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Alzheimers Disease (AD) is marked by pronounced sex differences in pathophysiology and progression. However, the field has yet to fully recognize AD as a womens health issue, delaying the development of targeted preventative strategies and treatments. This perspective explores the elements impacting AD in women, identifying sex specificity in risk factors, highlighting new diagnostic approaches with electronic health records, and reviewing key molecular studies to underscore the need for integrative precision medicine approaches. Established AD risk factors such as advancing age, the apolipoprotein E4 allele, and poorer cardiovascular health affect women differently. We also shed light on sociocultural risk factors, focusing on the gender disparities that may play a role in AD development. From a biological perspective, sex differences in AD are apparent in biomarkers and transcriptomics, further emphasizing the need for targeted diagnostics and treatments. The convergence of novel multiomics data and cutting-edge computational tools provides a unique opportunity to study the molecular underpinnings behind sex dimorphism in AD. Thus, precision medicine emerges as a promising framework for understanding AD pathogenesis through the integration of genetics, sex, environment, and lifestyle. By characterizing AD as a womens health challenge, we can catalyze a transformative shift in AD research and care, marked by improved diagnostic accuracy, targeted interventions, and ultimately, enhanced clinical outcomes.

Samiah Shahid,1,2 Ayesha Khan,1 Wajeehah Shahid,3 Mehvesh Rehan,2 Roha Asif,1 Haseeb Nisar,4 Qudsia Kanwal,5 Jeong Ryeol Choi6 1Research Centre for Health Sciences (RCHS), The University of Lahore, Lahore, Pakistan; 2Institute of Molecular Biology and Biotechnology (IMBB), The University of Lahore, Lahore, Pakistan; 3Department of Physics, The University of Lahore, Lahore, Pakistan; 4School of Life Sciences, University of Management and Technology, Lahore, Pakistan; 5Department of Chemistry, The University of Lahore, Lahore, Pakistan; 6School of Electronic Engineering, Kyonggi University, Suwon, Kyeonggi-do, 16227, Republic of KoreaCorrespondence: Samiah Shahid, Research Centre for Health Sciences (RCHS), Associate Professor, Institute of Molecular Biology and Biotechnology (IMBB), The University of Lahore, Lahore, 54590, Pakistan, Email samiah.shahid@yahoo.com Jeong Ryeol Choi, School of Electronic Engineering, Kyonggi University, Suwon, Kyeonggi-do, 16227, Republic of Korea, Email choiardor@hanmail.netAbstract: Breast and ovarian cancers, despite having chemotherapy and surgical treatment, still have the lowest survival rate. Experimental stages using nanoenzymes/nanozymes for ovarian cancer diagnosis and treatment are being carried out, and correspondingly the current treatment approaches to treat breast cancer have a lot of adverse side effects, which is the reason why researchers and scientists are looking for new strategies with less side effects. Nanoenzymes have intrinsic enzyme-like activities and can reduce the shortcomings of naturally occurring enzymes due to the ease of storage, high stability, less expensive, and enhanced efficiency. In this review, we have discussed various ways in which nanoenzymes are being used to diagnose and treat breast and ovarian cancer. For breast cancer, nanoenzymes and their multi-enzymatic properties can control the level of reactive oxygen species (ROS) in cells or tissues, for example, oxidase (OXD) and peroxidase (POD) activity can be used to generate ROS, while catalase (CAT) or superoxide dismutase (SOD) activity can scavenge ROS. In the case of ovarian cancer, most commonly nanoceria is being investigated, and also when folic acid is combined with nanoceria there are additional advantages like inhibition of beta galactosidase. Nanocarriers are also used to deliver small interfering RNA that are effective in cancer treatment. Studies have shown that iron oxide nanoparticles are actively being used for drug delivery, similarly ferritin carriers are used for the delivery of nanozymes. Hypoxia is a major factor in ovarian cancer, therefore MnO2-based nanozymes are being used as a therapy. For cancer diagnosis and screening, nanozymes are being used in sonodynamic cancer therapy for cancer diagnosis and screening, whereas biomedical imaging and folic acid gold particles are also being used for image guided treatments. Nanozyme biosensors have been developed to detect ovarian cancer. This review article summarizes a detailed insight into breast and ovarian cancers in light of nanozymes-based diagnostic and therapeutic approaches. Keywords: breast cancer, ovarian cancer, nanoenzymes, diagnosis, treatment

