontinence. The provision of support and treatment for those affected as well as shared decision making regarding treatment should be informed by a solid understanding of the prevalence, nature, and severity of symptoms. We conducted a systematic review of population-based studies presenting patient-reported bowel symptoms to synthesize evidence on symptom prevalence and severity following pelvic radiotherapy. Multiple different bowel symptoms have been reported, and prevalence varies from 1% (bleeding) to 59% (anal bleeding for >12 months). We found substantial variation in the reported methods and few data pertaining to cancers other than prostate. Our review supports the view that bowel symptoms are a significant problem following pelvic radiotherapy and highlights limitations of the evidence base that should be addressed in future research. Pelvic radiotherapy can damage surrounding tissue and organs, causing chronic conditions including bowel symptoms. We systematically identified quantitative, population-based studies of patient-reported bowel symptoms following pelvic radiotherapy to synthesize evidence of symptom type, prevalence, and severity. Medline, CINAHL, EMBASE, and PsychINFO were searched from inception to September 2022. Following independent screening of titles, abstracts, and full-texts, population and study characteristics and symptom findings were extracted, and narrative synthesis was conducted. In total, 45 papers (prostate, n = 39; gynecological, n = 6) reporting 19 datasets were included. Studies were methodologically heterogeneous. Most frequently assessed was bowel function ('score', 26 papers, 'bother', 19 papers). Also assessed was urgency, diarrhea, bleeding, incontinence, abdominal pain, painful hemorrhoids, rectal wetness, constipation, mucous discharge, frequency, and gas. Prevalence ranged from 1% (bleeding) to 59% (anal bleeding for >12 months at any time since start of treatment). In total, 10 papers compared radiotherapy with non-cancer comparators and 24 with non-radiotherapy cancer patient groups. Symptom prevalence/severity was greater/worse in radiotherapy groups and symptoms more common/worse post-radiotherapy than pre-diagnosis/treatment. Symptom prevalence varied between studies and symptoms. This review confirms that many people experience chronic bowel symptoms following pelvic radiotherapy. Greater methodological consistency, and investigation of less-well-studied survivor populations, could better inform the provision of services and support. [ABSTRACT FROM AUTHOR]

Higher education institutions are uniquely placed to introduce emotional coping skills to promote resilience in pre-registration nurses in order to reduce anxiety and increase confidence before they enter clinical placement for the first time. In this qualitative study, we will explore the use of a 360-degree video in developing skills for coping. The participants will be mental health nursing students. We will develop a 360-degree video in collaboration with a mental health service user. All participants will watch the video. A sub-group will receive a supportive clinical supervision discussion within a cognitive reappraisal/solution-focused/VERA framework. We will record the experiences of the participant to explore: (1) how students felt about the use of 360-degree video, as an education tool to build skills of resilience; (2) whether the students involved felt more confident and less anxious about the situation in the video as a result of participating in the cognitive reappraisal/solution-focused/VERA supervision discussion. [ABSTRACT FROM AUTHOR]

The 11th Revision of the International Statistical Classification of Diseases, Injuries, and Causes of Death (ICD-11) will replace its predecessor as international standard for cause-of death-statistics. The digitization of healthcare is a main motivation for its introduction. In parallel, the replacement of the paper-based death certificate with an electronic format is under evaluation. At the moment, the death certificate is used in paper-based format with ICD-10 for coding in Germany. To be prepared for the switch to ICD-11, the compatibility between ICD-11 and the electronic certificate should be assured. Objectives were to check the appropriateness of diagnosis-related information found on death certificates for an ICD-11 coding and to describe enhancements to the certificate's structure needed to fully utilize the strengths of ICD-11. As part of an exploratory test of a respective application, information from 453 electronic death certificates were provided by one local health authority. From a sample of 200 certificates, 433 diagnosis texts were coded into the German version of ICD-11. The appropriateness of the results as well as the further requirements of ICD-11, particularly with regard to post-coordination, were checked. For 430 diagnosis texts, 649 ICD-11 codes were used. Three hundred and sixty two diagnosis texts were rated as appropriately represented through the coding result. Almost all certificates contained diagnosis texts that lacked details required by ICD-11 for a precise coding. The distribution of diseases was very similar between ICD-10 and ICD-11 coding. A few gaps in ICD-11 were identified. Information requested by ICD-11 for a mandatory post-coordination were almost entirely absent from the death certificates. The structure and content of the death certificate are currently not well prepared for an ICD-11 coding. Necessary information was frequently missing. The line-oriented structure of death certificates has to be supplemented with a more flexible approach. Then, the semantic knowledge base of ICD-11 should better guide the content related input fields of a future electronic death certificate. [ABSTRACT FROM AUTHOR]

This paper focuses on the uncertainty and resentment that many persons with disabilities feel concerning their disability services in the welfare state of Finland. This paper elaborates on the theme through the lived citizenship of persons with disabilities using the key theory of disability tax as an analytical tool. The empirical data were collected through an online survey (n = 541) and six group interviews (n = 41) of persons with disabilities in 2023. The disability tax experiences are elaborated through four aspects: (1) rejected applications, (2) uncertain realisation, (3) laborious complaint mechanisms, and (4) the psycho–emotional effect. The findings of this study establish collective experiences of multi-layered disability tax throughout the disability services process. It concludes that disability services, which were originally planned to specifically ensure equal opportunities to participate in society for persons with disabilities, are increasingly becoming the very sources of burden as austerity has silently grown deeper over recent years and has become the clear policy of the current government. [ABSTRACT FROM AUTHOR]

Digital health technologies (DHTs) at the intersection of health, medical informatics, and business aim to enhance patient care through personalised digital approaches. Ensuring the efficacy and reliability of these innovations demands rigorous clinical validation. A PubMed literature review (January 2006 to July 2023) identified 1250 papers, highlighting growing academic interest. A focused narrative review (January 2018 to July 2023) delved into challenges, highlighting issues such as diverse regulatory landscapes, adoption issues in complex healthcare systems, and a plethora of evaluation frameworks lacking pragmatic guidance. Existing frameworks often omit crucial criteria, neglect empirical evidence, and clinical effectiveness is rarely included as a criterion for DHT quality. The paper underscores the urgency of addressing challenges in accreditation, adoption, business models, and integration to safeguard the quality, efficacy, and safety of DHTs. A pivotal illustration of collaborative efforts to address these challenges is exemplified by the Digital Health Validation Center, dedicated to generating clinical evidence of innovative healthcare technologies and facilitating seamless technology transfer. In conclusion, it is necessary to harmonise evaluation approaches and frameworks, improve regulatory clarity, and commit to collaboration to integrate rigorous clinical validation and empirical evidence throughout the DHT life cycle. [ABSTRACT FROM AUTHOR]

Studies have indicated that higher numbers of nurses regarding staffing ensure patient safety and a better practice environment. Using citation analysis, this study visualizes the landscape of nurse staffing research over the last two decades to show the overall publication trends, major contributors, and main research topics. We extracted bibliometric information from PubMed from January 2000 to September 2022. After clustering the network, we analyzed each cluster's characteristics by keyword. A total of 2167 papers were considered for analysis, and 14 clusters were created. The analysis showed that the number of papers published per year has been increasing. Researchers from the US, the UK, Canada, Australia, and Belgium have led this field. As the main clusters in nurse staffing research during the past two decades, the following five research settings were identified: nurse outcome and patient outcome research in acute care hospitals, nurse staffing mandate evaluation research, nursing home research, and school nurse research. The first three clusters accounted for more than 80% of the total number of published papers, and this ratio has not changed in the past 20 years. To further develop nurse staffing research globally, evidence from other geographic areas, such as African and Asian countries, and from long-term care or community settings is necessary. [ABSTRACT FROM AUTHOR]

Background: This study employed bibliometric analysis to ascertain the research focus areas among a group of Mexican physicians affiliated with the Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado (ISSSTE). ISSSTE, a healthcare institution catering to a diverse range of diseases, offers a distinctive perspective on the investigated specialties within the realm of health. The primary objective was to identify knowledge gaps in medical care disciplines through a comprehensive examination of scholarly publications. Methods: We retrieved Scopus papers affiliated with "ISSSTE" and saved them as.CSV files. Subsequently, we employed VOSviewer, biblioshiny, and bibliometrix for bibliometric analysis. This enabled us to identify prominent institutions, prolific authors, highly cited researchers, and their respective affiliations. Results: Our analysis identified 2063 publications; the specialty internal medicine accounted for the greatest proportion with 831 publications. Original papers accounted for 82% of the total, with 52% of them being written in Spanish. The majority of scientific output, 92%, originated from Mexico City. The annual production has steadily increased since 2010, peaking in 2021 with over 200 publications. However, papers on prevalent conditions, such as metabolic syndrome, received limited citations, and the L0 index (percentage of uncited items) for all papers is close to 60%. Scopus mislabeled one affiliation, and some cases show a low paper-to-author ratio of 0.5 Discussion: Additional concerns, such as honorary authorship due to excessive authors per paper, and the underlying causes of low citation rates in Mexican publications, warrant further examination. Moreover, our research emphasizes the urgency of bolstering research and development funding, which was consistently below 0.5% of GDP for the past four decades, falling short of legal mandates and international benchmarks. We endorse the establishment of robust research collectives in Latin America to address these challenges, foster regional scientific output, and transition from knowledge consumers to knowledge producers, thereby reducing dependence on foreign technology. [ABSTRACT FROM AUTHOR]

