Evaluation of total IgE in diverse allergosis. Statistical study. Part III.
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Humans↗
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Results for “diversity statistic”
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SURROGATE SELECTION OVERSAMPLES EXPANDED T CELL CLONOTYPES.
Surrogate selection is an experimental design that without sequencing any DNA can restrict a sample of cells to those carrying certain genomic mutations. In immunological disease studies, this design may provide a relatively easy approach to enrich a lymphocyte sample with cells relevant to the disease response because the emergence of neutral mutations associates with the proliferation history of clonal subpopulations. A statistical analysis of clonotype sizes provides a structured, quantitative perspective on this useful property of surrogate selection. Our model specification couples within-clonotype birth-death processes with an exchangeable model across clonotypes. Beyond enrichment questions about the surrogate selection design, our framework enables a study of sampling properties of elementary sample diversity statistics; it also points to new statistics that may usefully measure the burden of somatic genomic alterations associated with clonal expansion. We examine statistical properties of immunological samples governed by the coupled model specification, and we illustrate calculations in surrogate selection studies of melanoma and in single-cell genomic studies of T cell repertoires.
Bayes’s rule↗
Conduit urinary diversion and urinary-tract infection. II. Raised serum antibody titers against Escherichia coli and Proteus mirabilis in relation to bacteriologic findings.
Elevated serum antibody titers against Escherichia coli and/or Proteus mirabilis were found in 35% of 89 patients with a conduit urinary diversion. Statistical analysis showed significant correlation between the titers and growth of E. coli or P. mirabilis in conduit urine. But 17 (24%) of 72 patients without E. coli in urine cultures had raised E. coli antibody titer. Only 3 (4%) of 68 patients without growth of P. mirabilis had raised P. mirabilis antibody titer. When the post-diversion observation period was more than five years, the frequency of antibody titer elevation was greater than in patients with shorter post-diversion follow-up. The volume of residual urine in the conduit showed statistically significant correlation with presence of bacteriuria and with the antibody titer level against P. mirabilis. Patients with high antibody titers tended to have high readings of serum creatinine. Antibiotic therapy reduced elevated E. coli and P. mirabilis antibody titers. Titration of antibodies to E. coli and P. mirabilis is recommended in the follow-up care of patients with conduit urinary diversion.
Adolescent↗
The neonate's immunity gap, breast feeding and cot death.
In many mammals infant behaviour imposes a period during which the young will only take the mother's milk. It is suggested that the immunological components of the milk serve in this period to augment the baby's immune system while he traverses from the antigenic isolation of a fetus to his independent defence. In humans almost all cot deaths occur during this phase. Diverse statistics relating to factors associated with greater risk of cot death are drawn on, suggesting that a number of seemingly unconnected factors can all (including lack of breast-feeding) be interpreted as potential immunity defaults. This interpretation lends support to the idea of an immune mechanism underlying cot death which in some way is an abnormal response resulting from the default and which, with at least one other precipitating mechanism, leads to death.
Anaphylaxis↗
MultiDMPcaller: a one-stop software for detection and visualization of differentially methylated positions and regions.
MOTIVATION: Whole-genome bisulfite sequencing (WGBS/BS-Seq) is the gold standard for single-base resolution DNA methylome profiling. However, the diverse statistical models of existing computational methods lead to limited overlap between their results, highlighting the need for novel methods to detect differentially methylated positions (DMPs) and differentially methylated regions (DMRs). RESULTS: We developed MultiDMPcaller, an automated downstream methylome analysis software. It processes upstream outputs to profile DMPs, non-DMPs, DMRs, and context-specific (CpG/CHG/CHH) methylation status, alongside visualizing their chromosomal distribution and enrichment. The software features two key innovations: (i) an adaptive two-step P-value adjustment strategy based on organism-specific methylation patterns, with raw P-value ≤0.05 pre-filtering followed by false discovery rate (FDR) correction, to recover potential DMPs usually missed by standard FDR correction in plant CHG/CHH and animal CpG contexts; and (ii) a multiple pairwise comparison approach, which performs m × n pairwise comparisons for m control and n experimental replicates, followed by a voting system supporting both user-defined majority thresholds and model-based adaptive thresholds, to identify robust and reliable DMPs (with a stricter voting threshold exclusively for loci with low methylation differences) and DMRs. On real datasets from Arabidopsis, apple, and mouse, as well as simulated human datasets, MultiDMPcaller's results showed good agreement with those of other software, exhibiting high conservativeness and superior precision, which suggested a low false discovery proportion. AVAILABILITY AND IMPLEMENTATION: MultiDMPcaller is available at GitHub (https://github.com/jiantaoyuNWAFU/MultiDMPcaller) and via a web server (https://ciebioinfo.nwafu.edu.cn).