Background: Pancreatic neuroendocrine tumors (P-NETs) constitute a subset of pancreatic mass lesions characterized by diverse clinical presentations. Despite their inherent malignant potential, the timely identification and treatment of these tumors are critical for achieving favorable clinical outcomes. This study aims to shed light on the heterogeneous tumor biology of P-NETs and the management strategies employed at a tertiary care center in Pakistan.Method: A retrospective study encompassing all patients with a biopsy-confirmed diagnosis of P-NETs at Shifa International Hospital between January 1st, 2016, and June 30th, 2021, was conducted. Meticulous data extraction from pathology records and thorough searches of medical records were performed to gather relevant demographic and clinical information.Results: A total of 24 patients were retrieved from our database, with 13 (54%) female patients. The mean age was 49.5 ± 16.3 years. Eight out of the 24 patients presented with abdominal pain. Most patients (14 out of 24) had lesions in the pancreatic head region. In three cases, lesions exhibited multicentricity. The mean lesion size measured 4.4 ± 2.3 cm. Three of the 24 patients displayed distant liver metastasis at the presentation time. 19 out of the 24 patients underwent surgical resections, while endoscopic ultrasound (EUS)-guided biopsy was performed in 4 out of 24 cases. EUS-guided tissue biopsy yielded accurate diagnoses in all four cases.Conclusion: Most P-NETs are non-functional, and there is an almost equal distribution between male and female patients. Solitary lesions predominate, and metastasis is uncommon at initial presentation. EUS-guided fine needle biopsy stands out as a dependable diagnostic modality for P-NETs.

Objective: This study aims to diagnose Rotator Cuff Tears (RCT) and classify the severity of RCT in patients with Osteoporosis (OP) through the analysis of shoulder joint anteroposterior (AP) X-ray-based localized proximal humeral bone mineral density (BMD) measurements and clinical information based on machine learning (ML) models. Methods: A retrospective cohort of 89 patients was analyzed, including 63 with both OP and RCT (OPRCT) and 26 with OP only. The study analyzed a series of shoulder radiographs from April 2021 to April 2023. Grayscale values were measured after plotting ROIs based on AP X-rays of shoulder joint. Five kinds of ML models were developed and compared based on their performance in predicting the occurrence and severity of RCT from ROIs' greyscale values and clinical information (age, gender, advantage side, lumbar BMD, and acromion morphology (AM)). Further analysis using SHAP values illustrated the significant impact of selected features on model predictions. Results: R1-6 had a positive correlation with BMD respectively. The nine variables, including greyscale R1-6, age, BMD, and AM, were used in the prediction models. The RF model was determined to be superior in effectively diagnosing RCT in OP patients, with high AUC scores of 0.998, 0.889, and 0.95 in the training, validation, and testing sets, respectively. SHAP values revealed that the most influential factors on the diagnostic outcomes were the grayscale values of all cancellous bones in ROIs. A column-line graph prediction model based on nine variables was constructed, and DCA curves indicated that RCT prediction in OP patients was favored based on this model. Furthermore, the RF model was also the most superior in predicting the types of RCT within the OPRCT group, with an accuracy of 86.364% and 73.684% in the training and test sets, respectively. SHAP values indicated that the most significant factor affecting the predictive outcomes was the AM, followed by the grayscale values of the greater tubercle, among others. Conclusions: ML models, particularly the RF algorithm, show significant promise in diagnosing RCT occurrence and severity in OP patients using conventional shoulder X-rays based on the nine variables. This method presents a cost-effective, accessible, and non-invasive diagnostic strategy that has the potential to substantially enhance the early detection and management of RCT in OP patient population.

Myocarditis is a cardiovascular disease characterised by inflammation of the heart muscle which can lead to heart failure. There is heterogeneity in the mode of presentation, underlying aetiologies, and clinical outcome with impact on a wide range of age groups which lead to diagnostic challenges. Cardiovascular magnetic resonance (CMR) is the preferred imaging modality in the diagnostic work-up of those with acute myocarditis. There is a need for systematic analytical approaches to improve diagnosis. Artificial intelligence (AI) and machine learning (ML) are increasingly used in CMR and has been shown to match human diagnostic performance in multiple disease categories. In this review article, we will describe the role of CMR in the diagnosis of acute myocarditis followed by a literature review on the applications of AI and ML to diagnose acute myocarditis. Only a few papers were identified with limitations in cases and control size and a lack of detail regarding cohort characteristics in addition to the absence of relevant cardiovascular disease controls. Furthermore, often CMR datasets did not include contemporary tissue characterisation parameters such as T1 and T2 mapping techniques, which are central to the diagnosis of acute myocarditis. Future work may include the use of explainability tools to enhance our confidence and understanding of the machine learning models with large, better characterised cohorts and clinical context improving the diagnosis of acute myocarditis.