Reasonably allocating medical resources can effsectively optimize the utilization efficiency of such resources. This paper took Taiyuan City as an example and established a model to evaluate the rationality of medical resource spatial allocation, incorporating two key dimensions: the spatial layout and the supply and demand of medical resources. In terms of the spatial layout, three indexes were included: Firstly, the service coverage rates of different levels of medical institutions, based on residents' medical orientations, were calculated using network analysis methods. Secondly, the Huff-2SFCA method was improved to calculate the accessibility of medical resources for four different modes of transportation. Then, the Health Resource Agglomeration Degree (HRAD) and Population Agglomeration Degree (PAD) were used to quantify the equity of medical resources. In terms of the supply and demand of medical resources, one index was included: the supply–demand ratio of medical resources during sudden public health events, which was calculated using the number of beds per thousand people as an indicator. These four indexes were weighted using the entropy weight method to obtain the rationality grade of medical resource spatial allocation in Taiyuan City. The study found that the rationality evaluation level of medical resource allocation in the central urban area of Taiyuan City followed a "concentrically decreasing" pattern. The rating ranged from "very reasonable" to "less reasonable", with the area of each level expanding gradually. The areas rated within the top two categories only accounted for 19.92% of the study area, while the area rated as "less reasonable" occupied 38.73% of the total area. These results indicate that the model accounted for residents' travel for various medical orientations and the availability of resources during public health emergencies. It considered both the spatial layout and supply and demand of medical resources, offering recommendations for the precise allocation of urban medical resources. [ABSTRACT FROM AUTHOR]

The proportion of aged populations is increasing worldwide. Exercise has a palliating effect on some adverse implications of aging. Multicomponent training (MCT) is a recommended form of exercise for the aged population. The aims of this research were to (1) study the number of publications regarding MCT in the aged population following an exponential growth rate; (2) identify the journals, authors, and countries that stand out the most in this area; and (3) describe the most common themes and used keywords in this field. The analysis was performed through the traditional laws of bibliometrics, including, Price's, Lotka's, Bradford's, and Zipf's law. All documents published in journals indexed in the Web of Science (WoS) Core Collection from 2001 to November 2023 that met the inclusion criteria were included. The 485 documents included in this review revealed that the number of annual publications experienced an exponential growth phase, 15 journals with six or more publications formed the core journals on this topic, and the author Mikel Izquierdo and his collaborative network topped the lists of prominent and prolific co-authors. Spain was the leading country in number of publications. Various thematic lines and keywords regarding strength, sarcopenia, quality of life, falls, balance, dual-task exercise, and cognitive and physical functioning were identified. In conclusion, this work confirmed that research on this topic is going through an exponential growth phase and provided detailed information about the journals, authors, and countries involved in the subject, as well as the keywords most frequently used in the subject matter. [ABSTRACT FROM AUTHOR]

Simple Summary: Myeloid-derived suppressor cells (MDSCs) are immature cells that expand in the circulation of patients with cancer, sepsis or chronic inflammation, modulate the immune response against cancer (favoring tumor onset and progression) and promote neoangiogenesis. These premises suggest that MDSCs could be involved in the pathogenesis of primary myelofibrosis (PMF) (a myeloproliferative neoplasm characterized by chronic inflammation and extensive neoangiogenesis in bone marrow and spleen). In this paper, we found that (1) MDSCs are increased both in the circulation and in the spleen of PMF patients and strongly correlate with disease progression; and (2) reduced CXCR4 expression on MDSCs along with increased plasmatic SDF-1α can be involved in their mobilization. These findings suggest that circulating MDSCs can be considered a parameter of disease severity and set MDSCs as potential new targets for cancer therapy. Primary myelofibrosis (PMF) is a myeloproliferative neoplasm characterized by a chronic inflammatory state that plays a relevant role in the disease pathogenesis (as proven by high levels of inflammatory cytokines with prognostic significance and by a persistent oxidative stress) and by extensive neoangiogenesis in bone marrow (BM) and spleen. Myeloid-derived suppressor cells (MDSCs) are immature cells that expand in patients with cancer, sepsis or chronic inflammation, favoring tumor onset and progression mainly through the decrease in immune surveillance and the promotion of neoangiogenesis. In this paper, we evaluated the presence of circulating MDSCs in PMF patients, the plasmatic factors involved in their mobilization/expansion and the correlations with laboratory, genetic and clinical parameters. The data indicated that MDSCs could have a relevant role in PMF as a new pathogenic mechanism contributing to explaining the phenotypic diversity observed during the clinical course of the disease, or a potential new target for personalized treatment. [ABSTRACT FROM AUTHOR]

Objective: This scoping review aims to map the available literature and provide an overview of the published articles discussing the impact of electronic prescribing on medication errors and pharmacy workflow. Methods: The literature search was conducted using PubMed®, Web of Science®, and the Cochrane Database of Systematic Reviews®, as well as grey literature reports, using the search terms and related components of "pharmacists", "electronic prescribing", "medication errors", and "efficiency". The search included all articles that were published from January 2011 to September 2023. Twenty-two relevant articles were identified and fully reviewed, ten of which were included in this review. Results: Electronic prescribing (e-prescribing) provides a solution for some of the challenges that are associated with handwritten and paper prescriptions. However, the implementation of e-prescribing systems has been recognized as a source of new unforeseen medication errors in all the reviewed articles. Productivity in community pharmacies has been affected with receiving electronic prescriptions (e-prescriptions) and having to deal with the issues that arise from them. The pharmacists' interventions were not eliminated with e-prescriptions compared to other prescription formats. The most frequently reported reason for intervention was related to incomplete instructions in the field of directions of use. Other common challenges with e-prescriptions were related to missing information, quantity, inappropriate dose, dosage form, and drug. Discussion: This review demonstrates the scarcity of research about the impact of electronic prescribing on medication error and efficiency in community pharmacies. In the literature, most of the studies had mainly focused on hospital pharmacies. The literature search demonstrated that there are still some barriers to overcome with e-prescribing systems and that medication errors were not fully eliminated with e-prescriptions. New errors have been identified with e-prescriptions, all of which caused delays in processing, which affected the productivity of the pharmacy staff, and could have negatively impacted patients' safety if not properly resolved. Conclusion: e-Prescribing solved some of the challenges associated with illegibility of handwritten prescriptions. However, more time is required to allow e-prescribing systems to mature. Further training for prescribers and pharmacists is also recommended before and after the implementation. [ABSTRACT FROM AUTHOR]

Green finance is significant since it is the first organized effort by the financial industry to link financial performance with a positive environmental impact. Green finance products are being developed appropriately to achieve sustainability. The present study employs a fundamental bibliometric methodology to assess the current state and progress of academic research on green finance. 1748 papers are taken for this study. Data are extracted from a scholarly database i.e., SCOPUS and for network analysis, VOSviewer software is used. The present paper is focused on six research questions. Information is gathered to examine the above research questions and network maps are applied. We examined year-wise document publications, types of documents, subject areas, most influential articles, different journal sources, co-authorship of countries, and co-occurrence of keywords of green finance. We categorized keywords into clusters and discovered new trends in green finance. The paper also highlighted the recent issues and challenges. The study has also certain limitations and it is concluded by providing implications and suggestions for future studies. At last, this paper will give more insights to researchers, academicians, and others to discover the research gaps in this field of green finance. [ABSTRACT FROM AUTHOR]

Research suggests parental ability to recognise when their child has overweight is limited. It is hypothesised that recognition of child overweight/obesity is fundamental to its prevention, acting as a potential barrier to parental action to improve their child's health-related behaviours and/or help seeking. The purpose of this study was to investigate the efficacy of an intervention (MapMe) to improve parental ability to correctly categorise their child as having overweight one-month post-intervention, and reduce child body mass index (BMI) z-score 12 months post-intervention. MapMe consists of body image scales of known child BMI and information on the consequences of childhood overweight, associated health-related behaviours and sources of support. We conducted a three-arm (paper-based MapMe, web-based MapMe and control) randomised control trial in fifteen English local authority areas with parents/guardians of 4–5- and 10–11-year-old children. Parental categorisation of child weight status was assessed using the question 'How would you describe your child's weight at the moment?' Response options were: underweight, healthy weight, overweight, and very overweight. Child weight status and BMI z-scores were calculated using objectively measured height and weight data and UK90 clinical thresholds. There was no difference in the percentage of parents correctly categorising their child as having overweight/very overweight (n = 264: 41% control, 48% web-based, and 43% paper-based, p = 0.646). BMI z-scores were significantly reduced for the intervention group at 12 months post-intervention compared to controls (n = 338, mean difference in BMI z-score change −0.11 (95% CI −0.202 to −0.020, p = 0.017). MapMe was associated with a decrease in BMI z-score 12 months post-intervention, although there was no direct evidence of improved parental ability to correctly categorise child overweight status. Further work is needed to replicate these findings in a larger sample of children, investigate mechanisms of action, and determine the use of MapMe as a public health initiative. [ABSTRACT FROM AUTHOR]

