Health effects of selected environmental Exposomes Across the Life courSe in Indian populations using longitudinal cohort studies: GEOHealth HEALS Study protocol.

INTRODUCTION: Air pollution presents a major public health threat to India, affecting more than three quarters of the country's population. In the current project, GEOHealth Health Effects of Selected Environmental Exposomes Across the Life CourSe-India, we aim to study the effect of environmental exposomes-fine particulate matter (PM2.5), nitrogen dioxide (NO2), ozone (O3) and extremes of temperature-on multiple health outcomes using a modified life course approach. The associated training grant aims to build capacity in India to address the unique environmental health problems. METHODS AND ANALYSIS: The project aims to (A) Develop exposure assessments in seven cities, namely Delhi, Chennai, Sonipat, Vizag, Pune, Hyderabad and Bikaner, for: (1) A fine-scale spatiotemporal model for multiple pollutants (PM2.5, NO2, O3, temperature); (2) Combined ground monitoring and modelling for major chemical species of ambient PM2.5 at seven cities; and (3) Personal exposure assessment in a subsample from the six cities, except Pune, and (B) Conduct health association studies covering a range of chronic non-communicable diseases and their risk factors leveraging a unique approach using interdigitating cohorts. We have assembled existing pregnancy, child, adolescent, adult and older adult cohorts across India to explore health effects of exposomes using causal analyses. We propose to use Bayesian kernel machine regression to assess the effects of mixtures of all pollutants including species of PM2.5 on health while accounting for potential non-linearities and interactions between exposures. This builds on earlier work that constructed a fine spatiotemporal model for PM2.5 exposure to study health outcomes in two Indian cities. ETHICS AND DISSEMINATION: Ethical clearance for conduct of the study was obtained from the Institutional Ethics Committee (IEC) of the Centre for Chronic Disease Control, and all the participating institutes and organisations. National-level permission was provided by the Indian Council of Medical Research. The research findings will be disseminated through peer-reviewed publications, policy briefs, print and social media, and communicating with the participating communities and stakeholders. Training of Indian scientists will build the capacity to undertake research on selected adverse environmental exposures on population health in India.

Insights into the radiation and oxidative stress mechanisms in genus Deinococcus.

Deinococcus species, noted for their exceptional resistance to DNA-damaging environmental stresses, have piqued scientists' interest for decades. This study dives into the complex mechanisms underpinning radiation resistance in the Deinococcus genus. We have examined the genomes of 82 Deinococcus species and classified radiation-resistance proteins manually into five unique curated categories: DNA repair, oxidative stress defense, Ddr and Ppr proteins, regulatory proteins, and miscellaneous resistance components. This classification reveals important information about the various molecular mechanisms used by these extremophiles which have been less explored so far. We also investigated the presence or lack of these proteins in the context of phylogenetic relationships, core, and pan-genomes, which offered light on the evolutionary dynamics of radiation resistance. This comprehensive study provides a deeper understanding of the genetic underpinnings of radiation resistance in the Deinococcus genus, with potential implications for understanding similar mechanisms in other organisms using an interactomics approach. Finally, this study reveals the complexities of radiation resistance mechanisms, providing a comprehensive understanding of the genetic components that allow Deinococcus species to flourish under harsh environments. The findings add to our understanding of the larger spectrum of stress adaption techniques in bacteria and may have applications in sectors ranging from biotechnology to environmental research.

Novel genomic variants related to visceral adiposity index (VAI) and body adiposity index (BAI) in Indian sib-pairs.

