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Background: Efficient monitoring of glucose concentration in the human body necessitates the utilization of electrochemically active sensing materials in nonenzymatic glucose sensors. However, prevailing limitations such as intricate fabrication processes, lower sensitivity, and instability impede their practical application. Herein, ternary Cu-Co-Ni-S sulfides nanoporous network structure was synthesized on carbon fiber paper (CP) by an ultrafast, facile, and controllable technique through on-step cyclic voltammetry, serving as a superior self-supporting catalytic electrode for the high-performance glucose sensor. Results: The direct growth of free-standing Cu-Co-Ni-S on the interconnected three-dimensional (3D) network of CP boosted the active site of the composites, improved ion diffusion kinetics, and significantly promoted the electron transfer rate. The multiple oxidation states and synergistic effects among Co, Ni, Cu, and S further promoted glucose electrooxidation. The well-architected Cu-Co-Ni-S/CP presented exceptional electrocatalytic properties for glucose with satisfied linearity of a broad range from 0.3 to 16,000 μM and high sensitivity of 6829 μA mM− 1 cm− 2. Furthermore, the novel sensor demonstrated excellent selectivity and storage stability, which could successfully evaluate the glucose levels in human serum. Notably, the novel Cu-Co-Ni-S/CP showed favorable biocompatibility, proving its potential for in vivo glucose monitoring. Conclusion: The proposed 3D hierarchical morphology self-supported electrode sensor, which demonstrates appealing analysis behavior for glucose electrooxidation, holds great promise for the next generation of high-performance glucose sensors. [ABSTRACT FROM AUTHOR]

The trail making test (TMT) is a commonly used tool for evaluating executive functions, and the activation of cerebral oxygenation in the prefrontal cortex (PFC) during the test can reflect the participation of executive function. This study aimed to compare the differences in cerebral oxygenation in the PFC between the computer- and paper-based versions of the TMT and provide a theoretical basis for the optimization and clinical application of the computer-based version. A total of 32 healthy adult participants completed the computer- and paper-based TMT Types A and B. Cerebral oxygenation changes in the PFC were monitored during the experiment using near-infrared spectroscopy. Moreover, average changes in oxyhemoglobin (Δoxy-Hb) levels at the baseline and during activation periods in different types of testing were compared and analyzed. The number of correct connections in the computer-based version Type B was less than that in the paper-based version Type B (p <.001). The task time of the computer-based version was longer than that of the paper-based version (p <.001). The B/A ratio of the number of correct connections in the computer-based version was lower than that in the paper-based version (p <.001). The Δoxy-Hb in the PFC of the paper-based version was higher than that of the computer-based version (p <.001). Significant differences in oxygenation in the PFC were observed between the paper- and computer-based versions of TMT. After further improvement and correction in the subsequent development of the computer-based TMT, and taking into account the psychological feelings and preferences of the participants when performing different versions of the TMTs, the computer-based TMT is expected to play a good auxiliary role in clinical evaluation. [ABSTRACT FROM AUTHOR]

This autobiographical paper recounts the recovery journey of Lorna Collins, a survivor of severe and enduring anorexia nervosa (SE-AN). Her story begins with a traumatic brain injury at the age of 18, leading to a complex eating disorder that persisted for over two decades. Despite over 30 hospital admissions and various treatment modalities, her condition only worsened, compounded by other mental health challenges. The paper describes these multifaceted struggles, including mistreatment in healthcare, self-harm, further trauma and near-fatal illness. The author aims to culminate her story in an uplifting manner, by highlighting the pivotal role that integrated cognitive behaviour therapy, artistic expression, and a renewed connection with her family have made on her recovery. Collins' account is not only a personal testimony but also offers critical insights into the shortcomings of traditional eating disorder treatments and the importance of personalised, holistic approaches in mental health care. Lorna's story aims to bring hope, challenge the concept of SEED and form part of a growing evidence-base that recovery is possible irrespective of duration or eating disorder severity. [ABSTRACT FROM AUTHOR]

