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The genus Thibetana Efetov & Tarmann, 1995 includes six species occurring in southwest China and Indian Sikkim. In the present paper, Thibetana weii Li & He, sp. nov., the seventh species of the genus encountered at the foot of Galongla Snow Mountain, southeast Xizang of China is described. Habitus of the adult and genitalia of the new species are illustrated, and a checklist and a key of all Thibetana species are provided.

The genus Agnostrup Foddai, Bonato, Pereira & Minelli, 2003 is one of the least known genera within the family Mecistocephalidae Bollman, 1893. In this study, we rediscovered the genus Agnostrup in China and provided a comprehensive redescription of A. striatus (Takakuwa, 1949). Additionally, we conducted a molecular phylogenetic analysis using CO1, 16S, and 28S sequence data, revealing a low genetic distance between Agnostrup and Nannarrup Foddai, Bonato, Pereira & Minelli, 2003. After comparing the morphological characteristics of these two genera, we synonymized the genus Nannarrup syn. nov. with Agnostrup. As a result, three species previously belonging to the genus Nannarrup were transferred to Agnostrup: A. hoffmani (Foddai et al., 2003), comb. nov., A. innuptus (Tsukamoto, 2022), comb. nov., and A. oyamensis (Tsukamoto, 2022), comb. nov.

Mecistocephalus Newport, 1843 is the most diverse genus in the family Mecistocephalidae; however, only two species have been recorded in mainland China to date. Therefore, taxonomic research on Chinese Mecistocephalus needs further research. In this study, the species diversity of Mecistocephalus in southern China was investigated using the mitochondrial marker COI integrated with morphological evidence. Species delimitation using Automatic Barcode Gap Discovery, Poisson Tree Processes, and phylogenetic and morphological analyses revealed ten species, including two newly described species, M. chuensis Jiang & You, sp. nov. and M. huangi Jiang & You, sp. nov. Furthermore, based on newly collected specimens, the presence of the little-known species M. smithii Pocock, 1895 was confirmed in China and thoroughly re-described.

Abstract Background Targeting the STAT3 signaling pathway is a promising therapeutic approach for cancer patients. However, the association between STAT3 expression, the tumor immune microenvironment, and genetic variation remains unclear across human cancers, especially prostate cancer. Methods We used R software and other tools to analyze pan-cancer and mutation data from publicly available databases statistically. A comprehensive investigation was performed to assess the genetic heterogeneity and clinical relevance of STAT3 in various malignancies, with a specific focus on its role in the immune landscape and prognostic significance in prostate cancer. The findings were validated through immunohistochemistry (IHC) and multiplex immunofluorescence (mIF). Results STAT3 expression is abnormal in the majority of cancer tissues, which is strongly correlated with these patients' prognosis. Eight measures of tumor heterogeneity and six measures of tumor stemness of multiple tumor types showed a strong correlation with STAT3 expression. Furthermore, in individuals with prostate cancer, STAT3 expression indicated the degree of immune cell infiltration and the advancement of the disease. IHC analysis revealed that STAT3 was down-regulated in prostate tumor tissues, while mIF analysis demonstrated that STAT3 signaling (p-STAT3) was extensively active in tumor tissues and positive lymph node tissues. Conclusion STAT3 may serve as a valuable prognostic biomarker and therapeutic target across various cancers, with particular relevance to prostate cancer.

Abstract The effect of serum glucose-to-potassium ratio (GPR) on cerebrovascular diseases has been previously validated. However, the value of the GPR in patients with severe intracerebral hemorrhage (ICH) requiring ICU admission remains unclear. This study aimed to investigate the association between the GPR and the clinical prognosis of critically ill patients with ICH. This study identified patients with severe ICH requiring ICU admission from the Medical Information Mart for Intensive Care (MIMIC-IV) database and divided them into quartiles based on GPR levels. Outcomes included 30-day, 90-day, and 1-year mortality rates. The association between the GPR and clinical outcomes in critically ill patients with ICH was elucidated using Cox proportional hazards regression analysis and restricted cubic splines. In total, 2018 patients (53.8% male), with a median age of 70 years, were enrolled in the study. The 30-day, 90-day, and 1-year mortality rates were 23.9%, 30.1%, and 38.4%, respectively. Per multivariate Cox proportional hazards analysis, an elevated GPR was significantly associated with all-cause mortality. After adjusting for age, sex, Charlson Comorbidity Index, white blood cell count, red blood cell count, platelet count, and Glasgow Coma Scale, patients with an elevated GPR had a higher 30-day mortality (hazard ratio [HR]: 1.32; 95% confidence interval [CI]: 1.22–1.42; P

Abstract Background Manual placement of cervical pedicle screws is risky, and robot-assisted placement of atlantoaxial pedicle screws has not been reported. Case report We describe a 74-year-old female patient with atlantoaxial fracture and dislocation combined with spinal cord injury caused by a car accident. The left lower limb muscle strength was grade 0, the right upper limb muscle strength was grade 1, and the right lower limb muscle strength was grade 2. Loss of sensation below the clavicle level, decreased superficial sensation in the extremities, loss of deep sensation in the left lower extremity, and incontinence were observed. We successfully placed atlas pedicle screws with the assistance of the Mazor X robot. One week after the operation, radiological imaging revealed that the reduction effect was good, the placement of the pedicle screws was satisfactory, the left upper limb and left lower limb muscle strength was level 2, the right upper limb and the muscle strength of the right lower limb were grade 3, and the sensory function was partially restored. No complications related to screw placement were found at the 3-month postoperative follow-up. Conclusions Mazor X robot-assisted descending pedicle screw fixation of the atlas is feasible and safe.

Abstract Background Concerns have been raised regarding changes in lipid profiles among patients with chronic hepatitis B (CHB) during tenofovir alafenamide fumarate (TAF) treatment. We aimed to evaluate the effect of TAF treatment on the lipid profiles of patients with CHB. Methods A total of 430 patients with CHB from three hospitals were retrospectively included, including 158 patients treated with TAF and 272 patients treated with tenofovir disoproxil fumarate (TDF). Results In this multicenter cohort, the cumulative incidence of dyslipidemia was notably higher in the TAF group than in the TDF group (P

Abstract The lower respiratory tract (LRT) microbiome impacts human health, especially among critically ill patients. However, comprehensive characterizations of the LRT microbiome remain challenging due to low microbial mass and host contamination. We develop a chelex100-based low-biomass microbial-enrichment method (CMEM) that enables deep metagenomic profiling of LRT samples to recover near-complete microbial genomes. We apply the method to 453 longitudinal LRT samples from 157 intensive care unit (ICU) patients in three geographically distant hospitals. We recover 120 high-quality metagenome-assembled genomes (MAGs) and associated plasmids without culturing. We detect divergent longitudinal microbiome dynamics and hospital-specific dominant opportunistic pathogens and resistomes in pneumonia patients. Diagnosed pneumonia and the ICU stay duration were associated with the abundance of specific antibiotic-resistance genes (ARGs). Moreover, CMEM can serve as a robust tool for genome-resolved analyses. MAG-based analyses reveal strain-specific resistome and virulome among opportunistic pathogen strains. Evolutionary analyses discover increased mobilome in prevailing opportunistic pathogens, highly conserved plasmids, and new recombination hotspots associated with conjugative elements and prophages. Integrative analysis with epidemiological data reveals frequent putative inter-patient strain transmissions in ICUs. In summary, we present a genome-resolved functional, transmission, and evolutionary landscape of the LRT microbiota in critically ill patients.