Software↗
Models and statistics for species diversity.
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Models, Biological↗
F-statistics and analysis of gene diversity in subdivided populations.
It is show that Wright's F-statistics can be defined as ratios of gene diversities of heterozygosities rather than as the correlations of uniting gametes. This definition is applicable irrespective of the number of alleles involved or whether there is selection or not. The relationship between F-statistics and Nei's gene diversity analysis is discussed.
Alleles↗
Metabolomic and structural signatures of pigmented and non-pigmented Himalayan rice landraces.
BACKGROUND: This study investigated the anti-oxidant properties, starch composition, pasting behavior, structural properties, textural properties and non-targeted metabolomic profiles of pigmented and non-pigmented rice landraces as potential next-generation functional food ingredients. RESULTS: Pigmented rice demonstrated 1.34 times more anti-oxidant activity as compared to non-pigmented rice. Pigmented landraces showcased superior nutritional and functional attributes, including higher total dietary fiber and starch content. Fourier-transform infrared (FTIR) analysis revealed distinct molecular signatures with enhanced peak transmittance, while X-ray diffraction (XRD) indicated greater crystallinity ranging from 36-44.3% in pigmented rice compared with 30-40% in non-pigmented rice, suggesting improved digestibility and processing versatility. Pigmented rice recorded less amylose content hence tended to possess increased adhesiveness values whereas non-pigmented rice revealed greater amylose content hence was coupled with greater hardness values. Field-emission scanning electron microscopy (FE-SEM) images revealed that pigmented rice had densely packed and polygonal starch granules whereas non-pigmented rice had loosely packed starch granules with intergranular voids. Untargeted gas chromatography-mass spectrometry (GC-MS) profiling identified 84 metabolites, including unique compounds such as 3,3-dimethylbutanol and ethanoic acid, along with shared metabolites such as sucrose and linoleic acid, highlighting notable biochemical diversity. Multivariate statistical analyses using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway mapping further differentiated the metabolomic landscapes, with variable importance in the projection (VIP) scores identifying key bioactive contributors. CONCLUSION: Pigmented rice landraces exhibited significant functional and nutritional advantages, making them promising candidates for functional food development and nutritional improvement programs. These findings support their potential role in advancing sustainable and health-oriented food systems. © 2026 Society of Chemical Industry.
Oryza↗
Oral and gut microbiota profiles in patients with locally advanced rectal cancer with varying responses to neoadjuvant chemoradiotherapy.
Recent research has focused on gut bacteria in colorectal cancer, but the influence of other microbiota, including oral and nonbacterial gut microbiota, on treatment efficacy remains insufficiently explored. This study aimed to investigate their relationship with the efficacy of neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). Saliva and fecal samples were collected from patients with LARC before treatment. Shotgun metagenomic sequencing was used to profile bacterial, archaeal, eukaryotic, and viral taxonomic groups and to examine oral and gut microbial functions. An artificial intelligence-based prediction model was developed by integrating oral and gut microbiome data with clinical information. Statistical analyses compared diversity and response-associated microbial features between responders and non-responders to nCRT. Response-associated differences were observed in bacterial and nonbacterial taxonomic profiles and in oral and gut microbial functional profiles. In the internal test subset, the integrated analysis yielded an observed AUC of 0.917. Given the small cohort and the exploratory comparison of candidate classifiers, this estimate requires confirmation in larger, independent cohorts. Baseline oral and gut microbiome profiles were associated with response to nCRT. Integrating microbiome and clinical features showed potential for response prediction, but the model remains exploratory and requires validation in larger, independent cohorts before clinical application. Retrospectively registered on 01/08/2026, NCT07346729.
