Powerful and robust inference of complex phenotypes' causal genes with dependent expression quantitative loci by a median-based Mendelian randomization.

Isolating the causal genes from numerous genetic association signals in genome-wide association studies (GWASs) of complex phenotypes remains an open and challenging question. In the present study, we proposed a statistical approach, the effective-median-based Mendelian randomization (MR) framework, for inferring the causal genes of complex phenotypes with the GWAS summary statistics (named EMIC). The effective-median method solved the high false-positive issue in the existing MR methods due to either correlation among instrumental variables or noises in approximated linkage disequilibrium (LD). EMIC can further perform a pleiotropy fine-mapping analysis to remove possible false-positive estimates. With the usage of multiple cis-expression quantitative trait loci (eQTLs), EMIC was also more powerful than the alternative methods for the causal gene inference in the simulated datasets. Furthermore, EMIC rediscovered many known causal genes of complex phenotypes (schizophrenia, bipolar disorder, and total cholesterol) and reported many new and promising candidate causal genes. In sum, this study provided an efficient solution to discriminate the candidate causal genes from vast amounts of GWAS signals with eQTLs. EMIC has been implemented in our integrative software platform KGGSEE.

A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids.

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

Blockade of CCR5 and CXCR3 attenuates murine acute graft-versus-host disease through modulating donor-derived T-cell distribution and function.

Lymphocyte trafficking via chemokine receptors such as C-C chemokine receptor 5 (CCR5) and CXCR3 plays a critical role in the pathogenesis of acute graft-versus-host disease (aGVHD). Our previous studies showed that the addition of CCR5 or CXCR3 antagonists could only slightly alleviate the development of aGVHD. Given the specificity of T lymphocytes bearing CXCR3 and CCR5, we investigated whether combined CCR5 and CXCR3 blockade could further attenuate murine aGVHD. A mouse model of aGVHD was established to assess the efficacy of CCR5 and/or CXCR3 blockade on the development of aGVHD. The distribution of lymphocytes was calculated by quantification of immunostaining cells. The immunomodulatory effect on T cells was assessed by evaluating T-cell proliferation, viability, and differentiation. Using the murine allogeneic hematopoietic stem cell transplantation model, we demonstrated that blockade of both CCR5 and CXCR3 could efficiently alleviate the development of aGVHD. Further investigation on the immune mechanisms for this prophylactic effect showed that more T cells were detained into secondary lymphoid organs (SLOs), which may lead to reduced infiltration of T cells into GVHD target organs. Our study also showed that T cells detained in SLOs dampened the activation, suppressed the polarization toward T helper type 1 (Th1) and T cytotoxic type 1 (Tc1) cells, and induced the production of Treg cells. These data suggest that concurrent blockade of CCR5 and CXCR3 attenuates murine aGVHD through modulating donor-derived T-cell distribution and function, and this might be applicable for aGVHD prophylaxis in clinical settings.

Application of GWAS summary data and drug-induced gene expression profiles of neural progenitor cells in psychiatric drug prioritization analysis.

Common psychiatric disorders constitute one of the most substantial healthcare burdens worldwide. However, drug development in psychiatry remains hampered partially due to the lack of approaches to estimating drugs that can simultaneously modulate the expression of a nontrivial fraction of disease susceptibility genes. We proposed a new drug prioritization strategy under the framework of our previously proposed phenotype-associated tissues estimation approach (DESE) by investigating the drugs' selective perturbation effect on disease susceptibility genes. Based on the genome-wide association study summary data and drug-induced gene expression profiles of neural progenitor cells, we applied this strategy to prioritize candidate drugs for schizophrenia, depression and bipolar I disorder and identified several known therapeutic drugs among the top-ranked drug candidates. Also, our results revealed that the disease susceptibility genes involved in the selective gene perturbation analysis were enriched with many biologically sensible function terms and interacted with known therapeutic drugs. Our results suggested that selective gene perturbation analysis could be a promising starting point to prioritize biologically sensible drug candidates under the "one drug, multiple targets" paradigm for the drug development of common psychiatric disorders.

ACE2 deficiency inhibits thoracic aortic dissection by enhancing SIRT3 mediated inhibition of inflammation and VSCMs phenotypic switch.

