Evaluating site-of-care-related racial disparities in kidney graft failure using a novel federated learning framework.

OBJECTIVES: Racial disparities in kidney transplant access and posttransplant outcomes exist between non-Hispanic Black (NHB) and non-Hispanic White (NHW) patients in the United States, with the site of care being a key contributor. Using multi-site data to examine the effect of site of care on racial disparities, the key challenge is the dilemma in sharing patient-level data due to regulations for protecting patients' privacy. MATERIALS AND METHODS: We developed a federated learning framework, named dGEM-disparity (decentralized algorithm for Generalized linear mixed Effect Model for disparity quantification). Consisting of 2 modules, dGEM-disparity first provides accurately estimated common effects and calibrated hospital-specific effects by requiring only aggregated data from each center and then adopts a counterfactual modeling approach to assess whether the graft failure rates differ if NHB patients had been admitted at transplant centers in the same distribution as NHW patients were admitted. RESULTS: Utilizing United States Renal Data System data from 39 043 adult patients across 73 transplant centers over 10 years, we found that if NHB patients had followed the distribution of NHW patients in admissions, there would be 38 fewer deaths or graft failures per 10 000 NHB patients (95% CI, 35-40) within 1 year of receiving a kidney transplant on average. DISCUSSION: The proposed framework facilitates efficient collaborations in clinical research networks. Additionally, the framework, by using counterfactual modeling to calculate the event rate, allows us to investigate contributions to racial disparities that may occur at the level of site of care. CONCLUSIONS: Our framework is broadly applicable to other decentralized datasets and disparities research related to differential access to care. Ultimately, our proposed framework will advance equity in human health by identifying and addressing hospital-level racial disparities.

Genome-wide profiling of angiogenic cis-regulatory elements unravels cis-regulatory SNPs for vascular abnormality.

Angiogenesis is extensively involved in embryonic development and requires complex regulation networks, whose defects can cause a variety of vascular abnormalities. Cis-regulatory elements control gene expression at all developmental stages, but they have not been studied or profiled in angiogenesis yet. In this study, we exploited public DNase-seq and RNA-seq datasets from a VEGFA-stimulated in vitro angiogenic model, and carried out an integrated analysis of the transcriptome and chromatin accessibility across the entire process. Totally, we generated a bank of 47,125 angiogenic cis-regulatory elements with promoter (marker by H3K4me3) and/or enhancer (marker by H3K27ac) activities. Motif enrichment analysis revealed that these angiogenic cis-regulatory elements interacted preferentially with ETS family TFs. With this tool, we performed an association study using our WES data of TAPVC and identified rs199530718 as a cis-regulatory SNP associated with disease risk. Altogether, this study generated a genome-wide bank of angiogenic cis-regulatory elements and illustrated its utility in identifying novel cis-regulatory SNPs for TAPVC, expanding new horizons of angiogenesis as well as vascular abnormality genetics.

Racial/Ethnic Differences in Long-COVID-Associated Symptoms among Pediatrics Population: Findings from Difference-in-differences Analyses in RECOVER Program.

Racial/ethnic differences are associated with the potential symptoms and conditions of post-acute sequelae SARS-CoV-2 infection (PASC) in adults. These differences may exist among children and warrant further exploration. We conducted a retrospective cohort study for children and adolescents under the age of 21 from the thirteen institutions in the RECOVER Initiative. The cohort is 225,723 patients with SARS-CoV-2 infection or COVID-19 diagnosis and 677,448 patients without SARS-CoV-2 infection or COVID-19 diagnosis between March 2020 and October 2022. The study compared minor racial/ethnic groups to Non-Hispanic White (NHW) individuals, stratified by severity during the acute phase of COVID-19. Within the severe group, Asian American/Pacific Islanders (AAPI) had a higher prevalence of fever/chills and respiratory symptoms, Hispanic patients showed greater hair loss prevalence in severe COVID-19 cases, while Non-Hispanic Black (NHB) patients had fewer skin symptoms in comparison to NHW patients. Within the non-severe group, AAPI patients had increased POTS/dysautonomia and respiratory symptoms, and NHB patients showed more cognitive symptoms than NHW patients. In conclusion, racial/ethnic differences related to COVID-19 exist among specific PASC symptoms and conditions in pediatrics, and these differences are associated with the severity of illness during acute COVID-19.