Aged↗
Genetic predisposition to systemic inflammatory proteins is causally associated with inflammatory bowel disease: Insights from multi-omics association study and single-cell RNA-sequencing analysis.
Systemic inflammatory proteins have been reported to be related to inflammatory bowel disease (IBD) in previous observational research. However, their causal links remain obscure. Herein, we performed a Mendelian randomization (MR) analysis to analyze the causality between systemic inflammatory proteins and IBD. Genetic variants related to systemic inflammatory proteins were extracted from a meta-analysis of genome-wide association study (GWAS) data of 8293 European participants. Summary statistics of IBD diverse subtypes were obtained from the international IBD genetic consortium (IIBDGC). We conducted multi-omics method and MR study to detect the causal links through integrating GWAS and protein quantity trait loci (pQTL) data. Inverse variance weighted (IVW) approach was utilized as the dominated analysis method. Moreover, complementary approaches such as MR-Egger intercept test, Cochran Q test and leave-one-out analysis were utilized to validate pleiotropy and heterogeneity. Finally, single-cell RNA-sequencing analysis was performed to detect the expression of significant genes. For IBD, IVW estimates suggested that genetically predicted IL-10 and IL-13 were suggestively associated with an elevated risk of IBD (IL-10: OR: 1.12, 95% CI: 1.00-1.24, P = .04; IL-13: OR: 1.09, 95% CI: 1.01-1.18, P = .023), while CXCL10 was suggestively linked to a lower risk of IBD (CXCL10: OR: 0.90, 95% CI: 0.82-0.99, P = .037). For Crohn disease (CD), the IVW approach provided evidence to sustain that genetically determined IL-13 and CCL3 had a suggestive association with a higher risk of CD (IL-13: OR: 1.13, 95% CI: 1.02-1.26, P = .023; CCL3: OR: 1.22, 95% CI: 1.03-1.45, P = .018). Sensitivity analysis did not explore any heterogeneity and pleiotropy. Our findings supported the causal relationships between 4 specific inflammatory proteins (IL-10, IL-13, CXCL10, and CCL3) and the risk of IBD and CD, thereby providing promising biomarkers of various subtypes stratification and new insights for the prevention and therapeutic target of IBD.
Humans↗
A new potential mosquito-borne virus: detection of Human-derived Jingmenvirus in several-species of mosquitoes from Yaoundé, Cameroon.
BACKGROUND: Tick-borne Jingmenviruses are becoming an increasing arbovirus concern due to the rising number of reported infections in humans and animals, as well as their wide geographic distribution. The involvement of other hematophagous arthropods as vectors of Jingmenviruses is still unknown. METHODS: Mosquitoes were sampled in two different biotopes in Cameroon (Yaoundé and Garoua) during the rainy and the dry seasons in 2022 and 2023. Metatranscriptomics Next Generation Sequencing was conducted using Illumina technology. Viral sequences detection revealed the presence of several contigs with high sequence identity to a human-derived Jingmenvirus (HdJV) previously discovered in plasma from an individual from Yaoundé, Cameroon. A draft viral genome was constituted for each Jingmenvirus-positive samples. Maximum likelihood phylogenetic reconstructions were used to position mosquito-associated viruses within the diversity of Jingmenviruses. Statistical analyses were conducted to estimate the prevalence of infected mosquitoes and the effect of different variables (region, season, year, mosquito species) on Jingmenvirus detection. RESULTS: HdJV was identified during the dry and the rainy seasons in 4 species of mosquitoes: Aedes albopictus, Culex quinquefasciatus and Culex wansoni from Yaoundé, and Anopheles gambiae s.l. from Garoua. The overall prevalence of HdJV-infected mosquitoes was estimated to 0.90% [0.41-1.69]; and the unique variable significantly associated with HdJV detection was the sampling area: Yaoundé showed the highest prevalence (2.29% [0.95-4.68]) compared to Garoua (0.18% [0.01-0.79]). Mosquito-associated Jingmenviruses shared a high nucleotide identity (between 98.64-100% according to the segment) and clustered in the same clade in the phylogenetic analysis, that they belong to the same viral species circulating in different mosquito species. The viral genome shared between 96.4% and 98.9% nucleotide identity with a HdJV detected in the plasma of a patient suffering from febrile illness originating from the same area, suggesting the possible involvement of mosquitoes as vectors of arboviral Jingmenviruses in human infections. CONCLUSIONS: This finding provides new insights into the ecology and transmission dynamics of Jingmenviruses, highlighting mosquitoes as potential vectors, alongside ticks, in the zoonotic transmission of this virus group.