Abstract Although the relationship between hypertension and hyperuricemia is widely recognized, there is still a relative lack of research on prehypertensive individuals and the individual associations of systolic and diastolic blood pressure with the risk of hyperuricemia. From 2011 to 2016, we conducted a study on 53,323 individuals at Wuhu City Hospital in China. Based on initial blood pressure readings, participants were categorized into normal, prehypertension, or hypertension groups. We used Cox regression to analyze the associations with baseline factors. In subgroup analyses, systolic and diastolic pressures were treated as continuous variables, and their relationship with the risk of hyperuricemia was examined using restricted cubic spline analysis. The risk increased in the prehypertension and hypertension groups compared to the normal blood pressure group, with hazard ratios of 1.192 and 1.350, respectively. For each unit increase in blood pressure, the risk of hyperuricemia rose by 0.8% (systolic) and 0.9% (diastolic), especially when blood pressure levels exceeded 115/78 mmHg. Additionally, we observed that factors such as gender, alcohol consumption habits, obesity, and dyslipidemia might further influence this association. These findings emphasize the importance of early risk assessment and intervention in these patient populations in clinical practice.

Abstract Fatigue failure is invariably the most crucial failure mode for metallic structural components. Most microstructural strategies for enhancing fatigue resistance are effective in suppressing either crack initiation or propagation, but often do not work for both synergistically. Here, we demonstrate that this challenge can be overcome by architecting a gradient structure featuring a surface layer of nacre-like nanolaminates followed by multi-variant twinned structure in pure titanium. The polarized accommodation of highly regulated grain boundaries in the nanolaminated layer to cyclic loading enhances the structural stability against lamellar thickening and microstructure softening, thereby delaying surface roughening and thus crack nucleation. The decohesion of the nanolaminated grains along horizonal high-angle grain boundaries gives rise to an extraordinarily high frequency (≈1.7 × 103 times per mm) of fatigue crack deflection, effectively reducing fatigue crack propagation rate (by 2 orders of magnitude lower than the homogeneous coarse-grained counterpart). These intriguing features of the surface nanolaminates, along with the various toughening mechanisms activated in the subsurface twinned structure, result in a fatigue resistance that significantly exceeds those of the homogeneous and gradient structures with equiaxed grains. Our work on architecting the surface nanolaminates in gradient structure provides a scalable and sustainable strategy for designing more fatigue-resistant alloys.

Abstract Hydrocracking represents a complex and time-consuming chemical process that converts heavy oil fractions into various valuable products with low boiling points. It plays a pivotal role in enhancing the quality of products within the oil refining process. Consequently, the development of efficient surrogate models for simulating the hydrocracking process and identifying appropriate solutions for multi-objective oil refining is now an important area of research. In this study, a novel transferable preference learning-driven evolutionary algorithm is proposed to facilitate multi-objective decision analysis in the oil refining process. Specifically, our approach involves considering user preferences to divide the objective space into a region of interest (ROI) and other subspaces. We then utilize Kriging models to approximate the sub-problems within the ROI. In order to enhance the robustness and generalization capability of the Kriging models during the evolutionary process, we transfer the mutual information between the sub-problems in the ROI. To validate the effectiveness as well as efficiency of our proposed method, we undertake a series of experiments on both benchmarks and the oil refining process. The experimental results conclusively demonstrate the superiority of our approach.

The genus Lucasioides Kwon, 1993 (Isopoda: Oniscidea: Agnaridae) occurs in Asia, but confined only to China, Japan, Korea, and Russian Siberia. The ambiguously morphological differences among some members of the genus make a dilemma: the species recognition, whether morphologically similar or different, is uncertain. In this paper, we present first morphometric and molecular data for the genus from a broad sample. DNA sequences (mitochondrial COI, nuclear 18S rRNA, 28S rRNA, and NaK) were generated and integrated with morphological evidence to reveal the cryptic species and delimit the new species within the genus. Seven species are described as new to science: Lucasioides digitatus sp. nov., L. dissectus sp. nov., L. dianensis sp. nov., L. formosus sp. nov., L. gracilentus sp. nov., L. schmidti sp. nov. and L. subcurvatus sp. nov. To date, Lucasioides species from China are 44.4% as many as all the known congeners worldwide, showing the exceptional species diversity of Lucasioides species from China. The results demonstrate that the integrative taxonomy is especially important to reveal the cryptic species among the high morphological similarity of taxa, as well as providing an effective way for species identification to accelerate the exploration of woodlice biodiversity.

During the highway construction in the soft loess region of Northwestern China, there are always tens of thousands of cement mixing piles were used. Which generates a large amount of carbon emissions, thereby affecting the environment. The Simplified Energy and Emissions Assessment Model (SEEAM) is used to quantify carbon emissions considering monitoring data of IoT (Internet-of-Things) system. To reduce the error of the carbon emissions of large samples, Monte Carlo simulation was used to quantify carbon emissions based on the small samples. The results showed that cement had a 47,530.78 t carbon missions contributing the 95.64 % of the total carbon emissions. To concurrently ensure strength and reduce carbon emissions, this study investigates the unconfined compressive strength variations in white mud-cement composite material solidified soft loess. It indicated that 10 % and 20 % white mud provided an alkaline environment and nucleation sites for cement hydration reactions, combining the filling voids. According to the observation results of TG and SEM, the content of 10 % white mud increased the quantity of early hydration product CSH in cement. Which maintained a high level of strength by comparing the cement solidified soft loess. In addition, when the white mud content is 50 %, the white mud-cement composite material reduced 576 % carbon emissions in the cement mixing pile engineering. This study can provide guidance for the selection of engineering construction design schemes, as low-carbon emission schemes are conducive to green and sustainable development of the environment.