Globally, cardiovascular diseases stand as the primary cause of mortality. In response to the imperative to enhance operational efficiency and reduce expenses, healthcare organizations are currently undergoing a transformation. The incorporation of analytics into their IT strategy is vital for the successful execution of this transition. The approach involves consolidating data from various sources into a data lake, which is then leveraged with analytical models to revolutionize predictive analytics. The deployment of IoT-based predictive systems is aimed at diminishing mortality rates, particularly in the domain of coronary heart disease prognosis. However, the abundant and diverse nature of data across various disciplines poses significant challenges in terms of data analysis, extraction, management, and configuration within these large-scale data technologies and tools. In this context, a multi-level fuzzy rule generation approach is put forward to identify the characteristics necessary for heart disease prediction. These features are subsequently trained using an optimized recurrent neural network. Medical professionals assess and categorize the features into labeled classes based on the perceived risk. This categorization allows for early diagnosis and prompt treatment. In comparison to conventional systems, the proposed method demonstrates superior performance.

Objective: To assess the frequency and factors related to the presence of 17p deletion among patients diagnosed with chronic lymphocytic leukaemia at the Oncology Department of Combined Military Hospital Rawalpindi Study Design: Cross-sectional study. Setting And Duration Of Study: Oncology Department, Combined Military Hospital, Rawalpindi Pakistan, Feb 2020 to Mar 2021. Methodology: Patients with Chronic lymphocytic leukaemia were recruited for the study. The fluorescence in situ hybridization method was used to look for the presence of 17p deletion, using 10% cells as a cut-off value. Demographics, treatment status, and β2-microglobulin levels were correlated with 17p deletion in our study population. Results: A total of 102 patients diagnosed with Chronic Lymphocytic leukaemia were included in the analysis. The mean age of the patients was 55.82±7.176 years.74(72.5%) were male, while 28(27.5%) patients diagnosed with this condition were female. 17p deletion was present in 16(15.7%) patients, while 86(84.3%) patients were not detected with 17p deletion. Elevatedβ2-microglobulin levels were strongly related to 17p deletion in our target population (p-value-0.005). Conclusion: 17p deletion was a fairly common finding among patients of chronic lymphocytic leukaemia presenting to our department. Patients with elevated β2-microglobulin levels were more at risk of having this genetic mutation than those with normal β2-microglobulin levels.

Plasmodium knowlesi is a parasite that can spread from animals to humans. Over the past 20 years, scientists have become more and more interested in this parasite. This parasitic zoonotic infection is common in Southeast Asia, and 6-9 % of symptomatic adult who get it have severe symptoms. In this review paper, we will discuss recent and past studies on P. knowlesi. Additionally, we will describe the epidemiology, clinical aspects, diagnosis, and therapy of this infectious disease. In addition to this, we concentrate on the difficulties associated with the prevention and management of this important parasitic zoonotic disease.

Background & Aims: While cholangiocarcinoma (CCA) incidence and mortality rates are increasing globally, whether there are regional/temporal variations in these rates for different biliary tract cancer (BTC) subtypes, or whether they differ by sex, socioeconomic status, or route to diagnosis (RtD) remains unknown. In this work, we aimed to perform an in-depth analysis of data on the incidence, mortality, survival and RtD of CCA and other BTCs. Methods: Data on all BTCs diagnosed in England between 2001 and 2018 were extracted from NHS Digital’s National Cancer Registration Dataset. Age-standardised incidence rates (ASRs), mortality rates (ASMRs) and net survival rates were calculated, and Kaplan-Meier overall survival estimates and RtD trends were analysed. Analyses were stratified by sex, socioeconomic deprivation, tumour subtype and region. Results: The ASR for CCA rose from 2.9 in 2001-2003 to 4.6 in 2016-2018 and from 1.0 to 1.8 for gallbladder cancers (GBCs). ASMR trends mirror those of incidence, with most deaths due to iCCA. Over 20% of patients with CCA were under 65 years old. The ASRs and ASMRs were consistently higher in the most socioeconomically deprived group for CCA and GBC. The most common RtD was the emergency route (CCA 49.6%, GBC 46.2% and ampulla of Vater cancer 43.0%). The least deprived patients with CCA and ampulla of Vater cancer had better overall survival (p

Key Clinical Message This study paper's main goal is to report rare cases of skull base meningiomas that exemplify the complexities of diagnosis, therapy, and postoperative care. By describing these rare cases, we hope to advance knowledge of the clinical signs, difficulties, and prognoses of skull base meningiomas in a challenging anatomical setting. In the posterior cranial fossa, our investigation reveals a unique example of skull base meningioma that involved numerous cranial nerves and complex vasculature. A variety of visual abnormalities were present in the patient's clinical presentations, highlighting the wide range of symptoms that these tumors might cause depending on their precise positions. These cases highlight the critical importance of preoperative imaging, including high‐resolution MRI and angiography, as well as the diagnostic difficulties these tumors pertain. By reporting these instances, our research adds to the body of knowledge about skull base meningiomas and offers insightful information about the nuances of their therapies. Our findings highlight the importance of individualized treatment plans, interdisciplinary cooperation, and the demand for continued study to better comprehend these convoluted tumors. Such studies are essential for advancing our knowledge of these enigmatic tumors, guiding clinical judgment, and eventually improving patient outcomes. These findings are important because they can fill information gaps, improve treatment plans, and encourage additional research in neuro‐oncology. Abstract This study presents a series of three rare cases of skull base meningiomas, emphasizing the complexities in diagnosis, treatment, and postoperative care. The patients' clinical presentations and imaging highlighted the diverse symptoms and challenges associated with these tumors, found in intricate anatomical locations. The cases underscore the crucial role of preoperative high‐resolution imaging and angiography in diagnostic accuracy. Surgical intervention, guided by a multidisciplinary approach, is pivotal in managing these demanding cases. Histopathological examinations confirmed atypical meningiomas. The postoperative phases involved meticulous care to ensure optimal recovery and functional outcomes. Our findings contribute to the understanding of skull base meningiomas, emphasizing the need for personalized treatment plans and ongoing research to improve patient outcomes in neuro‐oncology.

Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, owing to its extreme degree of invasiveness and aggressive inclination. The early occurrences of this cancer can be clinically deceiving leading to a poor overall survival rate. The primary concerns from a clinical perspective include delayed diagnosis, rapid disease progression, resistance to various chemotherapeutic regimens, and aggressive metastasis, which collectively pose a substantial threat to prognosis. Conventional clinical practices observed since antiquity no longer offer the best possible options to circumvent these roadblocks. The world of current cancer research has been revolutionized with the advent of state-of-the-art technology-driven strategies that offer a ray of hope in confronting said challenges by highlighting the crucial underlying molecular mechanisms and drivers. In recent years, bioinformatics and Machine Learning (ML) techniques have enhanced the possibility of early detection, evaluation of prognosis, and individualization of therapy. This review elaborates on the application of the aforesaid techniques in unraveling potential hints from omics big data to address the complexities existing in various clinical facets of oral cancer. The first section demonstrates the utilization of omics data and ML to disentangle the impediments related to diagnosis. This includes the application of technology-based strategies to optimize early detection, classification, and staging via uncovering biomarkers and molecular signatures. Furthermore, breakthrough concepts such as salivaomics-driven non-invasive biomarker discovery and omics-complemented surgical interventions are articulated in detail. In the following part, the identification of novel disease-specific targets alongside potential therapeutic agents to confront oral cancer via omics-based methodologies is presented. Additionally, a special emphasis is placed on drug resistance, precision medicine, and drug repurposing. In the final section, we discuss the research approaches oriented toward unveiling the prognostic biomarkers and constructing prediction models to capture the metastatic potential of the tumors. Overall, we intend to provide a bird’s eye view of the various omics, bioinformatics, and ML approaches currently being used in oral cancer research through relevant case studies.

Two-dimensional (2D) nanomaterials have garnered enormous attention seemingly due to their unusual architecture and properties. Graphene and graphene oxide based 2D nanomaterials remained the most sought after for several years but the quest to design superior 2D nanomaterials which can find wider application gave rise to development of non-graphene 2D materials as well. Consequently, in addition to graphene based 2D nanomaterials, 2D nanostructures designed using macromolecules (such as DNAs, proteins, peptides and peptoids), transition metal dichalcogenides, transition-metal carbides and/or nitrides (MXene), black phosphorous, chitosan, hexagonal boron nitrides, and graphitic carbon nitride, and covalent organic frameworks have been developed. Interestingly, these 2D nanomaterials have found applications in diagnosis and treatment of various diseases including Alzheimer’s disease (AD). Although AD is one of the most debilitating neurodegenerative conditions across the globe; unfortunately, there remains a paucity of effective diagnostic and/or therapeutic intervention for it till date. In this scenario, nanomaterial-based biosensors, or therapeutics especially 2D nanostructures are emerging to be promising in this regard. This review summarizes the diagnostic and therapeutic platforms developed for AD using 2D nanostructures. Collectively, it is worth mentioning that these 2D nanomaterials would seemingly provide an alternative and intriguing platform for biomedical interventions.

Wilson’s disease is a rare inherited disorder of copper metabolism. If left untreated, it can turn into a multi systemic disease with copper deposition in the liver, brain, and other tissues. Diagnosis of Wilson’s is delayed in Pakistan by many years on average due to variable presentations. In adolescents, the initial signs are more likely to be neuropsychiatric. Here we present a case of Wilson’s disease that presented initially with hepatic symptoms and did not have signs specific to the disease such as Kayser-Fleischer rings. Our case was diagnosed to be Wilson’s Disease only on further investigations and subsequently the patient was treated with chelation therapy using D-Penicillamine.Wilson’s Disease should be kept in mind as a differential diagnosis in adolescent patients that present with unexplained acute liver failure and cytopenias without any neurological symptoms, as a missed diagnosis can prove to be fatal.

