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Abstract Background In recent years, the prevalence and incidence of porcine epidemic diarrhea virus (PEDV) infection have been on the rise. The occurrence of multiviral infections and recombination mutations has led to accelerated viral evolution and reduced vaccine efficacy. In the present study, a PEDV strain was isolated from a pig farm (Chongqing Province, China) with an outbreak of porcine diarrhea, and its S gene was found to be recombinant. Results The optimal trypsin concentration for blind passage of PEDV in Vero cells was determined to be 7.5 µg/mL. Following two blind passages of the virus in Vero cells, the virus was unable to adapt to the cells. Therefore, PEDV was blindly passaged in IPEC-J2 cells using the optimal concentration of trypsin (5 µg/mL). Next, a series of characterization experiments were performed. Recombination analyses of the isolates using software revealed that the S gene of strain CHCQ-2023 was derived from the primary parent strain PEDV-1 C and secondary parent strain SQ2014, with recombination occurring at a 3152 bp breakpoint. Furthermore, a specific B-cell antigenic epitope was predicted on the S2 subunit of the S protein. Conclusion A PEDV strain was isolated and characterized, and its S gene was characterized. The findings provide a bioinformatic basis for the study of PEDV strain variation due to genetic recombination.

Abstract Health event prediction is empowered by the rapid and wide application of electronic health records (EHR). In the Intensive Care Unit (ICU), precisely predicting the health related events in advance is essential for providing treatment and intervention to improve the patients outcomes. EHR is a kind of multi-modal data containing clinical text, time series, structured data, etc. Most health event prediction works focus on a single modality, e.g., text or tabular EHR. How to effectively learn from the multi-modal EHR for health event prediction remains a challenge. Inspired by the strong capability in text processing of large language model (LLM), we propose the framework CKLE for health event prediction by distilling the knowledge from LLM and learning from multi-modal EHR. There are two challenges of applying LLM in the health event prediction, the first one is most LLM can only handle text data rather than other modalities, e.g., structured data. The second challenge is the privacy issue of health applications requires the LLM to be locally deployed, which may be limited by the computational resource. CKLE solves the challenges of LLM scalability and portability in the healthcare domain by distilling the cross-modality knowledge from LLM into the health event predictive model. To fully take advantage of the strong power of LLM, the raw clinical text is refined and augmented with prompt learning. The embedding of clinical text are generated by LLM. To effectively distill the knowledge of LLM into the predictive model, we design a cross-modality knowledge distillation (KD) method. A specially designed training objective will be used for the KD process with the consideration of multiple modality and patient similarity. The KD loss function consists of two parts. The first one is cross-modality contrastive loss function, which models the correlation of different modalities from the same patient. The second one is patient similarity learning loss function to model the correlations between similar patients. The cross-modality knowledge distillation can distill the rich information in clinical text and the knowledge of LLM into the predictive model on structured EHR data. To demonstrate the effectiveness of CKLE, we evaluate CKLE on two health event prediction tasks in the field of cardiology, heart failure prediction and hypertension prediction. We select the 7125 patients from MIMIC-III dataset and split them into train/validation/test sets. We can achieve a maximum 4.48% improvement in accuracy compared to state-of-the-art predictive model designed for health event prediction. The results demonstrate CKLE can surpass the baseline prediction models significantly on both normal and limited label settings. We also conduct the case study on cardiology disease analysis in the heart failure and hypertension prediction. Through the feature importance calculation, we analyse the salient features related to the cardiology disease which corresponds to the medical domain knowledge. The superior performance and interpretability of CKLE pave a promising way to leverage the power and knowledge of LLM in the health event prediction in real-world clinical settings.

Moringa oleifera is a perennial medicinal and edible plant, and polyphenols as one of its main active ingredients. This study reviews the current status of development of the polyphenol types and contents of different parts, polyphenol extraction methods, polyphenol efficacy, and polyphenol applications of Moringa oleifera. Additionally, the current research on the antioxidant, anti-inflammatory, antibacterial, antiviral, anticancer, and hypoglycemic properties of polyphenols from Moringa oleifera is critically examined. The aim of this review is to provide a theoretical basis as well as new insights into the future research and applications of Moringa oleifera polyphenols.

Abstract Background Previous research on the risk of dementia associated with education attainment, smoking status, and alcohol use disorder (AUD) has yielded inconsistent results, indicating potential heterogeneous treatment effects (HTEs) of these factors on dementia risk. Thus, this study aimed to identify the important variables that may contribute to HTEs of these factors in older adults. Methods Using 2005–2021 data from the National Alzheimer’s Coordinating Center (NACC), we included older adults (≥ 65 years) with normal cognition at the first visit. The exposure of interest included college education or above, current smoking, and AUD and the outcome was all-cause dementia. We applied doubly robust learning to estimate risk differences (RD) and 95% confidence intervals (CI) between exposed and unexposed groups in the overall cohort and subgroups identified through a decision tree model. Results Of 10,062 participants included, 929 developed all-cause dementia over a median 4.4-year follow-up. College education or above was associated with a lower risk of all-cause dementia in the overall population (RD, -1.5%; 95%CI, -2.8 to -0.3), especially among the subpopulations without hypertension, regardless of the APOE4 status. Current smoking was not related to increased dementia risk overall (2.8%; -1.5 to 7.2) but was significantly associated with increased dementia risk among men with (21.1%, 3.1 to 39.1) and without (8.4%, 0.9 to 15.8) cerebrovascular disease. AUD was not related to increased dementia risk overall (2.0%; -7.7 to 11.7) but was significantly associated with increased dementia risk among men with neuropsychiatric disorders (31.5%; 7.4 to 55.7). Conclusions Our studies identified important factors contributing to HTEs of education, smoking, and AUD on risk of all-cause dementia, suggesting an individualized approach is needed to address dementia disparities.

A variety of polyphenols in walnut green husk have shown physiological benefits, but their primary hypoglycemic active ingredients remain unclear. We report the extraction of walnut green husk polyphenols (WGHP) and their hypoglycemic effects in vitro. WGHP was extracted using ultrasound-assisted ethanol extraction, with optimization via response surface methodology resulting in 88.0 ± 0.1 % purity after D101 macroporous resin purification. WGHP effectively inhibited α-glucosidase and α-amylase, with IC50 values of 3.42 μg/mL and 2.56 mg/mL, respectively. It also increased glycogen synthesis in insulin-resistant HepG2 cells and enhanced glucose consumption in 3T3-L1 and insulin-resistant HepG2 cells. Screening six α-glucosidase ligands from WGHP using affinity ultrafiltration and UPLC-MS/MS, combined with molecular docking, identified hydrogen bonds and binding energies between the ligands and the enzyme. These results highlight the hypoglycemic potential of walnut green husk polyphenols and provide a basis for future therapeutic research.

Abstract Resorcinol‐formaldehyde (RF) resin represents a promising visible‐light responding photocatalyst for oxygen reduction reaction (ORR) toward H2O2 production. However, its photocatalytic ORR activity toward H2O2 generation is still unsatisfied for practical application. Herein, 3‐hydroxythiophenol‐formaldehyde (3‐HTPF) resin microspheres synthesized through polycondensation reaction between 3‐HTP and formaldehyde at room temperature and subsequent hydrothermal treatment exhibit enhanced photocatalytic ORR activity is reported. The experimental results show that the partial substitution of hydroxy group (─OH) by sulfhydryl one (─SH) through using 3‐HTP to replace resorcinol could slow the rates of nucleation and growth of the resin particles and lead to strongly π‐stacked architecture in 3‐HTPF. The introduction of ─SH group can also improve adsorption ability of 3‐HTPF to O2 molecules and enhance ORR catalytic activity of the photocatalysts. Stronger built‐in electric field, better adsorption ability to O2 molecules, and increased surface catalytic activity collectively boost photocatalytic activity of 3‐HTPF microspheres. As a result, H2O2 production rate of 2010 µm h−1 is achieved over 3‐HTPF microspheres at 273 K, which is 3.4 times larger than that obtained using RF submicrospheres (591 µm h−1). The rational substituent group modulation provides a new strategy for designing polymeric photocatalysts at the molecular level toward high‐efficiency artificial photosynthesis.

