Rapunzel syndrome and gastric Peutz Jeghers (hamartomatous) polyps: case report

Rapunzel syndrome is an extremely rare complication of a trichobezoar. These females have a history of trichophagia and trichotillomania. Peutz Jeghers syndrome (PJS) is an uncommon autosomal dominant syndrome with a variable to high penetrance that leads to the development of the polyps within the gastrointestinal mucosa. This case report of a 25-year-old deaf and dumb female presented with pain and lump in upper abdomen, vomiting, nausea, loss of appetite, loss of weight. An exploratory laparotomy with anterior gastrotomy was performed and a giant trichobezoar with tail extending into the duodenum was removed. There were multiple polyps in the lower stomach excised. Histopathology reports showed Peutz Jeghers (hamartomatous polyps). She recovered well and was discharged on the 10th day. Patient was advised regular follow up

Association of TLR2 and TLR6 gene polymorphism with Trichomoniasis vaginalis Infection

Background: Toll-like receptors (TLR2 and TLR6) are a group of receptors that play a crucial role in the innate immune response and recognition of T. vaginalis. Single nucleotide polymorphisms (SNPs) in TLRs were manifested as important determinant affecting the susceptibility to trichomoniasis. This study aims to examine the impact of rs5743708 SNP in TLR2and rs5743810 SNP in TLR6 on Iraqi women infected with T. vaginalis.Methods: Vaginal swabs and blood samples were isolated from 186 female patients who were admitting the gynecology clinics in three public hospitals in Babel governorate in Iraq. The collected samples were obtained for molecular identification of the parasite, sequencing of the TLR2 and TLR6 genes as well as performing the corresponding immunological studies.Results: The PCR assays showed 40 positive women (95% CI, 15.85 to 28.11) of T. vaginalis β-tubulin gene. Genetic studies of rs5743708 SNP in TLR2 showed that the frequency of non-mutant G allele was clearly higher in infected women (37/64) than controls (27/64), and the GG genotype has significantly higher prevalence (90%) within infected women versus the GA (5%) and AA (5%) genotypes (p<0.001).Genetic analysis of rs5743810 SNP in TLR6, revealed that the mutant G allele was significantly higher in infected women (17/24) than healthy controls (5/24) (p=0.021), in addition, the heterozygous AG and the homozygous GG demonstrated significantly higher frequencies (13/16 and 2/3) in trichomoniasis women versus controls (3/13 and 1/3), respectively, p=0.013. Moreover, elevated concentrations of these two receptors were detected during T. vaginalis infection.Conclusion: G allele of rs5743708 might play a protective role against trichomonas is for TLR2, and women homozygous for AA were not significantly associated with increased risk of trichomonas infection. While the mutant G allele of rs5743810 SNP may make women more sensitive for infection with T. vaginalis and subjects carrying AG heterozygous and GG homozygous genotypes might have higher risk of trichomoniasis compared with AA homozygous genotype. However, more studies are needed to confirm these findings and to understand the underlying involved mechanisms

Plastic waste management: case study of tower market, Hyderabad

Plastic consumption is continuously increasing due to urbanization and growing global demand. The consumption of plastic deteriorates the quality of the urban environment of most cities, especially in developing countries. To overcome this issue to some extent, this study was conducted to prevent the usage of plastic products to provide a healthy environment. The data was collected by using the closed-ended questionnaire survey and by reviewing the literature. The collected data were assessed and analyzed on SPSS (Statistical Package for Social Sciences) software. The survey observed that there is no proper plastic waste disposal system in the study area. People who reside in the area and those who visit the market face an unhygienic environment. The results highlighted that 50% to 60% of residents use plastic items which are dumped at open spaces without proper management after their consumption. This study suggests short-term, mid-term and long-term mitigation measures to reduce the production by using bio-based plastic and consumption by reducing the unnecessary packaging of plastic waste

Determinants of short birth intervals among married women: A cross-sectional study in Karachi, Pakistan