Jingmenvirus↗
RAD-Seq-derived SNPs reveal no local population structure in the commercially important deep-sea queen snapper (Etelis oculatus) in Puerto Rico.
UNLABELLED: The queen snapper (Etelis oculatus Valenciennes in Cuvier & Valenciennes, 1828) is a deep-sea snapper whose commercial importance continues to increase in the US Caribbean. However, little is known about the biology and ecology of this species. In this study, the presence of a fine-scale population structure and genetic diversity of queen snapper from Puerto Rico was assessed through 16,188 SNPs derived from the Restriction site Associated DNA Sequencing (RAD-Seq) technique. Summary statistics estimated low genetic diversity (HO = 0.333-0.264) and did not reveal population differentiation within our samples (F ST = - 0.001-0.025). Principal component analysis and a model-based clustering method did not detect a fine-scale subpopulation structure among sampling sites, however, there was genetic variability within regions and sites. Our results have revealed comparable genetic and dispersal patterns to those observed in other shallow-water snapper species in Puerto Rico waters. It is crucial to further enhance our understanding of the ecological and biological aspect of the queen snapper to effectively manage and conserve this species as fishing pressure has been extended to deep water species in the US Caribbean. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42995-025-00289-7.
Caribbean Fisheries↗
Instrumented Walkway Gait Analysis Predicts Fallers in Neurological Disorders: Identifying Digital Biomarkers for Balance Monitoring.
Assessing balance is crucial in neurological rehabilitation, yet while wearable sensors enable real-world monitoring, identifying reliable digital biomarkers remains challenging. This study utilized a high-fidelity instrumented walkway to determine which gait parameters best predict balance impairment, providing robust targets for future wearable applications. We analyzed 49 steady-state gait metrics from 140 individuals with diverse neurological conditions. Using statistical analysis and machine learning, we evaluated these parameters against objective force plate sway scores and clinical fall-history labels. Group analysis identified 16 parameters significantly distinguishing fallers from non-fallers, and a neural network classified fallers with an area under the curve of 0.75. Across all analytical approaches, overall gait variability, e.g., Stride Width S.D. and the Gait Variability Index, emerged as a universal predictor of balance impairment and fall risk. Furthermore, while traditional linear models emphasized spatial postural control, machine learning classification uniquely identified inter-limb asymmetry as a premier driver of fall prediction. These findings indicate that instrumented gait analysis effectively identifies digital biomarkers for balance deficits. Isolating these specific metrics provides a clear blueprint for meaningful metrics required for continuous objective monitoring and future development of personalized, adaptive rehabilitation strategies.
Humans↗
Agnostic polygenic prediction of weight loss after bariatric surgery.