Abstract Anion-intercalation lithium metal batteries (AILMBs) are appealing due to their low cost and fast intercalation/de-intercalation kinetics of graphite cathodes. However, the safety and cycliability of existing AILMBs are constrained by the scarcity of compatible electrolytes. Herein, we showcase that a difluoroester can be applied as electrolyte solvent to realize high-performance AILMBs, which not only endows high oxidation resistance, but also efficiently tunes the solvation shell to enable highly reversible and kinetically fast cathode reaction beyond the trifluoro counterpart. The difluoroester-based electrolyte demonstrates nonflammability, high ionic conductivity, and electrochemical stability, along with excellent electrode compatibility. The Li| |graphite AILMBs reach a high durability of 10000 cycles with only a 0.00128% capacity loss per cycle under fast-cycling of 1 A g−1, and retain ~63% of room-temperature capacity when discharging at −65 °C, meanwhile supply stable power output under deformation and overcharge conditions. The electrolyte design paves a promising path toward fast-rate, low-temperature, durable, and safe AILMBs.

Walnut dreg protein hydrolysates (WDPHs) exhibit a variety of biological activities, however, the cyclooxygenase-2 (COX-2) inhibitory peptide of WDPHs remain unclear. The aim of this study was to rapidly screen for such peptides in WDPHs through a combination of in silico and in vitro analysis. In total, 1262 peptide sequences were observed by nano liquid chromatography/tandem mass spectrometry (nano LC-MS/MS) and 4 novel COX-2 inhibitory peptides (AGFP, FPGA, LFPD, and VGFP) were identif ied. Enzyme kinetic data indicated that AGFP, FPGA, and LFPD displayed mixed-type COX-2 inhibition, whereas VGFP was a non-competitive inhibitor. This is mainly because the peptides form hydrogen bonds and hydrophobic interactions with residues in the COX-2 active site. These results demonstrate that computer analysis combined with in vitro evaluation allows for rapid screening of COX-2 inhibitory peptides in walnut protein dregs.

Abstract Background Seasonal freeze‒thaw (FT) processes alter soil formation and cause changes in soil microbial communities, which regulate the decomposition of organic matter in alpine ecosystems. Soil aggregates are basic structural units and play a critical role in microbial habitation. However, the impact of seasonal FT processes on the distribution of microbial communities associated with soil pores in different aggregate fractions under climate change has been overlooked. In this study, we sampled soil aggregates from two typical alpine ecosystems (alpine meadow and alpine shrubland) during the seasonal FT processes (UFP: unstable freezing period, SFP: stable frozen period, UTP: unstable thawing period and STP: stable thawed period). The phospholipid fatty acid (PLFA) method was used to determine the biomass of living microbes in different aggregate fractions. Results The microbial biomass of 0.25–2 mm and 0.053–0.25 mm aggregates did not change significantly during the seasonal FT process while the microbial biomass of > 2 mm aggregates presented a significant difference between the STP and UTP. Bacterial communities dominated the microbes in aggregates, accounting for over 80% of the total PLFAs. The microbial communities of soil aggregates in the surface layer were more sensitive to the seasonal FT process than those in other soil layers. In the thawing period, Gram positive bacteria (GP) was more dominant. In the freezing period, the ratio of Gram-positive to Gram-negative bacterial PLFAs (GP/GN) was low because the enrichment of plant litter facilitated the formation of organic matter. In the freezing process, pores of 30–80 μm (mesopores) favored the habitation of fungal and actinobacterial communities while total PLFAs and bacterial PLFAs were negatively correlated with mesopores in the thawing process. Conclusions The freezing process caused a greater variability in microbial biomass of different aggregate fractions. The thawing process increased the differences in microbial biomass among soil horizons. Mesopores of aggregates supported the habitation of actinobacterial and fungal communities while they were not conducive to bacterial growth. These findings provide a further comprehension of biodiversity and accurate estimation of global carbon cycle.

Phlorizin (PHL) is a natural compound with strong antioxidant properties mainly found in apples. In this paper, the interaction mechanism of PHL with pepsin and trypsin was comparatively evaluated by computer simulation, fluorescence spectra, circular dichroism (CD), and fourier transform infrared (FT-IR) spectra at a molecular level. Fluorescence spectra showed that PHL quenches the pepsin/trypsin by static quenching. Thermodynamic parameters indicated that PHL binds to pepsin mainly through hydrogen bonds and van der Waals forces, and that of trypsin was electrostatic forces. The ground state complexes PHL and protease have a moderate affinity of 105 L/mol PHL binds more strongly to trypsin than to pepsin. CD and FT-IR spectra results showed that pepsin/trypsin decreased the β-sheet content and slightly changed its secondary structure upon PHL. These experimental results are mutually verified with the predicted computer-aid simulation results. Upon PHL and trypsin binding, the antioxidant capacity of PHL was elevated. Nevertheless, the antioxidant capacity of PHL was decreased after binding to pepsin. This work elucidates the binding of PHL binding mechanisms to pepsin/trypsin and provides useful information for the digestion of PHL to improve the application of PHL in food processing.

Aqueous secondary batteries are promising candidates for next-generation large-scale energy storage systems owing to their excellent safety and cost-effectiveness. However, their commercialization faces considerable challenges owing to a limited electrochemical stability window and lower energy density. In this study, we present a rationally designed hydrogel electrolyte, featuring a distinctive polymer network and reduced free water content, created using a UV-curing method. This innovation results in an impressive ionic conductivity of 43 mS cm−1, high mechanical strength and an enhanced electrochemical stability window of up to 2.5 V (vs. Zn/Zn2+). The hybrid electrolyte demonstrates impressive viability and versatility, enabling compatibility with various cathode materials for use in both aqueous Na–Zn hybrid batteries and Zn-ion batteries. Notably, when paired with a Prussian blue cathode, the assembled hybrid batteries show remarkable cyclability, enduring over 6000 cycles with a minimal capacity decay of only 0.0096% per cycle at a high current density of 25 C. Additionally, the Zn||Na2MnFe(CN)6 full battery using the synthesized hydrogel electrolyte achieves a high energy density of approximately 220 Wh kg−1 and outstanding rate performance reaching up to 5 C. This research provides important insights for designing aqueous hybrid electrolytes that combine both high ionic conductivity and an expansive electrochemical stability window.

Utilizing spent refractory material (SRM), generated after the overhaul of aluminum electrolytic cells, as a raw material for producing Al-Si alloys presents an efficient approach towards achieving full resource utilization of SRM. However, a bottleneck restricting this technology has become the dissolution of SRM. Based on the heat and mass transfer mechanism, the shrinkage core model of SRM particle dissolution was established. The effects of alumina concentration, silica concentration, electrolyte superheat, particle temperature, and turbulent kinetic energy dissipation rate on the mass dissolution rate and dissolution time of SRM particles were investigated. Calculation results and experimental data were compared to confirm the accuracy of the established model. The results show that by maintaining low alumina and silica concentrations, increasing the electrolyte superheat and particle preheating temperature, and increasing the electrolyte turbulent kinetic energy dissipation rate, SRM particles can dissolve faster. The dissolution of agglomerated particles is greatly influenced by the turbulent kinetic energy dissipation rate and superheat. The present research provides promising guidance for practical application in predicting particle dissolution time, controlling process parameters, and accelerating the dissolution of SRM particles.