Phylogenomics resolves the higher-level phylogeny of herbivorous eriophyoid mites (Acariformes: Eriophyoidea).

BACKGROUND: Eriophyoid mites (Eriophyoidea) are among the largest groups in the Acariformes; they are strictly phytophagous. The higher-level phylogeny of eriophyoid mites, however, remains unresolved due to the limited number of available morphological characters-some of them are homoplastic. Nevertheless, the eriophyoid mites sequenced to date showed highly variable mitochondrial (mt) gene orders, which could potentially be useful for resolving the higher-level phylogenetic relationships. RESULTS: Here, we sequenced and compared the complete mt genomes of 153 eriophyoid mite species, which showed 54 patterns of rearranged mt gene orders relative to that of the hypothetical ancestor of arthropods. The shared derived mt gene clusters support the monophyly of eriophyoid mites (Eriophyoidea) as a whole and the monophylies of six clades within Eriophyoidea. These monophyletic groups and their relationships were largely supported in the phylogenetic trees inferred from mt genome sequences as well. Our molecular dating results showed that Eriophyoidea originated in the Triassic and diversified in the Cretaceous, coinciding with the diversification of angiosperms. CONCLUSIONS: This study reveals multiple molecular synapomorphies (i.e. shared derived mt gene clusters) at different levels (i.e. family, subfamily or tribe level) from the complete mt genomes of 153 eriophyoid mite species. We demonstrated the use of derived mt gene clusters in unveiling the higher-level phylogeny of eriophyoid mites, and underlines the origin of these mites and their co-diversification with angiosperms.

Learning competing risks across multiple hospitals: one-shot distributed algorithms.

OBJECTIVES: To characterize the complex interplay between multiple clinical conditions in a time-to-event analysis framework using data from multiple hospitals, we developed two novel one-shot distributed algorithms for competing risk models (ODACoR). By applying our algorithms to the EHR data from eight national children's hospitals, we quantified the impacts of a wide range of risk factors on the risk of post-acute sequelae of SARS-COV-2 (PASC) among children and adolescents. MATERIALS AND METHODS: Our ODACoR algorithms are effectively executed due to their devised simplicity and communication efficiency. We evaluated our algorithms via extensive simulation studies as applications to quantification of the impacts of risk factors for PASC among children and adolescents using data from eight children's hospitals including the Children's Hospital of Philadelphia, Cincinnati Children's Hospital Medical Center, Children's Hospital of Colorado covering over 6.5 million pediatric patients. The accuracy of the estimation was assessed by comparing the results from our ODACoR algorithms with the estimators derived from the meta-analysis and the pooled data. RESULTS: The meta-analysis estimator showed a high relative bias (∼40%) when the clinical condition is relatively rare (∼0.5%), whereas ODACoR algorithms exhibited a substantially lower relative bias (∼0.2%). The estimated effects from our ODACoR algorithms were identical on par with the estimates from the pooled data, suggesting the high reliability of our federated learning algorithms. In contrast, the meta-analysis estimate failed to identify risk factors such as age, gender, chronic conditions history, and obesity, compared to the pooled data. DISCUSSION: Our proposed ODACoR algorithms are communication-efficient, highly accurate, and suitable to characterize the complex interplay between multiple clinical conditions. CONCLUSION: Our study demonstrates that our ODACoR algorithms are communication-efficient and can be widely applicable for analyzing multiple clinical conditions in a time-to-event analysis framework.

Transcriptome Profiling Reveals Molecular Responses to Salt Stress in Common Vetch (Vicia sativa L.).

