Characterizing identity by descent segments in Chinese interpopulation unrelated individual pairs.

Identity by descent (IBD) segments, uninterrupted DNA segments derived from the same ancestral chromosomes, are widely used as indicators of relationships in genetics. A great deal of research focuses on IBD segments between related pairs, while the statistical analyses of segments in irrelevant individuals are rare. In this study, we investigated the basic informative features of IBD segments in unrelated pairs in Chinese populations from the 1000 Genome Project. A total of 5922 IBD segments in Chinese interpopulation unrelated individual pairs were detected via IBIS and the average length of IBD was 3.71 Mb in length. It was found that 17.86% of unrelated pairs shared at least one IBD segment in the Chinese cohort. Furthermore, a total of 49 chromosomal regions where IBD segments clustered in high abundance were identified, which might be sharing hotspots in the human genome. Such regions could also be observed in other ancestry populations, which implies that similar IBD backgrounds also exist. Altogether, these results demonstrated the distribution of common background IBD segments, which helps improve the accuracy in pedigree studies based on IBD analysis.

Development of a 39 MM-InDel multiplex assay for the forensic application.

Insertion/deletion polymorphisms (InDels) are a category of highly prevalent markers in the human genome, characterized by their distinctive attributes, including short amplicon sizes and low mutation rates, which have shown great potential in forensic applications. Multi-allelic InDel and multi-InDel markers, collectively abbreviated as MM-InDels, were developed to enhance polymorphism by the introduction of novel alleles. Nevertheless, the relatively low mutation rates of InDels, coupled with the founder effect, result in distinct allele frequency distributions among populations. The divergent characteristics of InDels in different populations also pose challenges to the establishment of universally efficient InDel multiplex assays. To enhance the system efficiency of the InDel assay and its applicability across diverse populations, 39 MM-InDels with high polymorphism in five different ancestry superpopulations were selected from the 1000 Genomes Project dataset and combined with an amelogenin gender marker to construct a multiplex assay (named MMIDplex). The combined power of discrimination and the cumulative probability of exclusion of 39 MM-InDels were 1 - 1.3 × 10-23 and 1 - 9.83 × 10-6 in the Chinese Han population, and larger than 1-10-19 and 1-10-4 in the reference populations, relatively. These results demonstrate that the MMIDplex assay has the potential to obtain sufficient power for individual identification and paternity test in global populations.

Development of a multiplex panel with 31 multi-allelic InDels for forensic DNA typing.

Insertion/Deletion (InDel) polymorphic genetic markers are abundant in human genomes. Diallelic InDel markers have been widely studied for forensic purposes, yet the low polymorphic information content limits their application and current InDel panels remain to be improved. In this study, multi-allelic InDels located out of low complexity sequence regions were selected in the datasets from East Asian populations, and a multiplex amplification system containing 31 multi-allelic InDel markers and the Amelogenin marker (FA-HID32plex) was constructed and optimized. The preliminary study on sensitivity, species specificity, inhibitor tolerance, mixture resolution, and the detection of degraded samples demonstrates that the FA-HID32plex is highly sensitive, specific, and robust for traces and degraded samples. The combined power of discrimination (CPD) of 31 multi-allelic InDel markers was 0.999 999 999 999 999 999 85, and the cumulative probability of exclusion (CPE) was 0.999 920 in a Chinese Han population, which indicates a high discrimination power. Altogether, the FA-HID32plex panel could provide reliable supplements or stand-alone information in individual identification and paternity testing, especially for challenging samples.

DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome.

