RET Alterations Differentiate Molecular Profile of Medullary Thyroid Cancer.

PURPOSE: Medullary thyroid cancer (MTC) is a rare cancer originating from parafollicular C cells of the thyroid gland. Therapeutically relevant alterations in MTC are predominantly reported in RET oncogene, and lower-frequency alterations are reported in KRAS and BRAF. Nevertheless, there is an unmet need existing to analyze the MTC in the Indian cohort by using in-depth sequencing techniques that go beyond the identification of known therapeutic biomarkers. MATERIALS AND METHODS: Here, we characterize MTC using integrative whole-exome and whole-transcriptome sequencing of 32 MTC tissue samples. We performed clinically relevant variant analysis, molecular pathway analysis, tumor immune-microenvironment analysis, and structural characterization of RET novel mutation. RESULTS: Mutational landscape analysis shows expected RET mutations in 50% of the cases. Furthermore, we observed mutations in known cancer genes like KRAS, HRAS, SF3B1, and BRAF to be altered only in the RET-negative cohort. Pathway analysis showed differential enrichment of mutations in transcriptional deregulation genes in the RET-negative cohort. Furthermore, we observed novel RET kinase domain mutation Y900S showing affinity to RET inhibitors accessed via molecular docking and molecular dynamics simulation. CONCLUSION: Altogether, this study provides a detailed genomic characterization of patients with MTC of Indian origin, highlighting the possible utility of targeted therapies in this disease.

Cerebrospinal fluid proteomic signatures are associated with symptom severity of first-episode psychosis.

Apart from their diagnostic, monitoring, or prognostic utility in clinical settings, molecular biomarkers may be instrumental in understanding the pathophysiology of psychiatric disorders, including schizophrenia. Using untargeted metabolomics, we recently identified eight cerebrospinal fluid (CSF) metabolites unique to first-episode psychosis (FEP) subjects compared to healthy controls (HC). In this study, we sought to investigate the CSF proteomic signatures associated with FEP. We employed 16-plex tandem mass tag (TMT) mass spectrometry (MS) to examine the relative protein abundance in CSF samples of 15 individuals diagnosed with FEP and 15 age-and-sex-matched healthy controls (HC). Multiple linear regression model (MLRM) identified 16 differentially abundant CSF proteins between FEP and HC at p < 0.01. Among them, the two most significant CSF proteins were collagen alpha-2 (IV) chain (COL4A2: standard mean difference [SMD] = -1.12, p = 1.64 × 10-4) and neuron-derived neurotrophic factor (NDNF: SMD = -1.03, p = 4.52 × 10-4) both of which were down-regulated in FEP subjects compared to HC. We also identified several potential CSF proteins associated with the pathophysiology and the symptom profile and severity in FEP subjects, including COL4A2, NDNF, hornerin (HRNR), contactin-6 (CNTN6), voltage-dependent calcium channel subunit alpha-2/delta-3 (CACNA2D3), tropomyosin alpha-3 chain (TPM3 and TPM4). Moreover, several protein signatures were associated with cognitive performance. Although the results need replication, our exploratory study suggests that CSF protein signatures can be used to increase the understanding of the pathophysiology of psychosis.

Safety, feasibility, and impact on the gut microbiome of kefir administration in critically ill adults.