Salmonella Typhi infection in a patient in Pakistan initially responded to standard treatment but failed to respond to subsequent treatment. The first strain was susceptible to carbapenems and azithromycin; subsequent strains harbored the NDM-5 gene. Treatment with a combination of intravenous meropenem and colistin was successful. Carbapenem-resistant Salmonella Typhi emergence will hinder treatment.

Genetic skeletal disorders (GSDs) are a large group of rare heterogeneous disorders characterized by abnormal development, remodeling, and growth of the human skeleton's cartilage and bones. GSDs have a high spectrum of phenotypes that range from disproportionate short stature (dwarfism) in childhood to osteoarthritis in old age. According to the latest nosology classification of skeletal dysplasias, 461 disorders under 42 groups are classified according to specific radiographic, clinical, and molecular standards. In addition, correct molecular diagnosis for these rare GSDs is important for genetic and psychological counseling and treatment. GSDs are also associated with many syndromic forms that affect other parts such as hearing, vision, neurological, pulmonary, renal, or cardiac function. This review highlights the importance of GSDs and details a few selected disorders and their management strategies. [JBCGenetics 2023; 6(1.000): 57-69]

Aim Methods Results Conclusions This retrospective study aims to analyse the epidemiology, clinical and neuroimaging features, treatment modalities, and outcomes of paediatric idiopathic intracranial hypertension (IIH) in a tertiary care centre in Australia.Using the International Classification of Diseases Diagnostic Criteria for IIH, we identified and analysed a cohort of children diagnosed with IIH over a 5‐year period (2017–2022). Data on patient demographics, symptomatology, examination findings, investigative results, treatments and outcomes were collected from medical records and electronic health records.A total of 45 cases were analysed. The pre‐pubertal group saw a male predominance and the post‐pubertal a female one. Increased body mass index was an associated comorbidity in majority of patients. Headaches (89%) and visual symptoms (56%) were the most common symptoms, with tinnitus also seen in 20% of patients. Papilledema was detected in 91% of the cases examined. The commonest neuroimaging features were optic nerve sheath distention (78%) and empty sella (49%). Acetazolamide was the primary treatment, with most patients responding well. Only a minority required surgical intervention. Long‐term resolution of headaches was achieved in 89% of patients.The incidence of paediatric IIH in the West Australian population appears relatively high. It presents with subtle symptoms, emphasising the need for increased awareness among health‐care providers. Younger children may represent a distinct subgroup with unique clinical features. Timely diagnosis and aggressive medical management lead to favourable outcomes. However, weight loss interventions showed limited effectiveness. This study underscores the importance of early recognition and management of paediatric IIH to optimise patient outcomes. [ABSTRACT FROM AUTHOR]

Introduction: Vascular malignancies are categorized into benign hemangiomas, malignant angiosarcomas, and tumors of intermediate malignancy. Retiform hemangioendothelioma (RH) is one of the rare diagnoses belonging to the class of intermediate malignancies that was initially diagnosed. Case Presentation: In this case report, we have reported a rare case of RH, a locally aggressive, vascular tumor of malignant potential presenting at an unusual site. The most observed locations of this soft tissue tumor are skin and subcutaneous tissues of extremities; however, this case of RH was observed in an unusual site called pleura, which is a rare occurrence related to this tumor. The presence of cell surface markers like CD31 and ERG of vascular and endothelial origin and the presence of hobnail appearance of endothelial channels on the biopsy profile supported the vascular origin of the tumor; the clinical features and imaging studies further confirmed the diagnosis of RH. Conclusion: In this case report, a rare case of RH with an unusual site of origin was highlighted. RH is a vascular neoplasm; commonly observed sites of this vascular tumor were skin and subcutaneous tissue of the extremities; however, in this case, the site was unusually different, which was the pleura of the left lung. [ABSTRACT FROM AUTHOR]

The recent advancement of nanoparticles (NPs) holds significant potential for treating various ailments. NPs are employed as drug carriers for diseases like cancer because of their small size and increased stability. In addition, they have several desirable properties that make them ideal for treating bone cancer, including high stability, specificity, higher sensitivity, and efficacy. Furthermore, they might be taken into account to permit the precise drug release from the matrix. Drug delivery systems for cancer treatment have progressed to include nanocomposites, metallic NPs, dendrimers, and liposomes. Materials’ mechanical strength, hardness, electrical and thermal conductivity, and electrochemical sensors are significantly improved using nanoparticles (NPs). New sensing devices, drug delivery systems, electrochemical sensors, and biosensors can all benefit considerably from the NPs’ exceptional physical and chemical capabilities. Nanotechnology is discussed in this article from a variety of angles, including its recent applications in the medical sciences for the effective treatment of bone cancers and its potential as a promising option for treating other complex health anomalies via the use of anti-tumour therapy, radiotherapy, the delivery of proteins, antibiotics, and vaccines, and other methods. This also brings to light the role that model simulations can play in diagnosing and treating bone cancer, an area where Nanomedicine has recently been formulated. There has been a recent uptick in using nanotechnology to treat conditions affecting the skeleton. Consequently, it will pave the door for more effective utilization of cutting-edge technology, including electrochemical sensors and biosensors, and improved therapeutic outcomes.

