A Cambrian spiny stem mollusk and the deep homology of lophotrochozoan scleritomes.

Mollusks encompass enormous disparity, including familiar clams and snails alongside less familiar aculiferans (chitons and vermiform aplacophorans) with complex multicomponent skeletons. Paleozoic fossils trace crown mollusks to forms exhibiting a combination of biomineralized shells and sclerites (e.g., scales, spines, and spicules). We describe a shell-less, Cambrian stem mollusk, Shishania aculeata gen. et sp. nov., with conical, hollow chitinous sclerites and a smooth girdle, broad foot, and mantle cavity. The sclerites have a microstructure of narrow canals consistent with the impressions of chaetal microvilli found in annelids and brachiopods. Shishania sclerites provide a morphological stepping stone between typical chaetae (chitinous bristles) and the external organic part of aculiferan sclerites that encloses a mineralized body. This discovery reinforces a common origin of lophotrochozoan chaetae and the biomineralized aculiferan sclerites, suggesting that the mollusk ancestor was densely covered with hollow chitinous chaetae.

CX43 and oxidative stress are the targets of BCB staining to predict the developmental potential of buffalo oocytes.

This study used the brilliant cresyl blue (BCB) staining method to group buffalo oocytes (BCB+ and BCB-) and perform in vitro maturation, in vitro fertilization and embryo culture. At the same time, molecular biology techniques were used to detect gap junction protein expression and oxidative stress-related indicators to explore the molecular mechanism of BCB staining to predict oocyte developmental potential. The techniques of buffalo oocytes to analyse their developmental potential and used immunofluorescence staining to detect the expression level of CX43 protein, DCFH-DA probe staining to detect ROS levels and qPCR to detect the expression levels of the antioxidant-related genes SOD2 and GPX1. Our results showed that the in vitro maturation rate, embryo cleavage rate and blastocyst rate of buffalo oocytes in the BCB+ group were significantly higher than those in the BCB- group and the control group (p < .05). The expression level of CX43 protein in the BCB+ group was higher than that in the BCB- group both before and after maturation (p < .05). The intensity of ROS in the BCB+ group was significantly lower than that in the BCB- group (p < .05), and the expression levels of the antioxidant-related genes SOD2 and GPX1 in the BCB+ group were significantly higher than those in the BCB- group (p < .05). Brilliant cresyl blue staining could effectively predict the developmental potential of buffalo oocytes. The results of BCB staining were positively correlated with the expression of gap junction protein and antioxidant-related genes and negatively correlated with the reactive oxygen species level, suggesting that the mechanism of BCB staining in predicting the developmental potential of buffalo oocytes might be closely related to antioxidant activity.

Mode division multiplexing reconstructive spectrometer with an all-fiber photonics lantern.

This study presents a high-accuracy, all-fiber mode division multiplexing (MDM) reconstructive spectrometer (RS). The MDM was achieved by utilizing a custom-designed 3 × 1 mode-selective photonics lantern to launch distinct spatial modes into the multimode fiber (MMF). This facilitated the information transmission by increasing light scattering processes, thereby encoding the optical spectra more comprehensively into speckle patterns. Spectral resolution of 2 pm and the recovery of 2000 spectral channels were accomplished. Compared to methods employing single-mode excitation and two-mode excitation, the three-mode excitation method reduced the recovered error by 88% and 50% respectively. A resolution enhancement approach based on alternating mode modulation was proposed, reaching the MMF limit for the 3 dB bandwidth of the spectral correlation function. The proof-of-concept study can be further extended to encompass diverse programmable mode excitations. It is not only succinct and highly efficient but also well-suited for a variety of high-accuracy, high-resolution spectral measurement scenarios.

Genetic Variability of CYP4F2, CYP2D6, CYP2E1, and ACE in the Chinese Yi Population.

Genetic polymorphisms of very important pharmacogenes (VIP) are a significant factor contributing to inter-individual variability in drug therapy. The purpose of this study was to identify significantly different loci in the Yi population and to enrich their pharmacogenomic information. 54 VIP variants were selected from the Pharmacogenomics Knowledge Base (PharmGKB) and genotyped in 200 Yi individuals. Then, we compared their genotype distribution between the Yi population and the other 26 populations using the χ2 test. Compared with the other 26 populations, the genotype frequencies of 4 single nucleotide polymorphisms (SNPs), rs2108622 (CYP4F2), rs1065852 (CYP2D6), rs2070676 (CYP2E1), and rs4291 (ACE), had significant differences in the Yi population. For example, the TT genotype frequency of rs2108622 (8.1%) was higher than that of African populations, and the AA genotype frequency of rs1065852 (27.3%) was higher than that of other populations except East Asians. We also found that the Yi populations differed the least from East Asians and the most from Africans. Furthermore, the differences in these variants might be related to the effectiveness and toxicity risk of using warfarin, iloperidone, cisplatin cyclophosphamide, and other drugs in the Yi population. Our data complement the pharmacogenomic information of the Yi population and provide theoretical guidance for their personalized treatment.