BACKGROUND: Dysbiosis of the gut microbiome is frequent in the intensive care unit (ICU), potentially leading to a heightened risk of nosocomial infections. Enhancing the gut microbiome has been proposed as a strategic approach to mitigate potential adverse outcomes. While prior research on select probiotic supplements has not successfully shown to improve gut microbial diversity, fermented foods offer a promising alternative. In this open-label phase I safety and feasibility study, we examined the safety and feasibility of kefir as an initial step towards utilizing fermented foods to mitigate gut dysbiosis in critically ill patients. METHODS: We administered kefir in escalating doses (60 mL, followed by 120 mL after 12 h, then 240 mL daily) to 54 critically ill patients with an intact gastrointestinal tract. To evaluate kefir's safety, we monitored for gastrointestinal symptoms. Feasibility was determined by whether patients received a minimum of 75% of their assigned kefir doses. To assess changes in the gut microbiome composition following kefir administration, we collected two stool samples from 13 patients: one within 72 h of admission to the ICU and another at least 72 h after the first stool sample. RESULTS: After administering kefir, none of the 54 critically ill patients exhibited signs of kefir-related bacteremia. No side effects like bloating, vomiting, or aspiration were noted, except for diarrhea in two patients concurrently on laxatives. Out of the 393 kefir doses prescribed for all participants, 359 (91%) were successfully administered. We were able to collect an initial stool sample from 29 (54%) patients and a follow-up sample from 13 (24%) patients. Analysis of the 26 paired samples revealed no increase in gut microbial α-diversity between the two timepoints. However, there was a significant improvement in the Gut Microbiome Wellness Index (GMWI) by the second timepoint (P = 0.034, one-sided Wilcoxon signed-rank test); this finding supports our hypothesis that kefir administration can improve gut health in critically ill patients. Additionally, the known microbial species in kefir were found to exhibit varying levels of engraftment in patients' guts. CONCLUSIONS: Providing kefir to critically ill individuals is safe and feasible. Our findings warrant a larger evaluation of kefir's safety, tolerability, and impact on gut microbiome dysbiosis in patients admitted to the ICU. TRIAL REGISTRATION: NCT05416814; trial registered on June 13, 2022.

Understanding the Impact of Population and Cancer Type on Tumor Mutation Burden Scores: A Comprehensive Whole-Exome Study in Cancer Patients From India.

PURPOSE: The purpose of this study was to understand the impact of population diversity and geographic variation on tumor mutation burden (TMB) scores across cancers and its implication on stratification of patients for immune checkpoint inhibitor (ICI) therapy. MATERIALS AND METHODS: This retrospective study used whole-exome sequencing (WES) to profile 1,233 Indian patients with cancer across 30 different cancer types and to estimate their TMB scores. A WES-based pipeline was adopted, along with an indigenously developed strategy for arriving at true somatic mutations. A robust unsupervised machine learning approach was used to understand the distribution of TMB scores across different populations and within the population. RESULTS: The results of the study showed a biphasic distribution of TMB scores in most cancers, with different threshold scores across cancer types. Patients with cancer in India had higher TMB scores compared with the Caucasian patients. We also observed that the TMB score value at 90th percentile (predicting high efficacy to ICI) was high in four different cancer types (sarcoma, ovary, head and neck, and breast) in the Indian cohort as compared with The Cancer Genome Atlas or public cohort. However, in lung and colorectal cancers, the TMB score distribution was similar between the two population cohorts. CONCLUSION: The findings of this study indicate that it is crucial to benchmark both cancer-specific and population-specific TMB distributions to establish a TMB threshold for each cancer in various populations. Additional prospective studies on much larger population across different cancers are warranted to validate this observation to become the standard of care.

Real-World Evidence of EGFR Targeted Therapy in NSCLC- A Brief Report of Decade Long Single Center Experience.

The significance of EGFR targeted therapy in the lung adenocarcinoma is paramount. Several controlled clinical trials have reported considerable survival of EGFR mutation positive patients on receiving the EGFR tyrosine kinase inhibitor (TKI). However, the real-world evidence of benefits of EGFR TKI would be further useful to understand how the designated therapeutic regimen benefits the patients. In this study, we report a decade long real-world evidence of EGFR molecular testing in lung cancer at Tata Memorial Hospital (Mumbai, India). Laboratory and hospital records containing basic demographic details, clinical characteristics, treatment regimen, survival outcome were collected retrospectively. Statistical association and survival analysis were performed using the R programming. The cohort includes 9,053 lung cancer patients tested for EGFR mutations during 2011 to 2019. Baseline T790M and compound mutations were the only mutations observed co-occurring while all other EGFR mutations were mutually exclusive. Furthermore, the baseline T790M were also observed to be associated with TTF1 positivity, smoking and local metastasis. Overall survival of the patients harboring co-occurring compound mutations was significantly lesser than the other EGFR positive patients. Overall, our study suggests that EGFR TKI may provide real-world benefit to the lung cancer patients harboring mutually exclusive EGFR mutations. On the other hand, further systematic study is essential to develop better therapeutic regimen for co-occurring baseline EGFR T790M and other compound mutations.