BACKGROUND: Thoracic aortic dissection (TAD) is an irreversible cardiovascular disorder with high mortality and morbidity. However, the molecular mechanisms remain elusive. Thus, identifying an effective therapeutic target to prevent TAD is especially critical. The purpose of this study is to elucidate the potential mechanism of inflammation and vascular smooth muscle cell (VSMCs) phenotypic switch in ß-aminopropionitrile fumarate (BAPN)-induced TAD. METHODS: A mouse model of TAD induced by BAPN and IL-1ß -stimulated HVSMCs in vivo and in vitro models, respectively. ACE2 Knockdown mice treated with BAPN or without, and the TAD mouse model was treated with or without AAV-ACE2. Transthoracic ultrasound was conducted for assessment the maximum internal diameter of the thoracic aorta arch. RNA sequencing analysis was performed to recapitulate transcriptome profile changes. Western blot were used to detect the expression of MMP2, MMP9, ACE2, SIRT3, OPN, SM22α and other inflammatory markers. The circulating levels of ACE2 was measured by ELISA assay. Histological changes of thoracic aorta tissues were assessed by H&E, EVG and IHC analysis. RESULTS: We found that circulating levels of and the protein levels of ACE2 were increased in the TAD mouse model and in patients with TAD. For further evidence, ACE2 deficiency decelerated the formation of TAD. However, overexpression of ACE2 aggravated BAPN-induced aortic injury and VSMCs phenotypic switch via lowered SIRT3 expression and elevated inflammatory cytokine expression. CONCLUSION: ACE2 deficiency prevented the development of TAD by inhibiting inflammation and VSMCs phenotypic switch in a SIRT3-dependent manner, suggesting that the ACE2/SIRT3 signaling pathway played a pivotal role in the pathological process of TAD and might be a potential therapeutical target.

A Trapping-Micro-LC-FAIMS/dCV-MS Strategy for Ultrasensitive and Robust Targeted Quantification of Protein Drugs and Biomarkers.

The sensitivity of LC-MS in quantifying target proteins in plasma/tissues is significantly hindered by coeluted matrix interferences. While antibody-based immuno-enrichment effectively reduces interferences, developing and optimizing antibodies are often time-consuming and costly. Here, by leveraging the orthogonal separation capability of Field Asymmetric Ion Mobility Spectrometry (FAIMS), we developed a FAIMS/differential-compensation-voltage (FAIMS/dCV) method for antibody-free, robust, and ultrasensitive quantification of target proteins directly from plasma/tissue digests. By comparing the intensity-CV profiles of the target vs coeluted endogenous interferences, the FAIMS/dCV approach identifies the optimal CV for quantification of each target protein, thus maximizing the signal-to-noise ratio (S/N). Compared to quantification without FAIMS, this technique dramatically reduces endogenous interferences, showing a median improvement of the S/N by 14.8-fold for the quantification of 17 representative protein drugs and biomarkers in plasma or tissues and a 5.2-fold median increase in S/N over conventional FAIMS approach, which uses the peak CV of each target. We also discovered that the established CV parameters remain consistent over months and are matrix-independent, affirming the robustness of the developed FAIMS/dCV method and the transferability of the method across matrices. The developed method was successfully demonstrated in three applications: the quantification of monoclonal antibodies with subng/mL LOQ in plasma, an investigation of the time courses of evolocumab and its target PCSK9 in a preclinical setting, and a clinical investigation of low abundance obesity-related biomarkers. This innovative and easy-to-use method has extensive potential in clinical and pharmaceutical research, particularly where sensitive and high-throughput quantification of protein drugs and biomarkers is required.

Association between CBL gene polymorphism and susceptibility of microscopic polyangiitis in a Chinese population: A case-control analysis.