BACKGROUND: Obesity is among the leading public health threats globally. Over the last few years, visceral adiposity index (VAI), and body adiposity index (BAI), derived from anthropometric, and biochemical measures, have gained importance as a measure of obesity. However, unlike other common indices like body mass index, and waist circumference, the genetic predisposition of VAI, and BAI under-examined. METHODS: 2265 sib-pairs from Indian Migration Study were used for examining the association of genetic variants from the Cardio-Metabochip array with VAI, and BAI. Mixed linear regression models were run, and all inferences were based on the within-sib component of the Fulker's association models. Gene-environment/lifestyle interaction analyses were also undertaken. RESULTS: rs6659428 at LOC400796 | SEC16B (ß = 0.26, SE = 0.05), and rs7611535 at DRD3 | LOC645180 (ß = 0.18, SE = 0.04) were associated with VAI at suggestive significance value of <8.21 × 10-6. For BAI, rs73300702 at JAZF1-AS1 (ß = 0.27, SE = 0.06), was the top hit at p value < 8.21 × 10-6. Further, rs6659428 showed marginal effect modification with rural/urban location (ß = 0.26, SE = 0.13, p value = 0.047), and rs73300702 with physical activity (ß = -0.29,SE = 0.14, p value = 0.034). CONCLUSION: We report three novel genetic loci for VAI, and BAI in Indians that are important indicators of adiposity. These findings need to be replicated and validated with larger samples from different ethnicities. Further, functional studies for understanding the biological mechanisms of these adiposity indices need to be undertaken to understand the underlying pathophysiology.

Increased electrode impedance as an indicator for early detection of deep brain stimulation (DBS) hardware Infection: Clinical experience and in vitro study.

BACKGROUND: When deep brain stimulation (DBS) infections are identified, they are often too advanced to treat without complete hardware removal. New objective markers to promptly identify DBS infections are needed. We present a patient with GPi (globus pallidus interna) DBS for dystonia, where the electrode impedance unexpectedly increased 3-months post-operatively, followed by serologic and hematologic markers of inflammation at 6-months, prompting explantation surgery. We recreated these conditions in a laboratory environment to analyze the pattern of changing of electrical impedance across the contacts of a DBS lead following Staphylococcus biofilm formation. METHODS: A stainless-steel culture chamber containing 1 % brain heart infusion agar was used. A DBS electrode was dipped in peptone water containing a strain of S. aureus and subsequently introduced into the chamber. The apparatus was incubated at 37 °C for 6 days. Impedance was measured at 24hr intervals. A control experiment without S. Aureus inoculation was used to determine changes in impedance over a period of 6-days. RESULTS: The mean monopolar impedance on day-1 was 751.8 ± 23.8 Ω and on day-3 was 1004.8 ± 68.7 Ω, a 33.7 % rise (p = 0.007). A faint biofilm formation could be seen around the DBS lead by day-2 and florid growth by day-3. After addition of the linezolid solution, a 15.9 % decrease in monopolar impedance was observed from day 3-6 (p = 0.003). CONCLUSION: This study gives insight into impedance trends following a hardware infection in DBS. Increased impedance outside expected norms may be valuable for early prediction of infection. Furthermore, timely management using antibiotics might reduce the frequency of infection-related explant surgeries.

Association of Low Birth Weight with the Risk of Childhood Stunting in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis.

BACKGROUND: Stunting is an important predictor of growth and development of children under 5 years of age, and it remains the significant problem in LMIC. However, LBW emerges as risk factor, but its association with LMIC needs attention. OBJECTIVE: This systematic review and meta-analysis aimed to investigate the association of low birth weight with the risk of childhood stunting among the age group of 0-5 years in LMICs. METHODS: PubMed, Google Scholar, MEDLINE, Embase, and Web of Science databases were searched from January 1, 2010 untill December 20, 2021. Cross-sectional, cohort, and case-control study designs were included in the meta-analyses. The pooled odds ratio with a 95% confidence interval was reported considering the random-effects and the quality-effects models. The subgroup analysis and meta-regression were conducted for study design, geographical location, and sample size. RESULTS: Low birth weight was associated with >2-fold increased risk of childhood stunting (pooled OR: 2.32; 95% CI, 2.05-2.62). Asian studies have shown relatively higher risk than African studies in stratified analyses. The cohort studies predicted a higher risk of childhood stunting, followed by case-control and cross-sectional study designs, and the sample size stratification showed that studies with sample size <1,000 predicted much higher risk than relatively to the studies with sample size >1,000. The meta-regression was performed in all three subgroups, but none of the models appeared significant. CONCLUSION: This meta-analysis confirmed the association of low birth weight with the higher risk of childhood stunting among the 0-5 years' age group and suggests a moderately higher risk in Asia as compared to Africa.