Diabetes mellitus (DM) is a chronic metabolic disease characterized by hyperglycemia, which poses a serious threat to human health. Moringa oleifera Lam is a medicinal and edible plant with various physiological functions. However, its main hypoglycemic components and mechanisms are still unclear. In this study, network pharmacology and bioinformatics were used to analyze the potential bioactive substances of M. oleifera leaf extract (MOLE) and its hypoglycemic mechanism. Studies have shown that MOLE has the effect of increasing glucose consumption in insulin resistant-HepG2 cells. MOLE was found to contain 975 compounds by ultrahigh performance liquid chromatography-mass spectrometry (UHPLC-MS). Network pharmacology analysis indicated that the main active component was robinetin and the identified core genes were AKT1 and GAPDH. KEGG pathway enrichment analysis showed that the hypoglycemic effect of MOLE may be closely related to the PI3K-Akt signaling pathway. This study revealed the possible active components and mechanisms of action of M. oleifera for hypoglycemia, laying the theoretical foundation for subsequent studies.

The increasing concentration of Antimony (Sb) in ecological environments has raised serious concerns about its potential biotoxicological impact. This study investigated the toxicokinetics, Global DNA Methylation (GDM), biomarker expression, and Integrated Biological Response (IBR) of Sb at different concentrations in zebrafish. The toxic mechanism of Sb exposure was simulated using molecular dynamics (MD). The results showed that significant differences effect existed (BCFk: liver > ovary > gut > brain) and uptake saturation phenomenon of Sb among zebrafish tissues. Over a 54-day exposure period, the liver emerged as the main target site for Sb-induced GDM, and the restoration was slower than in other tissues during the 54-day recovery period. Moreover, the concentration of Sb had a significant impact on the normally expression of biomarkers, with GSTM1 inhibited and MTF2, MT1, TET3, and p53 showing varying degrees of activation at different Sb concentrations. This could be attributed to Sb3+ potentially occupying the active site or tightly binding to the deep cavity of these genes. The IBR and MD results highlighted DNMT1 as the most sensitive biomarker among those assessed. This heightened sensitivity can be attributed to the stable binding of Sb3+ to DNMT1, resulting in alterations in the conformation of DNMT1's catalytic domain and inhibition of its activity. Consequently, this disruption leads to damage to the integrity of GDM. The study suggests that DNA methylation could serve as a valuable biomarker for assessing the ecotoxicological impact of Sb exposure. It contributes to a better understanding of the toxicity mechanisms in aquatic environments caused potential pollutants.

Abstract Background The incidence and mortality of gastric cancer (GC) are high worldwide. Tumor stemness is a major contributor to tumorigenesis and development of GC, in which long non-coding RNAs (lncRNAs) are deeply involved. The purpose of this study was to investigate the influences and mechanisms of LINC00853 in the progression and stemness of GC. Methods The level of LINC00853 was assessed based on The Cancer Genome Atlas (TCGA) database and GC cell lines by RT-PCR and in situ hybridization. An evaluation of biological functions of LINC00853 including cell proliferation, migration, and tumor stemness was conducted via gain-and loss-of-function experiments. Furthermore, RNA pull-down and RNA immunoprecipitation (RIP) assay were utilized to validate the connection between LINC00853 and the transcription factor Forkhead Box P3 (FOXP3). Nude mouse xenograft model was used to identify the impacts of LINC00853 on tumor development. Results We identified the up-regulated levels of lncRNA-LINC00853 in GC, and its overexpression correlates with poor prognosis in GC patients. Further study indicated that LINC00853 promoted cell proliferation, migration and cancer stemness while suppressed cell apoptosis. Mechanistically, LINC00853 directly bind to FOXP3 and promoted FOXP3-mediated transcription of PDZK1 interacting protein 1(PDZK1IP1). Alterations of FOXP3 or PDZK1IP1 reversed the LINC00853-induced biological effects on cell proliferation, migration and stemness. Moreover, xenograft tumor assay was used to investigate the function of LINC00853 in vivo. Conclusions Taken together, these findings revealed the tumor-promoting activity of LINC00853 in GC, expanding our understanding of lncRNAs regulation on GC pathogenesis.

Understanding the behavior of lithium-ion battery electrolytes during thermal runaway is essential for designing safer batteries. However, current reports on electrolyte decomposition behaviors often focus on reactions with electrode materials. Herein we use quantum chemical calculations to develop a model for the thermal decomposition mechanism of electrolytes under both electrolyte and ambient atmosphere conditions. The thermal stability is found to be associated with the dielectric constants of electrolyte constituents. Within the electrolyte, the solvation effects between molecules increase electrolyte stability, making thermal decomposition a more difficult process. Furthermore, Li+ is observed to facilitate electrolyte thermal decomposition, as the energy required for the thermal decomposition reactions of molecules decreases when they are bonded with Li+. It is hoped that this study will offer a theoretical basis for understanding the complex reactions occurring during thermal runaway events.

Walnut protein-derived peptides have a variety of biological activities, but it is unclear whether walnut peptides have anti-colorectal cancer activity. Therefore, the aim of this study was to explore the anti-colorectal cancer peptides of walnut and the underlying mechanism of action by in silico analysis and in vitro evaluation. Walnut protein alcalase hydrolysate (WPH-Al) significantly inhibited the growth and induced the apoptosis of colon cancer HCT116 cells. The

BackgroundPrior studies have shown disparities in the uptake of cardioprotective newer glucose-lowering drugs (GLDs), including sodium-glucose cotranwsporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1a). This study aimed to characterize geographic variation in the initiation of newer GLDs and the geographic variation in the disparities in initiating these medications.MethodsUsing 2017-2018 claims data from a 15% random nationwide sample of Medicare Part D beneficiaries, we identified individuals diagnosed with type 2 diabetes (T2D), who had ≥1 GLD prescriptions, and did not use SGLT2i or GLP1a in the year prior to the index date,1/1/2018. Patients were followed up for a year. The cohort was spatiotemporally linked to Dartmouth hospital-referral regions (HRRs), with each patient assigned to 1 of 306 HRRs. We performed multivariable Poisson regression to estimate adjusted initiation rates, and multivariable logistic regression to assess racial disparities in each HRR.ResultsAmong 795,469 individuals with T2D included in the analyses, the mean (SD) age was 73 (10) y, 53.3% were women, 12.2% were non-Hispanic Black, and 7.2% initiated a newer GLD in the follow-up year. In the adjusted model including clinical factors, compared to non-Hispanic White patients, non-Hispanic Black (initiation rate ratio, IRR [95% CI]: 0.66 [0.64-0.68]), American Indian/Alaska Native (0.74 [0.66-0.82]), Hispanic (0.85 [0.82-0.87]), and Asian/Pacific islander (0.94 [0.89-0.98]) patients were less likely to initiate newer GLDs. Significant geographic variation was observed across HRRs, with an initiation rate spanning 2.7%-13.6%.ConclusionsThis study uncovered substantial geographic variation and the racial disparities in initiating newer GLDs.

Abstract We evaluate the prognostic value of chemotherapy and other prognostic factors on overall survival among colon patients with deficient mismatch repair (dMMR), and determine the optimum time to start chemotherapy after surgery. Data of 306 colon cancer patients with dMMR who received radical surgery were collected from three Chinese centers between August 2012 and January 2018. Overall survival (OS) was assessed with the Kaplan–Meier method and log-rank. Cox regression analysis were used to assess influencing prognosis factors. The median follow-up time for all patients was 45.0 months (range, 1.0–100). There was a nonsignificant OS benefit from chemotherapy for patients with stage I and stage II disease, including high-risk stage II disease (log-rank p: 0.386, 0.779, 0.921), and a significant OS benefit for patients with stage III and stage IV disease for receiving post-operation chemotherapy (log-rank p = 0.002, 0.019). Stage III patients benefitted from chemotherapy regimens that contained oxaliplatin (log-rank p = 0.004), and Starting chemotherapy with oxaliplatin treatment earlier resulted in better outcomes (95% CI 0.013–0.857; p = 0.035). Chemotherapy regimens containing oxaliplatin can prolong the survival time of stage III and IV dMMR colon cancer patients. This beneficial manifestation was more pronounced after starting chemotherapy treatment early post operation. High risk stage II dMMR colon patients including T4N0M0 cannot benefit from chemotherapy.