ABSTRACTSerum hepatitis B surface antigen (HBsAg) level < 100 IU/ml and undetectable hepatitis B virus (HBV) DNA have been recently proposed as an alternate endpoint of “partial cure” in chronic hepatitis B (CHB). We investigated clinical outcomes of hepatitis B e antigen (HBeAg)-negative CHB patients with HBsAg

BackgroundIn China, Atractylodes-containing Chinese medicines are widely used as adjuvant therapy to neoadjuvant chemotherapy (NAC) in individuals diagnosed with advanced gastric cancer (AGC). Nevertheless, the findings concerning its effectiveness are still restricted. The aim from this research was to examine the efficiency and security Atractylodes macrocephala-containing traditional Chinese medicine together with NAC in the management of AGC.MethodsLiterature was systematically searched across 8 electronic databases until September 20, 2023. Two researchers conducted a thorough review of the selected studies. The primary outcome measures included the objective response rate (ORR), disease control rate (DCR), quality of life (QOL), adverse drug reactions (ADRs), and levels of peripheral blood lymphocytes. The relevant effect estimates are as follows as risk ratios (RR) or mean differences (MD) with corresponding 95% confidence intervals (CI). Credibility of information was evaluated using the GRADE analyzer.ResultsThe results showed that solely on the basis of the accessible literature examined in NAC patients, individuals who received the therapeutic regimen containing Atractylodis Macrocephalae Chinese herbal preparations demonstrated a superior overall response rate (Relative Risk: 1.41, 95% confidence interval: 1.27-1.57, P < 0.001); DCR (RR: 1.20, 95% confidence interval: 1.13-1.27, P < 0.001), as compared to QOL (RR: 1.43, 95% confidence interval: 1.30-1.57, P < 0.001, MD: 8.47, 95% confidence interval: 7.16 - 9.77, P < 0.001); the proportions of CD3+ T-cells, CD4+ T-cells, CD8+ T-cells, CD4+CD8+ T-cells were increased; and the incidence of adverse reactions was decreased. Subgroup analyses showed that oral administration of all the traditional Chinese medicines containing Atractylodes macrocephala could improve tumor efficacy. Regardless of the duration of therapy of ≥8 weeks or

Abstract Background Triple-negative breast cancer (TNBC) is recognized as the most aggressive and immunologically infiltrated subtype of breast cancer. A high circulating neutrophil-to-lymphocyte ratio (NLR) is strongly linked to a poor prognosis among patients with breast cancer, emphasizing the critical role of neutrophils. Although the involvement of neutrophils in tumor metastasis is well documented, their interactions with primary tumors and tumor cells are not yet fully understood. Methods Clinical data were analyzed to investigate the role of neutrophils in breast cancer. In vivo mouse model and in vitro co-culture system were used for mechanism researches. Blocking experiments were further performed to identify therapeutic agents against TNBC. Results TNBC cells secreted GM-CSF to sustain the survival of mature neutrophils and upregulated CD11b expression. Through CD11b, neutrophils specifically binded to ICAM1 on TNBC cells, facilitating adhesion. Transcriptomic sequencing combined with human and murine functional experiments revealed that neutrophils, through direct CD11b-ICAM1 interactions, activated the MAPK signaling pathway in TNBC cells, thereby enhancing tumor cell invasion and migration. Atorvastatin effectively inhibited ICAM1 expression in tumor cells, and tumor cells with ICAM1 knockout or treated with atorvastatin were unresponsive to neutrophil activation. The MAPK pathway and MMP9 expression were significantly inhibited in the tumor tissues of TNBC patients treated with atorvastatin. Conclusions Targeting CD11b-ICAM1 with atorvastatin represented a potential clinical approach to reduce the malignant characteristics of TNBC. Graphical Abstract

Abstract Numerous clinical studies speculated the association between multiple myeloma (MM) and inflammatory diseases; however, there is limited validation of these claims via establishing a causal relationship and revealing the underlying mechanism. This exploratory study employed bidirectional Mendelian randomization (MR) analysis to investigate the causal relationships between MM and inflammatory diseases, including atherosclerosis, asthma, ankylosing spondylitis, Alzheimer's disease (AD), Parkinson's disease (PD), sarcoidosis, inflammatory bowel disease, nonalcoholic fatty liver disease, type II diabetes, and schizophrenia (SZ). Transcriptomic and genome‐wide Bayesian colocalization analyses were further applied to reveal the underlying mechanism. A significant and previously unrecognized positive association was identified between genetic predisposition to MM and the risk of SZ. Two independent case reports showed that treatment‐resistant psychosis is due to underlying MM and is resolved by treating MM. From our MR analyses, various statistical methods confirmed this association without detecting heterogeneity or pleiotropy effects. Transcriptomic analysis revealed shared inflammation‐relevant pathways in MM and SZ patients, suggesting inflammation as a potential pathophysiological mediator of MM's causal effect on SZ. Bayesian colocalization analysis identified rs9273086, which maps to the protein‐coding region of HLA‐DRB1, as a common risk variant for both MM and SZ. Polymorphism of the HLA‐DRB1 allele has been implicated in AD and PD, further highlighting the impact of our results. Additionally, we confirmed that interleukin‐6 (IL‐6) is a risk factor for SZ through secondary MR, reinforcing the role of neuroinflammation in SZ etiology. Overall, our findings showed that genetic predisposition to MM, HLA‐DRB1 polymorphism, and enhanced IL‐6 signaling are associated with the increased risk of SZ, providing evidence for a causal role for neuroinflammation in SZ etiology.

Abstract Background The association of hepatitis B virus (HBV) DNA levels and liver fibrosis in chronic hepatitis B (CHB) patients with immune-tolerant phase remains unclear. We explored the association between liver fibrosis and HBV DNA levels in HBeAg-positive CHB patients with normal alanine transaminase (ALT) with relatively high HBV DNA. Methods Six hundred and twenty-two HBeAg-positive CHB patients with normal ALT were included. Patients were divided into three categories: low (6 log10 IU/mL ≤ HBV DNA

Objective: Intracerebral hemorrhage (ICH) is a severe stroke that can adversely affect patient outcomes due to the accompanying inflammatory response. As a result, there is a growing interest in studying inflammation in ICH. We systematically reviewed relevant articles using the Web of Science to understand the literature on this subject. This study aims to provide a comprehensive overview of the field through bibliometric analysis, highlight its current status, identify frontiers, and speculate on future directions. Methods: We conducted a bibliometric analysis of the global English literature on inflammation related to ICH research based on the Web of Science from 1993 to the present to address publication trends and research hotspots. Results: A total of 885 publications were included from 1993 to 2023. These articles were authored by 7375 researchers from 1639 organizations in 68 countries and published in 571 journals. Collectively, they cited 48,980 references from 5621 journals. The author who published the most articles was Dr. Zhang, John H. Interestingly, 6 of the top ten most published authors were from China. Regarding the countries that published the most articles, China was at the top of the list, followed by the United States. The most frequently used keywords were “Inflammation”, “Neuroinflammation”, and “Microglia”. Regarding journal publication and reference citations, Stroke was the most published and cited journal. Conclusions: Over the past 30 years, there has been considerable progress in scientific research concerning inflammation in the context of ICH. The pivotal themes of these studies have been immune cells and inflammatory mediators. It is worth noting, however, that most of the published literature on inflammation in ICH pertains to preclinical studies, with comparatively fewer clinical investigations. Several challenges must be addressed to translate these promising research achievements into clinical practice.