MOTIVATION: Deciphering the language of non-coding DNA is one of the fundamental problems in genome research. Gene regulatory code is highly complex due to the existence of polysemy and distant semantic relationship, which previous informatics methods often fail to capture especially in data-scarce scenarios. RESULTS: To address this challenge, we developed a novel pre-trained bidirectional encoder representation, named DNABERT, to capture global and transferrable understanding of genomic DNA sequences based on up and downstream nucleotide contexts. We compared DNABERT to the most widely used programs for genome-wide regulatory elements prediction and demonstrate its ease of use, accuracy and efficiency. We show that the single pre-trained transformers model can simultaneously achieve state-of-the-art performance on prediction of promoters, splice sites and transcription factor binding sites, after easy fine-tuning using small task-specific labeled data. Further, DNABERT enables direct visualization of nucleotide-level importance and semantic relationship within input sequences for better interpretability and accurate identification of conserved sequence motifs and functional genetic variant candidates. Finally, we demonstrate that pre-trained DNABERT with human genome can even be readily applied to other organisms with exceptional performance. We anticipate that the pre-trained DNABERT model can be fined tuned to many other sequence analyses tasks. AVAILABILITY AND IMPLEMENTATION: The source code, pretrained and finetuned model for DNABERT are available at GitHub (https://github.com/jerryji1993/DNABERT). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Evaluation of one-step RT-PCR multiplex assay for body fluid identification.

The discrimination of body fluid stains provides crucial evidence during the investigation of criminal cases. Previous studies have demonstrated the practical value of mRNA profiling in body fluid identification. Conventional strategy of mRNA profiling entails reverse transcription and PCR amplification in two separate procedures with different buffer systems. In this study, we subjected the one-step multiplex reverse transcription PCR strategy to mRNA profiling with the inclusion of the same 18 tissue-specific biomarkers in the F18plex system targeting peripheral blood, menstrual blood, vaginal secretion, saliva, semen, and urine. The Qiagen OneStep RT-PCR kit and Titanium One-Step RT-PCR kit were applied to multiplex construction, while reproducible profiling results were obtained with both kits. Compared to the F18plex system, similar expression profiles of biomarkers were obtained in targeted tissues, while expected cross-reaction was observed in non-targeted body fluids. However, CYP2B7P1 and SPINK5 were detected in menstrual blood samples, which was not observed using the F18plex system. Full-profiling results were obtained in all samples using 0.1 ng peripheral blood and semen RNA, and 1 ng menstrual blood, vaginal secretion, saliva, and urine RNA. In conclusion, the application of one-step mRNA profiling strategy could be a reliable and economical method for the simplified, specific, and simultaneous analysis of tissue-specific biomarkers for the discrimination of body fluid origin.

ELLPMDA: Ensemble learning and link prediction for miRNA-disease association prediction.

Recently, accumulating evidences have indicated miRNAs play critical roles in the progression and development of various human complex diseases, which pointed out that identifying miRNA-disease association could enable us to understand diseases at miRNA level. Thus, revealing more and more potential miRNA-disease associations is a vital topic in biomedical domain. However, it will be extremely expensive and time-consuming if we examine all the possible miRNA-disease pairs. Therefore, more accurate and efficient methods are being highly requested to detect potential miRNA-disease associations. In this study, we developed a computational model of Ensemble Learning and Link Prediction for miRNA-Disease Association prediction (ELLPMDA) to achieve this goal. By integrating miRNA functional similarity, disease semantic similarity, miRNA-disease association and Gaussian profile kernel similarity for miRNAs and diseases, we constructed a similarity network and utilized ensemble learning to combine rank results given by three classic similarity-based algorithms. To evaluate the performance of ELLPMDA, we exploited global and local Leave-One-Out Cross Validation (LOOCV), 5-fold Cross Validation (CV) and three kinds of case studies. As a result, the AUCs of ELLPMDA is 0.9181, 0.8181 and 0.9193+/-0.0002 in global LOOCV, local LOOCV and 5-fold CV, respectively, which significantly exceed almost all the previous methods. Moreover, in three distinct kinds of case studies for Kidney Neoplasms, Lymphoma, Prostate Neoplasms, Colon Neoplasms and Esophageal Neoplasms, 88%, 92%, 86%, 98% and 98% out of the top 50 predicted miRNAs has been confirmed, respectively. Besides, ELLPMDA is based on global similarity measure and applicable to new diseases without any known related miRNAs.

Mutation analysis of 19 autosomal short tandem repeats in Chinese Han population from Shanghai.