Mendelian randomization (MR) is a powerful epidemiological method for causal inference. However, its recent surge in popularity has brought two concerning trends. First, the public availability of summary results from genome-wide association studies has led to an explosion of low-quality two-sample mendelian randomization (2SMR) studies. These studies add minimal – if any – value and overwhelm reviewers and journals. Second, the availability of large datasets with individual-level genotype data, like UK Biobank, has spurred the development and use of novel MR methods. However, some methods are being applied without proper testing, leading to misleading results, as exemplified by recent spurious findings that are being retracted and/or corrected relating to vitamin D. What can editors and peer reviewers do to handle the deluge of 2SMR studies and the premature application of highly complex MR methods? We advise editors to simply reject papers that only report 2SMR findings, with no additional supporting evidence. For reviewers receiving such papers, we provide a template for rejection. In addition, reviewers should demand rigorous testing of novel methods, including through the use of positive and negative controls before they are applied. Rejecting non-contributory 2SMR papers and imposing intensive scrutiny to novel methods is crucial if the scientific community is to reclaim MR. [ABSTRACT FROM AUTHOR]

Background: Unhealthy diet is a key risk factor for Non-Communicable Diseases (NCDs) that contribute to increased morbidity and premature mortality. With increased computer literacy and mobile phone penetration, there is a high opportunity for mobile application-based interventions. The current study was conducted to develop a mobile application to monitor dietary intake and to assess its acceptability and effectiveness in diet control compared to a similar paper-based intervention. A mobile application was developed based on research evidence and opinions of local experts. The mobile application was introduced to a selected group of office workers who were in preparation, action, and maintenance stages of the Trans Theoretical Model (TTM) and a paper-based intervention was used as the comparator. Socio-demographic data were collected through a self-administered questionnaire. Participants were followed up for three months for adherence. The effectiveness of interventions was assessed at the end of three months by comparing the progressive change in the stage of change and the change from unhealthy to healthy dietary intake between two groups as primary and secondary outcomes respectively. Results: Among 123 office workers who participated in the study, 19.5% preferred the mobile intervention over the paper-based intervention. Younger, unmarried office workers and those who do not have children, had a higher acceptance for the mobile intervention (p < 0.05). There was no difference in adherence (in all three months) or outcomes between the two groups of intervention. Conclusion and recommendations: Mobile application-based interventions are better accepted among the young age group and further studies are recommended to explore their applicability. Trial registration: The study was registered in the Sri Lankan Clinical Trial Registry (Registration No. SLCTR/2020/025; Date 15th December 2020). [ABSTRACT FROM AUTHOR]

Software that employs screening prioritization through active learning (AL) has accelerated the screening process significantly by ranking an unordered set of records by their predicted relevance. However, failing to find a relevant paper might alter the findings of a systematic review, highlighting the importance of identifying elusive papers. The time to discovery (TD) measures how many records are needed to be screened to find a relevant paper, making it a helpful tool for detecting such papers. The main aim of this project was to investigate how the choice of the model and prior knowledge influence the TD values of the hard-to-find relevant papers and their rank orders. A simulation study was conducted, mimicking the screening process on a dataset containing titles, abstracts, and labels used for an already published systematic review. The results demonstrated that AL model choice, and mostly the choice of the feature extractor but not the choice of prior knowledge, significantly influenced the TD values and the rank order of the elusive relevant papers. Future research should examine the characteristics of elusive relevant papers to discover why they might take a long time to be found. [ABSTRACT FROM AUTHOR]

Emergency general surgeons often provide care to severely ill patients requiring surgical interventions and intensive support. One of the primary drivers of morbidity and mortality is perioperative bleeding. In general, when addressing life threatening haemorrhage, blood transfusion can become an essential part of overall resuscitation. However, under all circumstances, indications for blood transfusion must be accurately evaluated. When patients decline blood transfusions, regardless of the reason, surgeons should aim to provide optimal care and respect and accommodate each patient's values and target the best outcome possible given the patient's desires and his/her clinical condition. The aim of this position paper was to perform a review of the existing literature and to provide comprehensive recommendations on organizational, surgical, anaesthetic, and haemostatic strategies that can be used to provide optimal peri-operative blood management, reduce, or avoid blood transfusions and ultimately improve patient outcomes. [ABSTRACT FROM AUTHOR]