Common vetch (Vicia sativa L.) is an important annual diploid leguminous forage. In the present study, transcriptomic profiling in common vetch in response to salt stress was conducted using a salt-tolerant line (460) and a salt-sensitive line (429). The common responses in common vetch and the specific responses associated with salt tolerance in 460 were analyzed. Several KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, including plant hormone and MAPK (mitogen-activated protein kinase) signaling, galactose metabolism, and phenylpropanoid phenylpropane biosynthesis, were enriched in both lines, though some differentially expressed genes (DEGs) showed distinct expression patterns. The roots in 460 showed higher levels of lignin than in 429. α-linolenic acid metabolism, carotenoid biosynthesis, the photosynthesis-antenna pathway, and starch and sucrose metabolism pathways were specifically enriched in salt-tolerant line 460, with higher levels of accumulated soluble sugars in the leaves. In addition, higher transcript levels of genes involved in ion homeostasis and reactive oxygen species (ROS) scavenging were observed in 460 than in 429 in response to salt stress. The transcriptomic analysis in common vetch in response to salt stress provides useful clues for further investigations on salt tolerance mechanism in the future.

One-shot distributed algorithms for addressing heterogeneity in competing risks data across clinical sites.

OBJECTIVE: To characterize the interplay between multiple medical conditions across sites and account for the heterogeneity in patient population characteristics across sites within a distributed research network, we develop a one-shot algorithm that can efficiently utilize summary-level data from various institutions. By applying our proposed algorithm to a large pediatric cohort across four national Children's hospitals, we replicated a recently published prospective cohort, the RISK study, and quantified the impact of the risk factors associated with the penetrating or stricturing behaviors of pediatric Crohn's disease (PCD). METHODS: In this study, we introduce the ODACoRH algorithm, a one-shot distributed algorithm designed for the competing risks model with heterogeneity. Our approach considers the variability in baseline hazard functions of multiple endpoints of interest across different sites. To accomplish this, we build a surrogate likelihood function by combining patient-level data from the local site with aggregated data from other external sites. We validated our method through extensive simulation studies and replication of the RISK study to investigate the impact of risk factors on the PCD for adolescents and children from four children's hospitals within the PEDSnet, A National Pediatric Learning Health System. To evaluate our ODACoRH algorithm, we compared results from the ODACoRH algorithms with those from meta-analysis as well as those derived from the pooled data. RESULTS: The ODACoRH algorithm had the smallest relative bias to the gold standard method (-0.2%), outperforming the meta-analysis method (-11.4%). In the PCD association study, the estimated subdistribution hazard ratios obtained through the ODACoRH algorithms are identical on par with the results derived from pooled data, which demonstrates the high reliability of our federated learning algorithms. From a clinical standpoint, the identified risk factors for PCD align well with the RISK study published in the Lancet in 2017 and other published studies, supporting the validity of our findings. CONCLUSION: With the ODACoRH algorithm, we demonstrate the capability of effectively integrating data from multiple sites in a decentralized data setting while accounting for between-site heterogeneity. Importantly, our study reveals several crucial clinical risk factors for PCD that merit further investigations.

Dasatinib suppresses collective cell migration through the coordination of focal adhesion and E-cadherin in colon cancer cells.

Collective cell migration is an important process in cancer metastasis. Unlike single-cell migration, collective cell migration requires E-cadherin expression in the cell cohort. However, the mechanisms underlying cellular contact and focal adhesions remain unclear. In this study, Src was hypothesized to coordinate focal adhesion and Rab11-mediated E-cadherin distribution during collective cell migration. This study primarily used confocal microscopy to visualize the 3D structure of cell-cell contacts with associated molecules. These results demonstrate that the clinical Src inhibitor dasatinib was less toxic to HT-29 colon cancer cells; instead, the cells aggregated. 3D immunofluorescence imaging showed that Rab11 was localized with E-cadherin at the adherens junctions of the apical cell-cell contacts. In the transwell assay, Rab11 colocalized with a broad range of E-cadherin proteins in collectively migrated cells, and dasatinib treatment significantly suppressed collective cell migration. Transmission electron microscopy demonstrated that dasatinib treatment increased cell membrane protrusion contacts and generated spaces between cells, which may allow epidermal growth factor receptor activity at the cell-cell contacts. This study suggests that dasatinib treatment does not inhibit cell survival but targets Src at different cellular compartments in the coordination of focal adhesions and cell-cell contacts in collective cell migration through E-cadherin dynamics in colon cancer cells.

Real-World Effectiveness of BNT162b2 Against Infection and Severe Diseases in Children and Adolescents.