OBJECTIVE: To assess whether Casitas B-lineage lymphoma (CBL) gene polymorphism influences the risk of microscopic polyangiitis (MPA) in Chinese populations. METHODS: In total, 266 MPA patients and 297 healthy controls were recruited for a case-control study. Five CBL SNPs were genotyped using multiplex polymerase chain reaction and high-throughput sequencing. The relationship between SNPs and the risk of MPA under different genetic models was evaluated by SNPstats. SNP-SNP interaction was analyzed by generalized multifactor dimensionality reduction (GMDR). Finally, the association between CBL SNPs and treatment effects were assessed. RESULTS: The results showed that CBL rs2276083 was associated with decreasing MPA risk under dominant (OR: 0.53; p = 0.014) and recessive models (OR: 0.52; p = 0.0034). Stratification analysis indicated that rs2276083 and rs2509671 in age < 60 years, rs2276083 in female or in Han population were protective factors for MPA. The CBL haplotype (A-A-G-C-T) was associated with an increased risk of MPA. GMDR suggested that CBL rs2276083, phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit alpha (PI3KCA) rs1607237, and autophagy-related gene 7 (ATG7) rs7549008 might interact with each other in MPA development (p = 0.0107). CBL rs1047417 with AG genotype and rs11217234 with AG genotype had better clinical treatment effects than other two genotypes (p = 0.048 and p = 0.025, respectively). CONCLUSION: The genetic polymorphism of CBL had a potential association with the risk of MPA and clinical treatment effects in Guangxi population in China.

A systematic analysis of ARM genes revealed that GhARM144 regulates the resistance against Verticillium dahliae via interaction with GhOSM34.

Proteins of the armadillo repeat gene family play important roles in plant pathogen response. Here, 169 armadillo (ARM) genes were identified in upland cotton (Gossypium hirsutum). Phylogenetic analysis grouped these into 11 subfamilies, with conserved protein structures within each subfamily. The results signify that the expansion of the gene family occurred via whole genome duplication and dispersed duplication. Expression profiling and network analysis suggest that GhARM144 may regulate cotton resistance to Verticillium dahliae. GhARM144 was upregulated in roots by V. dahliae infection or salicylic acid treatment. This upregulation indicates a negative regulatory role of GhARM144' in the cotton immune responses, potentially by manipulating salicylic acid biosynthesis. Protein interaction studies found that GhARM144 associates with an osmotin-like protein, GhOSM34, at the plasma membrane. Silencing GhOSM34 reduced the resistance to V. dahliae, suggesting it may play a positive regulatory role. The results demonstrate that GhARM144 modulates cotton immunity through interaction with GhOSM34 and salicylic acid signalling. Further study of these proteins may yield insights into disease resistance mechanisms in cotton and other plants.

Activation of CTU2 expression by LXR promotes the development of hepatocellular carcinoma.

Cytosolic thiouridylase 2 (CTU2) is an enzyme modifying transfer RNAs post-transcriptionally, which has been implicated in breast cancer and melanoma development. And we found CTU2 participated in hepatocellular carcinoma (HCC) progression here. HepG2 cells as well as xenograft nude mice model were employed to investigate the role of CTU2 in HCC development in vitro and in vivo respectively. Further, we defined CTU2 as a Liver X receptor (LXR) targeted gene, with a typical LXR element in the CTU2 promoter. CTU2 expression was activated by LXR agonist and depressed by LXR knockout. Interestingly, we also found CTU2 took part in lipogenesis by directly enhancing the synthesis of lipogenic proteins, which provided a novel mechanism for LXR regulating lipid synthesis. Meanwhile, lipogenesis was active during cell proliferation, particularly in tumor cells. Reduction of CTU2 expression was related to reduced tumor burden and synergized anti-tumor effect of LXR ligands by inducing tumor cell apoptosis and inhibiting cell proliferation. Taken together, our study identified CTU2 as an LXR target gene. Inhibition of CTU2 expression could enhance the anti-tumor effect of LXR ligand in HCC, identifying CTU2 as a promising target for HCC treatment and providing a novel strategy for the application of LXR agonists in anti-tumor effect.

ZIF-8 Used for the Selective Recovery of Heavy Rare Earth Elements from Mining Wastewater.