Background: In low-middle income countries, healthcare providers primarily use paper health records for capturing data. Paper health records are utilized predominately due to the prohibitive cost of acquisition and maintenance of automated data capture devices and electronic medical records. Data recorded on paper health records is not easily accessible in a digital format to healthcare providers. The lack of real time accessible digital data limits healthcare providers, researchers, and quality improvement champions to leverage data to improve patient outcomes. In this project, we demonstrate the novel use of computer vision software to digitize handwritten intraoperative data elements from smartphone photographs of paper anesthesia charts from the University Teaching Hospital of Kigali. We specifically report our approach to digitize checkbox data, symbol-denoted systolic and diastolic blood pressure, and physiological data. Methods: We implemented approaches for removing perspective distortions from smartphone photographs, removing shadows, and improving image readability through morphological operations. YOLOv8 models were used to deconstruct the anesthesia paper chart into specific data sections. Handwritten blood pressure symbols and physiological data were identified, and values were assigned using deep neural networks. Our work builds upon the contributions of previous research by improving upon their methods, updating the deep learning models to newer architectures, as well as consolidating them into a single piece of software. Results: The model for extracting the sections of the anesthesia paper chart achieved an average box precision of 0.99, an average box recall of 0.99, and an mAP0.5-95 of 0.97. Our software digitizes checkbox data with greater than 99% accuracy and digitizes blood pressure data with a mean average error of 1.0 and 1.36 mmHg for systolic and diastolic blood pressure respectively. Overall accuracy for physiological data which includes oxygen saturation, inspired oxygen concentration and end tidal carbon dioxide concentration was 85.2%. Conclusions: We demonstrate that under normal photography conditions we can digitize checkbox, blood pressure and physiological data to within human accuracy when provided legible handwriting. Our contributions provide improved access to digital data to healthcare practitioners in low-middle income countries. [ABSTRACT FROM AUTHOR]

Background: Undocumented immigrants face many obstacles in accessing emergency healthcare. Legal uncertainties, economic constraints, language differences, and cultural disparities lead to delayed medical care and thereby exacerbate health inequities. Addressing the healthcare needs of this vulnerable group is crucial for both humanitarian and public health reasons. Comprehensive strategies are needed to ensure equitable health outcomes. Objective: This study aimed to identify and analyze the barriers undocumented immigrants face in accessing emergency healthcare services and the consequences on health outcomes. Methods: We used a scoping review methodology that adhered to established frameworks. Utilizing MEDLINE/PubMed, Embase, Web of Science, PsychoInfo, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL), we identified 153 studies of which 12 focused on the specific challenges that undocumented immigrants encounter when accessing emergency healthcare services based on the inclusion and exclusion criteria. Results: The results show that undocumented immigrants encounter significant barriers to emergency healthcare, including legal, financial, linguistic, and cultural challenges. Key findings were the extensive use of emergency departments as primary care due to lack of insurance and knowledge of alternatives, challenges faced by health professionals in providing care to undocumented migrants, increased hospitalizations due to severe symptoms and lack of healthcare access among undocumented patients, and differences in emergency department utilization between irregular migrants and citizens. The findings also serve as a call for enhanced healthcare accessibility and the dismantling of existing barriers to mitigate the adverse effects on undocumented immigrants' health outcomes. Conclusions: Undocumented immigrants' barriers to emergency healthcare services are complex and multifaceted and therefore require multifaceted solutions. Policy reforms, increased healthcare provider awareness, and community-based interventions are crucial for improving access and outcomes for this vulnerable population. Further research should focus on evaluating the effectiveness of these interventions and exploring the broader implications of healthcare access disparities. [ABSTRACT FROM AUTHOR]

Gray mold of roses, caused by the necrotrophic fungal pathogen Botrytis cinerea, is an economically notorious disease and a well-known economic menace, leading to substantial annual losses estimated at no less than 30% of production. This disease takes a toll not only on the marketability of cut rose flowers but also on consumer and importer confidence due to the unsightly symptoms it induces. This fungus influences the rose foliage throughout cultivation, transportation, storage, and marketing. The interplay of conducive environmental conditions and genetic factors plays significant roles in developing the rose gray mold on rose flowers during the pre- and post-harvest phases. Nevertheless, the molecular mechanisms underlying B. cinerea-rose interactions are poorly understood, and the knowledge of how rose plants defend themselves against B. cinerea infection is not comprehensively investigated. It is worth noting that breeding for resistance to discover genetically resistant roses toward gray mold was unsuccessful despite research conducted over the past century. Consequently, synthetic fungicides remain the primary approach to controlling Botrytis blight in roses during the pre- and post-harvest stages. However, this measure has several drawbacks, including the emergence of fungicide-resistant B. cinerea and endangering human and animal health due to chemical residues in the food chain. This review aims to offer a comprehensive update on recent research findings on the biology and management of B. cinerea infection in roses and to propose novel strategies for managing gray mold disease. [ABSTRACT FROM AUTHOR]