Introduction: Birth spacing is a critical pathway to improving reproductive health. WHO recommends a minimum of 33-month interval between two consecutive births to reduce maternal, perinatal, infant morbidity and mortality. Our study evaluated factors associated with short birth intervals (SBIs) of less than 33 months between two consecutive births, in Karachi, Pakistan.Methods: We used data from a cross-sectional study among married women of reproductive age (MWRA) who had at least one live birth in the 6 years preceding the survey (N=2394). Information regarding their sociodemographic characteristics, reproductive history, fertility preferences, family planning history and a 6-year reproductive calendar were collected. To identify factors associated with SBIs, we fitted simple and multiple Cox proportional hazards models and computed HRs with their 95% CIs.Results: The median birth interval was 25 months (IQR: 14-39 months), with 22.9% (833) of births occurring within 33 months of the index birth. Women\u27s increasing age (25-30 years (aHR 0.63 (0.53 to 0.75), 30+ years (aHR 0.29, 95% CI 0.22 to 0.39) compared with 20-24 years; secondary education (aHR 0.75, 95% CI 0.63 to 0.88), intermediate education (aHR 0.62, 95% CI 0.48 to 0.80), higher education (aHR 0.69, 95% CI 0.51 to 0.92) compared with no education, and a male child of the index birth (aHR 0.81, 95% CI 0.70 to 0.94) reduced the likelihood of SBIs. Women\u27s younger age \u3c20 years (aHR 1.24, 95% CI 1.05 to 1.24) compared with 20-24 years, and those who did not use contraception within 9 months of the index birth had a higher likelihood for SBIs for succeeding birth compared with those who used contraception (aHR 2.23, 95% CI 1.93 to 2.58).Conclusion: Study shows that birth intervals in the study population are lower than the national average. To optimise birth intervals, programmes should target child spacing strategies and counsel MWRA on the benefits of optimal birth spacing, family planning services and contraceptive utilisation

Application of a gene modular approach for clinical phenotype genotype association and sepsis prediction using machine learning in meningococcal sepsis

Sepsis is a major global health concern causing high morbidity and mortality rates. Our study utilized a Meningococcal Septic Shock (MSS) temporal dataset to investigate the correlation between gene expression (GE) changes and clinical features. The research used Weighted Gene Co-expression Network Analysis (WGCNA) to establish links between gene expression and clinical parameters in infants admitted to the Pediatric Critical Care Unit with MSS. Additionally, various machine learning (ML) algorithms, including Support Vector Machine (SVM), Naive Bayes, K-Nearest Neighbors (KNN), Decision Tree, Random Forest, and Artificial Neural Network (ANN) were implemented to predict sepsis survival. The findings revealed a transition in gene function pathways from nuclear to cytoplasmic to extracellular, corresponding with Pediatric Logistic Organ Dysfunction score (PELOD) readings at 0, 24, and 48 h. ANN was the most accurate of the six ML models applied for survival prediction. This study successfully correlated PELOD with transcriptomic data, mapping enriched GE modules in acute sepsis. By integrating network analysis methods to identify key gene modules and using machine learning for sepsis prognosis, this study offers valuable insights for precision-based treatment strategies in future research. The observed temporal-spatial pattern of cellular recovery in sepsis could prove useful in guiding clinical management and therapeutic interventions

Advancing the Understanding of Clinical Sepsis Using Gene Expression-Driven Machine Learning to Improve Patient Outcomes

Sepsis remains a major challenge that necessitates improved approaches to enhance patient outcomes. This study explored the potential of Machine Learning (ML) techniques to bridge the gap between clinical data and gene expression information to better predict and understand sepsis. We discuss the application of ML algorithms, including neural networks, deep learning, and ensemble methods, to address key evidence gaps and overcome the challenges in sepsis research. The lack of a clear definition of sepsis is highlighted as a major hurdle, but ML models offer a workaround by focusing on endpoint prediction. We emphasize the significance of gene transcript information and its use in ML models to provide insights into sepsis pathophysiology and biomarker identification. Temporal analysis and integration of gene expression data further enhance the accuracy and predictive capabilities of ML models for sepsis. Although challenges such as interpretability and bias exist, ML research offers exciting prospects for addressing critical clinical problems, improving sepsis management, and advancing precision medicine approaches. Collaborative efforts between clinicians and data scientists are essential for the successful implementation and translation of ML models into clinical practice. ML has the potential to revolutionize our understanding of sepsis and significantly improve patient outcomes. Further research and collaboration between clinicians and data scientists are needed to fully understand the potential of ML in sepsis management

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

A Transcriptomic Appreciation of Childhood Meningococcal and Polymicrobial Sepsis from a Pro-Inflammatory and Trajectorial Perspective, a Role for Vascular Endothelial Growth Factor A and B Modulation?