In this paper, we consider a fractional Nernst-Planck-Poisson-Navier-Stokes system in $ \mathbb{R}^{3} $. First, we obtain a priori estimates by using energy estimates. Then, we construct an iterative solution sequence by solving the approximate problem and obtaining the local existence and uniqueness of the classical solution. Finally, combining the local existence with a priori estimates, the global existence and uniqueness of the classical solution with small initial data are obtained.

A combination of morphological traits and DNA data (COI and 28S rRNA partial sequences) was used to study the genus Mongoloniscus Verhoeff, 1930 from China. Four new species are described: M. crenatus Jiang, Li & Huang, sp. nov., M. orientalis Jiang, Li & Huang, sp. nov., M. polyacanthum Jiang, Li & Huang, sp. nov., and M. parvus Jiang, Li & Huang, sp. nov. Following an in-depth examination of the Mongoloniscus species, Lucasioides vannamei (Arcangeli, 1927), comb. nov. (from Mongoloniscus) is proposed, and M. chevronus Yang & An, 2021, syn. nov. is synonymized with Koreoniscus racovitzai (Arcangeli, 1927). A restrictive criterion for recognizing the genus Mongoloniscus is also provided in the present study.

Exalloniscus Stebbing, 1911 is investigated from China, and eleven species of the genus are now recorded from China. Five of them are described as new: E. duospinatus Li & Jiang, sp. nov., E. curvispinatus Li & Jiang, sp. nov., E. triangulus Li & Jiang, sp. nov., E. tridentatus Li & Jiang, sp. nov. and E. taitii Li & Jiang, sp. nov. A map of China showing the recorded localities of Exalloniscus members is provided.

Abstract Aims Relationship between body mass index (BMI), frailty, and clinical adverse events remains unclear in patients with heart failure (HF) with preserved ejection fraction (HFpEF) in different patient populations. We aimed to compare the association of BMI, frailty, and clinical adverse events between a US cohort from the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT) study and a Chinese cohort from the Heart Failure Registry of Patient Outcomes (HERO) study. Methods and results We used data of 1715 participants enrolled from America in the TOPCAT study and 1487 patients with HFpEF in the Chinese registry study, the HERO. We evaluated the relationship between BMI and frailty using multivariate restricted cubic spline logistic regression. Association between frailty and BMI categories and primary outcomes including HF hospitalization, aborted sudden death, and cardiovascular death, all‐cause mortality, and HF hospitalization were analysed by Cox proportional hazards models. The patients' mean age was 72 ± 11 years for both study populations, with 50% and 46% female for the TOPCAT study and the HERO study, respectively. Patients in the TOPCAT study had a higher mean BMI (33.9 vs. 24 kg/m2), with 72.3% vs. 52.9% defined as moderately to severely frail (frailty index > 0.3). In the TOPCAT study, risk of frailty rose as BMI increased, but not in the HERO study. Patients with frailty were at significant higher risk for the primary composite outcomes [hazard ratio (HR) 1.84 (95% confidence interval: 1.46–2.32)], all‐cause mortality [HR 1.73 (1.34–2.25)], and HF hospitalization [HR 1.83 (1.40–2.40)] in the TOPCAT study. The corresponding numbers in the HERO study were 1.26 (1.01–1.57), 2.21 (1.45–3.35), and 1.15 (0.81–1.37), respectively. The association of frailty with clinical outcomes did not vary with BMI categories in the two studies. Conclusions BMI distribution and association between BMI and frailty risk were different between the two study populations. Frailty was associated with clinical adverse events and this association was consistent across different BMI categories in both studies.

BackgroundDue to the rising standard of living and advances in public health and medical care in recent years in China, the health-related quality of life (HRQoL) has been increasingly acknowledged as an important part of health management of adults. This study aimed to analyze the HRQoL of Chinese adults and identify the influencing factors, proposing specific recommendations for improvement.MethodsA cross-sectional study was conducted among 1,291 selected adults from four provinces spanning different regions in China aged ≥18 years from July 2021 and January 2022. The EuroQol-5D-5L (EQ-5D-5L) was used to conduct the HRQoL survey, and a general questionnaire was administered to collect demographic characteristics, general information, and health behaviors of participants. The health utility value was measured, and one-way analysis of variance was performed. The Tobit regression model was employed to analyze the factors influencing the HRQoL of Chinese adults.ResultsThe mean health utility values and visual analog scale scores for adults were 0.9400 ± 0.1197 and 84.09 ± 14.392, respectively. Notably, 60.3% of respondents reported no difficulties in any of the five dimensions of EQ-5D. However, a substantial proportion faced challenges in anxiety/depression (27%) and pain/discomfort (26.2%). Tobit regression model revealed that age, marital status, educational level, diet, sleep, mental state, mood, and chronic diseases significantly impact the HRQoL of Chinese adults.ConclusionThe HRQoL among Chinese adults is generally satisfactory, but pay particular attention on areas such as pain, psychological anxiety, chronic diseases, and negative emotions is needed. The factors such as stress associated with marriage and the demands of high-skilled occupations might influence the overall health of the population. According to our findings, public health strategies to improve HRQoL should be developed to promote relatively healthy environments and lifestyles for older adults. Moreover, proactive measures are crucial for mitigating the potential health impacts associated with marital stress and high-skilled employment.

Tigecycline is a last-resort drug used to treat serious infections caused by multidrug-resistant bacteria. tet(X4) is a recently discovered plasmid-mediated tigecycline resistance gene that confers high-level resistance to tigecycline and other tetracyclines. Since the first discovery of tet(X4) in 2019, it has spread rapidly worldwide, and as a consequence, tigecycline has become increasingly ineffective in the clinical treatment of multidrug-resistant infections. In this study, we identified and analyzed tet(X4)-positive Escherichia coli isolates from duck farms in Hunan Province, China. In total, 976 samples were collected from nine duck farms. Antimicrobial susceptibility testing and whole-genome sequencing (WGS) were performed to establish the phenotypes and genotypes of tet(X4)-positive isolates. In addition, the genomic characteristics and transferability of tet(X4) were determined based on bioinformatics analysis and conjugation. We accordingly detected an E. coli strain harboring tet(X4) and seven other resistance genes in duck feces. Multi-locus sequence typing analysis revealed that this isolate belonged to a new clone, and subsequent genetic analysis indicated that tet(X4) was carried in a 4608-bp circular intermediate, flanked by ISVsa3-ORF2-abh elements. Moreover, it exhibited transferability to E. coli C600 with a frequency of 10-5. The detection of tet(X4)-harboring E, coli strains on duck farms enhances our understanding of tigecycline resistance dynamics. The transferable nature of the circular intermediate of tet(X4) contributing to the spread of tigecycline resistance genes poses a substantial threat to healthcare. Consequently, vigilant monitoring and proactive measures are necessary to prevent their spread.