Background: Endometriosis is a chronic, often debilitating condition with a current significant delay from symptom onset to diagnosis with much of this in primary care. Methods: A systematic review and meta-analysis of the primary literature was conducted to investigate the accuracy of symptoms, clinical history and first-line non-invasive tests to predict pelvic endometriosis (PROSPERO: CRD42020187543). We searched Medline, Embase, Web of Science and Scopus from conception (1966; 1972; 1997; 2004 respectively) to September 2022 for primary test accuracy studies assessing non-invasive tests against reference standard diagnosis for endometriosis. Two authors independently conducted data extraction and quality assessment. Grading of evidence was performed using a novel visual pentagon model. Meta-analyses of test accuracy was estimated using bivariate random effects models. Results: The 125 included studies (250,574 participants) showed mixed quality. Studies applying non-surgical (database/self-reporting) reference standard had a greater risk of bias. In 98 studies applying surgical reference standard, summary diagnostic odds ratios for endometriosis were: dysmenorrhoea 2.56 (95% confidence interval 1.99-3.29); pelvic pain 2.56 (1.73-3.74); dyschezia 2.05 (1.36-3.10); dyspareunia 2.45 (1.71-3.52); family history of endometriosis 6.79 (4.08-11.3); nulligravidity of 2.01 (1.62-2.50); body mass index (BMI) ≥30kg/m 2 0.37 (0.19-0.68); trans-vaginal ultrasound scan (TVUSS) endometrioma 91.2 (44.0-189); TVUSS invasive endometriosis 26.1 (9.28-73.5); and cancer antigen-125 (CA-125) >35U/mL 16.0 (8.09-31.7). Sensitivity analysis excluding all high-risk studies found concordant results. Conclusions: This meta-analysis collated the performance of non-invasive tests for endometriosis across a comprehensive and geographically varied population. Study quality was mixed, however results were consistent with high-risk studies excluded. These findings will inform future prediction models for triage in primary care.

The chief objective of this study is to employ a predictive software called adaptive neuro-fuzzy inference system (ANFIS) approach which assess stress amongst doctors employing industry 4.0 technology during their surgeries. This study further investigates factors contributing the operation accuracy, sensitivity and specificity amongst doctors. Also, the effective performance of doctors can be optimized through earlier prediction for percentage of incorporating Industry 4.0 technologies. Survey was conducted amongst doctors using industry 4.0 technologies who provided unbiased answers to several queries in the questionnaire. The ANFIS model was employed to predict success rate of surgeries through models build with the aid of several input parameters. The outcomes such as accuracy, sensitivity and specificity were studied while employing Industry 4.0 technology which were considered significant factors influencing the perceived various kinds of surgeries in different domains. Moreover, the results of the ANFIS modelling approach showed that with increase in percentage of industry 4.0 machines in medical equipment, the operations sensitivity and accuracy increased, hence the most critical predictors. While specificity did not have any major impact on the surgeries. Henceforth, doctors can take preventive actions and simultaneously plan their work load with the aid of industry 4.0, providing better health benefits to patients making the healthcare industry much more efficient and stress-free.

Delirium, a common and serious disorder in older hospitalized patients, remains underrecognized. While several delirium predictive models have been developed, only a handful have focused on electronic health record (EHR) data. This prospective cohort study of older inpatients (≥ 65 years old) aimed to determine if variables within our health system’s EHR could be used to identify delirium among hospitalized patients at the bedside. Trained researchers screened daily for delirium using the 3-minute diagnostic Confusion Assessment Method (3D-CAM). Patient demographic and clinical variables were extracted from the EHR. Among 408 participants, mean age was 75 years, 60.8% were female, and 82.6% were Black. Overall rate of delirium was 16.7%. Patients with delirium were older and more likely to have an infection diagnosis, prior dementia, higher Charlson comorbidity severity of illness score, lower Braden Scale score, and higher Morse Fall Scale score in the EHR (P < 0.01 for all). On multivariable analysis, a prior diagnosis of dementia (odds ratio: 5.0, 95% CI: 2.5–10.3) and a Braden score of < 18 (odds ratio: 2.8, 95% CI: 1.5–5.1) remained significantly associated with delirium among hospitalized patients. Further research in the development of an automated delirium prediction model is needed.