The RIGHT Scoring System for the Medicolegal Classification of Head Injury.

Background: In India, in case of an allegation of assault, the medical officer is required to classify the nature of injury into simple, grievous, and dangerous based upon the Indian Penal Code, which is outdated and has numerous gray areas. Objective: The aim of this study is twofold: first, to formulate an objective scoring system for the medicolegal classification of head injuries and Second to validate the proposed scoring system on patients with head injury. Methods and Material: A panel of experts consisting of neurosurgeons, radiologists, and forensic specialists came up with an objective scoring system, coined as the RIGHT (radiological-intervention-Glasgow Coma Scale (GCS)-based head trauma) scoring system consisting of three parameters, namely, the motor subscore of the GCS, computerized tomography image findings, and management of the patient. This was used to classify head injuries-into simple, grievous, and dangerous. A single-centre pilot study was planned-including patients with head trauma reporting to the emergency department. Medicolegal nature of the head injury was classified according to the proposed RIGHT score. A 6-month follow-up was performed using the Glasgow Outcome Score (GOS). Results: In total, 130 patients with head injury reported to the emergency department. There was a significant correlation between the RIGHT score assigned upon admission and the GOS at 6 months (P < 0.001). Conclusions: As the scoring system could be applied objectively and a significant correlation between nature of injury given by RIGHT score and 6-month outcome was present; therefore, the RIGHT scoring system proved to be an effective method in unambiguously classifying the nature of head injury for medicolegal opinions.

Behavior of higher-order MDD on energy ratios at the interface of thermoelastic and piezothermoelastic mediums.

This paper investigates the intricate energy distribution patterns emerging at an orthotropic piezothermoelastic half-space interface by considering the influence of a higher-order three-phase lags heat conduction law, accompanied by memory-dependent derivatives (referred to as HPS) within the underlying thermoelastic half-space (referred to as TS). This study explores the amplitude and energy ratios of reflected and transmitted waves. These waves span various incident types, including longitudinal, thermal, and transversal, as they propagate through the TS and interact at the interface. Upon encountering the interface, an intriguing dynamic unfolds: three waves experience reflection within the TS medium, while four waves undergo transmission into the HPS medium. A graphical representation effectively illustrates the impact of higher-order time differential parameters and memory to offer comprehensive insights. This visual representation reveals the nuanced fluctuations of energy ratios with the incidence angle. The model astutely captures diverse scenarios, showcasing its ability to interpret complex interface dynamics.

Emerging Field of Nanotechnology in Environment.

The art of utilizing and manipulating micro materials have been dated back to antient era. With the advancement in technologies, the state-of-art methods of nano technologies and nano sciences has been employed in various sectors including environment, product designing, food industry, pharmaceuticals industries to way out solve standard problem of mankind. Due to rapid industrialization and the alarming levels of pollution there has been an urgent need to address the environmental and energy issues. Environmental sustainability concerns the global climate change and pollution including air, water, soil. The field of nanotechnology has proven to be a promising field where sensing and remediation, have been dramatically advanced by the use of nanomaterials. This emergent science of surface to mass ratio is the principle theorem for manipulating structure at molecular levels. The review sums up all the advancements in the field of nanotechnology and their recent application in the environment. New opportunities and challenges have also been discussed in detail to understand the use of nanotechnology as problem-to-solution ratio. Graphical abstract: Image depicting the application of nanotechnology in environmental concerns. The combinations of technologies like bioremediations, bioaugmentations with state-of-the-art nanotechnology like carbon nanotubes and Nano capsules to answer the environmental challenges of soil quality, and plant productivity.

Genetic associations of TMEM154, PRC1 and ZFAND6 loci with type 2 diabetes in an endogamous business community of North India.