This study explored 1-year follow-up of Parmaco-invasive strategy with half-dose recombinant human prourokinase (PHDP) in patients with acute ST-segment elevation myocardial infarction (STEMI). The follow-up endpoints were major adverse cardiovascular events (MACEs) occurring within 30 days and 1 year, as well as postoperative bleeding events. The study ultimately included 150 subjects, with 75 in the primary percutaneous coronary intervention (PPCI) group and 75 in the PHDP group. This study found that the PHDP group had a shorter FMC-reperfusion time (42.00 min vs 96.00 min, P 0.05). The PHDP facilitates early treatment of infarct-related vessels, shortens FMC-reperfusion time, and does not increase the risk of MACEs.

This review offered a comprehensive analysis of tendon and ligament injuries, emphasizing the crucial role of tendon-derived stem cells (TDSCs) in tissue engineering as a potential solution for these challenging medical conditions. Tendon and ligament injuries, prevalent among athletes, the elderly, and laborers, often result in long-term disability and reduced quality of life due to the poor intrinsic healing capacity of these avascular structures. The formation of biomechanically inferior scar tissue and a high rate of reinjury underscore the need for innovative approaches to enhance and guide the regenerative process. This review delved into the complexities of tendon and ligament structure and function, types of injuries and their impacts, and the limitations of the natural repair process. It particularly focused on the role of TDSCs within the context of tissue engineering. TDSCs, with their ability to differentiate into tenocytes, are explored in various applications, including biocompatible scaffolds for cell tracking, co-culture systems to optimize tendon-bone healing, and graft healing techniques. The review also addressed the challenges of immunoreactivity post-transplantation, the importance of pre-treating TDSCs, and the potential of hydrogels and decellularized matrices in supporting tendon regeneration. It concluded by highlighting the essential roles of mechanical and molecular stimuli in TDSC differentiation and the current challenges in the field, paving the way for future research directions.

Modern power systems are gradually evolving into low-inertia systems due to the integration of high penetration of renewable energy and power electronic equipment. For the natural inertia on the rotor, doubly-fed induction generator (DFIG) based wind farms are expected to provide inertia support for systems. The paper proposed an analytical model of DFIG with df/dt inertia control for studying frequency dynamics, and investigates the optimal design of virtual inertia from wind farms, as well as its equivalent inertia contribution to system. The inertia response differences between DFIG and synchronous generator (SG) are discussed and analyzed for the first time, and then to accurately describe the frequency response with low cost, an analytical model of DFIG with inertia control is developed considering wind turbine aerodynamic characteristics. The explicit expression of virtual inertia provided by DFIG is derived according to the kinetic energy equilibrium, and the key factors that dominate the magnitude of virtual inertia are illustrated. Based on the system frequency response model including wind farms, taking the system frequency nadir (SFN) and the time of reaching nadir (ToN) as targets, a multi-objective optimal configuration model of virtual inertia is constructed and solved through MOPSO. The time domain simulations of a generic two machine four bus system and modified IEEE 9-bus test system are both performed in MATLAB/Simulink, the accuracy and efficiency of our proposed DFIG model on system frequency dynamics research are demonstrated, the pareto frontiers of virtual inertia configuration under different working conditions are optimized and analyzed as well as the impacts of different parameters on inertia evaluation.

Bacterial exonuclease III (ExoIII), widely acknowledged for specifically targeting double-stranded DNA (dsDNA), has been documented as a DNA repair-associated nuclease with apurinic/apyrimidinic (AP)-endonuclease and 3′→5′ exonuclease activities. Due to these enzymatic properties, ExoIII has been broadly applied in molecular biosensors. Here, we demonstrate that ExoIII (Escherichia coli) possesses highly active enzymatic activities on ssDNA. By using a range of ssDNA fluorescence-quenching reporters and fluorophore-labeled probes coupled with mass spectrometry analysis, we found ExoIII cleaved the ssDNA at 5′-bond of phosphodiester from 3′ to 5′ end by both exonuclease and endonuclease activities. Additional point mutation analysis identified the critical residues for the ssDNase action of ExoIII and suggested the activity shared the same active center with the dsDNA-targeted activities of ExoIII. Notably, ExoIII could also digest the dsDNA structures containing 3′-end ssDNA. Considering most ExoIII-assisted molecular biosensors require the involvement of single-stranded DNA (ssDNA) or nucleic acid aptamer containing ssDNA, the activity will lead to low efficiency or false positive outcome. Our study revealed the multi-enzymatic activity and the underlying molecular mechanism of ExoIII on ssDNA, illuminating novel insights for understanding its biological roles in DNA repair and the rational design of ExoIII-ssDNA involved diagnostics.

Abstract Since the impressive superior performance demonstrated by deep learning methods is widely used in histopathological image analysis and diagnosis, existing work cannot fully extract the information in the breast cancer images due to the limited high resolution of histopathological images. In this study, we construct a novel intermediate layer structure that fully extracts feature information and name it DMBANet, which can extract as much feature information as possible from the input image by up-dimensioning the intermediate convolutional layers to improve the performance of the network. Furthermore, we employ the depth-separable convolution method on the Spindle Structure by decoupling the intermediate convolutional layers and convolving them separately, to significantly reduce the number of parameters and computation of the Spindle Structure and improve the overall network operation speed. We also design the Spindle Structure as a multi-branch model and add different attention mechanisms to different branches. Spindle Structure can effectively improve the performance of the network, the branches with added attention can extract richer and more focused feature information, and the branch with residual connections can minimize the degradation phenomenon in our network and speed up network optimization. The comprehensive experiment shows the superior performance of DMBANet compared to the state-of-the-art method, achieving about 98% classification accuracy, which is better than existing methods. The code is available at https://github.com/Nagi-Dr/DMBANet-main .