Multi-omics strategy reveals potential role of antimicrobial resistance and virulence factor genes responsible for Simmental diarrheic calves caused by Escherichia coli.

Escherichia coli (E. coli) is reported to be an important pathogen associated with calf diarrhea. Antibiotic resistance genes (ARGs) and virulence factor genes (VFGs) pose a considerable threat to both animal and human health. However, little is known about the characterization of ARGs and VFGs presented in the gut microbiota of diarrheic calves caused by E. coli. In this study, we used multi-omics strategy to analyze the ARG and VFG profiles of Simmental calves with diarrhea caused by E. coli K99. We found that gut bacterial composition and their microbiome metabolic functions varied greatly in diarrheic calves compared to healthy calves. In total, 175 ARGs were identified, and diarrheal calves showed a significantly higher diversity and abundance of ARGs than healthy calves. Simmental calves with diarrhea showed higher association of VFGs with pili function, curli assembly, and ferrienterobactin transport of E. coli. Co-occurrence patterns based on Pearson correlation analysis revealed that E. coli had a highly significant (P < 0.0001) correlation coefficient (>0.8) with 16 ARGs and 7 VFGs. Metabolomics analysis showed that differentially expressed metabolites in Simmental calves with diarrhea displayed a high correlation with the aforementioned ARGs and VFGs. Phylotype analysis of E. coli genomes showed that the predominant phylogroup B1 in diarrheic Simmental calves was associated with 10 ARGs and 3 VFGs. These findings provide an overview of the diversity and abundance of the gut microbiota in diarrheic calves caused by E. coli and pave the way for further studies on the mechanisms of antibiotic resistance and virulence in the calves affected with diarrhea.IMPORTANCESimmental is a well-recognized beef cattle breed worldwide. They also suffer significant economic losses due to diarrhea. In this study, fecal metagenomic analysis was applied to characterize the antibiotic resistance gene (ARG) and virulence factor gene (VFG) profiles of diarrheic Simmental calves. We identified key ARGs and VFGs correlated with Escherichia coli isolated from Simmental calves. Additionally, metabolomics analysis showed that differentially expressed metabolites in Simmental calves with diarrhea displayed a high correlation with the aforementioned ARGs and VFGs. Our findings provide an insight into the diversity and abundance of the gut microbiota in diarrheic calves caused by Escherichia coli and pave the way for further studies on the mechanisms of antibiotic resistance and virulence in the diarrheal calves from cattle hosts.

Genome-wide copy number variant analysis reveals candidate genes associated with milk production traits in water buffalo (Bubalus bubalis).

Buffaloes are vital contributors to the global dairy industry. Understanding the genetic basis of milk production traits in buffalo populations is essential for breeding programs and improving productivity. In this study, we conducted whole-genome resequencing on 387 buffalo genomes from 29 diverse Asian breeds, including 132 river buffaloes, 129 swamp buffaloes, and 126 crossbred buffaloes. We identified 36,548 copy number variants (CNV) spanning 133.29 Mb of the buffalo genome, resulting in 2,100 CNV regions (CNVR), with 1,993 shared CNVR being found within the studied buffalo types. Analyzing CNVR highlighted distinct genetic differentiation between river and swamp buffalo subspecies, verified by evolutionary tree and principal component analyses. Admixture analysis grouped buffaloes into river and swamp categories, with crossbred buffaloes displaying mixed ancestry. To identify candidate genes associated with milk production traits, we employed 3 approaches. First, we used Vst-based population differentiation, revealing 11 genes within CNVR that exhibited significant divergence between different buffalo breeds, including genes linked to milk production traits. Second, expression quantitative loci analysis revealed differentially expressed CNVR-derived genes (DECG) associated with milk production traits. Notably, known milk production-related genes were among these DECG, validating their relevance. Last, a GWAS identified 3 CNVR significantly linked to peak milk yield. Our study provides comprehensive genomic insights into buffalo populations and identifies candidate genes associated with milk production traits. These findings facilitate genetic breeding programs aimed at increasing milk yield and improving quality in this economically important livestock species.

The construction of a novel prognostic prediction model for glioma based on GWAS-identified prognostic-related risk loci.