Background: Peripheral artery disease (PAD) involves atherosclerosis of the lower extremity arteries and is a major contributor to limb loss and death worldwide. Several studies have demonstrated that interleukins (ILs) play an important role in the development and progression of PAD; however, a comprehensive literature review has not been performed. Methods: A systematic review was conducted and reported according to PRISMA guidelines. MEDLINE was searched from inception to 5 December 2022, and all studies assessing the association between ILs and PAD were included. Results: We included 17 studies from a pool of 771 unique articles. Five pro-inflammatory ILs (IL-1β, IL-2, IL-5, IL-6, and IL-8) and one pro-atherogenic IL (IL-12) were positively correlated with PAD diagnosis and progression. In contrast, two anti-inflammatory ILs (IL-4 and IL-10) were protective against PAD diagnosis and adverse limb events. Specifically, IL-6 and IL-8 were the most strongly associated with PAD and can act as potential disease biomarkers to support the identification and treatment of PAD. Conclusions: Ongoing work to identify and validate diagnostic/prognostic inflammatory biomarkers for PAD has the potential to assist clinicians in identifying high-risk patients for further evaluation and management which could reduce the risk of adverse cardiovascular and limb events.

Prompt diagnostics and appropriate cancer therapy necessitate the use of gene expression databases. The integration of analytical methods can enhance detection precision by capturing intricate patterns and subtle connections in the data. This study proposes a diagnostic-integrated approach combining Empirical Bayes Harmonization (EBS), Jensen–Shannon Divergence (JSD), deep learning, and contour mathematics for cancer detection using gene expression data. EBS preprocesses the gene expression data, while JSD measures the distributional differences between cancerous and non-cancerous samples, providing invaluable insights into gene expression patterns. Deep learning (DL) models are employed for automatic deep feature extraction and to discern complex patterns from the data. Contour mathematics is applied to visualize decision boundaries and regions in the high-dimensional feature space. JSD imparts significant information to the deep learning model, directing it to concentrate on pertinent features associated with cancerous samples. Contour visualization elucidates the model’s decision-making process, bolstering interpretability. The amalgamation of JSD, deep learning, and contour mathematics in gene expression dataset analysis diagnostics presents a promising pathway for precise cancer detection. This method taps into the prowess of deep learning for feature extraction while employing JSD to pinpoint distributional differences and contour mathematics for visual elucidation. The outcomes underscore its potential as a formidable instrument for cancer detection, furnishing crucial insights for timely diagnostics and tailor-made treatment strategies.

Introduction: Breast Implant-Associated Anaplastic Large Cell Lymphoma (BIA-ALCL) commonly presents as a peri-implant effusion (seroma). CD30 (TNFRSF8) is a consistent marker of tumor cells but also can be expressed by activated lymphocytes in benign seromas. Diagnosis of BIA-ALCL currently includes cytology and detection of CD30 by immunohistochemistry or flow cytometry, but these studies require specialized equipment and pathologists’ interpretation. We hypothesized that a CD30 lateral flow assay (LFA) could provide a less costly rapid test for soluble CD30 that eventually could be used by non-specialized personnel for point-of-care diagnosis of BIA-ALCL. Methods: We performed LFA for CD30 and enzyme-linked immunosorbent assay (ELISA) for 15 patients with pathologically confirmed BIA-ALCL and 10 patients with benign seromas. To determine the dynamic range of CD30 detection by LFA, we added recombinant CD30 protein to universal buffer at seven different concentrations ranging from 125 pg/mL to 10,000 pg/mL. We then performed LFA for CD30 on cryopreserved seromas of 10 patients with pathologically confirmed BIA-ALCL and 10 patients with benign seromas. Results: Recombinant CD30 protein added to universal buffer produced a distinct test line at concentrations higher than 1000 pg/mL and faint test lines at 250–500 pg/mL. LFA produced a positive test line for all BIA-ALCL seromas undiluted and for 8 of 10 malignant seromas at 1:10 dilution, whereas 3 of 10 benign seromas were positive undiluted but all were negative at 1:10 dilution. Undiluted CD30 LFA had a sensitivity of 100.00%, specificity of 70.00%, positive predictive value of 76.92%, and negative predictive value of 100.00% for BIA-ALCL. When specimens were diluted 1:10, sensitivity was reduced to 80.00% but specificity and positive predictive values increased to 100.00%, while negative predictive value was reduced to 88.33%. When measured by ELISA, CD30 was below 1200 pg/mL in each of six benign seromas, whereas seven BIA-ALCL seromas contained CD30 levels > 2300 pg/mL, in all but one case calculated from dilutions of 1:10 or 1:50. Conclusions: BIA-ALCL seromas can be distinguished from benign seromas by CD30 ELISA and LFA, but LFA requires less time (