In this study, the effects of cellulase addition, ethanol volume fraction, cellulase digestion time and ultrasound time on the extraction rate of Moringa oleifera seeds polyphenols were investigated. At the same time, the extraction process of Moringa oleifera seeds polyphenols by ultrasound-assisted cellulase method was optimized using response surface methodology. In addition, the in vitro antioxidant and hypoglycemic and hypolipidemic activities of Moringa oleifera seeds polyphenols were also investigated. The results showed that the optimal process for the extraction of Moringa oleifera seed polyphenols by ultrasound-assisted cellulase was 0.30% enzyme addition, 53.00% volume fraction of ethanol, 31.00 min enzymatic digestion time, and 31.00 min ultrasound time. Under this process condition, the amount of Moringa oleifera seed polyphenols extracted obtained was 6.90 mg/g, which was not significantly different from the predicted value. In addition, the study found that Moringa oleifera seed polyphenols had good antioxidant activity, and its IC50 for scavenging ABTS radicals and DPPH radicals were 0.76 and 0.61 mg/mL, respectively. Meanwhile, Moringa oleifera seed polyphenols had some pancreatic lipase and α-amylase inhibitory activities, and theirs IC50 for pancreatic lipase and α-amylase inhibition rate were 1.35 and 6.55 mg/mL, respectively. This study provides a theoretical basis for the extraction and application of Moringa oleifera seed polyphenols.

Abstract Background Risk factors for urolithiasis have not been identified. Here, we aimed to identify potentially causal risk factors driving the risk of urolithiasis. Methods Two sets of instrumental variables were used for analysis, derived from publicly available databases. Summary-level statistical data for urolithiasis were obtained from the MRC-IEU Consortium and UK biobank (Neale Lab). Mendelian randomization (MR) was conducted to identify causal risk of urolithiasis. Finally, the results of the two databases were combined and a meta-analysis was performed. Results In the MRC-IEU consortium, the odds of urolithiasis increased per 1-SD increase of body mass index (BMI) (OR = 1.0016, 95% CI:1.0004–1.0029, p = 0.010), triglycerides (OR = 1.0016, 95% CI:1.0003–1.0029, p = 0.017), adiponectin (OR = 1.0027, 95% CI:1.0003–1.0050, p = 0.024), and body fat percentage (OR = 1.008, 95% CI:1.0001–1.0161, p = 0.047). In addition, alcohol intake also increased the incidence of urolithiasis (OR = 1.0030, 95% CI:1.0009–1.0051, p = 0.005). In the UK biobank, the odds of urolithiasis increased per 1-SD increase of waist circumference (OR = 1.0215, 95% CI:1.0061–1.0372, p = 0.008) and body fat percentage (OR = 1.0239, 95% CI:1.0043–1.0440, p = 0.020). Surprisingly, we found that the risk of urolithiasis decreased with increasing hip circumference (OR = 0.9954, 95% CI:0.9915–0.9992, p = 0.017). In a meta-analysis of MR results, higher BMI (OR = 1.0016, 95% CI:1.0004–1.0027, p = 0.009), waist circumference (OR = 1.0073, 95% CI:1.0020–1.0126, p = 0.007), adiponectin (OR = 1.0026, 95% CI:1.0008–1.0043, p = 0.004), triglycerides (OR = 1.0015, 95% CI:1.0004–1.0026, p = 0.008) and body fat percentage (OR = 1.0104, 95% CI:1.0030–1.0178, p = 0.006) increased the risk of urolithiasis. Furthermore, alcohol intake also increased the incidence of urolithiasis (OR = 1.0033, 95% CI:1.0012–1.0053, p = 0.002). Conclusions Our MR study found that higher BMI, triglycerides, waist circumference, adiponectin, body fat percentage, and alcohol intake increased the risk of urolithiasis.

Abstract Background We evaluated the prognostic role of deficient mismatch repair (dMMR) systems in stage II and stage III colon cancer patients during different postoperative periods. We also assessed whether patients aged ≥75 could benefit from chemotherapy. Methods This retrospective study was conducted across three medical centers in China. Kaplan–Meier survival methods and Cox proportional hazards models were used to evaluate the differences in overall survival (OS) and disease-free survival (DFS) rates. Propensity score matching was performed to reduce imbalances in the baseline characteristics of the patients. Landmark analysis was performed to evaluate the role of dMMR during different postoperative periods. Results The median follow-up time for all patients was 45.0 months (25–75 IQR: 38.0–82.5). There was no significant OS (p = 0.350) or DFS (p = 0.752) benefit associated with dMMR for stage II and III patients during the first postoperative year. However, significant OS (p

As an emerging new type of battery chemistry, the anion shuttle battery (ASB), based on the shuttling and storage of anions, is considered a sustainable alternative to gigawatt-scale energy storage due to the associated resource abundance, low cost, high safety, and high energy density. Although significant progress has been achieved, practical applications of ASBs are still hindered by tough challenges, such as short lifetime, limited reversible capacity, and low Coulombic efficiency. Therefore, it is very necessary to design and explore new electrolyte systems with high electrochemical/chemical stability, sufficient compatibility towards electrodes, and excellent kinetics/reversibility for anion electrochemical reactions. Here, we review the recent achievements and main challenges in developing electrolytes for ASBs, which include solid, non-aqueous, and aqueous electrolytes. We mainly focus on the unique properties and basic principles of designing these electrolytes, and their various performance parameters. Perspectives on design strategies for ASB electrolytes are also presented, which could facilitate the development of advanced ASBs for grid-scale energy storage.

Abstract Background The association between triglyceride and prostate cancer (PCa) has been reported in observational studies. However, the causality from triglyceride on PCa remained unknown. Method Two-sample Mendelian randomization (MR) was performed with triglyceride genome-wide association study (GWAS) data from 177,861 individuals and GWAS summary statistics of PCa from 463,010 individuals. Then, 48 single nucleotide polymorphisms (SNPs) of triglyceride were used as instrumental variables (IVs) to conduct MR analysis on PCa. Inverse‐variance weighted (IVW), Weighted median, MR‐Egger regression, Simple mode and Weighted mode were used for MR analysis. To verify the sensitivity of the data, heterogeneity test, pleiotropy test and leave-one-out sensitivity test were performed. Results Association for an effect of triglyceride on PCa risk was found in IVW (odds ratio [OR]: 1.002, 95% confidence interval (CI): 1.000–1.004, p = 0.016). However, opposing results were observed using the weighted median (OR: 1.001, 95% CI: 0.999–1.003, p = 0.499) and MR‐Egger (OR: 0.999, 95% CI: 0.995–1.002, p = 0.401) approach. After MRPRESSO, the same result was obtained by using IVW method (OR: 1.002, 95% CI: 1.001–1.004, p = 0.004). Conclusions The large MR analysis indicated that the potential causal effect of triglyceride on PCa. The odds of PCa would increase with high levels of triglyceride.

Porcine epidemic diarrhea virus (PEDV) mainly invades the small intestine and promotes an inflammatory response, eventually leading to severe diarrhea, vomiting, dehydration, and even death of piglets, which seriously threatens the economic development of pig farming. In recent years, researchers have found that probiotics can improve the intestinal microenvironment and reduce diarrhea. At the same time, certain probiotics have been shown to have antiviral effects; however, their mechanisms are different. Herein, we aimed to investigate the inhibitory effect of Lactiplantibacillus plantarum supernatant (LP-1S) on PEDV and its mechanism. We used IPEC-J2 cells as a model to assess the inhibitory effect of LP-1S on PEDV and to further investigate the relationship between LP-1S, Ca2+, and PEDV. The results showed that a divalent cation chelating agent (EGTA) and calcium channel inhibitors (Bepridil hydrochloride and BAPTA-acetoxymethylate) could inhibit PEDV proliferation while effectively reducing the intracellular Ca2+ concentration. Furthermore, LP-1S could reduce PEDV-induced loss of calcium channel proteins (TRPV6 and PMCA1b), alleviate intracellular Ca2+ accumulation caused by PEDV infection, and promote the balance of intra- and extracellular Ca2+ concentrations, thereby inhibiting PEDV proliferation. In summary, we found that LP-1S has potential therapeutic value against PEDV, which is realized by modulating Ca2+. This provides a potential new drug to treat PEDV infection.