BACKGROUND: The efficacy of the BNT162b2 vaccine in pediatrics was assessed by randomized trials before the Omicron variant's emergence. The long-term durability of vaccine protection in this population during the Omicron period remains limited. OBJECTIVE: To assess the effectiveness of BNT162b2 in preventing infection and severe diseases with various strains of the SARS-CoV-2 virus in previously uninfected children and adolescents. DESIGN: Comparative effectiveness research accounting for underreported vaccination in 3 study cohorts: adolescents (12 to 20 years) during the Delta phase and children (5 to 11 years) and adolescents (12 to 20 years) during the Omicron phase. SETTING: A national collaboration of pediatric health systems (PEDSnet). PARTICIPANTS: 77 392 adolescents (45 007 vaccinated) during the Delta phase and 111 539 children (50 398 vaccinated) and 56 080 adolescents (21 180 vaccinated) during the Omicron phase. INTERVENTION: First dose of the BNT162b2 vaccine versus no receipt of COVID-19 vaccine. MEASUREMENTS: Outcomes of interest include documented infection, COVID-19 illness severity, admission to an intensive care unit (ICU), and cardiac complications. The effectiveness was reported as (1-relative risk)*100, with confounders balanced via propensity score stratification. RESULTS: During the Delta period, the estimated effectiveness of the BNT162b2 vaccine was 98.4% (95% CI, 98.1% to 98.7%) against documented infection among adolescents, with no statistically significant waning after receipt of the first dose. An analysis of cardiac complications did not suggest a statistically significant difference between vaccinated and unvaccinated groups. During the Omicron period, the effectiveness against documented infection among children was estimated to be 74.3% (CI, 72.2% to 76.2%). Higher levels of effectiveness were seen against moderate or severe COVID-19 (75.5% [CI, 69.0% to 81.0%]) and ICU admission with COVID-19 (84.9% [CI, 64.8% to 93.5%]). Among adolescents, the effectiveness against documented Omicron infection was 85.5% (CI, 83.8% to 87.1%), with 84.8% (CI, 77.3% to 89.9%) against moderate or severe COVID-19, and 91.5% (CI, 69.5% to 97.6%) against ICU admission with COVID-19. The effectiveness of the BNT162b2 vaccine against the Omicron variant declined 4 months after the first dose and then stabilized. The analysis showed a lower risk for cardiac complications in the vaccinated group during the Omicron variant period. LIMITATION: Observational study design and potentially undocumented infection. CONCLUSION: This study suggests that BNT162b2 was effective for various COVID-19-related outcomes in children and adolescents during the Delta and Omicron periods, and there is some evidence of waning effectiveness over time. PRIMARY FUNDING SOURCE: National Institutes of Health.

Confidence score: a data-driven measure for inclusive systematic reviews considering unpublished preprints.

OBJECTIVES: COVID-19, since its emergence in December 2019, has globally impacted research. Over 360 000 COVID-19-related manuscripts have been published on PubMed and preprint servers like medRxiv and bioRxiv, with preprints comprising about 15% of all manuscripts. Yet, the role and impact of preprints on COVID-19 research and evidence synthesis remain uncertain. MATERIALS AND METHODS: We propose a novel data-driven method for assigning weights to individual preprints in systematic reviews and meta-analyses. This weight termed the "confidence score" is obtained using the survival cure model, also known as the survival mixture model, which takes into account the time elapsed between posting and publication of a preprint, as well as metadata such as the number of first 2-week citations, sample size, and study type. RESULTS: Using 146 preprints on COVID-19 therapeutics posted from the beginning of the pandemic through April 30, 2021, we validated the confidence scores, showing an area under the curve of 0.95 (95% CI, 0.92-0.98). Through a use case on the effectiveness of hydroxychloroquine, we demonstrated how these scores can be incorporated practically into meta-analyses to properly weigh preprints. DISCUSSION: It is important to note that our method does not aim to replace existing measures of study quality but rather serves as a supplementary measure that overcomes some limitations of current approaches. CONCLUSION: Our proposed confidence score has the potential to improve systematic reviews of evidence related to COVID-19 and other clinical conditions by providing a data-driven approach to including unpublished manuscripts.

Prognostic significance and immunological role of HPRT1 in human cancers.