Avian influenza, commonly called bird flu, is highly contagious and pandemic zoonosis of global importance, primarily affecting birds and other mammals, including humans. The present review is intended to highlight a report on the prevalence of avian influenza in humans and different bird species of Indonesia.The study is based on 27 scientific articles from 2004 to May 2021 in which the prevalence of avian influenza is determined mainly by the following molecular, virological, and serological tests: polymerase chain reaction (PCR), hemagglutination inhibition (HI), enzyme-linked immunosorbent assay (ELISA), and ®Rapid antigen detection test. A vast divergence in the prevalence of avian influenza was observed due to the diversity in sensitivity and specificity of the tests applied. The prevalence of avian influenza varies due to spatial and temporal factors, bird species, and breed differences. An average maximum prevalence (25%)) was found in poultry (domestic and commercial birds) as compared to ducks (20.13%) and other birds (10.66%). An average documented prevalence (16.3%) was found in humans. Birds sold in live bird markets showed maximum prevalence due to different geographical distribution. The already published studies dissection illustrates that avian influenza infects all types of birds and humans in Indonesia. A proper surveillance system, effective vaccination plan, and segregation and culling strategy regarding avian influenza-infected birds are desperately needed to eradicate avian influenza in Indonesia.

A multitargeted loop-mediated isothermal amplification (MT-LAMP) assay targeting mpt64 (Rv1980c) and IS6110 was designed to diagnose genitourinary tuberculosis (GUTB) cases. While assessing gel-based, hydroxynaphthol blue (HNB) and SYBR Green I MT-LAMP assays on GUTB specimens (n = 28) in a pilot study, both gel-based/SYBR Green I assays exhibited better sensitivity than HNB LAMP. Since SYBR Green MT-LAMP is easier to perform compared with a gel-based assay, a higher number of GUTB specimens (n = 55) were evaluated by SYBR Green MT-LAMP, wherein 85.5% sensitivity and 94.4% specificity (n = 36) were obtained. Moreover, the sensitivity attained by MT-LAMP was significantly higher (p

Tuberculosis (TB) is one of the major global public health concerns particularly affecting population of lowincome countries. Early detection of disease coupled with other parameters help in treatment and reducing disease transmission. The current study was conducted to assess the sensitivity and specificity of the GeneXpert MTB/RIF (Cepheid Sunnyvale, CA, United States) in comparison to conventional techniques used for the diagnosis of TB. Our study is one of the first ones from Pakistan investigating and assessing the performance of GeneXpert. We recruited eight hundred clinically TB suspects initially and included seven hundred and sixteen clinically TB suspects in the final analysis. The results of GeneXpert were compared with Mycobacteria Growth Indicator Tube (MGIT) and Ziehl-Neelsen (ZN) staining. In comparison to MGIT and ZN staining the sensitivity of GeneXpert with 95 % confidence interval (CI) was (99.7 %, CI 0.98-0.99) and (95.1 %, CI 0.92-0.97) respectively. The positive and negative predictive values with 95 % CI were (97.1 %, CI 0.94-0.98) and (99.7 %, CI 0.98-0.99) when results of GeneXpert were compare with MGIT results. The results of this study confirm the performance of GeneXpert. With high sensitivity and rapid detection, GeneXpert is ready to be considered as preferred diagnostic tool for TB. [ABSTRACT FROM AUTHOR]

Sustainable development relies heavily on a food system that is both safe and secure. Several approaches may lead to sustainability and food safety. An increase in the cultivation of legume crops is one of the approaches for enhancing agricultural viability and ensuring adequate food supply. Legumes may increase daily intake of fiber, folate, and protein as substitutes for meat and dairy. They are also crucial in various intercropping systems worldwide. However, legume production has been hampered by Rhizoctonia solani due to its destructive lifestyle. R. solani causes blights, damping off, and rotting diseases in legume crops. Our knowledge of the global distribution of R. solani associated with legume crops (alfalfa, soybean, chickpea, pea, lentil, common bean, and peanut), detection, diagnosis, and management of legume crops diseases caused by R. solani is limited. Traditional approaches rely on the incubation of R. solani, visual examination of symptoms on host legume crops, and microscopy identification. However, these approaches are time-consuming, require technical expertise, fail to detect a minimal amount of inoculum, and are unreliable. Biochemical and molecular-based approaches have been used with great success recently because of their excellent sensitivity and specificity. Along with conventional PCR, nested PCR, multiplex PCR, real-time PCR, magnetic-capture hybridization PCR, and loop-mediated isothermal amplification have been widely used to detect and diagnose R. solani. In the future, Next-generation sequencing will likely be used to a greater extent to detect R. solani. This review outlines global distribution, survival, infection and disease cycle, traditional, biochemical, molecular, and next-generation sequencing detection and diagnostic approaches, and an overview of the resistant resources and other management strategies to cope with R. solani.

Abstract Our case highlights the occurrence of severe cutaneous adverse reactions with flurbiprofen use and alerts physicians to its odds with safer drugs.