Community care encompasses inherent risks for both clients and healthcare providers. Maintaining a safe environment for the delivery of care services ensures that any risk of unintentional or intentional personal harm is minimised. The aim of this scoping review is to (a) provide an overview of existing knowledge by summarising the current literature and (b) identify gaps pertaining to understanding and managing environmental risk in community care settings. Guided by the Population/Concept/Context approach and PRISMA guidelines, this paper used two questions to answer how a score-based tool for assessing client suitability in community care is developed and how an environmental screening tool assists with reducing risk to community care workers. Literature searches of CINAHL, PubMed (Medline), Web of Science and PsychINFO databases were conducted between September 2023 and November 2023. We included full text articles published from 2018 to 2023. The following four broad areas were identified as key components in the structure of an environmental screening tool: environmental factors, health factors, socioeconomic factors and cultural factors. The results of this review provide valuable information which can be utilised by care organisations to develop and/or refine tools to ensure the safety and wellbeing of workers within the community care sector. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper presents a novel approach to produce virtual contrast enhanced (VCE) images for nasopharyngeal cancer (NPC) without the use of contrast agents, which carry certain risks. This model uses pixelwise gradient term to capture the shape and a GAN terms to capture the texture of the real contrast enhanced T1C images With similar accuracy to existing models, our method shows an advantage in reproducing texture closer to the realistic contrast-enhanced images. This results are tested by various measures, including mean absolute error (MAE), mean square error (MSE) and structural similarity index (SSIM) for similarity accuracy; total mean square variation per mean intensity (TMSVPMI), the total absolute vari-ation per mean intensity (TAVPMI), Tenengrad function per mean intensity (TFPMI) and variance function per mean intensity (VFPMI) Various variations of the model, including fine-tuning of the hyperparameters, normalization methods on the images and using single modality, have also been investigated to test the optimal performance. Background: The development of advanced computational models for medical imaging is crucial for improving diagnostic accuracy in healthcare. This paper introduces a novel approach for virtual contrast enhancement (VCE) in magnetic resonance imaging (MRI), particularly focusing on nasopharyngeal cancer (NPC). Methods: The proposed model, Pixelwise Gradient Model with GAN for Virtual Contrast Enhancement (PGMGVCE), makes use of pixelwise gradient methods with Generative Adversarial Networks (GANs) to enhance T1-weighted (T1-w) and T2-weighted (T2-w) MRI images. This approach combines the benefits of both modalities to simulate the effects of gadolinium-based contrast agents, thereby reducing associated risks. Various modifications of PGMGVCE, including changing hyperparameters, using normalization methods (z-score, Sigmoid and Tanh) and training the model with T1-w or T2-w images only, were tested to optimize the model's performance. Results: PGMGVCE demonstrated a similar accuracy to the existing model in terms of mean absolute error (MAE) (8.56 ± 0.45 for Li's model; 8.72 ± 0.48 for PGMGVCE), mean square error (MSE) (12.43 ± 0.67 for Li's model; 12.81 ± 0.73 for PGMGVCE) and structural similarity index (SSIM) (0.71 ± 0.08 for Li's model; 0.73 ± 0.12 for PGMGVCE). However, it showed improvements in texture representation, as indicated by total mean square variation per mean intensity (TMSVPMI) (0.124 ± 0.022 for ground truth; 0.079 ± 0.024 for Li's model; 0.120 ± 0.027 for PGMGVCE), total absolute variation per mean intensity (TAVPMI) (0.159 ± 0.031 for ground truth; 0.100 ± 0.032 for Li's model; 0.153 ± 0.029 for PGMGVCE), Tenengrad function per mean intensity (TFPMI) (1.222 ± 0.241 for ground truth; 0.981 ± 0.213 for Li's model; 1.194 ± 0.223 for PGMGVCE) and variance function per mean intensity (VFPMI) (0.0811 ± 0.005 for ground truth; 0.0667   ± 0.006 for Li's model; 0.0761   ± 0.006 for PGMGVCE). Conclusions: PGMGVCE presents an innovative and safe approach to VCE in MRI, demonstrating the power of deep learning in enhancing medical imaging. This model paves the way for more accurate and risk-free diagnostic tools in medical imaging. [ABSTRACT FROM AUTHOR]

Data science has become increasingly popular due to emerging technologies, including generative AI, big data, deep learning, etc. It can provide insights from data that are hard to determine from a human perspective. Data science in finance helps to provide more personal and safer experiences for customers and develop cutting-edge solutions for a company. This paper surveys the challenges and opportunities in applying data science to finance. It provides a state-of-the-art review of financial technologies, algorithmic trading, and fraud detection. Also, the paper identifies two research topics. One is how to use generative AI in algorithmic trading. The other is how to apply it to fraud detection. Last but not least, the paper discusses the challenges posed by generative AI, such as the ethical considerations, potential biases, and data security. [ABSTRACT FROM AUTHOR]

Simple Summary: Adaptive proton therapy (APT) is an evolving approach to proton beam scanning treatment planning. We performed dosimetric study on two groups of head and neck (H&N) patients to evaluate the influence of plan adaptation on planning target volume (PTV) and organs at risk (OARs) doses, resulting from the changes in patient anatomy observed in control computed tomography (CT). The adapted treatment plans, which incorporated the changes observed in the control CT images, statistically improved mostly PTV coverage compared to initial plan. Study shows that applying adaptive procedures in clinical workflow may increased efficiency by controlling the proper irradiation of the treated area for H&N cancer patients. Applying a proton beam in radiotherapy enables precise irradiation of the tumor volume, but only for continuous assessment of changes in patient anatomy. Proton beam range uncertainties in the treatment process may originate not only from physical beam properties but also from patient-specific factors such as tumor shrinkage, edema formation and sinus filling, which are not incorporated in tumor volume safety margins. In this paper, we evaluated variations in dose distribution in proton therapy resulting from the differences observed in the control tomographic images and the dosimetric influence of applied adaptive treatment. The data from weekly computed tomography (CT) control scans of 21 patients, which serve as the basis for adaptive radiotherapy, were used for this study. Dosimetric analysis of adaptive proton therapy (APT) was performed on patients with head and neck (H&N) area tumors who were divided into two groups: patients with tumors in the sinus/nasal area and patients with tumors in the brain area. For this analysis, the reference treatment plans were forward-calculated using weekly control CT scans. A comparative evaluation of organ at risk (OAR) dose-volume histogram (DVH) parameters, as well as conformity and homogeneity indices, was conducted between the initial and recalculated dose distributions to assess the necessity of the adaptation process in terms of dosimetric parameters. Changes in PTV volume after replanning were observed in seventeen patient cases, showing a discrepancy of over 1 cm 3 in ten cases. In these cases, tumor progression occurred in 30% of patients, while regression was observed in 70%. The statistical analysis indicates that the use of the adaptive planning procedure results in a statistically significant improvement in dose distribution, particularly in the PTV area. The findings led to the conclusion that the adaptive procedure provides significant advantages in terms of dose distribution within the treated volume. However, when considering the entire patient group, APT did not result in a statistically significant dose reduction in OARs (α = 0.05). [ABSTRACT FROM AUTHOR]

Simple Summary: Colorectal cancer (CRC) is one of the most common causes of death worldwide. Today, this disease does not have an effective treatment, leading to the exploration of novel pharmacological molecules. In this paper, we design and synthesize with a new synthetic route the lipophilic cation derived from gallic acid (TPP+C10) and gentisic acid (GA-TPP+C10), both able to reach mitochondria and uncouple the electron transport chain. Our results show that combining 5-fluorouracil with GA-TPP+C10 has a synergistic cytotoxic effect on CRC cells. Both compounds show antimigratory effects, decreasing signaling pathways and biomarkers. Our results show that mitochondrial agents could be an alternative to standard CRC drugs against this disease. Colorectal cancer (CRC) is the third leading cause of cancer deaths in the world. Standard drugs currently used for the treatment of advanced CRC—such as 5-fluorouracil (5FU)—remain unsatisfactory in their results due to their high toxicity, high resistance, and adverse effects. In recent years, mitochondria have become an attractive target for cancer therapy due to higher transmembrane mitochondrial potential. We synthesized gallic acid derivatives linked to a ten-carbon aliphatic chain associated with triphenylphosphonium (TPP+C10), a lipophilic cationic molecule that induces the uncoupling of the electron transport chain (ETC). Other derivatives, such as gentisic acid (GA-TPP+C10), have the same effects on colorectal cancer cells. Although part of our group had previously reported preparing these structures by a convergent synthesis route, including their application via flow chemistry, there was no precedent for a new methodology for preparing these compounds. In this scenario, this study aims to develop a new linear synthesis strategy involving an essential step of Steglich esterification under mild conditions (open flask) and a high degree of reproducibility. Moreover, the study seeks to associate GA-TPP+C10 with 5FU to evaluate synergistic antineoplastic effects. In addition, we assess the antimigratory effect of GA-TPP+C10 and TPP+C10 using human and mouse metastatic CRC cell lines. The results show a new and efficient synthesis route of these compounds, having synergistic effects in combination with 5FU, increasing apoptosis and enhancing cytotoxic properties. Additionally, the results show a robust antimigratory effect of GATPP+C10 and TPP+C10, reducing the activation pathways linked to tumor progression and reducing the expression of VEGF and MMP-2 and MMP-9, common biomarkers of advanced CRC. Moreover, TPP+C10 and GA-TPP+C10 increase the activity of metabolic signaling pathways through AMPK activation. The data allow us to conclude that these compounds can be used for in vivo evaluations and are a promising alternative associated with conventional therapies for advanced colorectal cancer. Additionally, the reported intermediates of the new synthesis route could give rise to analog compounds with improved therapeutic activity. [ABSTRACT FROM AUTHOR]