Bovine reproductive immunoinfertility: pathogenesis and immunotherapy.

Infertility is one of the primary factors for cattle reproduction in the present scenario. Reproduction-related immunoinfertility mainly involves immunization against the antigens related to reproductive hormones (LHRH, GnRH, Gonadal steroids, PGF2α and oxytocin), spermatozoa, seminal plasma and ovum. Anovulation, delayed ovulation, sperm immobilization, failure of fertilization, prolonged uterine involution, extended calving interval, prolonged post-partum estrus and reduced conception rate could be a result of immunoinfertility that occur due to the blockage of receptor site by antibodies formed against hormones, sperm and ovum. Immunoinfertility can be treated in the animal by giving sexual rest to females, by using various reproductive technologies such as in-vitro fertilization, gamete intra fallopian tube transfer, and intracytoplasmic sperm injection, sperm washing and by treating the animals with immunomodulators such as LPS, Oyster glycogen, etc. This review summarizes the different causes of bovine reproductive immunoinfertility and amelioration strategies to overcome it.

Gut Microbiome Wellness Index 2 for Enhanced Health Status Prediction from Gut Microbiome Taxonomic Profiles.

Recent advancements in human gut microbiome research have revealed its crucial role in shaping innovative predictive healthcare applications. We introduce Gut Microbiome Wellness Index 2 (GMWI2), an advanced iteration of our original GMWI prototype, designed as a robust, disease-agnostic health status indicator based on gut microbiome taxonomic profiles. Our analysis involved pooling existing 8069 stool shotgun metagenome data across a global demographic landscape to effectively capture biological signals linking gut taxonomies to health. GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence (i.e., outside the "reject option"). The enhanced classification accuracy of GMWI2 outperforms both the original GMWI model and traditional species-level α-diversity indices, suggesting a more reliable tool for differentiating between healthy and non-healthy phenotypes using gut microbiome data. Furthermore, by reevaluating and reinterpreting previously published data, GMWI2 provides fresh insights into the established understanding of how diet, antibiotic exposure, and fecal microbiota transplantation influence gut health. Looking ahead, GMWI2 represents a timely pivotal tool for evaluating health based on an individual's unique gut microbial composition, paving the way for the early screening of adverse gut health shifts. GMWI2 is offered as an open-source command-line tool, ensuring it is both accessible to and adaptable for researchers interested in the translational applications of human gut microbiome science.

Evaluating the prebiotic effect of oligosaccharides on gut microbiome wellness using in vitro fecal fermentation.

We previously proposed the Gut Microbiome Wellness Index (GMWI), a predictor of disease presence based on a gut microbiome taxonomic profile. As an application of this index for food science research, we applied GMWI as a quantitative tool for measuring the prebiotic effect of oligosaccharides. Mainly, in an in vitro anaerobic batch fermentation system, fructooligosaccharides (FOS), galactooligosaccharides (GOS), xylooligosaccharides (XOS), inulin (IN), and 2'-fucosyllactose (2FL), were mixed separately with fecal samples obtained from healthy adult volunteers. To find out how 24 h prebiotic fermentation influenced the GMWI values in their respective microbial communities, changes in species-level relative abundances were analyzed in the five prebiotics groups, as well as in two control groups (no substrate addition at 0 h and for 24 h). The GMWI of fecal microbiomes treated with any of the five prebiotics (IN (0.48 ± 0.06) > FOS (0.47 ± 0.03) > XOS (0.33 ± 0.02) > GOS (0.26 ± 0.02) > 2FL (0.16 ± 0.06)) were positive, which indicates an increase of relative abundances of microbial species previously found to be associated with a healthy, disease-free state. In contrast, the GMWI of samples without substrate addition for 24 h (-0.60 ± 0.05) reflected a non-healthy, disease-harboring microbiome state. Compared to the original prebiotic index (PI) and α-diversity metrics, GMWI provides a more data-driven, evidence-based indexing system for evaluating the prebiotic effect of food components. This study demonstrates how GMWI can be applied as a novel PI in dietary intervention studies, with wider implications for designing personalized diets based on their impact on gut microbiome wellness.