BACKGROUND: More than 250 loci have been identified by genome-wide scans for type 2 diabetes in different populations. South Asians have a very different manifestation of the diseases and hence role of these loci need to be investigated among Indians with huge burden of cardio-metabolic disorders. Thus the present study aims to validate the recently identified GWAS loci in an endogamous caste population in North India. METHODS: 219 T2D cases and 184 controls were recruited from hospitals and genotyped for 15 GWAS loci of T2D. Regression models adjusted for covariates were run to examine the association for T2D and fasting glucose levels. RESULTS: We validated three variants for T2D namely, rs11634397 at ZFAND6 (OR = 3.05, 95%CI = 1.02-9.19, p = 0.047) and rs8042680 at PRC1 (OR = 3.67, 95%CI = 1.13-11.93, p = 0.031) showing higher risk and rs6813195 at TMEM154 (OR = 0.28, 95%CI = 0.09-0.90, p = 0.033) showing protective effect. The combined risk of 9 directionally consistent variants was also found to be significantly associated with T2D (OR = 1.91, 95%CI = 1.18-3.08, p = 0.008). One variant rs10842994 at KLHDC5 was validated for 9.15mg/dl decreased fasting glucose levels (SE = -17.25-1.05, p = 0.027). CONCLUSION: We confirm the role of ZFAND6, PRC1 and TMEM154 in the pathophysiology of type 2 diabetes among Indians. More efforts are needed with larger sample sizes to validate the diabetes GWAS loci in South Asian populations for wider applicability.

Microbial diversity characterizations, associated pathogenesis and antimicrobial resistance profiling of Najafgarh drain.

The Najafgarh drain plays a significant role in the pollution of the Yamuna River, accounting for 40% of the total pollution. Therefore, it is crucial to investigate and analyze the microbial diversity, metabolic functional capacity, and antibiotic resistance genes (ARGs) present in the Najafgarh drain. Additionally, studying the water quality and its relationship with the proliferation of microorganisms in the drain is of utmost importance. Results obtained confirmed the deteriorated water quality as physico-chemical parameters such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), and total suspended solids (TSS) in the range of 125-140, 400-460, 0-0.2, 25-140.4 mg/l respectively violated the standard permissible national and global standards. In addition, the next generation sequencing (NGS) analysis confirm the presence of genus such as Thauera, Arcobacter, Pseudomonas, Geobacter, Dechloromonas, Tolumonas, Sulfurospirullum, Desulfovibrio, Aeromonas, Bacteroides, Prevotella, Cloacibacterium, Bifidobacterium, Clostridium etc. along with 864 ARGs in the wastewater obtained from the Najafgarh drain. Findings confirm that the pathogenic species reported from this dataset possess severe detrimental impact on faunal and human health. Further, Pearson's r correlation analysis indicated that environmental variables, mainly total dissolved solids (TDS) and chemical oxygen demand (COD), play a pivotal role in driving microbial community structure of this heavily polluted drain. Thus, the poor water quality, presence of a microbial nexus, pathogenic markers, and ARGs throughout this drain confirmed that it would be one potential contributor to the dissemination of disease-causing agents (pathogens) to the household and drinking water supplies in the near future.

Mechanical behaviour of reconstructed defected skull with custom PEEK implant and Titanium fixture plates under dynamic loading conditions using FEM.