Simple Summary: Nonlinear curve fitting of the pharmacokinetic model to DCE-MRI concentration curves is highly time-consuming. The estimation of highly non-linear dispersion-related parameter in MR dispersion imaging (MRDI) makes the process even more tedious. The fast MRDI (fMRDI) model is proposed to simplify and accelerate the MRDI model by representing the dispersion-applied arterial input function (AIF) as the weighted-sum of a fast and a slow population-based AIFs. A deep learning-based two-stage inference method is proposed to accelerate quantitative MRDI. The deep learning model makes a initial estimation of the parameters directly from the concentration curves and the parameters is then refined by a number of iterative optimization. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) measures microvascular perfusion by capturing the temporal changes of an MRI contrast agent in a target tissue, and it provides valuable information for the diagnosis and prognosis of a wide range of tumors. Quantitative DCE-MRI analysis commonly relies on the nonlinear least square (NLLS) fitting of a pharmacokinetic (PK) model to concentration curves. However, the voxel-wise application of such nonlinear curve fitting is highly time-consuming. The arterial input function (AIF) needs to be utilized in quantitative DCE-MRI analysis. and in practice, a population-based arterial AIF is often used in PK modeling. The contribution of intravascular dispersion to the measured signal enhancement is assumed to be negligible. The MR dispersion imaging (MRDI) model was recently proposed to account for intravascular dispersion, enabling more accurate PK modeling. However, the complexity of the MRDI hinders its practical usability and makes quantitative PK modeling even more time-consuming. In this paper, we propose fast MR dispersion imaging (fMRDI) to effectively represent the intravascular dispersion and highly accelerated PK parameter estimation. We also propose a deep learning-based, two-stage framework to accelerate PK parameter estimation. We used a deep neural network (NN) to estimate PK parameters directly from enhancement curves. The estimation from NN was further refined using several steps of NLLS, which is significantly faster than performing NLLS from random initializations. A data synthesis module is proposed to generate synthetic training data for the NN. Two data-processing modules were introduced to improve the model's stability against noise and variations. Experiments on our in-house clinical prostate MRI dataset demonstrated that our method significantly reduces the processing time, produces a better distinction between normal and clinically significant prostate cancer (csPCa) lesions, and is more robust against noise than conventional DCE-MRI analysis methods. [ABSTRACT FROM AUTHOR]

Simple Summary: Oral cancer affects the mouth and throat areas. It is a major cause of death for older people in developed countries. This review looked at how living in rural areas influences oral cancer trends in these countries. The studies from these countries showed increasing rates of oral cancer in rural areas of the US, Australia, Canada, and Europe. Older people are more affected by these cancers than younger groups. The main risk factors are tobacco use, alcohol consumption, and HPV infections. People in rural areas often do not know much about HPV-related cancers. They also tend to use more tobacco and alcohol than city dwellers. Even in developed countries, living in rural areas can lead to shorter lifespans for oral cancer patients. This is mainly because it is harder for them to access specialized cancer treatment centres and advanced medical care. In summary, where people live can significantly impact their chances of surviving oral cancer, even in wealthy nations. Oral cancer is the general term used to describe cancers of the oral cavity and oropharyngeal region. These cancers are one of the leading causes of death in elderly residents within the Organisation for Economic Co-operation and Development (OECD) member countries in the 21st century. This scoping review was carried out to assess the influence of rurality on oral cancer trends and patterns among OECD member countries. Four online databases (Medline, PubMed, Scopus, and CINAHL) were searched for studies that reported on oral cancer trends in rural and remote areas in OECD member countries. A total of 1143 articles were obtained initially; among them, 995 papers were screened to include 18 articles for this scoping review. Studies have reported increasing incidence and prevalence in the United States, Australia, Canada, and European countries wherein risk factors such as tobacco, alcohol, and human papilloma virus (HPV) infections were associated with oral and oropharyngeal cancers. Awareness among people living in rural areas about HPV-related cancers was very low, while rates of tobacco and alcohol abuse were noted to be rising more rapidly than among their urban counterparts. Furthermore, the ageing population was most affected compared to the younger age groups of people with oral and oropharyngeal cancer that are prevalent in these regions. Overall, despite living in developed countries, rurality was noted to be a significant factor in the lower life expectancy of oral cancer patients, mainly due to the limited accessibility to tertiary cancer care centres and advanced medical care. [ABSTRACT FROM AUTHOR]

Simple Summary: Skin diseases can be serious, and early detection is key to effective treatment. Unfortunately, the quality of images used to diagnose these diseases often suffers due to interference from hair, making accurate diagnosis challenging. This research introduces a novel technology, the DM–AHR, a self-supervised conditional diffusion model designed specifically to generate clear, hairless images for better skin disease diagnosis. Our work not only presents a new, advanced model that expertly identifies and removes hair from dermoscopic images but also introduces a specialized dataset, DERMAHAIR, to further research and improve diagnostic processes. The enhancements in image quality provided by DM–AHR significantly improve the accuracy of skin disease diagnoses, and it promises to be a valuable tool in medical imaging. Accurate skin diagnosis through end-user applications is important for early detection and cure of severe skin diseases. However, the low quality of dermoscopic images hampers this mission, especially with the presence of hair on these kinds of images. This paper introduces DM–AHR, a novel, self-supervised conditional diffusion model designed specifically for the automatic generation of hairless dermoscopic images to improve the quality of skin diagnosis applications. The current research contributes in three significant ways to the field of dermatologic imaging. First, we develop a customized diffusion model that adeptly differentiates between hair and skin features. Second, we pioneer a novel self-supervised learning strategy that is specifically tailored to optimize performance for hairless imaging. Third, we introduce a new dataset, named DERMAHAIR (DERMatologic Automatic HAIR Removal Dataset), that is designed to advance and benchmark research in this specialized domain. These contributions significantly enhance the clarity of dermoscopic images, improving the accuracy of skin diagnosis procedures. We elaborate on the architecture of DM–AHR and demonstrate its effective performance in removing hair while preserving critical details of skin lesions. Our results show an enhancement in the accuracy of skin lesion analysis when compared to existing techniques. Given its robust performance, DM–AHR holds considerable promise for broader application in medical image enhancement. [ABSTRACT FROM AUTHOR]

Background: As global migration increases, nurse managers' effectiveness in multi-cultural nursing work environments is crucial due to the rising cultural diversity within healthcare teams. Despite the increasing international recruitment of qualified nurses to address the worldwide nursing shortage, no studies have synthesised the impact of nurse managers' attributes on nurses in multi-cultural nursing teams. Therefore, it was conducted a literature review aimed to synthesise the available literature on how nurse managers' personality traits, competencies, behaviours, and leadership styles influence nurse outcomes in multi-cultural nursing teams. Methods: Scoping review conducted according to the Joanna Briggs Institute guidelines to map the relationship or influence of nurse managers' personality traits, competencies, behaviours, and leadership styles on the outcomes of nurses in multi-cultural settings across various clinical environments. Searches were conducted across electronic databases such as CINAHL and MEDLINE, along with grey literature. Results: This review included 39 studies, highlighting 29 personality traits, 9 competencies, 115 behaviours, and 5 leadership styles that impact nurses' outcomes. Key findings emphasise the importance of nurse managers being supportive, culturally competent, and effective communicators, with transformational leadership style being particularly beneficial. Conclusions: These findings provide insights for planning and developing training programmes to equip current and future nurse managers with skills to effectively lead in multi-cultural care settings. [ABSTRACT FROM AUTHOR]

This paper reports on a service evaluation of PeerTalk, a nationwide charity that organises and facilitates peer support groups for individuals with depression. Therefore, the aim was to gather and synthesise benefits perceived by support group attendees. Thematic analysis was undertaken following the collection of data from two group interviews comprising PeerTalk support group attendees. Once those data were analysed, five key themes emerged: (1) talking/listening, (2) socialising, (3) contrast with other services, (4) personal benefits, and (5) structure and accessibility. Two further minor themes were also identified: (6) wider benefits and (7) areas for development that could lead to overall improvements to the service. PeerTalk's support groups provide multiple opportunities for attendees to meet others who have similar experiences within an environment that does not require formal engagement or commitment. Those that attend find benefit from supporting others and socialising within the group. These benefits are complementary to mainstream services that they may concurrently be involved with, rather than replacing or hindering them. Peer support groups can therefore provide a resource for healthcare professionals to which they can direct individuals who may feel benefit from engaging with other individuals with similar experiences. Sheffield Hallam University granted ethics approval for the study (ER:59716880) prior to its commencement (16 February 2024). [ABSTRACT FROM AUTHOR]

Background/Objectives: Rett syndrome is a rare neurodevelopmental disorder that can severely affect motor functioning, particularly walking. Previous training programs proposed treadmills as tools to increase walking endurance of patients with Rett syndrome, but these trainings did not include virtual reality (VR). The aim of this study was to assess the feasibility of a short treadmill training coupled to VR in girls with Rett syndrome. Methods: Nine patients with Rett syndrome underwent a 3-day treadmill walking program performed in semi-immersive VR. During the training, the happiness index and performance metrics were collected. At the end of the training parents filled out the Suitability Evaluation Questionnaire (SEQ) and, when feasible, patients underwent a gait assessment. Results: All the subjects recruited performed the three GRAIL sessions and parents showed a good satisfaction and considered the integration of treadmill and VR a good possibility for future rehabilitative programs. Participants showed greater satisfaction in environments requiring walking and their attention increased during training sessions, hypothesizing the feasibility of longer trainings with treadmill and VR. Data collected from gait analysis provided insights, although preliminary, concerning differences in gait pattern amongst the recruited subjects. Conclusions: Despite the small sample size and limited training duration, the paper suggests that a walking training with a treadmill combined with VR can represent a new strategy for Rett rehabilitation. [ABSTRACT FROM AUTHOR]