In this study, a sample of 2-methylimidazole zinc salt (ZIF-8) demonstrated high selectivity for the recovery of heavy rare earth elements (REEs) from real rare earth mining wastewater. Results show that the distribution coefficient values of Y3+ (4.02 × 104 mL·g-1), Gd3+ (7.8 × 104 mL·g-1), and Dy3+ (6.8 × 104 mL·g-1) are orders of magnitude higher than those of K+ (359.51 mL·g-1), Mn2+ (266.67 mL·g-1), Ca2+ (396.42 mL·g-1), and Mg2+ (239.48 mL·g-1). Moreover, the desorption efficiency of heavy REEs exceeded 40%. Advanced characterizations and density functional theory (DFT) calculations were utilized to elucidate that the heavy REEs were more likely to bind to the nitrogen atoms of imidazole groups on ZIF-8 compared to non-REEs. Furthermore, the adsorption and desorption of heavy REEs primarily depend on the chemical interaction confirmed by adsorption kinetics, isotherm model, and thermodynamic analysis, which involves the dissociation of water and the formation of REE-O bonds. Finally, the ZIF-8 exhibits a remarkable recovery efficiency of over 40% for heavy REEs in column tests conducted over 7h. The findings reported here provide new insights into the selective recovery of heavy REEs from real mining wastewater.

High-Efficiency Effect-Directed Analysis Leveraging Five High Level Advancements: A Critical Review.

Organic contaminants are ubiquitous in the environment, with mounting evidence unequivocally connecting them to aquatic toxicity, illness, and increased mortality, underscoring their substantial impacts on ecological security and environmental health. The intricate composition of sample mixtures and uncertain physicochemical features of potential toxic substances pose challenges to identify key toxicants in environmental samples. Effect-directed analysis (EDA), establishing a connection between key toxicants found in environmental samples and associated hazards, enables the identification of toxicants that can streamline research efforts and inform management action. Nevertheless, the advancement of EDA is constrained by the following factors: inadequate extraction and fractionation of environmental samples, limited bioassay endpoints and unknown linkage to higher order impacts, limited coverage of chemical analysis (i.e., high-resolution mass spectrometry, HRMS), and lacking effective linkage between bioassays and chemical analysis. This review proposes five key advancements to enhance the efficiency of EDA in addressing these challenges: (1) multiple adsorbents for comprehensive coverage of chemical extraction, (2) high-resolution microfractionation and multidimensional fractionation for refined fractionation, (3) robust in vivo/vitro bioassays and omics, (4) high-performance configurations for HRMS analysis, and (5) chemical-, data-, and knowledge-driven approaches for streamlined toxicant identification and validation. We envision that future EDA will integrate big data and artificial intelligence based on the development of quantitative omics, cutting-edge multidimensional microfractionation, and ultraperformance MS to identify environmental hazard factors, serving for broader environmental governance.

Regulation of blue infertile flower pigmentation by WD40 transcription factor HmWDR68 in Hydrangea macrophylla 'forever summer'.

BACKGROUND: WD40 transcription factors are crucial in plant growth and developmental, significantly impacting plant growth regulation. This study investigates the WD40 transcription factor HmWDR68's role in developing the distinctive blue infertile flower colors in Hydrangea macrophylla 'Forever Summer'. METHODS AND RESULTS: The HmWDR68 gene was isolated by PCR, revealing an open reading frame of 1026 base pairs, which encodes 341 amino acids. Characterized by four WD40 motifs, HmWDR68 is a member of the WD40 family. Phylogenetic analysis indicates that HmWDR68 shares high homology with PsWD40 in Camellia sinensis and CsWD40 in Paeonia suffruticosa, both of which are integral in anthocyanin synthesis regulation. Quantitative real-time PCR (qRT-PCR) analysis demonstrated that HmWDR68 expression in the blue infertile flowers of 'Forever Summer' hydrangea was significantly higher compared to other tissues and organs. Additionally, in various hydrangea varieties with differently colored infertile flowers, HmWDR68 expression was markedly elevated in comparison to other hydrangea varieties, correlating with the development of blue infertile flowers. Pearson correlation analysis revealed a significant association between HmWDR68 expression and the concentration of delphinidin 3-O-glucoside, as well as key genes involved in anthocyanin biosynthesis (HmF3H, HmC3'5'H, HmDFR, and HmANS) in the blue infertile flowers of 'Forever Summer' hydrangea (P < 0.01). CONCLUSION: These findings suggest HmWDR68 may specifically regulate blue infertile flower formation in hydrangea by enhancing delphinidin-3-O-glucoside synthesis, modulating expression of HmF3H, HmC3'5'H, HmDFR and HmANS. This study provides insights into HmWDR68's role in hydrangea's blue flowers development, offering a foundation for further research in this field.

miR-542-5p targets GREM1 to affect the progression of renal fibrosis.