Skull reconstruction using cranial implants is often required for repairing skull defects caused due to trauma, diseases, or malignancy to protect intracranial structures. For relieving Intracranial Pressure (ICP) surgeons restore cranial defects either using natural bones or fabricated custom cranial implants. With the increase in Traumatic Brain Injuries (TBI) and challenges faced by TBI patients to regain normalcy, it is imperative to analyse the mechanical behaviour of skull-implant assemblies under some Head Injury Criteria (HIC). Medical grade materials including Titanium Alloys (Ti-6Al-4V) and Polyether-ether-ketone (PEEK) are used by fabricating Patient-Specific Implants (PSI) manufactured using 3D imaging, modelling and printing techniques. 3D technologies are preferred over conventional manufacturing methods, as they enable fabrication of custom shapes, sizes and properties for these PSI. For an effective attachment of PSI with a defective skull, a stable joint and plate arrangement as fixture plates is necessary at their interface. These fixtures can have variable numbers, design shapes, materials and location arrangements. This paper presents the Finite Element Method/Analysis (FEM/FEA) study of PSI attached to a defected skull for reconstruction, with linear shaped fixture configuration, when subjected to an external dynamic loading at 5 m/s, strain rate of 10s-1 to 243s-1 and ICP of 15mm Hg from three sides of the skull faces. Three different materials as Neoprene (soft), Concrete (medium rigid) and E-Glass (highly rigid) have been used, in the form of a rectangular thin cuboidal wall structure, at an angle of 45° with the skull face. Four linear shaped fixture plates which were simplest to design, were used to attach the PSI-skull assembly, to ensure that weight of the PSI-fixation assembly on the patient remains minimal, overall assembly has symmetrical fixations and efforts required by a surgeon for fitment of these plates remain minimal. Placement of these fixture plates has been optimized to encompass the complete PSI-skull interface section, due to which the stresses within all the assembly components (PSI, fixture plate and skull) reduced by nearly 2.5 times than the initial design and remained within yielding limits, thereby, averting any failure under heavy external dynamic loading.

Comparative genomics and integrated system biology approach unveiled undirected phylogeny patterns, mutational hotspots, functional patterns, and molecule repurposing for monkeypox virus.

Monkeypox is a viral zoonosis with symptoms that are reminiscent of those experienced in previous smallpox cases. The GSAID database (Global Initiative on Sharing Avian Influenza Data) was used to assess 630 genomes of MPXV. The phylogenetic study revealed six primary clades, as well as a smaller percentage in radiating clades. Individual clades that make up various nationalities may have formed as a result of a particular SNP hotspot type that mutated in a specific population. The most significant mutation based on a mutational hotspot analysis was found at G3729A and G5143A. The gene ORF138, which encodes the Ankyrin repeat (ANK) protein, was found to have the most mutations. This protein mediates molecular recognition via protein-protein interactions. It was shown that 243 host proteins interacted with 10 monkeypox proteins identified as the hub proteins E3, SPI2, C5, K7, E8, G6, N2, B14, CRMB, and A41 through 262 direct connections. The interaction with chemokine system-related proteins provides further evidence that the monkeypox virus suppresses human proteins to facilitate its survival against innate immunity. Several FDA-approved molecules were evaluated as possible inhibitors of F13, a significant envelope protein on the membrane of extracellular versions of the virus. A total of 2500 putative ligands were individually docked with the F13 protein. The interaction between the F13 protein and these molecules may help prevent the monkeypox virus from spreading. After being confirmed by experiments, these putative inhibitors could have an impact on the activity of these proteins and be used in monkeypox treatments.

Deep Learning-Based Robust Automated System for Predicting Human Sperm DNA Fragmentation Index.

Background: Determining the DNA fragmentation index (DFI) by the sperm chromatin dispersion (SCD) test involves manual counting of stained sperms with halo and no halo. Aims: The aim of this study is to build a robust artificial intelligence-based solution to predict the DFI. Settings and Design: This is a retrospective experimental study conducted in a secondary in vitro fertilisation setup. Materials and Methods: We obtained 24,415 images from 30 patients after the SCD test using a phase-contrast microscope. We classified the dataset into two, binary (halo/no halo) and multiclass (big/medium/small halo/degraded (DEG)/dust). Our approach consists of a training and prediction phase. The 30 patients' images were divided into training (24) and prediction (6) sets. A pre-processing method M was developed to automatically segment the images to detect sperm-like regions and was annotated by three embryologists. Statistical Analysis Used: To interpret the findings, the precision-recall curve and F1 score were utilised. Results: Binary and multiclass datasets containing 8887 and 15,528 cropped sperm image regions showed an accuracy of 80.15% versus 75.25%. A precision-recall curve was determined and the binary and multiclass datasets obtained an F1 score of 0.81 versus 0.72. A confusion matrix was applied for predicted and actuals for the multiclass approach where small halo and medium halo confusion were found to be highest. Conclusion: Our proposed machine learning model can standardise and aid in arriving at accurate results without using expensive software. It provides accurate information about healthy and DEG sperms in a given sample, thereby attaining better clinical outcomes. The binary approach performed better with our model than the multiclass approach. However, the multiclass approach can highlight the distribution of fragmented and non-fragmented sperms.