Background/Objectives: Women of childbearing age not only reside in agricultural communities but also form an integral part of the agricultural labor force. Limited research investigates the impact of prenatal fungicide exposure on infant health, specifically ethylenebisdithiocarbamates and their toxic by-product, ethylenethiourea (ETU), particularly in occupational settings. This paper describes the background, aims, protocol, and baseline sample characteristics for the SEMILLA study, which investigates prenatal ETU exposure, neonatal thyroid function, infant growth, and neurobehavioral development in an agricultural region of Ecuador. Methods: This cohort study follows pregnant women and their infants up to 18 months of age, incorporating urinary biomarkers and survey data on ETU exposure and infant growth and neurodevelopmental measures. Data collection includes detailed questionnaires, scales, and physical examinations on maternal and infant health and development, as well as environmental factors. Descriptive statistics on key characteristics of the study population at baseline are presented. Results: SEMILLA enrolled 409 participants (72% enrollment rate): 111 agricultural workers (mostly floricultural), 149 non-agricultural workers, and 149 non-workers. Baseline characteristics show comparability between work sector groups, with some economic differences. Conclusions: SEMILLA will provide key evidence on prenatal fungicide exposure and infant development and encompass comprehensive multistage data collection procedures in pregnancy and infancy, focusing on structural and social determinants of health as well as individual-level chemical exposures. The community-based approach has proven essential, even amid challenges like the COVID-19 pandemic. The medium-term objective is to inform sustainable interventions promoting maternal and child health, with a long-term goal to reduce community exposures and improve worker health policies, particularly for women and pregnant workers. [ABSTRACT FROM AUTHOR]

Objectives: This paper explores parent coaching experiences supporting parents of young children newly diagnosed with type 1 diabetes in a clinical trial. Methods: In a trial for 157 parents, those in the intervention arm (n = 116) were paired with a parent coach (n = 37; Mage = 37.9 years, SD = 3.9; 94.6% mothers, 81.1% White non-Hispanic). Parent coaches provided diabetes-specific social support. Parent coaches completed monthly surveys and satisfaction/feasibility surveys, with a subset (n = 7) undergoing qualitative interviews at the end of this study. Results: There were 2262 contacts between participants and their parent coaches, averaging 14.4 (SD = 9.3) per participant. Parent coaches reported that the most commonly used methods were text messages (67.9%) and emails (18.7%), with 33.6% having in-person visits. Coaches reported high satisfaction and belief in their usefulness to participants during the first 9 months after T1D diagnosis. Themes discussed by parent coaches about their experience in mentoring included relationship building, expertise sharing, personal growth, gratification, and intervention optimization suggestions. Conclusions: Parent coaching post T1D diagnosis involves regular, multi-method contacts. It is highly acceptable and valuable for parent coaches to mentor other parents of young children newly diagnosed with T1D. [ABSTRACT FROM AUTHOR]

In 2020 it is estimated that 281 million people were international migrants. Migrants constitute a potentially vulnerable population in terms of facing discrimination, poor living and housing conditions, and insufficient access to healthcare services. Due to the armed conflict in Ukraine in 2022, almost 10 million people crossed the Polish border within a year of the outbreak of the conflict. The objective of this paper is to present the use of primary healthcare services by people migrating from Ukraine to Poland and identify the barriers in access to healthcare by this group of persons. This study used a qualitative research technique in the form of an expert interview using individual in-depth interviews (IDI). The study group consisted of professionally active primary healthcare providers (doctors, nurses, and facility managers) in Poland. Research was carried out in the areas regarding the availability of healthcare, the potential threats and challenges, and possible system solutions. The results showed that the most common cause for doctor's appointments among migrants are respiratory infections, including COVID-19. Many cases were related to back pain, mainly resulting from the physical work of the patients. Additionally, some barriers to access and the provision of healthcare services for patients from Ukraine were identified. The majority (75%) of respondents indicated language as a significant barrier when providing services. Based on the study results, we recommend creating a dedicated website and telephone hotline for this group of persons as well as the use of traditional media to distribute information about access to healthcare services. It is also essential to focus on assistance for older people, since they may experience more difficulties with language and navigating the healthcare system. [ABSTRACT FROM AUTHOR]

Background: Emergency medical services (EMS) are intended to provide people with immediate, effective, and safe access to the healthcare system. The effects of pandemics on emergency medical services (EMS) have not been studied sufficiently. The aim of this paper is to assess the frequency and structure of calls at an ambulance station in Kazakhstan during the period of 2019–2023. Methods: A retrospective analysis was conducted to estimate the incidence of emergency assistance cases from 2019 to 2023. Results: An analysis of the structure and number of ambulance calls before the pandemic, during the pandemic, and post-pandemic period did not reveal significant changes, except for calls in urgency category IV. Patients of urgency category IV handled by an ambulance decreased by 2 and 1.7 times in 2020 and 2021, respectively, which appears to be related to quarantine measures. In 2022 and 2023, category IV calls were 4.7 and 4.5 times higher than in 2019. Conclusions: This study's findings suggest no changes in the dynamics of ambulance calls, except urgency category IV calls. The number of category IV urgent calls decreased significantly during the COVID-19 pandemic and increased in the post-pandemic period. [ABSTRACT FROM AUTHOR]

Simple Summary: Prostate cancer (PCa) has significant disparities based on geography, affecting healthcare access and outcomes. This study reviews how Geographic Information Systems (GIS) are used to research these disparities. GIS helps visualize PCa incidence, survival, and mortality trends, but its application varies, leading to inconsistent results. The review followed Cochrane and PRISMA guidelines, analyzing 25 relevant studies. Most studies used GIS for mapping PCa data, geocoding, and spatial analysis to identify areas with poor PCa outcomes. However, inconsistencies in GIS methods and geographical scales used reduced the robustness of findings. The review suggests that better GIS techniques and interdisciplinary collaboration could improve the accuracy of PCa disparity research and support public health interventions. Introduction: PCa is one of the cancers that exhibits the widest disparity gaps. Geographical place of residence has been shown to be associated with healthcare access/utilization and PCa outcomes. Geographical Information Systems (GIS) are widely being utilized for PCa disparities research, however, inconsistencies in their application exist. This systematic review will summarize GIS application within PCa disparities research, highlight gaps in the literature, and propose alternative approaches. Methods: This paper followed the methods of the Cochrane Collaboration and the criteria set of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Articles published in peer-reviewed journals were searched through the PubMed, Embase, and Web of Science databases until December 2022. The main inclusion criteria were employing a GIS approach and examining a relationship between geographical components and PCa disparities. The main exclusion criteria were studies conducted outside the US and those that were not published in English. Results: A total of 25 articles were included; 23 focused on PCa measures as outcomes: incidence, survival, and mortality, while only 2 examined PCa management. GIS application in PCa disparities research was grouped into three main categories: mapping, processing, and analysis. GIS mapping allowed for the visualization of quantitative, qualitative, and temporal trends of PCa factors. GIS processing was mainly used for geocoding and smoothing of PCa rates. GIS analysis mainly served to evaluate global spatial autocorrelation and distribution of PCa cases, while local cluster identification techniques were mainly employed to identify locations with poorer PCa outcomes, soliciting public health interventions. Discussion: Varied GIS applications and methodologies have been used in researching PCa disparities. Multiple geographical scales were adopted, leading to variations in associations and outcomes. Geocoding quality varied considerably, leading to less robust findings. Limitations in cluster-detection approaches were identified, especially when variations were captured using the Spatial Scan Statistic. GIS approaches utilized in other diseases might be applied within PCa disparities research for more accurate inferences. A novel approach for GIS research in PCa disparities could be focusing more on geospatial disparities in procedure utilization especially when it comes to PCa screening techniques. Conclusions: This systematic review summarized and described the current state and trend of GIS application in PCa disparities research. Although GIS is of crucial importance when it comes to PCa disparities research, future studies should rely on more robust GIS techniques, carefully select the geographical scale studied, and partner with GIS scientists for more accurate inferences. Such interdisciplinary approaches have the potential to bridge the gaps between GIS and cancer prevention and control to further advance cancer equity. [ABSTRACT FROM AUTHOR]

Necrotizing gingivitis (NG) is an acute inflammatory process with an estimated prevalence of less than 1%. The treatment of choice is usually antibiotics in addition to periodontal treatment. This scoping review aims to detail extent and type of proof related to NG in paediatric patient; moreover, a decision tree protocol was developed to define NG management in paediatric patients based on the presence or absence of systemic compromission. In addition, we also propose the use of ozone treatment as an adjuvant therapy. Seven papers (3 case reports, 2 guidelines, and 2 reviews) were selected for evaluation by reading the full texts. This review outlines the lack of research on the treatment of NG in paediatric patients; we, however, demonstrate the efficacy of the decision tree protocol by describing two case reports in which patients were treated with antibiotics according to the presence or absence of systemic involvement through the implementation of an individualized therapeutic approach, with periodontal ozone therapy. Moreover, the supportive use of this molecule in the management of NG can be a valuable tool in the healing of gingival tissues. [ABSTRACT FROM AUTHOR]