Abstract Background Immunotherapy has significantly improved survival of esophageal squamous cell cancer (ESCC) patients, however the clinical benefit was limited to only a small portion of patients. This study aimed to perform a deep learning signature based on H&E-stained pathological specimens to accurately predict the clinical benefit of PD-1 inhibitors in ESCC patients. Methods ESCC patients receiving PD-1 inhibitors from Shandong Cancer Hospital were included. WSI images of H&E-stained histological specimens of included patients were collected, and randomly divided into training (70%) and validation (30%) sets. The labels of images were defined by the progression-free survival (PFS) with the interval of 4 months. The pretrained ViT model was used for patch-level model training, and all patches were projected into probabilities after linear classifier. Then the most predictive patches were passed to RNN for final patient-level prediction to construct ESCC-pathomics signature (ESCC-PS). Accuracy rate and survival analysis were performed to evaluate the performance of ViT-RNN survival model in validation cohort. Results 163 ESCC patients receiving PD-1 inhibitors were included for model training. There were 486,188 patches of 1024*1024 pixels from 324 WSI images of H&E-stained histological specimens after image pre-processing. There were 120 patients with 227 images in training cohort and 43 patients with 97 images in validation cohort, with balanced baseline characteristics between two groups. The ESCC-PS achieved an accuracy of 84.5% in the validation cohort, and could distinguish patients into three risk groups with the median PFS of 2.6, 4.5 and 12.9 months (P

Partial discharge (PD) is the main cause of insulation breakdown in high voltage electrical equipment, which poses a potential threat to the safety and reliability of equipment. Traditional PD detection methods have limitations in liquid insulation systems. In this paper, an interferometric method for detecting PD in liquid is proposed. Through the experimental platform based on the Michelson interference method, the PD in the water sample is excited by the voltage applied by the lightning surge generator, and the interference fringes distorted are collected by the CCD camera. The experimental results show that the peak value of the phase distribution recovered from interferogram increases when the voltage increases. In addition, when the liquid contains particles that degrade the insulation properties, the effect on the insulation properties can be judged according to the interferometry. This study verifies the feasibility and effectiveness of PD detection in liquid based on Michelson interferometry, and provides a new idea for condition monitoring and fault diagnosis of liquid insulation system.

X-ray is a commonly used imaging method for the diagnosis and evaluation of osteoporosis, which has crucial clinical diagnostic significance. To ensure the high fidelity requirements of medical image diagnosis and achieve high-quality transmission and storage of image data, this study uses deep learning to design a dual stream lossless compression network suitable for X-ray images. The results demonstrated that the designed network performed well in compression and bit rates on different datasets, with a minimum bit rate of 0.204 and a maximum compression rate of 0.946. Compared to other advanced models, this network had the highest peak signal-to-noise ratio and lower distortion of compressed images. In the compression process of X-ray images of osteoporosis, this network outperformed other models in different structural similarity indices, with values above 0.90, showing significant advantages. The equivalent number of views of the compressed image reached 0.93, and the visual quality of the lossless compressed image was high, ensuring the efficiency and accuracy of diagnosis. The research method can significantly improve the theoretical research level of lossless compression technology and enhance its practical value in remote medical diagnosis.

Carbon emissions have become a key environmental indicator as air pollution increases. It is urgent for multiobjective optimization of chemical processes to take into account carbon emissions, while ensuring economic benefits. Aiming to improve the treatment of multiphase pollutants, this study builds a three-objective optimization model by considering the optimization of treatment effect, energy consumption, and an innovatively constructed optimization objective of direct and indirect carbon emissions. We run nondominated sorting genetic algorithm-II (NSGA-II) to optimize the operating parameters with respect to the three objectives to get a set of Pareto nondominated solutions on the established Aspen Plus steady-state process simulation, which is based on physical properties and process mechanisms. Finally, we find the optimal solutions through the technique for order preference by similarity to ideal solution (TOPSIS) and knee point. Under the same experimental conditions, we compare our model with the multiphase pollutant treatment research only considering the waste-water flow and energy consumption. Additionally, a life cycle analysis of the three treatment processes (G1, G2 and G3) was conducted. The experimental results show that the proposed model has achieved good results on the three objectives, which have demonstrated the effectiveness of our model. Overall, this study offers a new perspective to the optimization and decision-making of multiphase pollutant treatment considering carbon emissions.

Abstract Atomic-scale defects generated in materials under both equilibrium and irradiation conditions can significantly impact their physical and mechanical properties. Unraveling the energetically most favorable ground-state configurations of these defects is an important step towards the fundamental understanding of their influence on the performance of materials ranging from photovoltaics to advanced nuclear fuels. Here, using fluorite-structured thorium dioxide (ThO2) as an exemplar, we demonstrate how density functional theory and machine learning interatomic potential can be synergistically combined into a powerful tool that enables exhaustive exploration of the large configuration spaces of small point defect clusters. Our study leads to several unexpected discoveries, including defect polymorphism and ground-state structures that defy our physical intuitions. Possible physical origins of these unexpected findings are elucidated using a local cluster expansion model developed in this work.

Abstract Background One noteworthy concern within the realm of education is the level of engagement demonstrated by students. Among the factor that can have a crucial role in this domain is teacher support, especially emotional support which has an impact on several aspects of learners’ education. Furthermore, various studies have investigated the relationship between Emotional Intelligence (EI) and learners’ engagement. Methods Accordingly, this study investigated the possible role of trait EI and the emotional support of teachers and how these constructs may work to associate learners’ engagement. For this objective, a total of 309 Chinese students across different colleges and universities in 5 provinces of Beijing, Shanghai, Jiangsu, Hubei, and Shaanxi were enrolled. They were 126 females and 183 males, with ages ranging from 18 to 30 years old (Mean = 24.6). Results The results of this research through running Structural Equation Modeling (SEM) demonstrated that teachers’ emotional support and trait EI both can associate students’ learning engagement. The final measurement model shows that about 73% of changes in learners’ engagement can be associated by their trait EI and teachers’ emotional support. Conclusions This study underscores the importance of emotional support from teachers and the trait of EI in relation to students’ engagement in learning. Both factors were shown to play a significant role in associating student engagement. Moreover, this study could potentially have wider impacts on members of academic teams.

In the cigarette manufacturing industry, machine vision and artificial intelligence algorithms have been employed to improve production efficiency by detecting product defects. However, achieving both high accuracy and real-time defect detection for cigarettes with complex patterns remains a challenge. To address these issues, this study proposes a model based on RESNET18, combined with a feature enhancement algorithm, to improve detection accuracy. Additionally, a method is designed to deploy the model on a field-programmable gate array (FPGA) with high parallel processing capabilities to achieve high-speed detection. Experimental results demonstrate that the proposed detection model achieves a detection accuracy of 95.88% on a cigarette filter defect dataset with an end-to-end detection speed of only 9.38 ms.

This study presents a bi-objective optimization model for the Green Vehicle-Routing Problem in cold chain logistics, with a focus on symmetric distance matrices, aiming to minimize total costs, including carbon emissions, while maximizing customer satisfaction. To address this complex challenge, we developed a Stage-Specific Multi-Objective Five-Element Cycle Optimization algorithm (MOFECO-SS), which dynamically adjusts optimization strategies across different stages of the process, thereby enhancing overall efficiency. Extensive comparative analyses with existing algorithms demonstrate that MOFECO-SS consistently outperforms in solving the multi-objective optimization model, particularly in reducing total costs and carbon emissions while maintaining high levels of customer satisfaction. The symmetric nature of the distance matrix further aids in achieving balanced and optimized route planning. The results highlight that MOFECO-SS offers decision-makers flexible route planning options that balance cost efficiency with environmental sustainability, ultimately improving the effectiveness of cold chain logistics operations.