The mutation of short tandem repeat (STR) loci is affected by several factors, such as sex, age, and DNA architectures. Previous studies have shown a different profile of mutation rates at autosomal STR loci among populations. It is important to provide population data and reveal underlying factors influencing the evaluation of STR mutation rates. In this study, we performed a comprehensive analysis on the mutation of 19 autosomal STR loci through 124,773 parent-child allelic transfers from 5846 paternity testing cases. A total of 197 mutations were observed including 187 single-step mutations. The observed mutation rates ranged from 0.15 × 10-3 (TH01) to 4.57 × 10-3 (FGA), and the average mutation rate across all the 19 loci was 1.58 × 10-3. Furthermore, the average mutation rate of STR loci increases with the paternal conception ages and remains relatively stable in different maternal age groups, which suggest the profile of paternal conception ages as a potential factor influencing the evaluation of STR mutation rates and the ratio of paternal versus maternal mutation rate in populations. Multidimensional scaling analysis (MDS) shows a difference in the profile of mutation rates at 13 CODIS STR loci among ethnical groups. Based on our data, our results support that short alleles are biased towards expansion mutation and longer alleles favor contraction mutation. In conclusion, our results provide useful information for further investigation on STR mutation in forensic genetics and population genetics.

Dithiol-PEG-PDLLA micelles: preparation and evaluation as potential topical ocular delivery vehicle.

Thiol-modified nanoparticles have potential applications in mucoadhesive drug delivery and have been examined in this regard for topical ocular delivery. In this paper we provide a simple method for the synthesis of a dithiol terminated amphiphilic diblock copolymer. Bidentate dithiol-poly(ethylene glycol)-poly(d,l-lactide) (SH2-PEG-PDLLA) was synthesized and micelles with dithiol-containing coronas were prepared from this block copolymer via the emulsion method. In vitro release studies indicated that the presence of the thiol groups at the surface did not affect the rate of release of dexamethasone, used as a representative ocular drug. The micelles also showed low cytotoxicity to human corneal epithelial cells (HCEC) and murine fibroblast cells (3T3 cells). A hydrophobic red fluorophore, Nile red, was loaded into the core of micelles and confocal microscopy was used to study HCEC uptake and retention of the micelles. The micelles were rapidly endocytosed by the HCEC, with intracellular micelle levels remaining unchanged with incubation times from 5 to 120 min. Interestingly, Nile red was eliminated significantly more slowly from HCECs treated with the thiolated micelles. These results suggest that these dithiolated micelles may be effective for topical ocular drug delivery.

DNABERT-S: LEARNING SPECIES-AWARE DNA EMBEDDING WITH GENOME FOUNDATION MODELS.

Effective DNA embedding remains crucial in genomic analysis, particularly in scenarios lacking labeled data for model fine-tuning, despite the significant advancements in genome foundation models. A prime example is metagenomics binning, a critical process in microbiome research that aims to group DNA sequences by their species from a complex mixture of DNA sequences derived from potentially thousands of distinct, often uncharacterized species. To fill the lack of effective DNA embedding models, we introduce DNABERT-S, a genome foundation model that specializes in creating species-aware DNA embeddings. To encourage effective embeddings to error-prone long-read DNA sequences, we introduce Manifold Instance Mixup (MI-Mix), a contrastive objective that mixes the hidden representations of DNA sequences at randomly selected layers and trains the model to recognize and differentiate these mixed proportions at the output layer. We further enhance it with the proposed Curriculum Contrastive Learning (C2LR) strategy. Empirical results on 18 diverse datasets showed DNABERT-S's remarkable performance. It outperforms the top baseline's performance in 10-shot species classification with just a 2-shot training while doubling the Adjusted Rand Index (ARI) in species clustering and substantially increasing the number of correctly identified species in metagenomics binning. The code, data, and pre-trained model are publicly available at https://github.com/Zhihan1996/DNABERT_S.

The long-run effects of fetal PM2.5 exposure on mental health: evidence from China.