Giant Cell Arteritis in an Elderly Female With Pulmonary Tuberculosis.

Giant cell arteritis (GCA) is a type of systemic vasculitis that primarily affects people over the age of 50 and affects the medium to large arteries. GCA's clinical manifestations can be varied and non-specific, similar to those observed in atherosclerosis. Here, the authors present a case of an elderly woman with pulmonary tuberculosis with GCA masquerading as atherosclerosis.

Patients with ACPA-positive and ACPA-negative rheumatoid arthritis show different serological autoantibody repertoires and autoantibody associations with disease activity.

Patients with rheumatoid arthritis (RA) can test either positive or negative for circulating anti-citrullinated protein antibodies (ACPA) and are thereby categorized as ACPA-positive (ACPA+) or ACPA-negative (ACPA-), respectively. In this study, we aimed to elucidate a broader range of serological autoantibodies that could further explain immunological differences between patients with ACPA+ RA and ACPA- RA. On serum collected from adult patients with ACPA+ RA (n = 32), ACPA- RA (n = 30), and matched healthy controls (n = 30), we used a highly multiplex autoantibody profiling assay to screen for over 1600 IgG autoantibodies that target full-length, correctly folded, native human proteins. We identified differences in serum autoantibodies between patients with ACPA+ RA and ACPA- RA compared with healthy controls. Specifically, we found 22 and 19 autoantibodies with significantly higher abundances in ACPA+ RA patients and ACPA- RA patients, respectively. Among these two sets of autoantibodies, only one autoantibody (anti-GTF2A2) was common in both comparisons; this provides further evidence of immunological differences between these two RA subgroups despite sharing similar symptoms. On the other hand, we identified 30 and 25 autoantibodies with lower abundances in ACPA+ RA and ACPA- RA, respectively, of which 8 autoantibodies were common in both comparisons; we report for the first time that the depletion of certain autoantibodies may be linked to this autoimmune disease. Functional enrichment analysis of the protein antigens targeted by these autoantibodies showed an over-representation of a range of essential biological processes, including programmed cell death, metabolism, and signal transduction. Lastly, we found that autoantibodies correlate with Clinical Disease Activity Index, but associate differently depending on patients' ACPA status. In all, we present candidate autoantibody biomarker signatures associated with ACPA status and disease activity in RA, providing a promising avenue for patient stratification and diagnostics.

GMWI-webtool: a user-friendly browser application for assessing health through metagenomic gut microbiome profiling.

SUMMARY: We recently introduced the Gut Microbiome Wellness Index (GMWI), a stool metagenome-based indicator for assessing health by determining the likelihood of disease given the state of one's gut microbiome. The calculation of our wellness index depends on the relative abundances of health-prevalent and health-scarce species. Encouragingly, GMWI has already been utilized in various studies focusing on differences in the gut microbiome between cases and controls. Herein, we introduce the GMWI-webtool, a user-friendly browser application that computes GMWI, health-prevalent/-scarce species' relative abundances, and α-diversities from stool shotgun metagenome taxonomic profiles. Users of our interactive online tool can visualize their results and compare them side-by-side with those from our pooled reference dataset of metagenomes, as well as export data in.csv format and high-resolution figures. AVAILABILITY AND IMPLEMENTATION: GMWI-webtool is freely available here: https://gmwi-webtool.github.io/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

TaxiBGC: a Taxonomy-Guided Approach for Profiling Experimentally Characterized Microbial Biosynthetic Gene Clusters and Secondary Metabolite Production Potential in Metagenomes.