Due to the increasing cost of health insurance, for decades, many countries have endeavored to constrain the cost of insurance by utilizing a DRG payment system. In most cases, under the DRG payment system, hospitals cannot exactly know which DRG code inpatients are until they are discharged. This paper focuses on the prediction of what DRG code appendectomy patients will be classified with when they are admitted to hospital. We utilize two models (or classifiers) constructed using the C4.5 algorithm and back-propagation neural network (BPN). We conducted experiments with the data collected from two hospitals. The results show that the accuracies of these two classification models can be up to 97.84% and 98.70%, respectively. According to the predicted DRG code, hospitals can effectively arrange medical resources with certainty, then, in turn, improve the quality of the medical care patients receive. [ABSTRACT FROM AUTHOR]

Simple Summary: Breast cancer is the most prevalent cancer among women. Extensive research has been conducted on eating patterns, and increasing evidence suggests that diet significantly influences the development, progression, and prevention of breast cancer. However, besides the well-known role of alcohol and red and processed meat, the impact of other dietary components remains a subject of debate. Specifically, the potential connection between sugar, dairy components, and soy with breast cancer risk raises questions. Focusing on the studies conducted in the last decade, our literature review shows a negative association between breast cancer incidence and both dairy product and soy consumption, while complex data emerged about sugar intake by itself. However, high heterogeneity across studies' findings was observed, thus highlighting the need for comprehensive investigations considering both patient- and cancer-related factors to develop preventive strategies that should be incorporated into international guidelines. Breast cancer (BC) constitutes a prevalent health condition among women. Recent years have witnessed the identification of dietary proto-oncogenic factors that deserve attention. Besides the well-known role of alcohol and red and processed meat in BC development, the impact of other dietary components remains unclear. Our narrative review aims to explore the diet-BC relationship, focusing on sugar, dairy, and soy consumption. We conducted a PubMed literature search covering the last decade (2013–2023) and included 35 papers. We found limited evidence on the association between high sugar intake and BC incidence. On the other hand, dairy and soy consumption displayed a protective effect in the majority of the analyzed papers. However, a significant degree of heterogeneity was reported among the results. Menopausal status and the specific BC molecular subtypes were the main factors influencing the interpretation of the results. Exploring dietary factors and BC revealed inconsistencies: high glycemic index post-menopause may be a risk factor, while sugar-sweetened drinks and artificial sweeteners yielded conflicting results; fermented dairy showed potential benefits, non-fermented dairy presented inconsistent findings; soy impact on BC varied according to molecular subtype, with some studies suggesting a positive association in luminal-like BC. Hence, further investigation is crucial to obtain a uniform consensus on the diet-BC relationship. [ABSTRACT FROM AUTHOR]

Simple Summary: Within the rapidly evolving landscape of Machine Learning in the medical field, this paper focuses on the forefront advancements in neuro-oncological radiology. More specifically, it aims to provide the reader with an in-depth exploration of the latest advancements in employing Deep Learning methodologies for the classification of brain tumor radiological images. This review meticulously scrutinizes papers published from 2018 to 2023, unveiling ongoing topics of research while underscoring the main remaining challenges and potential avenues for future research identified by those studies. Beyond the review itself, the paper also underscores the importance of placing the image data modelling provided by Deep Learning techniques within the framework of analytical pipeline research. This means that data quality control and pre-processing should be correctly coupled with modelling itself, in a way that emphasizes the importance of responsible data utilization, as well as the critical need for transparency in data disclosure to ensure trustworthiness and reproducibility of findings. Machine Learning is entering a phase of maturity, but its medical applications still lag behind in terms of practical use. The field of oncological radiology (and neuro-oncology in particular) is at the forefront of these developments, now boosted by the success of Deep-Learning methods for the analysis of medical images. This paper reviews in detail some of the most recent advances in the use of Deep Learning in this field, from the broader topic of the development of Machine-Learning-based analytical pipelines to specific instantiations of the use of Deep Learning in neuro-oncology; the latter including its use in the groundbreaking field of ultra-low field magnetic resonance imaging. [ABSTRACT FROM AUTHOR]

In recent years, the globe has faced a series of topics of growing concern, such as the COVID-19 pandemic, the international financial crisis, rising socio-economic inequalities, the negative outcomes of greenhouse gas emissions, which resulted in climate change, and many others. Organizations worldwide have confronted these new challenges of sustainable finance by incorporating environmental, social, and corporate governance (ESG) factors and digital transformation (DT) in their innovation business strategies. The healthcare sector represents a large share of the global economy (about 10% of global economic output), employs a large number of workers, and needs to rely more on an open innovation model where interested parties, especially patients, are going to have a say in their own well-being. Thus, it is imperative that healthcare providers be efficient, effective, resilient, and sustainable in the face of significant challenges and risks. At the same time, they must offer sustainable development goals and digital transformation to healthcare users through limited governmental resources. This study investigates the role, importance, and correlation of ESG factors and digital transformation to the sustainable finance of healthcare systems through an innovative model. The main purpose of the paper is to present the already implemented ESG and DT factors in the healthcare sector and to propose a mutual and combined implementation strategy based on common evaluation tools, methods, and actions. A set of proposed actions and strategies are presented for the sustainability and resilience of the healthcare sector. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, after conducting a comprehensive review of 1356 papers that evaluated the diagnostic performance of deep learning (DL) methods based on medical images for hepatocellular carcinoma (HCC), the findings showed a pooled sensitivity of 89% (95% CI: 87–91), a specificity of 90% (95% CI: 87–92), and an AUC of 0.95 (95% CI: 0.93–0.97). In addition, both the DL methods and human clinicians demonstrated similar levels of performance in HCC detection, with receiver operating characteristic curve (ROC) values of 0.97 (95% CI: 0.95–0.98) for both groups, indicating no discernible difference. Although the heterogeneity was obvious, the utilization of DL methods for diagnosing HCC through medical images has shown promising outcomes. (1) Background: The aim of our research was to systematically review papers specifically focused on the hepatocellular carcinoma (HCC) diagnostic performance of DL methods based on medical images. (2) Materials: To identify related studies, a comprehensive search was conducted in prominent databases, including Embase, IEEE, PubMed, Web of Science, and the Cochrane Library. The search was limited to studies published before 3 July 2023. The inclusion criteria consisted of studies that either developed or utilized DL methods to diagnose HCC using medical images. To extract data, binary information on diagnostic accuracy was collected to determine the outcomes of interest, namely, the sensitivity, specificity, and area under the curve (AUC). (3) Results: Among the forty-eight initially identified eligible studies, thirty studies were included in the meta-analysis. The pooled sensitivity was 89% (95% CI: 87–91), the specificity was 90% (95% CI: 87–92), and the AUC was 0.95 (95% CI: 0.93–0.97). Analyses of subgroups based on medical image methods (contrast-enhanced and non-contrast-enhanced images), imaging modalities (ultrasound, magnetic resonance imaging, and computed tomography), and comparisons between DL methods and clinicians consistently showed the acceptable diagnostic performance of DL models. The publication bias and high heterogeneity observed between studies and subgroups can potentially result in an overestimation of the diagnostic accuracy of DL methods in medical imaging. (4) Conclusions: To improve future studies, it would be advantageous to establish more rigorous reporting standards that specifically address the challenges associated with DL research in this particular field. [ABSTRACT FROM AUTHOR]

Multimorbidity is defined as the presence of two or more chronic medical conditions in a person, whether physical, mental or long-term infectious diseases. This is especially common in older populations, affecting their quality of life and emotionally impacting their caregivers and family. Technology can allow for monitoring, managing, and motivating older adults in their self-care, as well as supporting their caregivers. However, when several conditions are present at once, it may be necessary to manage several types of technologies, or for technology to manage the interaction between conditions. This work aims to understand and describe the technologies that are used to support the management of multimorbidity for older adults. We conducted a systematic review of ten years of scientific literature from four online databases. We reviewed a corpus of 681 research papers, finally including 25 in our review. The technologies used most frequently by older adults with multimorbidity are mobile applications and websites, and they are mostly focused on communication and connectivity. We then propose opportunities for future research on addressing the challenges in the management of several simultaneous health conditions, potentially creating a better approach than managing each condition as if it were independent. [ABSTRACT FROM AUTHOR]

(1) Background: The nursing of the elderly has received more and more attention, especially the nursing of urination and defecation for the elderly. (2) Purpose: Design an excretion nursing equipment that can accurately identify and deal with urine and stool. (3) Methods: In this paper, based on the analysis of the requirements of excretion nursing equipment, a split mechanical design method and a modular control method are used to design the equipment. The Dempster–Shafer (D-S) evidence theory is used in the identification of urine and stool. (4) Results: The excretion nursing equipment designed in this paper works well according to functional test, and the success rate of stool and urine identification method using D-S evidence theory is 20% higher than that of traditional methods, reaching 90%. (5) Conclusions: The urine and stool recognition and detection algorithm based on the D-S evidence theory used in this paper can improve the recognition accuracy of traditional detection methods, and the designed excretion nursing equipment can realize the function of excretion care for patients. [ABSTRACT FROM AUTHOR]