This paper investigates the long-run effects of PM2.5 exposure in utero on the mental health of adolescents. Using nationally representative survey data from China, we instrument the PM2.5 exposure with wind speed to tackle the possible endogeneity problem. Our results show that mothers' PM2.5 exposure during their pregnancy negatively affects the mental health of their children aged between 10 and 15 years. A 1 µg/m3 increase in PM2.5 exposure in utero increases the probability of having a severe mental illness for adolescents by 0.6%. Our evidence supports the "fetal origins" hypothesis. We also find that fetal PM2.5 exposure leads adolescents to be more likely to be absent from school and quarrel with their parents, implying that fetal PM2.5 exposure may affect individuals' behavior when they grow up.

Latent Class-Conditional Noise Model.

Learning with noisy labels has become imperative in the Big Data era, which saves expensive human labors on accurate annotations. Previous noise-transition-based methods have achieved theoretically-grounded performance under the Class-Conditional Noise model (CCN). However, these approaches builds upon an ideal but impractical anchor set available to pre-estimate the noise transition. Even though subsequent works adapt the estimation as a neural layer, the ill-posed stochastic learning of its parameters in back-propagation easily falls into undesired local minimums. We solve this problem by introducing a Latent Class-Conditional Noise model (LCCN) to parameterize the noise transition under a Bayesian framework. By projecting the noise transition into the Dirichlet space, the learning is constrained on a simplex characterized by the complete dataset, instead of some ad-hoc parametric space wrapped by the neural layer. We then deduce a dynamic label regression method for LCCN, whose Gibbs sampler allows us efficiently infer the latent true labels to train the classifier and to model the noise. Our approach safeguards the stable update of the noise transition, which avoids previous arbitrarily tuning from a mini-batch of samples. We further generalize LCCN to different counterparts compatible with open-set noisy labels, semi-supervised learning as well as cross-model training. A range of experiments demonstrate the advantages of LCCN and its variants over the current state-of-the-art methods. The code is available at here.

Validation of phylogenetic informative Y-InDels in Y-chromosomal haplogroup O-M175.

The Y-chromosomal haplogroup tree, which consists of a group of Y-chromosomal loci with phylogenetic information, has been widely applied in anthropology, archaeology and population genetics. With the continuous updating of the phylogenetic structure, Y-chromosomal haplogroup tree provides more information for recalling the biogeographical origin of Y chromosomes. Generally, Y-chromosomal insertion-deletion polymorphisms (Y-InDels) are genetically stable as Y-chromosomal single nucleotide polymorphisms (Y-SNPs), and therefore carry mutations that can accumulate over generations. In this study, potential phylogenetic informative Y-InDels were filtered out in haplogroup O-M175, which is dominant in East Asia, based on population data retrieved from the 1000 Genomes Project. A group of 22 phylogenetic informative Y-InDels were identified and then assigned to their corresponding subclades of haplogroup O-M175, which provided a supplement for the update and application of Y-chromosomal markers. Especially, four Y-InDels were introduced to define subclades determined using a single Y-SNP.

Mitochondrial Hydrogen Peroxide Activates PTEN and Inactivates Akt Leading to Autophagy Inhibition-Dependent Cell Death in Neuronal Models of Parkinson's Disease.