It is prudent to take a unified approach to exploring how contextual social determinants of health (SDoH) relate to COVID-19 occurrence and outcomes. Poor geographically represented data and a small number of contextual SDoH examined in most previous research studies have left a knowledge gap in the relationships between contextual SDoH and COVID-19 outcomes. In this study, we linked 199 contextual SDoH factors covering 11 domains of social and built environments with electronic health records (EHRs) from a large clinical research network (CRN) in the National Patient-Centered Clinical Research Network (PCORnet) to explore the relation between contextual SDoH and COVID-19 occurrence and hospitalization. We identified 15,890 COVID-19 patients and 63,560 matched non-COVID-19 patients in Florida between January 2020 and May 2021. We adopted a two-phase multiple linear regression approach modified from that in the exposome-wide association (ExWAS) study. After removing the highly correlated SDoH variables, 86 contextual SDoH variables were included in the data analysis. Adjusting for race, ethnicity, and comorbidities, we found six contextual SDoH variables (i.e., hospital available beds and utilization, percent of vacant property, number of golf courses, and percent of minority) related to the occurrence of COVID-19, and three variables (i.e., farmers market, low access, and religion) related to the hospitalization of COVID-19. To our best knowledge, this is the first study to explore the relationship between contextual SDoH and COVID-19 occurrence and hospitalization using EHRs in a major PCORnet CRN. As an exploratory study, the causal effect of SDoH on COVID-19 outcomes will be evaluated in future studies.

Embedding is widely used in recommendation models to learn feature representations. However, the traditional embedding technique that assigns a fixed size to all categorical features may be suboptimal due to the following reasons. In recommendation domain, the majority of categorical features' embeddings can be trained with less capacity without impacting model performance, thereby storing embeddings with equal length may incur unnecessary memory usage. Existing work that tries to allocate customized sizes for each feature usually either simply scales the embedding size with feature's popularity or formulates this size allocation problem as an architecture selection problem. Unfortunately, most of these methods either have large performance drop or incur significant extra time cost for searching proper embedding sizes. In this article, instead of formulating the size allocation problem as an architecture selection problem, we approach the problem from a pruning perspective and propose Pruning-based Multi-size Embedding (PME) framework. During the search phase, we prune the dimensions that have the least impact on model performance in the embedding to reduce its capacity. Then, we show that the customized size of each token can be obtained by transferring the capacity of its pruned embedding with significant less search cost. Experimental results validate that PME can efficiently find proper sizes and hence achieve strong performance while significantly reducing the number of parameters in the embedding layer.

Elemental mercury impaction in the appendix can cause subsequent local and systemic complications. We present a case of a teenage boy who ingested approximately 10 mL of elemental mercury, resulting in residual mercury sequestration in the appendix after conservative management. We performed laparoscopic appendectomy to remove the residual mercury. The patient made a complete clinical recovery without adverse events related to mercury poisoning over the 6-month follow-up. We highlight the advantages of laparoscopic appendectomy, abdominal computed tomography (CT), negative pressure operating rooms, and surgeon protection to improve surgical success rates. This case report adds to the literature on the management of elemental mercury impaction in the appendix and provides valuable insights for clinical decision-making.

IntroductionTo predict the factors of residual stones after percutaneous nephrolithotomy (PCNL) by analyzing the characteristics of the renal anatomical structure in intravenous urography, so as to make a reasonable operation plan, reduce the risk of residual stones in PCNL, and improve the stone-free rate (SFR).MethodsA retrospective study was performed between January 2019 and September 2020 for patients treated with PCNL. According to the results of a kidney ureter bladder review after PCNL, 245 patients were divided into a residual stone group (71 patients, stone size >4 mm) and a stone-free group (174 patients, stone size ≤4 mm). An independent sample t-test was used to analyze the age, the length and width of channel calices, the angle between the channel calices and the involved calices, and the length and width of the involved calices. The gender, the channel types, the number of channels, the degree of hydronephrosis, and the number of involved calices were analyzed by using the chi-square test. A score of p

Hot dry rock (HDR) is considered a new clean and renewable energy source. China is rich in HDR resources, but viable and reliable resource evaluation techniques and exploration methods have not been available yet. This research method, consisting of deep exploration combined with shallow drilling, screens the geothermal anomaly regions using heavy magnetic, electric measurement, seismic and thermal joint interpretation technology, and verifies the geophysical multiplicity with massive oilfield drilling data to locate the favorable HDR target region. The research results show a regionally geothermal abnormal area. We use relative impedance combined with seismic profile to recognize the HDR target region. The geophysical exploration and geological joint interpretation technology are faster and more accurate than the single geophysical exploration technology. The comprehensive analysis believes that the high resistance granite body in the southern Paleo-central uplift zone, with its area 500 km2, its thickness 150–330 m, its static formation temperature reaching 152° in the depth of 3360 m, its high rock thermal conductivity, its good deep fracture, and base fracture development, is a fragmented granite and weathered shell, easy for artificial reservoir re-constructing. There is high preciseness in locating the favorable target region for HDR development.

ObjectiveTo better understand the alterations in gut microbiota and metabolic pathways in children with focal epilepsy, and to further investigate the changes in the related gut microbiota and metabolic pathways in these children before and after treatment.MethodsTen patients with newly diagnosed focal epilepsy in Hunan Children’s Hospital from April, 2020 to October, 2020 were recruited into the case group. The case group was further divided into a pre-treatment subgroup and a post-treatment subgroup. Additionally, 14 healthy children of the same age were recruited into a control group. The microbial communities were analyzed using 16s rDNA sequencing data. Metastas and LEfSe were used to identify different bacteria between and within groups. The Kyoto Encyclopedia of Genes and Genomes database was used to KEGG enrichment analysis.ResultsThere were significant differences in α diversity among the pre-treatment, post-treatment, and control groups. Besides, the differences in gut microbiota composition in 3 groups were identified by principal co-ordinates analysis (PCoA), which showed a similar composition of the pre-treatment and post-treatment subgroups. At the phyla level, the relative abundance of Actinobacteria in the pre-treatment subgroup was significantly higher than that in the control group, which decreased significantly after 3 months of treatment and showed no significant difference between the control group. In terms of the genus level, Escherichia/Shigella, Streptococcus, Collinsella, and Megamonas were enriched in the pre-treatment subgroup, while Faecalibacterium and Anaerostipes were enriched in the control group. The relative abundance of Escherichia/Shigella, Streptococcus, Collinsella, and Megamonas was reduced significantly after a three-month treatment. Despite some genera remaining significantly different between the post-treatment subgroup and control group, the number of significantly different genera decreased from 9 to 4 through treatment. Notably, we found that the carbohydrate metabolism, especially succinate, was related to focal epilepsy.ConclusionChildren with focal epilepsy compared with healthy controls were associated with the statistically significant differences in the gut microbiota and carbohydrate metabolism. The differences were reduced and the carbohydrate metabolism improved after effective treatment. Our research may provide new directions for understanding the role of gut microbiota in the pathogenesis of focal epilepsy and better alternative treatments.