Simple Summary: The journey of discovering melanoma—the most dangerous type of skin cancer—biomarkers is never-ending. Under that assumption, this study attempts to partially fill a gap in that journey by identifying melanoma-related biomarkers. This research paper studied the genetic and molecular profiling of melanoma. A transcriptome-wide association study (TWAS) was conducted to reveal the significant biomarkers associated with melanoma. A molecular network was constructed to represent the significant interactions between genes and microRNAs (miRNAs). The related biological processes, the enriched pathways, and the associated diseases were identified. The hotspot biomarkers were discovered to elucidate further the mechanism of these genes and miRNAs in melanoma pathogenesis. This work reveals the pathogenesis and biologically important molecular interactions of melanoma and provides new insights into the molecular mechanisms of melanoma. A transcriptome-wide association study (TWAS) was conducted on genome-wide association study (GWAS) summary statistics of malignant melanoma of skin (UK Biobank dataset) and The Cancer Genome Atlas-Skin Cutaneous Melanoma (TCGA-SKCM) gene expression weights to identify melanoma susceptibility genes. The GWAS included 2465 cases and 449,799 controls, while the gene expression testing was conducted on 103 cases. Afterward, a gene enrichment analysis was applied to identify significant TWAS associations. The melanoma's gene–microRNA (miRNA) regulatory network was constructed from the TWAS genes and their corresponding miRNAs. At last, a disease enrichment analysis was conducted on the corresponding miRNAs. The TWAS detected 27 genes associated with melanoma with p-values less than 0.05 (the top three genes are LOC389458 (RBAK), C16orf73 (MEIOB), and EIF3CL). After the joint/conditional test, one gene (AMIGO1) was dropped, resulting in 26 significant genes. The Gene Ontology (GO) biological process associated the extended gene set (76 genes) with protein K11-linked ubiquitination and regulation of cell cycle phase transition. K11-linked ubiquitin chains regulate cell division. Interestingly, the extended gene set was related to different skin cancer subtypes. Moreover, the enriched pathways were nsp1 from SARS-CoV-2 that inhibit translation initiation in the host cell, cell cycle, translation factors, and DNA repair pathways full network. The gene-miRNA regulatory network identified 10 hotspot genes with the top three: TP53, BRCA1, and MDM2; and four hotspot miRNAs: mir-16, mir-15a, mir-125b, and mir-146a. Melanoma was among the top ten diseases associated with the corresponding (106) miRNAs. Our results shed light on melanoma pathogenesis and biologically significant molecular interactions. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer arises through the accumulation of somatic mutations in key biological pathways. This paper aims to develop a probabilistic approach to delineate the temporal order of mutations during cancer development based on mutation profile data from a cohort of patients. A unique feature of our method is that it incorporates intra-tumor heterogeneity (ITH) information, which refers to the heterogeneous cell populations within a tumor and characterizes the evolutionary history of the tumor. We showed that by integrating ITH, pathways, and functional annotation information, our method yielded high accuracy in inferring the temporal order of pathway mutations during carcinogenesis. The development of cancer involves the accumulation of somatic mutations in several essential biological pathways. Delineating the temporal order of pathway mutations during tumorigenesis is crucial for comprehending the biological mechanisms underlying cancer development and identifying potential targets for therapeutic intervention. Several computational and statistical methods have been introduced for estimating the order of somatic mutations based on mutation profile data from a cohort of patients. However, one major issue of current methods is that they do not take into account intra-tumor heterogeneity (ITH), which limits their ability to accurately discern the order of pathway mutations. To address this problem, we propose PATOPAI, a probabilistic approach to estimate the temporal order of mutations at the pathway level by incorporating ITH information as well as pathway and functional annotation information of mutations. PATOPAI uses a maximum likelihood approach to estimate the probability of pathway mutational events occurring in a specific sequence, wherein it focuses on the orders that are consistent with the phylogenetic structure of the tumors. Applications to whole exome sequencing data from The Cancer Genome Atlas (TCGA) illustrate our method's ability to recover the temporal order of pathway mutations in several cancer types. [ABSTRACT FROM AUTHOR]

Simple Summary: The B cell receptor (BCR) is a membrane-bound protein complex that is required for the normal development of B cells. BCR signalling is also involved in the pathogenesis of B cell cancers. While there is substantial literature on genomic analyses of the BCR, there are limited proteomic studies of receptor structure and its interactions with neighbouring proteins. This is partly due to the location of the BCR in the surface-membrane lipid environment that has limited the ability to enrich the complex for proteomic analysis. Here, we report an enrichment technique that can be used for mass spectrometry analyses of the BCR from live B cells. B cells are central to the adaptive immune response and provide long-lasting immunity after infection. B cell activation is mediated by the surface membrane-bound B cell receptor (BCR) following recognition of a specific antigen. The BCR has been challenging to analyse using mass spectrometry (MS) due to the difficulty of isolating and enriching this membrane-bound protein complex. There are approximately 120,000 BCRs on the B cell surface; however, depending on the B cell activation state, there may be hundreds-of-millions to billions of proteins in a B cell. Consequently, advanced proteomic techniques such as MS workflows that use purified proteins to yield structural and protein-interaction information have not been published for the BCR complex. This paper describes a method for enriching the BCR complex that is MS-compatible. The method involves a Protein G pull down on agarose beads using an intermediary antibody to each of the BCR complex subcomponents (CD79a, CD79b, and membrane immunoglobulin). The enrichment process is shown to pull down the entire BCR complex and has the advantage of being readily compatible with further proteomic study including MS analysis. Using intermediary antibodies has the potential to enrich all isotypes of the BCR, unlike previous methods described in the literature that use protein G-coated beads to directly pull down the membrane IgG (mIgG) but cannot be used for other mIg isotypes. [ABSTRACT FROM AUTHOR]

Clinical reasoning is an essential component of nursing. It has emerged as a concept that integrates the core competencies of quality and safety education for nurses. In cooperation with five European partners, Instituto Politécnico de Setúbal (IPS) realized the "Clinical Reasoning in Nursing and Midwifery Education and Practice" project as part of the Erasmus+ project. As a partner, our team designed a multiplier event—the student training course. The aim of this report is to describe the construction and development of this clinical reasoning training course for nursing students. We outline the pedagogical approach of an undergraduate training course on clinical reasoning in 2023, which we separated into four stages: (i) welcoming, (ii) knowledge exploration, (iii) pedagogical learning, and (iv) sharing experience. This paper presents the learning outcomes of the collaborative reflection on and integration of the clinical reasoning concept among nursing students. This educational experience fostered reflection and discussion within the teaching team of the nursing department regarding the concept, models, and teaching/learning methods for clinical reasoning, with the explicit inclusion of clinical reasoning content in the nursing curriculum. We highlight the importance of implementing long-term pedagogical strategies in nursing education. [ABSTRACT FROM AUTHOR]

Nurses are at high risk of burnout and subsequent mental health concerns due to problems with overstaffing, immense workload volume, and personal health risks associated with the job. Effective mental health treatments are available but potential barriers to receiving care may prevent nurses from benefiting. The Emotional Health and Well-Being Clinic (EHWC) at Houston Methodist is an outpatient mental health clinic offering therapy and medication management services for employees and employee dependents of our institution. The EHWC is uniquely positioned to observe how nurses utilize mental health services and to address barriers to effective care for this vital group of healthcare professionals. This paper provides descriptive data on the utilization of mental health services by nurses in the EHWC and a discussion of possible challenges faced by this group when seeking care. Based on these data, we propose potential solutions to ensure that nurses can achieve maximum benefit from outpatient mental health services. [ABSTRACT FROM AUTHOR]

Simple Summary: The diagnosis of oral cancer can require multiple biopsies to increase the likelihood of sampling the most pathologic site within a lesion. Optical coherence tomography (OCT) enables the examination of subsurface morphology and has shown potential in biopsy guidance. OCT captures changes in tissue stratification related to depth, topology, and presence of the epithelial-stromal boundary, which are structural biomarkers for pre-invasive and invasive oral cancer. This study presents a neural network pipeline to simplify OCT interpretation by providing information about epithelial depth and stratification through simple en face maps. U-net models were employed to segment the boundaries of the epithelial layer, and supporting convolutional neural networks were used for identification of the imaging field and artifacts. Non-cancerous, precancerous, and cancerous pathologies across the oral cavity were evaluated. The predictions demonstrate as-good-as or better agreement than inter-rater agreement, suggesting strong predictive power. This paper aims to simplify the application of optical coherence tomography (OCT) for the examination of subsurface morphology in the oral cavity and reduce barriers towards the adoption of OCT as a biopsy guidance device. The aim of this work was to develop automated software tools for the simplified analysis of the large volume of data collected during OCT. Imaging and corresponding histopathology were acquired in-clinic using a wide-field endoscopic OCT system. An annotated dataset (n = 294 images) from 60 patients (34 male and 26 female) was assembled to train four unique neural networks. A deep learning pipeline was built using convolutional and modified u-net models to detect the imaging field of view (network 1), detect artifacts (network 2), identify the tissue surface (network 3), and identify the presence and location of the epithelial–stromal boundary (network 4). The area under the curve of the image and artifact detection networks was 1.00 and 0.94, respectively. The Dice similarity score for the surface and epithelial–stromal boundary segmentation networks was 0.98 and 0.83, respectively. Deep learning (DL) techniques can identify the location and variations in the epithelial surface and epithelial–stromal boundary in OCT images of the oral mucosa. Segmentation results can be synthesized into accessible en face maps to allow easier visualization of changes. [ABSTRACT FROM AUTHOR]