Hypoxanthine phosphoribosyl transferase 1 (HPRT1), once considered a housekeeping gene, has been identified as playing an important role in several tumors. Its role in pan-cancer, however, has not been systematically studied. This study evaluates the relationship between HPRT1 and clinical parameters, survival prognosis, and tumor immunity based on multi omics data from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Drug sensitivity analysis screened 16 effective drugs against HPRT1, exploring the interactions with chemicals and genes. The significance of HPRT1 in tumor immunotherapy has also been investigated. Immunohistochemistry confirmed significant differences in the expression of HPRT1 between five tumor types (colon adenocarcinoma [COAD], head-neck squamous cell carcinoma [HNSC], lung adenocarcinoma [LUAD], thyroid carcinoma [THCA], and uterine corpus endometrial carcinoma [UCEC]) and adjacent normal tissues (P < 0.05). HPRT1 competitive endogenous RNA network was constructed in HNSC. Through cytological experiments, it was verified that HPRT1 plays a carcinogenic role in HNSC and is associated with tumor cell proliferation, migration, invasion, and apoptosis. In addition, there was a significant positive correlation between HPRT1 and programmed cell death-1 (PD-1) expression in HNSC (P < 0.05). These findings suggest that HPRT1 may be a potential biomarker for predicting and treating cancer.

Choroid plexus mast cells drive tumor-associated hydrocephalus.

Tumor-associated hydrocephalus (TAH) is a common and lethal complication of brain metastases. Although other factors beyond mechanical obstructions have been suggested, the exact mechanisms are unknown. Using single-nucleus RNA sequencing and spatial transcriptomics, we find that a distinct population of mast cells locate in the choroid plexus and dramatically increase during TAH. Genetic fate tracing and intracranial mast-cell-specific tryptase knockout showed that choroid plexus mast cells (CPMCs) disrupt cilia of choroid plexus epithelia via the tryptase-PAR2-FoxJ1 pathway and consequently increase cerebrospinal fluid production. Mast cells are also found in the human choroid plexus. Levels of tryptase in cerebrospinal fluid are closely associated with clinical severity of TAH. BMS-262084, an inhibitor of tryptase, can cross the blood-brain barrier, inhibit TAH in vivo, and alleviate mast-cell-induced damage of epithelial cilia in a human pluripotent stem-cell-derived choroid plexus organoid model. Collectively, we uncover the function of CPMCs and provide an attractive therapy for TAH.

Real-world Effectiveness of BNT162b2 Against Infection and Severe Diseases in Children and Adolescents.

Background: The efficacy of the BNT162b2 vaccine in pediatrics was assessed by randomized trials before the Omicron variant's emergence. The long-term durability of vaccine protection in this population during the Omicron period remains limited. Objective: To assess the effectiveness of BNT162b2 in preventing infection and severe diseases with various strains of the SARS-CoV-2 virus in previously uninfected children and adolescents. Design: Comparative effectiveness research accounting for underreported vaccination in three study cohorts: adolescents (12 to 20 years) during the Delta phase, children (5 to 11 years) and adolescents (12 to 20 years) during the Omicron phase. Setting: A national collaboration of pediatric health systems (PEDSnet). Participants: 77,392 adolescents (45,007 vaccinated) in the Delta phase, 111,539 children (50,398 vaccinated) and 56,080 adolescents (21,180 vaccinated) in the Omicron period. Exposures: First dose of the BNT162b2 vaccine vs. no receipt of COVID-19 vaccine. Measurements: Outcomes of interest include documented infection, COVID-19 illness severity, admission to an intensive care unit (ICU), and cardiac complications. The effectiveness was reported as (1-relative risk)*100% with confounders balanced via propensity score stratification. Results: During the Delta period, the estimated effectiveness of BNT162b2 vaccine was 98.4% (95% CI, 98.1 to 98.7) against documented infection among adolescents, with no significant waning after receipt of the first dose. An analysis of cardiac complications did not find an increased risk after vaccination. During the Omicron period, the effectiveness against documented infection among children was estimated to be 74.3% (95% CI, 72.2 to 76.2). Higher levels of effectiveness were observed against moderate or severe COVID-19 (75.5%, 95% CI, 69.0 to 81.0) and ICU admission with COVID-19 (84.9%, 95% CI, 64.8 to 93.5). Among adolescents, the effectiveness against documented Omicron infection was 85.5% (95% CI, 83.8 to 87.1), with 84.8% (95% CI, 77.3 to 89.9) against moderate or severe COVID-19, and 91.5% (95% CI, 69.5 to 97.6)) against ICU admission with COVID-19. The effectiveness of the BNT162b2 vaccine against the Omicron variant declined after 4 months following the first dose and then stabilized. The analysis revealed a lower risk of cardiac complications in the vaccinated group during the Omicron variant period. Limitations: Observational study design and potentially undocumented infection. Conclusions: Our study suggests that BNT162b2 was effective for various COVID-19-related outcomes in children and adolescents during the Delta and Omicron periods, and there is some evidence of waning effectiveness over time. Primary Funding Source: National Institutes of Health.