Graph neural networks (GNNs) have been widely used in various graph analysis tasks. As the graph characteristics vary significantly in real-world systems, given a specific scenario, the architecture parameters need to be tuned carefully to identify a suitable GNN. Neural architecture search (NAS) has shown its potential in discovering the effective architectures for the learning tasks in image and language modeling. However, the existing NAS algorithms cannot be applied efficiently to GNN search problem because of two facts. First, the large-step exploration in the traditional controller fails to learn the sensitive performance variations with slight architecture modifications in GNNs. Second, the search space is composed of heterogeneous GNNs, which prevents the direct adoption of parameter sharing among them to accelerate the search progress. To tackle the challenges, we propose an automated graph neural networks (AGNN) framework, which aims to find the optimal GNN architecture efficiently. Specifically, a reinforced conservative controller is designed to explore the architecture space with small steps. To accelerate the validation, a novel constrained parameter sharing strategy is presented to regularize the weight transferring among GNNs. It avoids training from scratch and saves the computation time. Experimental results on the benchmark datasets demonstrate that the architecture identified by AGNN achieves the best performance and search efficiency, comparing with existing human-invented models and the traditional search methods.

Grapes, an important and widespread fruit crop providing multiple products, face increasing flooding risks due to intense and frequent extreme rainfall. It is thus imperative to fully understand the flood-tolerance mechanisms of grapevines. Here, RNA-seq and LC-MS/MS technologies were used to analyze the transcriptome and metabolome changes in the roots of SO4 (tolerant to flooding) and Kyoho (sensitive to flooding) grapes under flooding and post-flooding conditions. The results showed that the abundance of many metabolites in the phenylpropanoids and polyketides, organic acids and their derivatives, and organic oxygen compounds superclasses changed in different patterns between the Kyoho and SO4 grapes under flooding and post-flooding conditions. Jasmonic acid and the ascorbic acid–glutathione cycle played a pivotal role in coping with both hypoxia stress and reoxygenation stress incurred during flooding and post-flooding treatments in the SO4 cultivar. Under flooding stress, the regulatory mechanistic shift from aerobic respiration to anaerobic fermentation under hypoxia is partly missing in the Kyoho cultivar. In the post-flooding stage, many genes related to ethylene, gibberellins, cytokinins, and brassinosteroids biosynthesis and brassinosteroids-responsive genes were significantly downregulated in the Kyoho cultivar, adversely affecting growth recovery; however, their expression was not reduced in the SO4 cultivar. These findings enhance our understanding of the flooding-tolerance mechanisms in grapes.

Abstract Background Dyschromatosis universalis hereditaria (DUH) is a pigmentary dermatosis characterized by generalized mottled macules with hypopigmention and hyperpigmention. ABCB6 and SASH1 are recently reported pathogenic genes related to DUH, and the aim of this study was to identify the causative mutations in a Chinese family with DUH. Methods Sanger sequencing was performed to investigate the clinical manifestation and molecular genetic basis of these familial cases of DUH, bioinformatics tools and multiple sequence alignment were used to analyse the pathogenicity of mutations. Results A novel missense mutation, c.1529G>A, in the SASH1 gene was identified, and this mutation was not found in the National Center for Biotechnology Information Database of Short Genetic Variation, Online Mendelian Inheritance in Man, ClinVar, or 1000 Genomes Project databases. All in silico predictors suggested that the observed substitution mutation was deleterious. Furthermore, multiple sequence alignment of SASH1 revealed that the p.S510N mutation was highly conserved during evolution. In addition, we reviewed the previously reported DUH-related gene mutations in SASH1 and ABCB6. Conclusion Although the affected family members had identical mutations, differences in the clinical manifestations of these family members were observed, which reveals the complexity of the phenotype-influencing factors in DUH. Our findings reveal the mutation responsible for DUH in this family and broaden the mutational spectrum of the SASH1 gene.

Different branching architectures reflect the adaptation strategies of different plants and affect their resistance to wind erosion. This study presents field-based observations that demonstrate the relationship between the branching architecture of Artemisia ordosica and its resistance to wind erosion. This species is the dominant plant species in the semi-fixed and fixed dunes of the Mu Us Sandy land. The overall bifurcation ratio (OBR) of semi-fixed sandy land is higher than the fixed sandy land 0.27; Similarly, the total stepwise bifurcation ratio (SBR) is higher than the fixed sandy land about 0.74; The length of first levels of total branches is also higher than 8.07. The aerodynamic roughness was greater than the A. ordosica community in the fixed and semi-fixed sandy land than in the bare sandy land. The airflow fields in the cross-wind direction were strongly affected by the windward shape of the plants, which became gradually narrower from the base to the top, while in the leeward direction, the wind speed at different heights behind the plant returned to the incoming airflow velocity. The result confirms that the influence of the windward shape of the plant on the surrounding airflow field is much larger than the influence of plant thickness, porosity or other factors.

Abstract Background Emotions after surviving cancer can be complicated. The survivors may have gained new strength to continue life, but some of them may begin to deal with complicated feelings and emotional stress due to trauma and fear of cancer recurrence. The widespread use of Twitter for socializing has been the alternative medium for data collection compared to traditional studies of mental health, which primarily depend on information taken from medical staff with their consent. These social media data, to a certain extent, reflect the users’ psychological state. However, Twitter also contains a mix of noisy and genuine tweets. The process of manually identifying genuine tweets is expensive and time-consuming. Methods We stream the data using cancer as a keyword to filter the tweets with cancer-free and use post-traumatic stress disorder (PTSD) related keywords to reduce the time spent on the annotation task. Convolutional Neural Network (CNN) learns the representations of the input to identify cancer survivors with PTSD. Results The results present that the proposed CNN can effectively identify cancer survivors with PTSD. The experiments on real-world datasets show that our model outperforms the baselines and correctly classifies the new tweets. Conclusions PTSD is one of the severe anxiety disorders that could affect individuals who are exposed to traumatic events, including cancer. Cancer survivors are at risk of short-term or long-term effects on physical and psycho-social well-being. Therefore, the evaluation and treatment of PTSD are essential parts of cancer survivorship care. It will act as an alarming system by detecting the PTSD presence based on users’ postings on Twitter.

Abstract Online social network has become a new form of infrastructure for communities in spreading situational information in disasters. Developing effective interventions to improve the network performance of information diffusion is essential for people to rapidly retrieve information in coping with disasters and subsequent disruptions. Existing studies have investigated multiple aspects of online social networks in stationary situations and a separate manner. However, the networks are dynamic and different properties of the networks are co-related in the evolving disaster situations. In particular, disaster events motivate people to communicate online, create and reinforce their connections, and lead to a dynamic reticulation of the online social networks. To understand the relationship among these elements, we proposed an Online Network Reticulation (ONR) framework to examine four modalities (i.e., enactment, activation, reticulation, and network performance) in the evolution of online social networks to analyze the interplays among disruptive events in disasters, user activities, and information diffusion performance on social media. Accordingly, we examine the temporal changes in four elements for characterization of reticulation: activity timing, activity types (post, share, reply), reticulation mechanism (creation of new links versus reinforcement of existing links), and structure of communication instances (self-loop, converging, and reciprocal). Finally, the aggregated effects of network reticulation, using attributed network-embedding approach, are examined in the average latent distance among users as a measure of network performance for information propagation. The application of the proposed framework is demonstrated in a study of network reticulation on Twitter for a built environment disruption event during 2017 Hurricane Harvey in Houston. The results show that the main underlying mechanism of network reticulation in evolving situations was the creation of new links by regular users. The main structure for communication instances was converging, indicating communication instances driven by information-seeking behaviors in the wake of a disruptive event. With the evolution of the network, the proportion of converging structures to self-loop and reciprocal structures did not change significantly, indicating the existence of a scale-invariance property for network structures. The findings demonstrate the capability of the proposed online network reticulation framework for characterizing the complex relationships between events, activities, and network performance in online social networks during disasters.