Defective autophagy relates to the pathogenesis of Parkinson's disease (PD), a typical neurodegenerative disease. Our recent study has demonstrated that PD toxins (6-OHDA, MPP+, or rotenone) induce neuronal apoptosis by impeding the AMPK/Akt-mTOR signaling. Here, we show that treatment with 6-OHDA, MPP+, or rotenone triggered decreases of ATG5/LC3-II and autophagosome formation with a concomitant increase of p62 in PC12, SH-SY5Y cells, and primary neurons, suggesting inhibition of autophagy. Interestingly, overexpression of wild-type ATG5 attenuated the inhibitory effect of PD toxins on autophagy, reducing neuronal apoptosis. The effects of PD toxins on autophagy and apoptosis were found to be associated with activation of PTEN and inactivation of Akt. Overexpression of dominant negative PTEN, constitutively active Akt and/or pretreatment with rapamycin rescued the cells from PD toxins-induced downregulation of ATG5/LC3-II and upregulation of p62, as well as consequential autophagosome diminishment and apoptosis in the cells. The effects of PD toxins on autophagy and apoptosis linked to excessive intracellular and mitochondrial hydrogen peroxide (H2O2) production, as evidenced by using a H2O2-scavenging enzyme catalase, a mitochondrial superoxide indicator MitoSOX and a mitochondria-selective superoxide scavenger Mito-TEMPO. Furthermore, we observed that treatment with PD toxins reduced the protein level of Parkin in the cells. Knockdown of Parkin alleviated the effects of PD toxins on H2O2 production, PTEN/Akt activity, autophagy, and apoptosis in the cells, whereas overexpression of wild-type Parkin exacerbated these effects of PD toxins, implying the involvement of Parkin in the PD toxins-induced oxidative stress. Taken together, the results indicate that PD toxins can elicit mitochondrial H2O2, which can activate PTEN and inactivate Akt leading to autophagy inhibition-dependent neuronal apoptosis, and Parkin plays a critical role in this process. Our findings suggest that co-manipulation of the PTEN/Akt/autophagy signaling by antioxidants may be exploited for the prevention of neuronal loss in PD.

KGML-xDTD: a knowledge graph-based machine learning framework for drug treatment prediction and mechanism description.

BACKGROUND: Computational drug repurposing is a cost- and time-efficient approach that aims to identify new therapeutic targets or diseases (indications) of existing drugs/compounds. It is especially critical for emerging and/or orphan diseases due to its cheaper investment and shorter research cycle compared with traditional wet-lab drug discovery approaches. However, the underlying mechanisms of action (MOAs) between repurposed drugs and their target diseases remain largely unknown, which is still a main obstacle for computational drug repurposing methods to be widely adopted in clinical settings. RESULTS: In this work, we propose KGML-xDTD: a Knowledge Graph-based Machine Learning framework for explainably predicting Drugs Treating Diseases. It is a 2-module framework that not only predicts the treatment probabilities between drugs/compounds and diseases but also biologically explains them via knowledge graph (KG) path-based, testable MOAs. We leverage knowledge-and-publication-based information to extract biologically meaningful "demonstration paths" as the intermediate guidance in the Graph-based Reinforcement Learning (GRL) path-finding process. Comprehensive experiments and case study analyses show that the proposed framework can achieve state-of-the-art performance in both predictions of drug repurposing and recapitulation of human-curated drug MOA paths. CONCLUSIONS: KGML-xDTD is the first model framework that can offer KG path explanations for drug repurposing predictions by leveraging the combination of prediction outcomes and existing biological knowledge and publications. We believe it can effectively reduce "black-box" concerns and increase prediction confidence for drug repurposing based on predicted path-based explanations and further accelerate the process of drug discovery for emerging diseases.

Investigation of Linear Amplification Using Abasic Site-Containing Primers Coupled to Routine STR Typing for LT-DNA Analysis.

Obtaining a full short tandem repeat (STR) profile from a low template DNA (LT-DNA) still presents a challenge for conventional methods due to significant stochastic effects and polymerase slippage. A novel amplification method with a lower cost and higher accuracy is required to improve the DNA amount. Previous studies suggested that DNA polymerases without bypass activity could not perform processive DNA synthesis beyond abasic sites in vitro and our results showed a lack of bypass activity for Phusion, Pfu and KAPA DNA polymerases in this study. Based on this feature, we developed a novel linear amplification method, termed Linear Aamplification for double-stranded DNA using primers with abasic sites near 3' end (abLAFD), to limit the replication error. The amplification efficiency was evaluated by qPCR analysis with a result of approximately a 130-fold increase in target DNA. In a LT-DNA analysis, the abLAFD method can be employed as a pre-PCR. Similar to nested PCRs, primer sets used for the abLAFD method were designed as external primers suitable for commercial multiplex STR amplification assays. The practical performance of the abLAFD method was evaluated by coupling it to a routine PP21 STR analysis using 50 pg and 25 pg DNA. Compared to reference profiles, all abLAFD profiles showed significantly recovered alleles, increased average peak height and heterozygote balance with a comparable stutter ratio. Altogether, our results support the theory that the abLAFD method is a promising strategy coupled to STR typing for forensic LT-DNA analysis.