The irregular joint network unique to columnar joints separates the rock mass into several irregular polygonal prisms. Similar physical model specimens of columnar jointed rock mass (CJRM) were fabricated using a rock-like material. The effect of the irregularity of the joint network was considered in the horizontal plane, and the effect of the dip angle of the joint network was considered in the vertical plane. The strength and deformation moduli of the specimen were investigated using uniaxial compression tests. A total of four failure modes of regular columnar jointed rock mass (RCJRM) and irregular columnar jointed rock mass (ICJRM) were identified through the tests. The peak stress of the irregular columnar jointed rock mass specimen is reduced by 56.65%. The strength and deformation moduli of RCJRM were greater than those of ICJRM, while the anisotropic characteristics of ICJRM were stronger. The failure mode of CJRM was determined by the dip angle. With the increase in the dip angle, the strength and deformation moduli of irregular columnar jointed rock mass are a symmetrical “V” type distribution, 45° corresponds to the minimum strength, and 30° obtains the minimum deformation modulus. With the increase in the irregularity coefficient, the strength and deformation moduli of CJRM decreased first and then increased gradually. When the irregularity coefficient is 0.1, the linear deformation modulus reaches the minimum value. When the irregularity coefficient is 0.7, the median deformation modulus reaches the minimum value. The fitting function proposed in the form of the cosine function managed to predict the strength value of CJRM and showed the strength of the anisotropic characteristics caused by the change in the dip angle. Compared with the existing physical model test results, it is determined that the strength of the specimen is positively correlated with the addition amount of rock-like material and the loading rate, and negatively correlated with the water consumption.

With the deepening of national efforts toward green energy transformation, the power system is evolving into one characterized by “double high”—a high proportion of new energy integration and a high level of power electronic systems. This results in a more complex system topology, necessitating improvements in various prevention and control measures. Traditional model-based methods for locating power oscillation disturbance sources in power systems are no longer sufficient to meet the operational demands of modern power systems. With the rapid development of wide-area measurement systems (WAMS), there is growing interest in disturbance source localization using system response data. System dynamics provide a wealth of easily extractable data that can accurately reflect the power system’s behavior under normal conditions. This paper proposes a numerical method for locating disturbance sources, combining energy functions with normal distribution identification, based on power oscillation mechanisms and system response data. The method identifies potential disturbance sources, including small random load fluctuations and large forced power oscillations. The innovation lies in the introduction of a 3 Sigma value criterion to pinpoint the disturbance source location, addressing the limitations of traditional energy function methods that require manual intervention. By quantifying the localization of power oscillation disturbance sources, this method significantly improves both efficiency and accuracy.

Abstract This study modeled the habitat distribution of Pterocarpus santalinus, a valuable rosewood species, across China under current and future climate scenarios (SSPs126, SSPs245, and SSPs585) using MaxEnt. Our findings reveal that the current suitable habitat, spanning approximately 409,600 km2, is primarily located in the central and southern parts of Guangdong, Guangxi, Fujian, and Yunnan, as well as in the Hainan provinces, along with the coastal regions of Taiwan, and the Sichuan–Chongqing border. The habitat's distribution is significantly influenced by climatic factors such as temperature seasonality (bio4), mean temperature of the wettest quarter (bio8), annual mean temperature (bio1), and annual precipitation (bio12), while terrain and soil factors play a lesser role. Under future climate scenarios, the suitable habitat for P. santalinus is projected to expand, with a northeastward shift in its distribution center. This research not only sheds light on the geoecological characteristics and geographical distribution of P. santalinus in China but also offers a scientific basis for planning its cultivation areas and enhancing cultivation efficiency under changing climate conditions.

Considering the granularity of embedded data in the design of reversible data hiding scheme has important research significance for the permission control and management of multi-granularity information. To broaden the application possibilities of encrypted data in cloud environments, the researchers propose a fine-grained reversible data hiding method leveraging the cipher-text redundancy of ElGamal encryption. Initially, prior to the encryption process, pixels are organized into a full binary tree based on fine-grained access permissions. Subsequently, a chaotic sequence generator is employed to assign distinct embedding keys to each layer of the full binary tree according to the access permissions. Following this, an XOR operation is conducted between the embedding key and the corresponding secret information in each layer to derive the target features of the cipher-text, facilitating subsequent fine-grained data hiding. Throughout the ElGamal encryption process, iterative manipulation of the random variable ensures alignment between the cipher-text output and the target feature, enabling the embedding of secret information across different layers. This approach facilitates the fine-grained blind extraction of secret information from an encrypted state, thereby expanding the potential applications of cipher-text by extracting information without revealing the original data. Furthermore, the scheme enhances information security through distributed storage and conceals the presence of information hiding by leveraging the separability of lossless decryption and information extraction. Simulation results demonstrate that secret information of three granularities can be embedded and extracted without interference within a three-layer full binary structure, with a maximum embedding capacity of up to 1.75 bpp.

Background Understanding the evolution of circadian rhythm dysfunction and psychopathology in the high-risk population has important implications for the prevention of bipolar disorder. Nevertheless, some of the previous studies on the emergence of psychopathologies and circadian dysfunction among high-risk populations were inconsistent and limited.Aims To examine the prevalence rates of sleep and circadian dysfunctions, mental disorders and their symptoms in the offspring of parents with (O-BD) and without bipolar disorder (O-control).Methods The study included 191 O-BD and 202 O-control subjects aged 6–21 years from the Greater Bay Area, China. The diagnoses and symptoms of sleep/circadian rhythm and mental disorders were assessed by the Diagnostic Interview for Sleep Patterns and Disorders, and the Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version, respectively. Generalised estimating equations and shared frailty proportional hazards models of survival analysis were applied to compare the outcomes in the offspring.Results Adjusting for age, sex and region of recruitment, there was a significantly higher risk of delayed sleep phase symptoms (9.55% vs 2.58%, adjusted OR: 4.04) in O-BD than in O-control. O-BD had a nearly fivefold higher risk of mood disorders (11.70% vs 3.47%, adjusted OR: 4.68) and social anxiety (6.28% vs 1.49%, adjusted OR: 4.70), a fourfold higher risk of depressive disorders (11.17% vs 3.47%, adjusted OR: 3.99) and a threefold higher risk of mood symptoms (20.74% vs 10.40%, adjusted OR: 2.59) than O-control. Subgroup analysis revealed that O-BD children (aged under 12 years) had a nearly 2-fold higher risk of any mental and behavioural symptoms than O-control, while there was a nearly 4-fold higher risk of delayed sleep phase symptoms, a 7.5-fold higher risk of social anxiety and a 3-fold higher risk of mood symptoms in O-BD adolescents (aged 12 years and over).Conclusions There was an increase in delayed sleep phase symptoms in O-BD adolescents compared with their control counterparts, confirming the central role of circadian rhythm dysfunction in bipolar disorder. The findings of the specific age-related and stage-related developmental patterns of psychopathologies and circadian dysfunction in children and adolescent offspring of parents with bipolar disorder paved the way to develop specific and early clinical intervention and prevention strategies.Trial registration number NCT03656302.