A large interindividual variability in weight loss outcomes following bariatric surgery is reported. To ensure optimal management of patients, it is crucial to accurately identify candidates most likely to benefit the most from the intervention. Since genetic variants largely contribute to surgery response, polygenic scores (PGS) derived from genome-wide association studies (GWAS) could constitute valuable tools for clinical decision making. We developed and evaluated PGS to predict the weight loss response in 540 patients with a body mass index (BMI) of 35 kg/m2 or higher who underwent biliopancreatic diversion with duodenal switch. Summary statistics derived from BMI-derived GWAS, together with summary statistics from previously published GWAS of BMI and adiposity features, were used to construct, evaluate, and benchmark weight loss PGS. The full-adjusted BMI PGS model built in the entire cohort explained 39.6% of the mean-over-time excessive body weight loss (%EBWL), while the BMI-PGS built in the training dataset explained 38.9%. All benchmarked PGS based on BMI showed a significant relationship with mean-over-time %EBWL. These findings highlight the potential of BMI PGS in predicting weight loss after bariatric surgery and support their use as promising tools to improve the effectiveness of future antiobesity treatments.
Humans↗
CRISPGen: A deep generative framework for multi-objective CRISPR/Cas9 guide RNA design via Conditional Latent Diffusion and Dual-Critic Reinforcement Learning.
MOTIVATION: The CRISPR-Cas9 system offers transformative potential for precision genome editing, yet its clinical translation remains constrained by the risk of unintended off-target double-strand breaks. While current discriminative models excel at evaluating pre-specified candidate guides, resolving the fundamental antagonism between on-target cleavage efficiency and off-target specificity within a fixed sequence search space remains a major challenge. RESULTS: We present CRISPGen, a unified deep generative framework that reframes sgRNA design as a multi-objective constrained sequence synthesis problem. It integrates (i) DNABERT-2 genomic-language embeddings, (ii) a conditional latent diffusion generator conditioned on a user-specified on-target efficiency target, and (iii) a dual-critic reinforcement-learning (RL) stage that couples a frozen on-target efficiency critic with a cross-attention off-target discriminator (validation Pearson R=0.8157) trained on a unified corpus of experimental off-target events from six detection platforms. Across 1000 generated sgRNAs, CRISPGen reduces the mean off-target discriminator score by 99.7% relative to the pre-RL baseline and, under an exhaustive whole-genome screen of all 302,631,056 NGG PAM sites in GRCh38, yields zero perfect-match and only 55 one-mismatch genomic hits. We further show, transparently, that the internal on-target critic saturates under RL optimization - an instance of Goodhart's Law - and therefore assess on-target viability using an independent external CRISPRon screen (mean 47.10/100). Repeating the RL fine-tuning stage under three random seeds (with the diffusion generator, DNABERT-2 embeddings, and off-target discriminator held fixed) yields a stable operating point across seeds. Full diversity, per-mismatch, and reproducibility statistics are reported in the Results. AVAILABILITY: Source code is available at https://github.com/malekpouri/CRISPGen; the pre-trained checkpoints and the 3,000,000-sequence library are hosted on Hugging Face (https://huggingface.co/malekpouri/CRISPGen-Checkpoints) and archived on Zenodo under DOI 10.5281/zenodo.21428641.
CRISPR-Cas9↗
Comparison of clinical efficacy and gut microbiota characteristics in children with ASD treated with fecal microbiota transplantation and ketogenic diet.
OBJECTIVE: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social communication and interaction, along with restricted, repetitive patterns of behavior. It is often accompanied by gastrointestinal dysfunction and gut microbiota dysbiosis. Fecal Microbiota Transplantation (FMT) and the Ketogenic Diet (KD) are interventions targeting the gut microbiota for ASD. METHODS: 30 participants were diagnosed with ASD according to DSM-5 and ADOS-2. ASD core symptoms were evaluated with CARS and ABC. Gut microbiota composition was analyzed by shotgun metagenomic sequencing. RESULTS: Both groups demonstrated significant improvements in core symptoms. In the FMT group, the mean CARS score significantly decreased from 34.87 to 33.53 (p < 0.01); in the KD group, it declined from 35.13 to 33 (p < 0.01). The mean ABC score reduced from 79.93 to 69.33 (p = 0.064) in the FMT group and from 63.07 to 42.73 (p < 0.01) in the KD group. Following the intervention, no statistically significant changes were observed in α-diversity or β-diversity within either group. LEfSe analysis revealed distinct post-intervention microbial signatures: FMT significantly enriched butyrate-producing taxa (Wujia chipingensis, Eubacterium sp. MSJ-33, and Butyrivibrio crossotus), while KD elevated Blautia massiliensis and decreased propionate metabolism -associated taxa (Veillonella sp. S12025-13 and Veillonella nakazawae). KEGG enrichment analysis revealed that KD enriched propionate metabolism (Fold enrichment = 3.747, q = 0.010) and aromatic compound degradation (Fold enrichment = 3.591, q = 0.010). CONCLUSIONS: Both interventions significantly improved clinical symptoms among children with ASD, potentially through distinct patterns of gut microbiota modulation. CLINICAL TRIALS NUMBER: NCT06348433 (03/21/2024).