Biosynthetic gene clusters (BGCs) in microbial genomes encode bioactive secondary metabolites (SMs), which can play important roles in microbe-microbe and host-microbe interactions. Given the biological significance of SMs and the current profound interest in the metabolic functions of microbiomes, the unbiased identification of BGCs from high-throughput metagenomic data could offer novel insights into the complex chemical ecology of microbial communities. Currently available tools for predicting BGCs from shotgun metagenomes have several limitations, including the need for computationally demanding read assembly, predicting a narrow breadth of BGC classes, and not providing the SM product. To overcome these limitations, we developed taxonomy-guided identification of biosynthetic gene clusters (TaxiBGC), a command-line tool for predicting experimentally characterized BGCs (and inferring their known SMs) in metagenomes by first pinpointing the microbial species likely to harbor them. We benchmarked TaxiBGC on various simulated metagenomes, showing that our taxonomy-guided approach could predict BGCs with much-improved performance (mean F1 score, 0.56; mean PPV score, 0.80) compared with directly identifying BGCs by mapping sequencing reads onto the BGC genes (mean F1 score, 0.49; mean PPV score, 0.41). Next, by applying TaxiBGC on 2,650 metagenomes from the Human Microbiome Project and various case-control gut microbiome studies, we were able to associate BGCs (and their SMs) with different human body sites and with multiple diseases, including Crohn's disease and liver cirrhosis. In all, TaxiBGC provides an in silico platform to predict experimentally characterized BGCs and their SM production potential in metagenomic data while demonstrating important advantages over existing techniques. IMPORTANCE Currently available bioinformatics tools to identify BGCs from metagenomic sequencing data are limited in their predictive capability or ease of use to even computationally oriented researchers. We present an automated computational pipeline called TaxiBGC, which predicts experimentally characterized BGCs (and infers their known SMs) in shotgun metagenomes by first considering the microbial species source. Through rigorous benchmarking techniques on simulated metagenomes, we show that TaxiBGC provides a significant advantage over existing methods. When demonstrating TaxiBGC on thousands of human microbiome samples, we associate BGCs encoding bacteriocins with different human body sites and diseases, thereby elucidating a possible novel role of this antibiotic class in maintaining the stability of microbial ecosystems throughout the human body. Furthermore, we report for the first time gut microbial BGC associations shared among multiple pathologies. Ultimately, we expect our tool to facilitate future investigations into the chemical ecology of microbial communities across diverse niches and pathologies.

Combination therapy with lansoprazole and cholecalciferol is associated with a slower decline in residual beta-cell function and lower insulin requirements in children with recent onset type 1 diabetes: results of a pilot study.

OBJECTIVE: To investigate the effects of combination therapy with cholecalciferol and lansoprazole on residual ß-cell function and glycemic control in children with new-onset type 1 diabetes. METHODS: Children aged 6-12 years with type 1 diabetes were allocated to receive cholecalciferol and lansoprazole (Group 1) or no treatment (Group 2). Children were maintained on their respective insulin regimens and kept records of blood sugar and insulin doses taken. Children were followed at three-month intervals for six months. Changes in mean fasting C-peptide and HbA1c levels, daily insulin doses, fasting blood glucose and mean blood glucose levels from baseline to end of the study were analyzed. RESULTS: Twenty-eight children (14 per group) met the eligibility criteria. Fasting C-peptide levels decreased significantly from baseline to study end in both groups (mean decrease -0.19±0.09ng/mL and -0.28±0.08ng/mL, p=0.04 and p=0.001; Group 1 and Group 2 respectively). However, fasting C-peptide level drop was significantly smaller in Group 1 compared to Group 2 (30.6% and 47.5% respectively; p=0.001). Likewise, daily insulin doses decreased significantly in both groups (-0.59±0.14units/kg and -0.37±0.24units/kg respectively; p=0.001). All patients recruited completed the study. No adverse events were reported. CONCLUSION: Combined therapy with cholecalciferol and lansoprazole for six months was associated with smaller decline in residual ß-cell function and lower insulin requirements in children with new-onset type 1 diabetes. Preliminary findings of this small-scale study need to be confirmed by larger studies. REGISTRY OF CLINICAL TRIALS: (www.ctri.nic.in) under number REF/2021/03/041415 N.