Renal fibrosis (RF) is a typical pathological presentation of end-stage chronic kidney disease (CKD) and autosomal dominant polycystic kidney disease (ADPKD). However, the precise regulatory mechanisms governing this re-expression process remain unclear. Differentially expressed microRNAs (miRNAs) associated with RF were screened by microarray analysis using the Gene Expression Omnibus (GEO) database. The miRNAs upstream of the genes in question were predicted using the miRWalk database. The miRNAs involved in the two GEO data sets were intersected to identify key miRNAs; their regulatory pathways were investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Subsequently, the effects and the underlying mechanisms of target miRNA on RF were examined in a unilateral ureteral obstruction (UUO)-induced mice renal fibrotic model and a transforming growth factor-ß1 (TGF-ß1)-induced tubular epithelium (HK-2) fibrotic cell model. In total, 109 and 32 differentially expressed miRNAs were identified in the GSE133530 and GSE80247 data sets, respectively. GREM1 was identified as a hub gene, where its 2196 upstream miRNAs were predicted; miR-574-5p was found to be downregulated and closely related to fibrosis after data set intersection and enrichment analyses, thus was selected for further investigation. A differential expression heatmap (GSE162794) showed that miR-542-5p was downregulated. The expression of GREM1 mRNA was upregulated, whereas that of miR-542-5p was downregulated in UUO mice and fibrotic HK-2 cells as compared with the relevant controls. The binding site of miR-542-5p was predicted at the 3'UTR region of GREM1 and was confirmed by subsequent dual luciferase reporter gene assay. Western blot analysis showed that Gremlin-1 and Fibronectin were significantly upregulated after induction of TGF-ß1; when miR-542-5p was overexpressed or GREM1 mRNA was interfered, the upregulations of Gremlin-1 and Fibronectin were significantly reduced. Our research demonstrates that miR-542-5p plays a critical role in the progression of RF, and thus may be a promising therapeutic target for CKD and ADPKD.

Measurements of the gravitational constant using two independent methods.

The Newtonian gravitational constant, G, is one of the most fundamental constants of nature, but we still do not have an accurate value for it. Despite two centuries of experimental effort, the value of G remains the least precisely known of the fundamental constants. A discrepancy of up to 0.05 per cent in recent determinations of G suggests that there may be undiscovered systematic errors in the various existing methods. One way to resolve this issue is to measure G using a number of methods that are unlikely to involve the same systematic effects. Here we report two independent determinations of G using torsion pendulum experiments with the time-of-swing method and the angular-acceleration-feedback method. We obtain G values of 6.674184 × 10-11 and 6.674484 × 10-11 cubic metres per kilogram per second squared, with relative standard uncertainties of 11.64 and 11.61 parts per million, respectively. These values have the smallest uncertainties reported until now, and both agree with the latest recommended value within two standard deviations.

A simple nomogram for predicting aspiration associated with dysphagia in hospitalized patients after stroke.

BACKGROUND: Aspiration is a common complication of poststroke dysphagia (PSD) and is associated with poor prognosis and mortality. There is no uniform criterion for determining aspiration associated with dysphagia. The aim of this study was to identify early predictors of aspiration, leading to the development of a simple nomogram for identifying aspiration risk associated with dysphagia in hospitalized patients after stroke. METHODS: Demographic information and clinical characteristics of 330 patients with PSD in the training cohort were utilized to develop a nomogram. The LASSO regression method was used to screen variables, and logistic regression was used to construct the nomogram. Internal validation was performed with bootstrap in the training cohort, and external validation was performed in the validation cohort of another 82 patients. The area under the curve (AUC), calibration curves, and decision curve analysis (DCA) were used to evaluate the performance of the nomogram. RESULTS: Seven variables were selected based on LASSO and multivariate logistic regression. The AUC of the nomogram was 0.834 (95% CI, 0.790-0.878) in the training cohort, 0.806 (95% CI, 0.791-0.880) in the internal validation cohort, and 0.882 (95% CI, 0.810-0.954) in the external validation cohort, which indicated that the model had good discrimination. The calibration and DCA curves showed that the nomogram had good accuracy and clinical utility. CONCLUSIONS: In this study, we established a nomogram that can be used to identify the risk of aspiration associated with dysphagia after stroke, and patients may benefit from early screening and preventive care.