Simple Summary: The current approach to breast cancer screening, which is based on a person's age, overlooks individual-level differences in breast cancer risk. As a result, many people are over- or under-screened according to their actual risk of breast cancer. Risk-stratified breast screening may overcome the limitations of age-based screening, but there are still many knowledge gaps regarding how best to implement it in the population setting. This study will generate the first Canadian evidence on the adoption of breast cancer risk assessment in the population setting, to support the future implementation of risk-stratified breast cancer screening. This study demonstrated that, while risk assessment for risk-stratified screening at the population level is feasible, an equity lens must be considered in implementation to ensure cancer-screening disparities are not widened. Risk-stratified breast screening has been proposed as a strategy to overcome the limitations of age-based screening. A prospective cohort study was undertaken within the PERSPECTIVE I&I project, which will generate the first Canadian evidence on multifactorial breast cancer risk assessment in the population setting to inform the implementation of risk-stratified screening. Recruited females aged 40–69 unaffected by breast cancer, with a previous mammogram, underwent multifactorial breast cancer risk assessment. The adoption of multifactorial risk assessment, the effectiveness of methods for collecting risk factor information and the costs of risk assessment were examined. Associations between participant characteristics and study sites, as well as data collection methods, were assessed using logistic regression; all p-values are two-sided. Of the 4246 participants recruited, 88.4% completed a risk assessment, with 79.8%, 15.7% and 4.4% estimated at average, higher than average and high risk, respectively. The total per-participant cost for risk assessment was CAD 315. Participants who chose to provide risk factor information on paper/telephone (27.2%) vs. online were more likely to be older (p = 0.021), not born in Canada (p = 0.043), visible minorities (p = 0.01) and have a lower attained education (p < 0.0001) and perceived fair/poor health (p < 0.001). The 34.4% of participants requiring risk factor verification for missing/unusual values were more likely to be visible minorities (p = 0.009) and have a lower attained education (p ≤ 0.006). This study demonstrates the feasibility of risk assessment for risk-stratified screening at the population level. Implementation should incorporate an equity lens to ensure cancer-screening disparities are not widened. [ABSTRACT FROM AUTHOR]

Background: Healthcare-associated infections (HAIs) pose a significant global threat, particularly in developing regions such as Southeast Asia. International bodies emphasize the role of formal undergraduate training in the prevention and control of HAIs. To address this, we aimed to explore the perceptions of Southeast Asian nursing students regarding a novel educational approach developed by a European–Southeast Asian project consortium. Methods: A pilot study was conducted in four nursing higher education institutions from Cambodia and Vietnam. First, local nursing educators conducted a 2 h classroom-based training session. Then, students were invited to participate for the first time in one of twelve evidence-based simulation scenarios developed by the research team, covering a range of nursing care situations related to the prevention and control of HAIs. After attending both components, students were asked to complete a paper-based questionnaire and rate their agreement with a set of statements on the appropriateness and meaningfulness of both components. Results: A total of 430 nursing students enrolled in the pilot study; 77.4% were female, with an average age of 19.8 years. The PrevInf educational intervention received positive feedback from participating students across settings, with strong agreement on the importance of proactiveness in competency development (M = 5.9, SD = 1.4). Notable differences between Cambodian and Vietnamese students were observed in terms of their receptiveness to the pre-selected teaching materials (p = 0.001) and strategies (p = 0.01) used by the nursing educators during their experience with the simulation scenarios. Conclusions: The PrevInf educational intervention shows promise in engaging Southeast Asian nursing students and fostering a deeper understanding of the prevention and control of HAIs. Further studies are warranted to refine the learning content and standardize the pedagogical strategies used by nursing educators across settings. This study was not registered. [ABSTRACT FROM AUTHOR]

Worldwide, nurse shortages constitute a problem, including in the Netherlands. Every region in the country has a shortage of all types of nurses. At the same time, there are large hidden reserves: persons who have been trained as a nurse but do not work in the healthcare sector. The size of the hidden reserve exceeds the shortage of nurses. Until now, the literature has not paid much attention to spatial aspects of the nursing shortage problem. In this paper, we analyze the size of the hidden reserves and how they are distributed over the country, across large and smaller cities, and across different nurse categories. We find that especially densely populated areas have relatively small shares of trained nurses as well as large hidden reserves relative to their population. These areas are also facing the largest nurse shortages. As nurse labor markets are local, policies that are more focused on local situations are necessary to activate these hidden reserves. [ABSTRACT FROM AUTHOR]

The effects of preterm birth, neonatal morbidities and environmental influences on infant sleep development is an important yet under-researched topic, with little known about normative sleep for infants born sick or preterm. The aim of this prospective, observational longitudinal study was to evaluate maternal perceptions and degree of bother with infant sleep behaviours and feeding outcomes across the first 9 months after discharge for sick/preterm infants cared for in the neonatal intensive care unit (NICU) and for healthy term-born infants. This paper reports outcomes for the sick/preterm cohort (I = 94) that were recruited from two NICUs in Perth, Western Australia. Total bother scores were on average 20.2% higher at 9 months than at two weeks post-discharge (p < 0.001). Increased night waking frequency, evening settling duration and crying duration were all positively associated with total bother scores. Maternal confidence scores were negatively associated with maternal bother scores; with each unit increase in confidence, maternal bother decreased by 8.5% (p < 0.001). Covariates such as birth gestation, breastfeeding status and multiple births were not associated with maternal bother. Families may benefit from additional support when experiencing increased night waking frequency and crying and settling durations in the first 9 months after discharge from NICU. [ABSTRACT FROM AUTHOR]

To actively respond to the challenges posed by population aging, people are paying more and more attention to healthy behavioral lifestyles, and the impact of social capital as an informal system on health behaviors cannot be ignored. This paper explores the impact of social capital on health behaviors of middle-aged and older adults based on 2020 CHARLS data. Using binary logistic regression models, we discussed the association between social capital and five health behaviors. The results suggest that structural social capital significantly increases physical activity and physical examination behaviors among middle-aged and older adults but also decreases the probability of abstinence behaviors. Cognitive social capital increases the probability that middle-aged and older adults will have a reasonable amount of sleep and physical activity. However, it also decreases the probability that smoking cessation behaviors will occur. Further attention needs to be paid to the role of social capital, the creation of a harmonious social environment and the enhancement of social trust, the strengthening of communities and grass-roots social organizations, and the provision of more platforms for the participation of middle-aged and older adults in social activities, to improve the quality of the healthy lives of middle-aged and older adults and, in turn, to promote the establishment of healthy behaviors. [ABSTRACT FROM AUTHOR]

Family caregivers are vital to enabling people with dementia to live longer in their own homes. For these caregivers, chatting with clinicians—being listened to empathetically and receiving reassurance—can be seen as not incidental but important to supporting them. This paper considers and identifies the significance of this relational work for family carers by re-examining data originally collected to document caregivers' perspectives on quality in crisis response teams. This reveals that chatting, for family caregivers, comprises three related features: (i) that family caregivers by responding to a person's changing and sometimes challenging needs and behaviors inhabit a precarious equilibrium; (ii) that caregivers greatly appreciate 'chatting' with visiting clinicians; and (iii) that while caregivers appreciate these chats, they can be highly critical of the institutionalized character of a crisis response team's involvement with them. [ABSTRACT FROM AUTHOR]

Simple Summary: The role of neurogenic locus notch homolog protein 1 (NOTCH1)- and nuclear factor erythroid 2-related factor 2 (NRF2)-related pathways is highly heterogeneous in small cell lung cancer (SCLC) and, when they are both abnormally activated, they can synergistically cause neoplastic proliferation. In this paper, we investigate the possible role of KEAP1 silencing in NRF2 and NOTCH axis deregulation in SCLC by evaluating its impact on the modulation of cellular defense systems, cell growth, and differentiation. We also investigate the impact of these systems' impairment in response to conventional chemotherapies and NOTCH inhibitors in silenced SCLC cell lines with different Kelch-like ECH-associated protein 1 (KEAP1) alterations. The KEAP1/NRF2 pathway is a master regulator of several redox-sensitive genes implicated in the resistance of tumor cells against therapeutic drugs. The dysfunction of the KEAP1/NRF2 system has been correlated with neoplastic patients' outcomes and responses to conventional therapies. In lung tumors, the growth and the progression of cancer cells may also involve the intersection between the molecular NRF2/KEAP1 axis and other pathways, including NOTCH, with implications for antioxidant protection, survival of cancer cells, and drug resistance to therapies. At present, the data concerning the mechanism of aberrant NRF2/NOTCH crosstalk as well as its genetic and epigenetic basis in SCLC are incomplete. To better clarify this point and elucidate the contribution of NRF2/NOTCH crosstalk deregulation in tumorigenesis of SCLC, we investigated genetic and epigenetic dysfunctions of the KEAP1 gene in a subset of SCLC cell lines. Moreover, we assessed its impact on SCLC cells' response to conventional chemotherapies (etoposide, cisplatin, and their combination) and NOTCH inhibitor treatments using DAPT, a γ-secretase inhibitor (GSI). We demonstrated that the KEAP1/NRF2 axis is epigenetically controlled in SCLC cell lines and that silencing of KEAP1 by siRNA induced the upregulation of NRF2 with a consequent increase in SCLC cells' chemoresistance under cisplatin and etoposide treatment. Moreover, KEAP1 modulation also interfered with NOTCH1, HES1, and DLL3 transcription. Our preliminary data provide new insights about the downstream effects of KEAP1 dysfunction on NRF2 and NOTCH deregulation in this type of tumor and corroborate the hypothesis of a cooperation of these two pathways in the tumorigenesis of SCLC. [ABSTRACT FROM AUTHOR]