Effect of endogenous hormones, antisperm antibody and oxidative stress on semen quality of crossbred bulls.

The present study was designed to evaluate the effect of factors like hormones, antisperm antibody (ASA), and oxidative stress and its relation with semen quality in crossbred bulls. Ejaculates from two bulls were categorized into good (n = 12) and poor (n = 12) based on initial progressive motility, that is, ≥70% and ≤50%, respectively. The level of hormones like Testosterone (p < 0.05) and PGE2 (p < 0.01) was significantly higher in good-quality ejaculates compared to poor-quality ejaculates; however, estradiol (p < 0.05), progesterone, oxidative stress, and ASAs were significantly higher (p < 0.01) in poor-quality ejaculates compared to good-quality ejaculates. Therefore, it could be concluded that oxidative stress and hormonal imbalance might have resulted in high number of dead and defective spermatozoa which was ultimately responsible for poor quality semen ejaculates.

Heavy metals controlling cardiovascular diseases risk factors in myocardial infarction patients in critically environmentally heavy metal-polluted steel industrial town Mandi-Gobindgarh (India).

Heavy metals (HMs) have a very significant clinical role in the pathogenesis, progression and management of cardiovascular diseases (CVDs). The prevalence of CVDs was reported to be higher in critically environmentally HM-polluted (EHMP) steel industrial town Mandi-Gobindgarh (India) for the last more than a decade. To ascertain the role of HMs in the onset of CVDs, the present study was chosen to investigate HMs content in myocardial infarction (MI) patients from EHMP steel industrial town Mandi-Gobindgarh. Total of 110 MI patients along with number- and age-matched healthy volunteers were recruited in the present investigation. The CVDs risk factors estimated in MI patients were overweight (higher body mass index), hypertension (higher systolic and diastolic blood pressures), dyslipidaemia (higher serum cholesterol, triglycerides and lower HDL cholesterol), inflammation (higher-serum C reactive protein and aldosterone) and elevated oxidative stress (higher urinary 8-hydroxydeoxyguanosine). An imbalance of serum electrolyte concentrations including Na (hypernatremia), Ca (hypercalcaemia) and K (hypokalaemia) was also observed in MI patients in which CVDs risk factors were found to correlate positively with serum Na and Ca and negatively with serum K, respectively. Hair HM analysis was used as a bio-indicator for monitoring body HM status from past environmental HM exposure in which CVDs risk factors were observed to correlate positively with higher hair concentrations of Zn, Fe, Mo, Pb, As, Ca and Na and negatively with lower hair concentrations of Cu, Mg, Mn and K in MI patients, respectively. Thus, higher hair concentrations of Zn and Pb indicate their higher environmental exposure and possible cause of higher CVDs risk factors in MI patients from Mandi-Gobindgarh.

Stochastic block models reveal a robust nested pattern in healthy human gut microbiomes.

A key question in human gut microbiome research is what are the robust structural patterns underlying its taxonomic composition. Herein, we use whole metagenomic datasets from healthy human guts to show that such robust patterns do exist, albeit not in the conventional enterotype sense. We first introduce the concept of mixed-membership enterotypes using a network inference approach based on stochastic block models. We find that gut microbiomes across a group of people (hosts) display a nested structure, which has been observed in a number of ecological systems. This finding led us to designate distinct ecological roles to both microbes and hosts: generalists and specialists. Specifically, generalist hosts have microbiomes with most microbial species, while specialist hosts only have generalist microbes. Moreover, specialist microbes are only present in generalist hosts. From the nested structure of microbial taxonomies, we show that these ecological roles of microbes are generally conserved across datasets. Our results show that the taxonomic composition of healthy human gut microbiomes is associated with robustly structured combinations of generalist and specialist species.