PCGA: a comprehensive web server for phenotype-cell-gene association analysis.

Most complex disease-associated loci mapped by genome-wide association studies (GWAS) are located in non-coding regions. It remains elusive which genes the associated loci regulate and in which tissues/cell types the regulation occurs. Here, we present PCGA (https://pmglab.top/pcga), a comprehensive web server for jointly estimating both associated tissues/cell types and susceptibility genes for complex phenotypes by GWAS summary statistics. The web server is built on our published method, DESE, which represents an effective method to mutually estimate driver tissues and genes by integrating GWAS summary statistics and transcriptome data. By collecting and processing extensive bulk and single-cell RNA sequencing datasets, PCGA has included expression profiles of 54 human tissues, 2,214 human cell types and 4,384 mouse cell types, which provide the basis for estimating associated tissues/cell types and genes for complex phenotypes. We develop a framework to sequentially estimate associated tissues and cell types of a complex phenotype according to their hierarchical relationships we curated. Meanwhile, we construct a phenotype-cell-gene association landscape by estimating the associated tissues/cell types and genes of 1,871 public GWASs. The association landscape is generally consistent with biological knowledge and can be searched and browsed at the PCGA website.

Molecular mechanisms of cytochrome P450-mediated detoxification of tetraniliprole, spinetoram, and emamectin benzoate in the fall armyworm, Spodoptera frugiperda (J.E. Smith).

The fall armyworm (FAW) Spodoptera frugiperda (J.E. Smith) is a highly damaging invasive omnivorous pest that has developed varying degrees of resistance to commonly used insecticides. To investigate the molecular mechanisms of tolerance to tetraniliprole, spinetoram, and emamectin benzoate, the enzyme activity, synergistic effect, and RNA interference were implemented in S. frugiperda. The functions of cytochrome P450 monooxygenase (P450) in the tolerance to tetraniliprole, spinetoram, and emamectin benzoate in S. frugiperda was determined by analysing changes in detoxification metabolic enzyme activity and the effects of enzyme inhibitors on susceptibility to the three insecticides. 102 P450 genes were screened via transcriptome and genome, of which 67 P450 genes were differentially expressed in response to tetraniliprole, spinetoram, and emamectin benzoate and validated by quantitative real-time PCR. The expression patterns of CYP9A75, CYP340AA4, CYP340AX8v2, CYP340L16, CYP341B15v2, and CYP341B17v2 were analysed in different tissues and at different developmental stages in S. frugiperda. Silencing CYP340L16 significantly increased the susceptibility of S. frugiperda to tetraniliprole, spinetoram, and emamectin benzoate. Furthermore, knockdown of CYP340AX8v2, CYP9A75, and CYP341B17v2 significantly increased the sensitivity of S. frugiperda to tetraniliprole. Knockdown of CYP340AX8v2 and CYP340AA4 significantly increased mortality of S. frugiperda to spinetoram. Knockdown of CYP9A75 and CYP341B15v2 significantly increased the susceptibility of S. frugiperda to emamectin benzoate. These results may help to elucidate the mechanisms of tolerance to tetraniliprole, spinetoram and emamectin benzoate in S. frugiperda.

Influence of hip prosthesis position on postoperative gait in symptomatic hip osteoarthritis secondary to hip dysplasia patients after primary total hip arthroplasty: a short-term follow-up study.

BACKGROUND: The aim of this study was to analyze the influence of the positioning of the components of total hip arthroplasty (THA) evaluated by the acetabular anteversion (AA) and femoral anteversion (FA) angle on postoperative gait in patients with symptomatic hip osteoarthritis secondary to hip dysplasia undergoing THA. METHODS: Between May 2023 and May 2024, patients with symptomatic hip osteoarthritis secondary to hip dysplasia (Crowe Type I and IV) who underwent THA were enrolled in the study. The AA angle and FA angle were measured by computer tomography (CT). Gait data were determined by using the Dynamic Right Gait & Posture analysis system. The relationship between FA, AA and gait data was analyzed by Pearson correlation test, subgroup Pearson correlation test, multiple linear regression. RESULTS: A total of 40 patients (45hips) were included in the study. Compared with preoperative, the patient's postoperative foot progression angle, foot contact angle, plantarflexion velocity, swing foot speed, gait velocity, cadence, stride length were significantly improved. Preoperative FA is significantly different from postoperative FA (P < 0.05), while the difference between preoperative and postoperative AA is not significant. BMI, Crowe Type, AA were related to change of cadence. The less the postoperative AA of patients, and the more the cadence in the postoperative gait of patients. CONCLUSION: Our study showed that THA could improve the gait function of patients with symptomatic hip osteoarthritis secondary to hip dysplasia. Adjusting AA lower could obtain a much more postoperative cadence.