Abstract Background Monochamus alternatus Hope is one of the insect vectors of pinewood nematode (Bursaphelenchus xylophilus), which causes the destructive pine wilt disease. The microorganisms within the ecosystem, comprising plants, their environment, and insect vectors, form complex networks. This study presents a systematic analysis of the bacterial microbiota in the M. alternatus midgut and its habitat niche. Methods Total DNA was extracted from 20 types of samples (with three replicates each) from M. alternatus and various tissues of healthy and infected P. massoniana (pines). 16S rDNA amplicon sequencing was conducted to determine the composition and diversity of the bacterial microbiota in each sample. Moreover, the relative abundances of bacteria in the midgut of M. alternatus larvae were verified by counting the colony-forming units. Results Pinewood nematode infection increased the microbial diversity in pines. Bradyrhizobium, Burkholderia, Dyella, Mycobacterium, and Mucilaginibacter were the dominant bacterial genera in the soil and infected pines. These results indicate that the bacterial community in infected pines may be associated with the soil microbiota. Interestingly, the abundance of the genus Gryllotalpicola was highest in the bark of infected pines. The genus Cellulomonas was not found in the midgut of M. alternatus, but it peaked in the phloem of infected pines, followed by the phloem of heathy pines. Moreover, the genus Serratia was not only present in the habitat niche, but it was also enriched in the M. alternatus midgut. The colony-forming unit assays showed that the relative abundance of Serratia sp. peaked in the midgut of instar II larvae (81%). Conclusions Overall, the results indicate that the bacterial microbiota in the soil and in infected pines are correlated. The Gryllotalpicola sp. and Cellulomonas sp. are potential microbial markers of pine wilt disease. Additionally, Serratia sp. could be an ideal agent for expressing insecticidal protein in the insect midgut by genetic engineering, which represents a new use of microbes to control M. alternatus.

Backround: Leprosy is very prevalent in many populations around the world, which is well known that both alleles for human leukocyte antigen (HLA) as well as single nucleotide polymorphisms (SNPs) in the HLA region are common in leprosy patients. Previous studies have identified leprosy-associated susceptibility genes that explain only part of disease risk and heritability. In view of the complicated characteristics of the major histocompatibility complex (MHC) region, this study aimed to explore the development and variation of HLA in leprosy and its possible mechanism.Methods: Previous genome-wide association data were extracted from Han and minority populations in southern China for HLA fine-mapping studies. Insertion and deletion (INDEL), SNP, and copy number variation (CNV) imputation were determined by using the Thousand People Database (1KGP Phase 3 Dataset) as a reference panel. The HAN-MHC database was used to input the HLA classical alleles and amino acids in the MHC region, and further step-regression analysis was performed to analyze independent variation signals associated with leprosy.Results: The most significant locus rs75324027 (the same locus as rs602875 in the HLA-DR region) [p = 7.49E-09, OR= 0.62, 95%,CI: 0.52–0.73] in the intergene region between HLA-DQA1 and HLA-DRB1 was related with leprosy in M-S(Han leprosy patients in south China)disease. In M-SM (Leprosy patients of ethnic minorities in south China)disease, one of the most significant loci of the HLA-DQB1 gene was 6-32626438-A-T (p = 4.49E-08, OR = 0.36, 95%,CI: 0.25–0.52). Therefore, rs75324027 is a locus in M-S disease, and 6-32626438-a-T may be a new locus in M-SM disease. The interaction between 6 and 32626438-A-T and RS75324027 was analyzed, and A significant interaction relationship was found. In the optimal model, the accuracy of prediction was 0.5974, cross-validation Consistency:10, p = 0.0107.Conclusion: In conclusion, this study is the first to assess the association between HLA and leprosy susceptibility in Han and other minority populations in southern China using the Thousand Population database and the Han MHC database. In addition, our analysis validated the previously reported locus rs602875 in the HLA-DR region and for the first time identified an unreported independent locus in leprosy among ethnic minorities in southern China.

Objectives To separately examine and comprehensively compare the risk factors for hospital-acquired (HAPIs) and community-acquired pressure injuries (CAPIs).Design A mixed case–control study.Setting Four medical centres in China.Participants Inclusion criteria included patients who were (1) aged ≥18 years on admission; (2) admitted between January 2014 and December 2018, and (3) diagnosed with HAPIs (cases) or with no HAPIs (controls) during hospitalisation in the HAPIs study, and confirmed with CAPIs (cases) or with no PIs (controls) on admission in the CAPIs study. The exclusion criteria were as follows: (1) admitted for childbirth, psychiatric reasons or rehabilitation; (2) admitted for observation; (3) transferred from another hospital and (4) confirmed to have suffered PIs from previous hospitalisations in the CAPIs study. In total, 320 cases and 1657 controls were included in the HAPIs study, and 1763 cases and 1786 controls were included in the CAPIs study.Primary and secondary outcome measures The outcome variable was the occurrence of PIs.Results The existence of PIs or scars from previous PIs on admission, presence of forced posture, use of medical devices and surgery during hospitalisation were found to be independent risk factors for HAPIs, as evidenced by the corresponding OR and 95% CI values of 51.931 (34.241 to 78.763), 2.006 (1.405 to 2.864), 3.226 (1.709 to 6.089) and 2.161 (1.452 to 3.215), respectively. Age, sex, Braden rating and diabetes were found to be independent risk factors for CAPIs, as evidenced by the corresponding OR and 95% CI values of 1.031 (1.026 to 1.036), 0.810 (0.698 to 0.941), 1.235 (1.167 to 1.307) and 2.059 (1.332 to 3.184), respectively.Conclusions The existence of PIs or scars from previous PIs on admission, presence of forced posture, use of medical devices and surgery during hospitalisation are suggested to be included as independent items for the risk assessment of PIs, together with the Braden scale. The Braden rating plays different roles in the development of CAPIs and HAPIs.

Background: Invasive dental treatment in patients exposed to antiresorptive and antiangiogenic drugs can cause medication-related osteonecrosis of the jaw (MRONJ). Currently, the exact pathogenesis of this disease is unclear. Methods: In March 2022, Medline (Ovid), Embase (Ovid), Scopus, and Web of Science were screened to identify eligible in vitro studies investigating the effects of antiresorptive and antiangiogenic compounds on orally derived cells. Results: Fifty-nine articles met the inclusion criteria. Bisphosphonates were used in 57 studies, denosumab in two, and sunitinib and bevacizumab in one. Zoledronate was the most commonly used nitrogen-containing bisphosphonate. The only non-nitrogen-containing bisphosphonate studied was clodronate. The most frequently tested tissues were gingival fibroblasts, oral keratinocytes, and alveolar osteoblasts. These drugs caused a decrease in cell proliferation, viability, and migration. Conclusions: Antiresorptive and antiangiogenic drugs displayed cytotoxic effects in a dose and time-dependent manner. Additional research is required to further elucidate the pathways of MRONJ.

Alzheimer’s disease (AD) and AD-related dementias (AD/ADRD) are a group of progressive neurodegenerative diseases. The progression of AD can be conceptualized as a continuum in which patients progress from normal cognition to preclinical AD (i.e., no symptoms but biological changes in the brain) to mild cognitive impairment (MCI) due to AD (i.e., mild symptoms but not interfere with daily activities), followed by increasing severity of dementia due to AD. Early detection and prediction models for the transition of MCI to AD/ADRD are needed, and efforts have been made to build predictions of MCI conversion to AD/ADRD. However, most existing studies developing such prediction models did not consider the competing risks of death, which may result in biased risk estimates. In this study, we aim to develop a prediction model for AD/ADRD among patients with MCI considering the competing risks of death using a semi-competing risk approach.