Identification and assessment of a subset of Y-SNPs with recurrent mutation for forensic purpose.

Y chromosome has an important role in the forensic practice due to its unique paternal inheritance pattern. Y-chromosomal single nucleotide polymorphisms (Y-SNPs) could provide supplementary information while the application of Y-chromosomal STR (Y-STR) haplotypes encounter their limitations. Y-SNPs with recurrent mutation can be seen in different Y-chromosomal haplogroups, which might help discriminate different paternal pedigrees. In this study, a host of candidate Y-SNPs with recurrent mutation were obtained based on population data from 1000 Genome Project. Further, 8 Y-SNPs from a small part of candidates were confirmed to be polymorphic in 2 or more Y-chromosomal haplogroups (sub-haplogroups) in the Chinese Han population. With a haplotype diversity value of 0.9367, the investigated subset of Y-SNPs with recurrent mutation shows a high discrimination power. Therefore, Y-SNPs with recurrent mutation should function as useful markers to provide information in the forensic applications.

Resveratrol induces autophagy impeding BAFF-stimulated B-cell proliferation and survival by inhibiting the Akt/mTOR pathway.

Therapeutically targeting B cells has received great attention in the treatment of B-cell malignancies and autoimmune diseases. The B-cell activating factor (BAFF) is critical to the survival of normal and neoplastic B cells, and excess production of BAFF contributes to autoimmune diseases. Resveratrol, a natural polyphenolic compound, has a positive effect on the treatment of autoimmune diseases. However, how resveratrol affects BAFF-stimulated B-cell proliferation and survival is poorly understood. Here, we show that resveratrol increased autophagosome formation and ATG5/LC3-II levels and decreased p62 level, promoting autophagic flux/autophagy and thereby suppressing the basal or human soluble BAFF (hsBAFF)-stimulated proliferation and survival of normal and B-lymphoid (Raji) cells. This is supported by the findings that inhibition of autophagy with 3-methyladenine (3-MA, an inhibitor of Vps34) or ATG5 shRNA attenuates resveratrol-induced autophagy and -reduced proliferation/viability in B-cells. Inhibition of mTOR with rapamycin or knockdown of mTOR potentiated resveratrol-induced autophagy and inhibition of hsBAFF-stimulated B-cell proliferation/viability, while overexpression of wild-type mTOR conferred resistance to the actions of resveratrol. Similarly, inhibition of Akt with Akt inhibitor X or ectopic expression of dominant negative Akt reinforced resveratrol-induced autophagy and inhibition of hsBAFF-stimulated B-cell proliferation/viability, whereas expression of constitutively active Akt conferred resistance to the actions of resveratrol. Taken together, these results indicate that resveratrol induces autophagy impeding BAFF-stimulated proliferation and survival via blocking the Akt/mTOR signaling pathway in normal and neoplastic B cells. Our findings highlight that resveratrol has a great potential for prevention and treatment of excessive BAFF-elicited aggressive B-cell disorders and autoimmune diseases.

Water-dispersible superparamagnetic microspheres adorned with two types of surface chains.

Water-dispersible superparamagnetic polymer/γ-Fe(2)O(3) composite microspheres adorned with two types of surface polymer chains are prepared and characterized. To prepare these spheres, we first synthesize uniform γ-Fe(2)O(3) nanoparticles that are covered by poly(2-cinnamoyloxyethyl methacrylate)-block-poly(acrylic acid) (PCEMA-b-PAA). These nanoparticles are then mixed with a PCEMA homopolymer in CHCl(3) to form an oil phase. The oil phase is dispersed into water under vigorous stirring with the help of two diblock copolymer surfactants, PGMA-b-PCEMA and PSGMA-b-PCEMA. Here PGMA and PSGMA denote poly(glyceryl monomethacrylate) and succinated PGMA, respectively. Solid microspheres with cores composed of PCEMA and PCEMA-b-PAA-covered γ-Fe(2)O(3) nanoparticles are obtained after CHCl(3) evaporation and PCEMA photo-cross-linking. Under certain conditions, the coronal PGMA and PSGMA chains become segregated, thus producing surface bumps, ridges, and valleys. The PSGMA chains preferentially cover the protruding regions. The PSGMA carboxyl groups are used to immobilize bovine serum albumin (BSA). The immobilized BSA retains its activity and binds with anti-BSA. These spheres should be useful in immunoassays.