Phylogenetic analysis and interactomics study unveil gene co-optive evolution of LysR-type transcription regulators across non-pathogenic, opportunistic, and pathogenic mycobacteria.

Mycobacterial species is known for inhabiting various niches ranging from soil to harsh intracellular environment of animal hosts and their survival through constant changes. For survival and persistence, these organisms must quickly adapt by bringing shift in their metabolism. Metabolic shifts are brought by sensing the environmental cues usually by membrane localized sensor molecules. These signals are transmitted to regulators of various metabolic pathways leading to post-translational modifications of regulators ultimately resulting in altered metabolic state of the cell. Multiple regulatory mechanisms have been unearthed so far that play crucial role in adapting to these situations, and among them, the signal-dependent transcriptional regulators mediated responses are integral for the microbes to perceive environmental signals and generate appropriate adaptive responses. LysR-type transcriptional regulators (LTTRs) form the largest family of transcriptional regulators, which are present in all kingdoms of life. Their numbers vary among bacterial genera and even in different mycobacterial species. To understand the evolutionary aspect of pathogenicity based on LTTRs, we performed phylogenetic analysis of LTTRs encoded by several mycobacterial species representing non-pathogenic (NP), opportunistic (OP), and totally pathogenic (TP) mycobacteria. Our results showed that LTTRs of TP clustered separately from LTTRs of NP and OP mycobacteria. In addition, LTTRs frequency per Mb of genome was reduced in TP when compared with NP and OP. Further, the protein-protein interactions and degree-based network analysis showed concomitant increased interactions per LTTRs with increase in pathogenicity. These results suggested the increase in regulon of LTTRs during evolution of TP mycobacteria.

Computational Approaches for the Structure-Based Identification of Novel Inhibitors Targeting Nucleoid-Associated Proteins in Mycobacterium Tuberculosis.

Implementation of computational tools in the identification of novel drug targets for Tuberculosis (TB) has been a promising area of research. TB has been a chronic infectious disease caused by Mycobacterium tuberculosis (Mtb) localized primarily on the lungs and it has been one of the most successful pathogen in the history of mankind. Extensively arising drug resistivity in TB has made it a global challenge and need for new drugs has become utmost important.The involvement of Nucleoid-Associated Proteins (NAPs) in maintaining the structure of the genomic material and regulating various cellular processes like transcription, DNA replication, repair and recombination makes significant, has opened a new arena to find the drugs targeting Mtb. The current study aims to identify potential inhibitors of NAPs through a computational approach. In the present work we worked on the eight NAPs of Mtb, namely, Lsr2, EspR, HupB, HNS, NapA, mIHF and NapM. The structural modelling and analysis of these NAPs were carried out. Moreover, molecular interaction were checked and binding energy was identified for 2500 FDA-approved drugs that were selected for antagonist analysis to choose novel inhibitors targeting NAPs of Mtb. Drugs including Amikacin, streptomycin, kanamycin, and isoniazid along with eight FDA-approved molecules that were found to be potential novel targets for these mycobacterial NAPs and have an impact on their functions. The potentiality of several anti-tubercular drugs as therapeutic agents identified through computational modelling and simulation unlocks a new gateway for accomplishing the goal to treat TB. Complete framework of the methodology employed in this study to predict inhibitors against mycobacterial NAPs.

Draft genome sequence of Streptomyces sp. KD18, isolated from industrial soil.

The present study scrutinizes the presence of Streptomyces strains in the soil sample collected from industrial area of Bahadurgarh (Haryana) India. The morphological approach manifested the isolated strain belong to Streptomyces species and named as Streptomyces sp. KD18. Sequencing of Streptomyces sp. KD18 genome was performed by Illumina Nextseq500 platform. 65 contigs were generated via SPAdes v3.11.1 and harboured genome size of 7.2 Mb. AntiSMASH server revealed the presence of 25 biosynthetic gene clusters in KD18 genome where BGC of lipstatin was of more interest from industrial and pharmaceutical purpose. The draft genome sequence represented via ANI values claimed that the KD18 strain belongs to Streptomyces toxytricini and finally named as S. toxytricini KD18. The LC-MS analysis of the extracted metabolite confirmed the production of lipstatin. The genome sequence data have been deposited to NCBI under the accession number of GCA_014748315.1. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03453-3.