Background: Abnormally expressed Runt-associated transcription factor (RUNX) family has been reported in multiple tumors. Nevertheless, the immunological role of RUNX family in kidney renal clear cell carcinoma (KIRC) remains unknown. Methods: We studied the RNA-seq data regarding tumor and healthy subjects from several public databases in detail for evaluating the prognostic and immunological functions owned by three RUNX genes in cancer patients. Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) and immunohistochemical (IHC) staining served for detecting their expressions in tumor and normal samples. Results: We observed that KIRC patients presented high expressions of RUNX1, RUNX2, and RUNX3. The expressions of three genes were validated by qRT-PCR, which was same as bioinformatical results. Prognostic analysis indicated that the overexpression of RUNX1 and RUNX2 negatively affects the outcomes in patients with KIRC. Related functional predictions indicated that the RUNXs and co-expression genes were significantly related to the immune response pathway. Moreover, three RUNX members were associated with immune infiltration cells and their related gene markers. The expression of RUNX family in several immune cells is positively or negatively correlated, and its dysregulation is obviously associated with the differential distribution of immune cells. RUNX family genes were abnormally expressed in KIRC patients, and were closely related to the crosstalk of immune cells. Conclusions: Our findings may help to understand the pathogenesis and immunologic roles of the RUNX family in KIRC patients from new perspectives.

IntroductionThe uridine diphosphate (UDP)-glycosyltransferase (UGT) family is the largest glycosyltransferase family, which is involved in the biosynthesis of natural plant products and response to abiotic stress. UGT has been studied in many medicinal plants, but there are few reports on Platycodon grandiflorus. This study is devoted to genome-wide analysis of UGT family and identification of UGT genes involved in drought stress of Platycodon grandiflorus (PgUGTs).MethodsThe genome data of Platycodon grandiflorus was used for genome-wide identification of PgUGTs, online website and bioinformatics analysis software was used to conduct bioinformatics analysis of PgUGT genes and the genes highly responsive to drought stress were screened out by qRT-PCR, these genes were cloned and conducted bioinformatics analysis.ResultsA total of 75 PgUGT genes were identified in P.grandiflorus genome and clustered into 14 subgroups. The PgUGTs were distributed on nine chromosomes, containing multiple cis-acting elements and 22 pairs of duplicate genes were identified. Protein-protein interaction analysis was performed to predict the interaction between PgUGT proteins. Additionally, six genes were upregulated after 3d under drought stress and three genes (PGrchr09G0563, PGrchr06G0523, PGrchr06G1266) responded significantly to drought stress, as confirmed by qRT-PCR. This was especially true for PGrchr06G1266, the expression of which increased 16.21-fold after 3d of treatment. We cloned and conducted bioinformatics analysis of three candidate genes, both of which contained conserved motifs and several cis-acting elements related to stress response, PGrchr06G1266 contained the most elements.DiscussionPgGT1 was confirmed to catalyze the C-3 position of platycodin D and only eight amino acids showed differences between gene PGr008G1527 and PgGT1, which means PGr008G1527 may be able to catalyze the C-3 position of platycodin D in the same manner as PgGT1. Seven genes were highly expressed in the roots, stems, and leaves, these genes may play important roles in the development of the roots, stems, and leaves of P. grandiflorus. Three genes were highly responsive to drought stress, among which the expression of PGrchr06G1266 was increased 16.21-fold after 3d of drought stress treatment, indicating that PGrchr06G1266 plays an important role in drought stress tolerance. To summarize, this study laied the foundation to better understand the molecular bases of responses to drought stress and the biosynthesis of platycodin.

Summary: The vaginal microbiome’s composition varies among ethnicities. However, the evolutionary landscape of the vaginal microbiome in the multi-ethnic context remains understudied. We perform a systematic evolutionary analysis of 351 vaginal microbiome samples from 35 multi-ethnic pregnant women, in addition to two validation cohorts, totaling 462 samples from 90 women. Microbiome alpha diversity and community state dynamics show strong ethnic signatures. Lactobacillaceae have a higher ratio of non-synonymous to synonymous polymorphism and lower nucleotide diversity than non-Lactobacillaceae in all ethnicities, with a large repertoire of positively selected genes, including the mucin-binding and cell wall anchor genes. These evolutionary dynamics are driven by the long-term evolutionary process unique to the human vaginal niche. Finally, we propose an evolutionary model reflecting the environmental niches of microbes. Our study reveals the extensive ethnic signatures in vaginal microbial ecology and evolution, highlighting the importance of studying the host-microbiome ecosystem from an evolutionary perspective.

Accurate and fast classification of FDEs is crucial to power systems situation awareness and stability control. However, various database used in recent studies makes it hard to directly compare different classification methods. To relieve the lack of a standardized database that can be used as a benchmark, this work proposes an open-source package which generates frequency events based on PowerFactory named PF-FEDG. PF-FEDG can produce various labeled FDEs with random parameters such as generator trips, load disconnections, line outages, frequency ramp ups, frequency ramp downs, and frequency oscillations. Furthermore, the package includes three reference FDEs classifiers based on deep learning techniques. These models are tested on the IEEE 39-bus system and IEEE 118-bus system and achieve high performance. The package generating capability and the reference classifiers can be used by the community as benchmarks for comparison and development of new algorithms for FDEs detection. The code of PF-FEDG is available on GitLab.

In this work, a mechanistic model is proposed for ion-irradiated nanocrystalline (NC) metals to characterize the evolution of hardness as a function of the indentation depth at room temperature and under quasi-static loading condition. At the grain level, grain interiors (GIs) and grain boundaries (GBs)-dominated hardening are addressed simultaneously in the developed model, which is able to effectively characterize the contribution of geometrically necessary dislocations (GNDs), statistically stored dislocations (SSDs), irradiation-induced defects, Hall-Petch effect and the intrinsic strength of GBs. Thereinto, the GIs-dominated hardening mechanisms are systematically analyzed by considering the evolution of microstructures, which include the average density of dislocations and irradiation-induced defects within the plastic zone, and are noticed to be affected by the high ratio of GBs. Main attentions are focused on the description of GBs influence that covers dislocation hardening and defect hardening. The rationality and accuracy of the proposed model are validated by comparing the theoretical results with corresponding experimental data under different irradiation conditions. The proposed model offers a promising way to analyze the irradiation hardening mechanisms of NC metals.