Backgrounds: Glioma is a highly malignant brain tumor with a grim prognosis. Genetic factors play a role in glioma development. While some susceptibility loci associated with glioma have been identified, the risk loci associated with prognosis have received less attention. This study aims to identify risk loci associated with glioma prognosis and establish a prognostic prediction model for glioma patients in the Chinese Han population. Methods: A genome-wide association study (GWAS) was conducted to identify risk loci in 484 adult patients with glioma. Cox regression analysis was performed to assess the association between GWAS-risk loci and overall survival as well as progression-free survival in glioma. The prognostic model was constructed using LASSO Cox regression analysis and multivariate Cox regression analysis. The nomogram model was constructed based on the single nucleotide polymorphism (SNP) classifier and clinical indicators, enabling the prediction of survival rates at 1-year, 2-year, and 3-year intervals. Additionally, the receiver operator characteristic (ROC) curve was employed to evaluate the prediction value of the nomogram. Finally, functional enrichment and tumor-infiltrating immune analyses were conducted to examine the biological functions of the associated genes. Results: Our study found suggestive evidence that a total of 57 SNPs were correlated with glioma prognosis (p < 5 × 10-5). Subsequently, we identified 25 SNPs with the most significant impact on glioma prognosis and developed a prognostic model based on these SNPs. The 25 SNP-based classifier and clinical factors (including age, gender, surgery, and chemotherapy) were identified as independent prognostic risk factors. Subsequently, we constructed a prognostic nomogram based on independent prognostic factors to predict individualized survival. ROC analyses further showed that the prediction accuracy of the nomogram (AUC = 0.956) comprising the 25 SNP-based classifier and clinical factors was significantly superior to that of each individual variable. Conclusion: We identified a SNP classifier and clinical indicators that can predict the prognosis of glioma patients and established a prognostic prediction model in the Chinese Han population. This study offers valuable insights for clinical practice, enabling improved evaluation of patients' prognosis and informing treatment options.

Transcriptome-Wide Association Study Reveals Potentially Candidate Genes Responsible for Milk Production Traits in Buffalo.

Identifying key causal genes is critical for unraveling the genetic basis of complex economic traits, yet it remains a formidable challenge. The advent of large-scale sequencing data and computational algorithms, such as transcriptome-wide association studies (TWASs), offers a promising avenue for identifying potential causal genes. In this study, we harnessed the power of TWAS to identify genes potentially responsible for milk production traits, including daily milk yield (MY), fat percentage (FP), and protein percentage (PP), within a cohort of 100 buffaloes. Our approach began by generating the genotype and expression profiles for these 100 buffaloes through whole-genome resequencing and RNA sequencing, respectively. Through comprehensive genome-wide association studies (GWAS), we pinpointed a total of seven and four single nucleotide polymorphisms (SNPs) significantly associated with MY and FP traits, respectively. By using TWAS, we identified 55, 71, and 101 genes as significant signals for MY, FP, and PP traits, respectively. To delve deeper, we conducted protein-protein interaction (PPI) analysis, revealing the categorization of these genes into distinct PPI networks. Interestingly, several TWAS-identified genes within the PPI network played a vital role in milk performance. These findings open new avenues for identifying potentially causal genes underlying important traits, thereby offering invaluable insights for genomics and breeding in buffalo populations.

Very important pharmacogenetic variants landscape and potential clinical relevance in the Zhuang population from Yunnan province.

The gradual evolution of pharmacogenomics has shed light on the genetic basis for inter-individual drug response variations across diverse populations. This study aimed to identify pharmacogenomic variants that differ in Zhuang population compared with other populations and investigate their potential clinical relevance in gene-drug and genotypic-phenotypic associations. A total of 48 variants from 24 genes were genotyped in 200 Zhuang subjects using the Agena MassARRAY platform. The allele frequencies and genotype distribution data of 26 populations were obtained from the 1000 Genomes Project, followed by a comparison and statistical analysis. After Bonferroni correction, significant differences in genotype frequencies were observed of CYP3A5 (rs776746), ACE (rs4291), KCNH2 (rs1805123), and CYP2D6 (rs1065852) between the Zhuang population and the other 26 populations. It was also found that the Chinese Dai in Xishuangbanna, China, Han Chinese in Beijing, China, and Southern Han Chinese, China showed least deviation from the Zhuang population. The Esan in Nigeria, Gambian in Western Division, The Gambia, and Yoruba in Ibadan, Nigeria exhibited the largest differences. This was also proved by structural analysis, Fst analysis and phylogenetic tree. Furthermore, these differential variants may be associated with the pharmacological efficacy and toxicity of Captopril, Amlodipine, Lisinopril, metoclopramide, and alpha-hydroxymetoprolol in the Zhuang population. Our study has filled the gap of pharmacogenomic information in the Zhuang population and has provided a theoretical framework for the secure administration of drugs in the Zhuang population.

Vertical migration behavior simulation and prediction of Pb and Cd in co-contaminated soil around Pb-Zn smelting slag site.

Heavy metal migration in soil poses a serious threat to the soil and groundwater. Understanding the migration pattern of heavy metals (HMs) under different factors could provide a more reasonable position for pollution evaluation and targetoriented treatment of soil heavy metal. In this study, the migration behavior of Pb and Cd in co-contaminated soil under different pH and ionic strength (NaCl concentration) was simulated using convective dispersion equation (CDE). We predicted the migration trends of Pb and Cd in soils after 5, 10, and 20 years via PHREEQC. The results showed that the migration time of Cd in the soil column experiment was about 60 days faster than that of Pb, and the migration trend was much steeper. The CDE was proved to describe the migration behavior of Pb and Cd (R2 > 0.75) in soil. The predicted results showed that Cd migrated to 15-20 cm of soil within 7 years and Pb stayed mainly in the top 0-6 cm of soil within 5 years as the duration of irrigation increased. Overall, our study is expected to provide new insight into the migration of heavy metal in soil ecosystems and guidance for reducing risk of heavy metal in the environment.