Early management of acute severe UC in the biologics era: development and international validation of a prognostic clinical index to predict steroid response.

OBJECTIVES: We aimed to determine whether changes in acute severe colitis (ASC) management have translated to improved outcomes and to develop a simple model predicting steroid non-response on admission. DESIGN: Outcomes of 131 adult ASC admissions (117 patients) in Oxford, UK between 2015 and 2019 were compared with data from 1992 to 1993. All patients received standard treatment with intravenous corticosteroids and endoscopic disease activity scoring (Ulcerative Colitis Endoscopic Index of Severity (UCEIS)). Steroid non-response was defined as receiving medical rescue therapy or surgery. A predictive model developed in the Oxford cohort was validated in Australia and India (Gold Coast University Hospital 2015-2020, n=110; All India Institute of Medical Sciences, New Delhi 2018-2020, n=62). RESULTS: In the 2015-2019 Oxford cohort, 15% required colectomy during admission vs 29% in 1992-1993 (p=0.033), while 71 (54%) patients received medical rescue therapy (27% ciclosporin, 27% anti-tumour necrosis factor, compared with 27% ciclosporin in 1992-1993 (p=0.0015). Admission C reactive protein (CRP) (false discovery rate, p=0.00066), albumin (0.0066) and UCEIS scores (0.015) predicted steroid non-response. A four-point model was developed involving CRP of ≥100 mg/L (one point), albumin of ≤25 g/L (one point), and UCEIS score of ≥4 (1 point) or ≥7 (2 points). Patients scoring 0, 1, 2, 3 and 4 in the validation cohorts had steroid response rates of 100, 75.0%, 54.9%, 18.2% and 0%, respectively. Scoring of ≥3 was 84% (95% CI 0.70 to 0.98) predictive of steroid failure (OR 11.9, 95% CI 10.8 to 13.0). Colectomy rates in the validation cohorts were were 8%-11%. CONCLUSIONS: Emergency colectomy rates for ASC have halved in 25 years to 8%-15% worldwide. Patients who will not respond to corticosteroids are readily identified on admission and may be prioritised for early intensification of therapy.

Assessing Menstrual Changes Among Young Indian Females Post-SARS-CoV-2 Vaccination.

Background The rollout of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines has significantly enhanced immunity against coronavirus disease 2019 (COVID-19), leading to a reduction in the severity of illness, hospitalizations, and deaths. While various side effects of the vaccine have been reported, its impact on the menstrual cycle remains unclear. Methods We conducted a cross-sectional study involving university students who had received either partial or full vaccination against SARS-CoV-2. Data was gathered through a questionnaire designed to assess the relationship between menstrual changes and the SARS-CoV-2 vaccination. Results A total of 773 participants, with a mean age of 20.6 ± 1.7 years, were included in this study. The participants reported a significant increase in the irregularity of the menstrual cycle. We observed a slight increase in the length of the menstrual cycle, from 30.0 ± 4.0 days (pre-vaccination) to 30.5 ± 5.6 days (post-vaccination), which was statistically significant (p<0.001). The duration of menstruation also increased, from 4.9 ± 1.7 days (pre-vaccination) to 5.0 ± 1.7 days (post-vaccination). However, this increase in menstrual length due to vaccination was not statistically significant (p = 0.898). Notably, there was a significant increase in pain reported by the participants after receiving the SARS-CoV-2 vaccine (p = 0.004). Conclusion The SARS-CoV-2 vaccination significantly impacted the regularity of the menstrual cycle, length of the menstrual cycle, and pain during menstruation, though temporarily. Our study found no significant differences in menstrual changes or the type of vaccine administered (Covishield and Covaxin).