Stochastic Interventional Vaccine Efficacy and Principal Surrogate Analyses of Antibody Markers as Correlates of Protection against Symptomatic COVID-19 in the COVE mRNA-1273 Trial.

The COVE trial randomized participants to receive two doses of mRNA-1273 vaccine or placebo on Days 1 and 29 (D1, D29). Anti-SARS-CoV-2 Spike IgG binding antibodies (bAbs), anti-receptor binding domain IgG bAbs, 50% inhibitory dilution neutralizing antibody (nAb) titers, and 80% inhibitory dilution nAb titers were measured at D29 and D57. We assessed these markers as correlates of protection (CoPs) against COVID-19 using stochastic interventional vaccine efficacy (SVE) analysis and principal surrogate (PS) analysis, frameworks not used in our previous COVE immune correlates analyses. By SVE analysis, hypothetical shifts of the D57 Spike IgG distribution from a geometric mean concentration (GMC) of 2737 binding antibody units (BAU)/mL (estimated vaccine efficacy (VE): 92.9% (95% CI: 91.7%, 93.9%)) to 274 BAU/mL or to 27,368 BAU/mL resulted in an overall estimated VE of 84.2% (79.0%, 88.1%) and 97.6% (97.4%, 97.7%), respectively. By binary marker PS analysis of Low and High subgroups (cut-point: 2094 BAU/mL), the ignorance interval (IGI) and estimated uncertainty interval (EUI) for VE were [85%, 90%] and (78%, 93%) for Low compared to [95%, 96%] and (92%, 97%) for High. By continuous marker PS analysis, the IGI and 95% EUI for VE at the 2.5th percentile (519.4 BAU/mL) vs. at the 97.5th percentile (9262.9 BAU/mL) of D57 Spike IgG concentration were [92.6%, 93.4%] and (89.2%, 95.7%) vs. [94.3%, 94.6%] and (89.7%, 97.0%). Results were similar for other D29 and D57 markers. Thus, the SVE and PS analyses additionally support all four markers at both time points as CoPs.

Determination of chlorphenesin in cosmetics, a preservative that can affect anti-doping test result interpretations.

Chlorphenesin is a legitimate preservative commonly used in cosmetics. It shares one urinary metabolite of 4-chlorophenoxyacetic acid with meclofenoxate, a prohibited stimulant in sports. Recently, there have been cases where athletes using chlorphenesin-containing products were falsely identified as users of meclofenoxate. This study developed and validated a liquid chromatography method with diode-array detection to determine the chlorphenesin content in 61 selected personal care products with various functions (e.g., facial care, body cleansing, sun protection, make-up, hairstyling, perfume, and oral cleaning). The analytical method demonstrated fit-for-purpose quantitation and provided good linearity, precision, accuracy, and recovery for analyzing different cosmetic matrices. Among the 27 cosmetics labeled with chlorphenesin, the chlorphenesin concentrations ranged from 0.10 to 2.67 mg/g, with three products showing no detection. None of the products exceeded the maximum limit of 3 mg/g (0.3%) set by regulatory authorities. Among the 34 cosmetics not labeled with chlorphenesin, none of them contained chlorphenesin. This study confirmed the absence of undeclared chlorphenesin in the selected cosmetics, supporting the correctness of chlorphenesin labeling in cosmetics sold in Taiwan. Further investigations studying urinary excretion patterns after different types, doses, frequencies, and sites of cosmetics applications could contribute to strengthen current testing approaches in anti-doping.