This study investigated the temporal dynamics of childhood sepsis by analyzing gene expression changes associated with proinflammatory processes. Five datasets, including four meningococcal sepsis shock (MSS) datasets (two temporal and two longitudinal) and one polymicrobial sepsis dataset, were selected to track temporal changes in gene expression. Hierarchical clustering revealed three temporal phases: early, intermediate, and late, providing a framework for understanding sepsis progression. Principal component analysis supported the identification of gene expression trajectories. Differential gene analysis highlighted consistent upregulation of vascular endothelial growth factor A (VEGF-A) and nuclear factor κB1 (NFKB1), genes involved in inflammation, across the sepsis datasets. NFKB1 gene expression also showed temporal changes in the MSS datasets. In the postmortem dataset comparing MSS cases to controls, VEGF-A was upregulated and VEGF-B downregulated. Renal tissue exhibited higher VEGF-A expression compared with other tissues. Similar VEGF-A upregulation and VEGF-B downregulation patterns were observed in the cross-sectional MSS datasets and the polymicrobial sepsis dataset. Hexagonal plots confirmed VEGF-R (VEGF receptor)–VEGF-R2 signaling pathway enrichment in the MSS cross-sectional studies. The polymicrobial sepsis dataset also showed enrichment of the VEGF pathway in septic shock day 3 and sepsis day 3 samples compared with controls. These findings provide unique insights into the dynamic nature of sepsis from a transcriptomic perspective and suggest potential implications for biomarker development. Future research should focus on larger-scale temporal transcriptomic studies with appropriate control groups and validate the identified gene combination as a potential biomarker panel for sepsis

Advancing sepsis clinical research: harnessing transcriptomics for an omics-based strategy - a comprehensive scoping review

Sepsis continues to be recognized as a significant global health challenge across all ages and is characterized by a complex pathophysiology. In this scoping review, PRISMA-ScR guidelines were adhered to, and a transcriptomic methodology was adopted, with the protocol registered on the Open Science Framework. We hypothesized that gene expression analysis could provide a foundation for establishing a clinical research framework for sepsis. A comprehensive search of the PubMed database was conducted with a particular focus on original research and systematic reviews of transcriptomic sepsis studies published between 2012 and 2022. Both coding and non-coding gene expression studies have been included in this review. An effort was made to enhance the understanding of sepsis at the mRNA gene expression level by applying a systems biology approach through transcriptomic analysis. Seven crucial components related to sepsis research were addressed in this study: endotyping (n = 64), biomarker (n = 409), definition (n = 0), diagnosis (n = 1098), progression (n = 124), severity (n = 451), and benchmark (n = 62). These components were classified into two groups, with one focusing on Biomarkers and Endotypes and the other oriented towards clinical aspects. Our review of the selected studies revealed a compelling association between gene transcripts and clinical sepsis, reinforcing the proposed research framework. Nevertheless, challenges have arisen from the lack of consensus in the sepsis terminology employed in research studies and the absence of a comprehensive definition of sepsis. There is a gap in the alignment between the notion of sepsis as a clinical phenomenon and that of laboratory indicators. It is potentially responsible for the variable number of patients within each category. Ideally, future studies should incorporate a transcriptomic perspective. The integration of transcriptomic data with clinical endpoints holds significant potential for advancing sepsis research, facilitating a consensus-driven approach, and enabling the precision management of sepsis

Standardised practices in the networked management of congenital hyperinsulinism: a UK national collaborative consensus

Congenital hyperinsulinism (CHI) is a condition characterised by severe and recurrent hypoglycaemia in infants and young children caused by inappropriate insulin over-secretion. CHI is of heterogeneous aetiology with a significant genetic component and is often unresponsive to standard medical therapy options. The treatment of CHI can be multifaceted and complex, requiring multidisciplinary input. It is important to manage hypoglycaemia in CHI promptly as the risk of long-term neurodisability arising from neuroglycopaenia is high. The UK CHI consensus on the practice and management of CHI was developed to optimise and harmonise clinical management of patients in centres specialising in CHI as well as in non-specialist centres engaged in collaborative, networked models of care. Using current best practice and a consensus approach, it provides guidance and practical advice in the domains of diagnosis, clinical assessment and treatment to mitigate hypoglycaemia risk and improve long term outcomes for health and well-being