Exploring m6A-linked aging genes in osteoarthritis and broad cancer spectrum: Prospects for diagnostic and therapeutic advancements.

Osteoarthritis (OA) is a prevalent degenerative joint disease that significantly impacts individuals and healthcare systems worldwide. However, the exploration of N6-methyladenosine (m6A)-related aging genes in OA pathogenesis remains largely underexplored. This study aimed to elucidate the role of m6A-related aging genes in OA and to develop a robust diagnostic model based on their expression profiles. Leveraging publicly available gene expression datasets, we conducted consensus clustering to categorize OA into distinct subtypes, guided by the expression patterns of m6A-related aging genes. Utilizing XGBoost, a cutting-edge machine learning approach, we identified key diagnostic genes and constructed a predictive model. Our investigation extended to the immune functions of these genes, shedding light on potential therapeutic targets and underlying regulatory mechanisms. Our analysis unveiled specific OA subtypes, each marked by unique expression profiles of m6A-related aging genes. We pinpointed a set of pivotal diagnostic genes, offering potential therapeutic avenues. The developed diagnostic model exhibited exceptional capability in distinguishing OA patients from healthy controls. To corroborate our computational findings, we performed quantitative real-time polymerase chain reaction analyses on two cell lines: HC-OA (representing adult osteoarthritis cells) and C-28/I2 (representative of normal human chondrocytes). The gene expression patterns observed were consistent with our bioinformatics predictions, further validating our initial results. In conclusion, this study underscores the significance of m6A-related aging genes as promising biomarkers for diagnosis and prognosis, as well as potential therapeutic targets in OA. Although these findings are encouraging, further validation and functional analyses are crucial for their clinical application.

Terrestrial vegetation carbon sink analysis and driving mechanism identification in the Qinghai-Tibet Plateau.

The estimation of terrestrial carbon sinks in the Qinghai-Tibet Plateau (QTP) still faces significant uncertainties, and the spatiotemporal dynamics of terrestrial carbon sinks along altitudinal gradients remain unexplored. Moreover, the driving mechanisms of terrestrial carbon sinks at the watershed scale in the QTP continue to be lacking. To address these research gaps, based on multi-source remote sensing data and meteorological data, this study calculated the Net Ecosystem Productivity (NEP) in the QTP from 2000 to 2020 using the Modis NPP-soil respiration model. Through the coefficient of variation (CV), the Mann-Kendall test (MK), and the spatial autocorrelation methods, the spatial distribution pattern and spatiotemporal trends of NEP were investigated. Employing a pixel accumulation method, the variation of NEP along altitudinal gradients was explored. Grey relation analysis, Pearson correlation analysis, and Geographical detector (GD) were used to investigate the driving mechanisms of NEP at the watershed scale. Results showed that: (1) the terrestrial ecosystem in the QTP served as a carbon sink, which produced a total of 2.04 Pg C from 2000 to 2020, and the multi-year average of total carbon sinks was 96.92 Tg C; (2) the spatial distribution of NEP shows a decreasing change from southeast to northwest, and the clustering characteristic of NEP is significant at the watershed scale; (3) the elevation of 4507 m we proposed is likely to be a key threshold for biophysical processes of the terrestrial ecosystems in the QTP; (4) the fluctuation and change trend of carbon sources and carbon sinks show significant differences between the East and West; (5) at the watershed scale, precipitation and temperature play a dominant role in the variation of NEP, while the impact of human activities on NEP variation is weak. Our study aims to address the existing knowledge gaps and provide valuable insights into the management of terrestrial carbon sinks in QTP.