Chitin-based hydrogel loaded with bFGF and SDF-1 for inducing endogenous mesenchymal stem cells homing to improve stress urinary incontinence.

Nonoperative treatments for Stress Urinary Incontinence (SUI) represent an ideal treatment method. Mesenchymal stem cell (MSCs) treatment is a new modality, but there is a lack of research in the field of gynecological pelvic floor and no good method to induce internal MSC homing to improve SUI. Herein, we develop an injectable and self-healing hydrogel derived from ß-chitin which consists of an amino group of quaternized ß-chitin (QC) and an aldehyde group of oxidized dextran (OD) between the dynamic Schiff base linkage.it can carry bFGF and SDF-1a and be injected into the vaginal forearm of mice in a non-invasive manner. It provides sling-like physical support to the anterior vaginal wall in the early stages. In the later stage, it slowly releasing factors and promoting the homing of MSCs in vivo, which can improve the local microenvironment, increase collagen deposition, repair the tissue around urethra and finally improve SUI (Scheme 1). This is the first bold attempt in the field of pelvic floor using hydrogel mechanical support combined with MSCs homing and the first application of chitin hydrogel in gynecology. We think the regenerative medicine approach based on bFGF/SDF-1/chitin hydrogel may be an effective non-surgical approach to combat clinical SUI.

Effect of prenatal perfluoroheptanoic acid exposure on spermatogenesis in offspring mice.

BACKGROUND: Perfluoroheptanoic acid (PFHpA), a persistent organic pollutant widespread in the environment, is suspected as an environmental endocrine disruptor for its disturbance effect on hormone homeostasis and reproductive development. Whereas the effect of intrauterine PFHpA exposure during gestation on spermatogenesis of male offspring mice is still unknown. OBJECTIVE: This study aimed to explore the effect of prenatal PFHpA exposure on the reproductive development of male offspring mice and the role of N6-methyladenosine (m6A) during the process. METHODS: Fifty-six C57BL/6 pregnant mice were randomly divided into 4 groups. During the gestation period, the pregnant mice were exposed to 0, 0.0015, 0.015, and 0.15 mg/kg bw/d PFHpA from gestational day 1 (GD1) to GD16 by oral gavage. The male offspring mice were sacrificed by spinal dislocation at 7 weeks old. The body weight, testicular weight, and brain weight were weighed, and the intra-testicular testosterone was detected. The sperm qualities were analyzed with computer-aided sperm analysis (CASA). The testicular tissues were taken to analyze the pathological changes and examine the global m6A RNA methylation levels. Quantitative real-time PCR (qRT-PCR) was adopted to figure out the mRNA expression levels of m6A-related enzymes in testicular tissues of different PFHpA treated groups. Methylated RNA immunoprecipitation sequencing (MeRIP-seq) was applied to further explore the m6A RNA methylation at a whole-genome scale. RESULTS: Compared with the control group, no significant differences were observed in body weight, testicular weight, testicular coefficient, and the visceral-brain ratio of testicular tissue in the PFHpA treated groups. And no significant change was observed in intra-testicular testosterone among the four groups. CASA results showed a decrease of sperm count, sperm concentration, and total cell count, as well as an increase of sperm progressive cells' head area after prenatal PFHpA exposure (P < 0.05). Hematoxylin and eosin staining of pathological sections showed seminiferous tubules morphological change, disorder arrangement of seminiferous epithelium, and reduction of spermatogenic cells in the PFHpA treated groups. PFHpA significantly decreased global levels of m6A RNA methylation in testicular tissue (P < 0.05). Besides, qRT-PCR results showed significant alteration of the mRNA expression levels of seven m6A-related enzymes (Mettl3, Mettl5, Mettl14, Pcif1, Wtap, Hnrnpa2b1, and Hnrnpc) in the PFHpA treated groups (P < 0.05). MeRIP-seq results showed a correlation between prenatal PFHpA exposure and activation and binding of cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP). Cnga3 and Mpzl3 showed differential expression in the enrichment subcategories or pathways. CONCLUSIONS: Exposure to PFHpA during the gestation period would adversely affect the development of seminiferous tubules and testicular m6A RNA methylation in offspring mice, which subsequently interferes with spermatogenesis and leads to reproductive toxicity.