Multimorbidity in Hospitalized Patients Admitted to General Practice Departments and Its Implications for the General Practice Healthcare System: A Four-Year Longitudinal Study in China.

Objective: China and many developing countries has placed high expectations on the general practice healthcare system in terms of lowering medical costs and improving the health status of the multimorbid population in recent years. However, the prevalence of multimorbidity among inpatients attending the general practice department of hospitals and its policy implications are largely unknown. The current study aimed to analyze the prevalence of comorbidities among inpatients attending the general practice department of the tertiary Grade-A Hospitals in China, and put forward evidence-based policy recommendations. Methods: Between December 2016 and November 2020, 351 registered general practitioners from 27 tertiary hospitals were selected, and their direct admissions were evaluated. The rate and composition ratio were used for descriptive analysis of the clinical and epidemiological characteristics of multimorbidity. A backward stepwise algorithm was used to explore independent variables. The absence of multicollinearity and plausible interactions among variables were tested to ensure the robustness of the logistic regression model. The pyramid diagram was used to show the link between gender and the involved human body system in multimorbidity. Results: Multimorbidity was present in 93.1% of the 64, 395 patients who were admitted directly. Multimorbidity was significantly more prevalent in patients aged 45-59 years (OR=3.018, 95% CI=1.945-4.683), 60-74 years (OR = 4.349, 95% CI = 2.574-7.349), ≥75 years (OR = 7.804, 95% CI = 3.665-16.616), and those with body mass index (BMI) ≥ 28 kg/m2 (OR = 3.770, 95% CI = 1.453-9.785). The circulatory system was found to be the most commonly involved human body system in multimorbidity, accounting for 79.2% (95% CI = 78.8-79.5%) of all cases. Significant gender inequity was further observed in the involved human body system in multimorbidity. Conclusion: Multimorbidity is likely common among the inpatients attending the general practice department of hospitals in China and many developing countries, with significant gender inequity in the involved human body systems. Effective countermeasures include establishing a GP-PCIC multimorbidity prevention and control model and enhancing the multimorbidity of elderly and obese patients at both the clinical and healthy lifestyle levels. The diagnosis and treatment capabilities of GPs on the circulatory, endocrine, metabolic, digestive, and respiratory systems should be prioritized.

Identification and Characterization of Nine Novel X-Chromosomal Short Tandem Repeats on Xp21.1, Xq21.31, and Xq23 Regions.

The application of X-chromosomal short tandem repeats (X-STRs) has been recognized as a powerful tool in complex kinship testing. To support further development of X-STR analysis in forensic use, we identified nine novel X-STRs, which could be clustered into three linkage groups on Xp21.1, Xq21.31, and Xq23. A multiplex PCR system was built based on the electrophoresis. A total of 198 unrelated Shanghai Han samples along with 168 samples from 43 families was collected to investigate the genetic polymorphism and forensic parameters of the nine loci. Allele numbers ranged from 5 to 12, and amplicon sizes ranged from 146 to 477 bp. The multiplex showed high values for the combined power of discrimination (0.99997977 in males and 0.99999999 in females) and combined mean exclusion chances (0.99997918 and 0.99997821 in trios, 0.99984939 in duos, and 0.99984200 in deficiency cases). The linkage between all pairs of loci was estimated via Kosambi mapping function and linkage disequilibrium test, and further investigated through the family study. The data from 43 families strongly demonstrated an independent transmission between LGs and a tight linkage among loci within the same LG. All these results support that the newly described X-STRs and the multiplex system are highly promising for further forensic use.