Child↗
Metagenomic Analysis of the Tonsil Virome Highlights Its Diagnostic Potential for Rheumatoid Arthritis.
Rheumatoid arthritis (RA) is a chronic autoimmune disease whose exact pathogenesis remains unclear, despite links to genetics, environmental factors, and microbial dysbiosis. Recent studies have highlighted the role of the microbiome in RA, yet the contribution of the tonsil virome remains unexplored. This study aims to investigate whether changes in the tonsil virome are associated with RA progression and assess its diagnostic potential. Using metagenomic data from 32 RA patients and 30 healthy controls (HCs), we identified 45 782 viral operational taxonomic units (vOTUs), with 14 341 classified as core vOTUs. RA patients exhibited significantly reduced virome richness and diversity, whereas Siphoviridae and Microviridae dominated both groups. Statistical analysis identified 235 RA-associated viral markers, including 13 enriched in RA and 222 in HCs. RA-enriched markers were primarily bacteriophages infecting Streptococcaceae, whereas HCs displayed more diverse viral-host interactions. Random forest models demonstrated strong discriminatory power of viral markers in distinguishing RA patients from HCs, achieving an AUC of 0.960, outperforming bacterial markers. Correlation analyses further linked viral markers to immune cell subsets, suggesting that tonsil virome alterations may influence immune dysregulation in RA. This study reveals significant changes in the tonsil virome of RA patients, highlighting its potential as a diagnostic tool and offering new insights into RA pathogenesis. These findings pave the way for future research into the virome's role in autoimmune diseases and therapeutic development.
Humans↗
Spiramycin fermentation residue-derived biochar regulates soil nutrient cycling, microbial communities, and antibiotic resistance gene dynamics.
Spiramycin fermentation residues (SFR) are hazardous wastes enriched with residual antibiotics, yet they can serve as potential feedstocks for resource recovery after appropriate treatment. In this study, SFR-derived biochar (SFR-BC) was produced by pyrolysis and applied to agricultural soil to evaluate its effects on soil properties, microbial communities, potential pathogenic bacteria, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs). A 60-day soil incubation experiment was conducted with one control and three SFR-BC application rates of 0.5%, 1.0%, and 2.0%. SFR-BC improved soil physicochemical properties, nutrient status, enzyme activities, and microbial alpha diversity. Metagenomic analysis showed that SFR-BC altered the abundance of functional genes associated with carbon and nitrogen cycling, indicating shifts in microbial functional potential. SFR-BC also changed bacterial co-occurrence patterns, with the high-dose treatment showing a more complex and highly connected network structure during incubation. In addition, high-dose SFR-BC reduced several potential pathogenic bacteria, including major plant pathogenic taxa. SFR-BC decreased soil ARG abundance by 9.38%-33.67% and MGE abundance by 6.49%-27.89% relative to the control, showing a dose-dependent reduction in antibiotic resistance-related genetic elements. Network and PLS-PM analyses further indicated that ARG variation was statistically associated with soil physicochemical properties, microbial diversity, potential bacterial hosts, and MGEs. Overall, these results suggest that SFR-BC can improve short-term soil nutrient status and reduce ARGs, MGEs, and several potential pathogenic taxa under controlled incubation conditions, providing useful evidence for the potential valorization of antibiotic fermentation residues through pyrolysis.
Charcoal↗