Bibliometric Analysis of Research Themes and Trends of the Co-Occurrence of Autism and ADHD.

Background: In recent years, there has been a growing body of research suggesting that ASD and ADHD are two disorders that often co-exist. Despite the rapid development of research, little is known about their etiology, diagnostic markers, and interventions, which has led us to review and summarise the development of the field in the hope that this will provide an opportunity to look for future directions. Methods: A bibliometric approach was used to analyse papers in the field of ASD co-morbidities in ADHD on Web of Science from 1991-2022, using CiteSpace and VOSview to map the country/institution, journal, author, co-citation, and keyword networks in the field and to visualise the results. Results: A total of 3284 papers were included, showing an increasing trend in terms of posting trends. Research on co-morbidities of ASD has proven to be mainly focused on universities. The USA (1662) published the most relevant literature in this area, followed by the UK (651) and Sweden (388). Lichtenstein P is the most published author (84), and research into the pathogenesis of ASD co-occurring ADHD and related clinical diagnostics is currently at the forefront of the field. Conclusion: This analysis identifies the most influential institutions and countries, cited journals, and authors in the field of ASD co-morbid ADHD research. The future direction of ASD co-occurring ADHD should be based on improving case identification, discovering the etiological and diagnostic markers of ASD and ADHD, and finding more effective clinical interventions.

Transcriptomic analysis revealed the candidate metabolic pathways and genes associated with cold tolerance in a mutant without anthocyanin accumulation in common vetch (Vicia sativa L.).

Common vetch (Vicia sativa L.) is a leguminous crop used to feed livestock with vegetative organs or fertilize soils by returning to the field. Survival of fall-seeded plants is often affected by freezing damage during overwintering. This study aims to investigate the transcriptomic profiling in response to cold in a mutant with reduced accumulation of anthocyanins under normal growth and low-temperature conditions for understanding the underlying mechanisms. The mutant had increased cold a tolerance with higher survival rate and biomass during overwintering compared to the wild type, which led to increased forage production. Transcriptomic analysis in combination with qRT-PCR and physiological measurements revealed that reduced anthocyanins accumulation in the mutant resulted from reduced expression of serial genes involving in anthocyanin biosynthesis, which led to the altered metabolism, with an increased accumulation of free amino acids and polyamines. The higher levels of free amino acids and proline in the mutant under low temperature were associated with improved cold tolerance. The altered expression of some genes involved in ABA and GA signaling was also associated with increased cold tolerance in the mutant.

Interpretable Machine Learning Models for Phase Prediction in Polymerization-Induced Self-Assembly.

While polymerization-induced self-assembly (PISA) has become a preferred synthetic route toward amphiphilic block copolymer self-assemblies, predicting their phase behavior from experimental design is extremely challenging, requiring time and work-intensive creation of empirical phase diagrams whenever self-assemblies of novel monomer pairs are sought for specific applications. To alleviate this burden, we develop here the first framework for a data-driven methodology for the probabilistic modeling of PISA morphologies based on a selection and suitable adaption of statistical machine learning methods. As the complexity of PISA precludes generating large volumes of training data with in silico simulations, we focus on interpretable low variance methods that can be interrogated for conformity with chemical intuition and that promise to work well with only 592 training data points which we curated from the PISA literature. We found that among the evaluated linear models, generalized additive models, and rule and tree ensembles, all but the linear models show a decent interpolation performance with around 0.2 estimated error rate and 1 bit expected cross entropy loss (surprisal) when predicting the mixture of morphologies formed from monomer pairs already encountered in the training data. When considering extrapolation to new monomer combinations, the model performance is weaker but the best model (random forest) still achieves highly nontrivial prediction performance (0.27 error rate, 1.6 bit surprisal), which renders it a good candidate to support the creation of empirical phase diagrams for new monomers and conditions. Indeed, we find in three case studies that, when used to actively learn phase diagrams, the model is able to select a smart set of experiments that lead to satisfactory phase diagrams after observing only relatively few data points (5-16) for the targeted conditions. The data set as well as all model training and evaluation codes are publicly available through the GitHub repository of the last author.