Small extracellular vesicle–derived microRNAs (sEV-miRNAs) have emerged as promising noninvasive biomarkers for early cancer diagnosis. Herein, we developed a molecular probe based on three-dimensional (3D) multiarmed DNA tetrahedral jumpers (mDNA-Js)-assisted DNAzyme activated by Na+, combined with a disposable paper-based electrode modified with a Zr-MOF–rGO–Au NP nanocomplex (ZrGA) to fabricate a novel biosensor for sEV-miRNAs Assay. Zr-MOF tightly wrapped by rGO was prepared via a one-step method, and it effectively aids electron transfer and maximizes the effective reaction area. In addition, the mechanically rigid, and nanoscale-addressable mDNA-Js assembled from the bottom up ensure the distance and orientation between fixed biological probes as well as avoid probe entanglement, considerably improving the efficiency of molecular hybridization. The fabricated bioplatform achieved the sensitive detection of sEV-miR-21 with a detection limit of 34.6 aM and a dynamic range from100 aM to 0.2 µM. In clinical blood sample tests, the proposed bioplatform showed results highly consistent with those of qRT-PCRs and the signal increased proportionally with the NSCLC staging. The proposed biosensor with a portable wireless USB-type analyzer is promising for the fast, easy, low-cost, and highly sensitive detection of various nucleic acids and their mutation derivatives, making it ideal for POC biosensing. [ABSTRACT FROM AUTHOR]

Background : The current UK standard for major trauma patients is to record notes in a paper trauma booklet. Through an innovative collaboration between a major trauma centre and a digital transformation industry partner, a TraumaApp was developed. Electronic notes have been shown to have fewer errors, granular data collection and enable time stamped contemporaneous record keeping. Implementation of digital clinical records presents a challenge within the context of trauma multidisciplinary trauma resuscitation. Data can be easily accessible and shared for quality improvement, audit and research purposes. This study compared paper and electronic notes for completeness and for acceptability data following the implementation of the TraumaApp. Methods: Trauma team members who performed scribe function attended training for the newly launched TraumaApp. Two staff members acted as scribe, using either the paper trauma booklet or TraumaApp, and attended major trauma calls. A framework for comparison of paper and electronic notes was created and used for a retrospective review of major trauma patients' notes. Statistical analysis was performed using a two-tailed t-test. Staff using the TraumaApp completed a System Usability Score questionnaire. Results: There was a total of 37 data points for collection per case. The mean numbers collected were paper notes 24.1 of 37 (65.1%) and electronic notes, 25.7 of 37 (69.5%). There was no statistical significance between the completeness of paper and electronic notes. The mean System Usability Score was 68.4. Discussion: Recording accurate patient information during a major trauma call can be challenging and the role of the scribe to accurately record events is critical for immediate and future care. There was no statistically significant difference in completeness of paper and electronic notes, however the mean System Usability Score was 68.4, which is greater than the internationally validated standard of acceptable usability. Conclusion: It is feasible to introduce digital data collection tools enabling accurate record keeping during trauma resuscitation and improve information sharing between clinicians. [ABSTRACT FROM AUTHOR]

Background: Academic paper writing holds significant importance in the education of medical students, and poses a clear challenge for those whose first language is not English. This study aims to investigate the effectiveness of employing large language models, particularly ChatGPT, in improving the English academic writing skills of these students. Methods: A cohort of 25 third-year medical students from China was recruited. The study consisted of two stages. Firstly, the students were asked to write a mini paper. Secondly, the students were asked to revise the mini paper using ChatGPT within two weeks. The evaluation of the mini papers focused on three key dimensions, including structure, logic, and language. The evaluation method incorporated both manual scoring and AI scoring utilizing the ChatGPT-3.5 and ChatGPT-4 models. Additionally, we employed a questionnaire to gather feedback on students' experience in using ChatGPT. Results: After implementing ChatGPT for writing assistance, there was a notable increase in manual scoring by 4.23 points. Similarly, AI scoring based on the ChatGPT-3.5 model showed an increase of 4.82 points, while the ChatGPT-4 model showed an increase of 3.84 points. These results highlight the potential of large language models in supporting academic writing. Statistical analysis revealed no significant difference between manual scoring and ChatGPT-4 scoring, indicating the potential of ChatGPT-4 to assist teachers in the grading process. Feedback from the questionnaire indicated a generally positive response from students, with 92% acknowledging an improvement in the quality of their writing, 84% noting advancements in their language skills, and 76% recognizing the contribution of ChatGPT in supporting academic research. Conclusion: The study highlighted the efficacy of large language models like ChatGPT in augmenting the English academic writing proficiency of non-native speakers in medical education. Furthermore, it illustrated the potential of these models to make a contribution to the educational evaluation process, particularly in environments where English is not the primary language. [ABSTRACT FROM AUTHOR]