Various coronaviruses have emerged as a result of cross-species transmission among humans and domestic animals. Porcine epidemic diarrhea virus (PEDV; family Coronaviridae, genus Alphacoronavirus) causes acute diarrhea, vomiting, dehydration, and high mortality in neonatal piglets. Porcine small intestinal epithelial cells (IPEC-J2 cells) can be used as target cells for PEDV infection. However, the origin of PEDV in pigs, the host range, and cross-species infection of PEDV remain unclear. To determine whether PEDV has the ability to infect human cells in vitro, human small intestinal epithelial cells (FHs 74 Int cells) were inoculated with PEDV LJX and PEDV CV777 strains. The results indicated that PEDV LJX, but not PEDV CV777, could infect FHs 74 Int cells. Furthermore, we observed M gene mRNA transcripts and N protein expression in infected FHs 74 Int cells. A one-step growth curve showed that the highest viral titer of PEDV occurred at 12 h post infection. Viral particles in vacuoles were observed in FHs 74 Int cells at 24 h post infection. The results proved that human small intestinal epithelial cells are susceptible to PEDV infection, suggesting the possibility of cross-species transmission of PEDV.

BackgroundMal de Meleda (MDM, OMIM 248300) is an autosomal recessive disease characterized by symmetrical and progressive palmoplantar hyperkeratosis soon after birth. Mutations in SLURP1 gene could lead to MDM. Clinically, MDM is easily misdiagnosed as other types of keratoderma due to phenotypic variation and overlap.Objective and MethodsA patient with suspected MDM was confirmed by the combination of next-generation sequencing and Exomiser, and the patient was attempted with the treatment of Ixekizumab and Adalimumab.ResultsA homozygous mutation c.256G>A (p.Gly86Arg) in the SLURP1 gene was identified in the patient. The inflammatory erythemas on his hands, feet and buttocks were mildly relieved after the treatment of high dose of Ixekizumab.ConclusionsOur findings helps to enhance the understanding of MDM. Ixekizumab may be a potential strategy to treat MDM.

Explainable machine learning attracts increasing attention as it improves the transparency of models, which is helpful for machine learning to be trusted in real applications. However, explanation methods have recently been demonstrated to be vulnerable to manipulation, where we can easily change a model's explanation while keeping its prediction constant. To tackle this problem, some efforts have been paid to use more stable explanation methods or to change model configurations. In this work, we tackle the problem from the training perspective, and propose a new training scheme called Adversarial Training on EXplanations (ATEX) to improve the internal explanation stability of a model regardless of the specific explanation method being applied. Instead of directly specifying explanation values over data instances, ATEX only puts constraints on model predictions which avoids involving second-order derivatives in optimization. As a further discussion, we also find that explanation stability is closely related to another property of the model, i.e., the risk of being exposed to adversarial attack. Through experiments, besides showing that ATEX improves model robustness against manipulation targeting explanation, it also brings additional benefits including smoothing explanations and improving the efficacy of adversarial training if applied to the model.

The important role of MHC in the pathogenesis of vitiligo and SLE has been confirmed in various populations. To map the most significant MHC variants associated with the risk of vitiligo and SLE, we conducted fine mapping analysis using 1117 vitiligo cases, 1046 SLE cases and 1693 healthy control subjects in the Han-MHC reference panel and 1000 Genomes Project phase 3. rs113465897 (P=1.03×10-13, OR=1.64, 95%CI =1.44–1.87) and rs3129898 (P=4.21×10-17, OR=1.93, 95%CI=1.66–2.25) were identified as being most strongly associated with vitiligo and SLE, respectively. Stepwise conditional analysis revealed additional independent signals at rs3130969(p=1.48×10-7, OR=0.69, 95%CI=0.60–0.79), HLA-DPB1*03:01 (p=1.07×10-6, OR=1.94, 95%CI=1.49–2.53) being linked to vitiligo and HLA-DQB1*0301 (P=4.53×10-7, OR=0.62, 95%CI=0.52-0.75) to SLE. Considering that epidemiological studies have confirmed comorbidities of vitiligo and SLE, we used the GCTA tool to analyse the genetic correlation between these two diseases in the HLA region, the correlation coefficient was 0.79 (P=5.99×10-10, SE=0.07), confirming their similar genetic backgrounds. Our findings highlight the value of the MHC region in vitiligo and SLE and provide a new perspective for comorbidities among autoimmune diseases.

The reduction of the cerebral glucose metabolism is closely related to the activation of the NOD-like receptor protein 3 (NLRP3) inflammasome in Alzheimer’s disease (AD); however, its underlying mechanism remains unclear. In this paper, 18F-flurodeoxyglucose positron emission tomography was used to trace cerebral glucose metabolism in vivo, along with Western blotting and immunofluorescence assays to examine the expression and distribution of associated proteins. Glucose and insulin tolerance tests were carried out to detect insulin resistance, and the Morris water maze was used to test the spatial learning and memory ability of the mice. The results show increased NLRP3 inflammasome activation, elevated insulin resistance, and decreased glucose metabolism in 3×Tg-AD mice. Inhibiting NLRP3 inflammasome activation using CY-09, a specific inhibitor for NLRP3, may restore cerebral glucose metabolism by increasing the expression and distribution of glucose transporters and enzymes and attenuating insulin resistance in AD mice. Moreover, CY-09 helps to improve AD pathology and relieve cognitive impairment in these mice. Although CY-09 has no significant effect on ferroptosis, it can effectively reduce fatty acid synthesis and lipid peroxidation. These findings provide new evidence for NLRP3 inflammasome as a therapeutic target for AD, suggesting that CY-09 may be a potential drug for the treatment of this disease.

The Bobbin tool friction stir welding (BT-FSW) process experiment was performed on 2219 aluminum alloy with different butt clearances and misalignments. The maximum allowable clearance and misalignment amount for BT-FSW were obtained, and the weld formation, mechanical properties and microstructure under different parameters were compared and analysed. The results show that the face and back sides of the weld joint surface are perfect and there are no defect inside with the butt clearance under 2 mm and the misalignment under 1.5 mm. During the increase of butt clearance and misalignment, the tensile strength of the weld will be decreased gradually. In comparison, the impact of misalignment on weld strength is lower than that of the butt clearance. The tensile strength from both of them will reach more than 60% of the base metal strength. The lowest hardness value occurs in the thermal-mechanical influence zone, which is 79.1HV, about 70% of the base metal hardness value. The microstructure characteristics are similar to those of conventional friction stir welding. The macroscopic morphology of the welded joint is typical ‘dumbbell type’, and there are many ‘dimples’ in the tensile fracture, which is a typical ductile fracture. A large number of dispersed phase particles (Al _2 Cu) were found in the dimples, which is the main reason for the decrease in mechanical strength and hardness compared with the substrate.

Background: Leprosy is a chronic infectious skin and neurological disease, and genetic background is considered to be one of the major factors of risk. The major histocompatibility complex (MHC) region not only affects susceptibility to leprosy but also its development and outcome. Given the complex traits of the MHC region, variants and the potential mechanism by which HLA influences leprosy development need to be further explored.Methods: We extracted previous genome-wide association study data from the Northern Han Chinese population to perform HLA fine-mapping. Using the 1,000 Genome Project Phase 3 dataset as the reference panel, single-nucleotide polymorphisms (SNP), insertion and deletion (INDEL) and copy number variant (CNV) imputation were carried out. HLA classical alleles and amino acids in the MHC region were imputed using the HAN-MHC database. Further stepwise regression analysis was conducted to analyze independent signals of variants related to leprosy.Results: We identified four independent variants: esv3608598, rs7754498, rs3130781 and rs144388449. Among them, esv3608598 is a CNV and the first HLA CNV associated with leprosy risk. SNP annotation using RegulomeDB, HaploReg, and rVarBase showed that three SNPs are likely to affect the pathogenesis of leprosy.Conclusion: In summary, this is the first study to assess the association between HLA CNV and leprosy susceptibility in a Northern Han Chinese population. By fine mapping of the MHC region in this population, our findings provide evidence for the contribution of HLA to leprosy susceptibility.