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Epithelial ovarian cancer (EOC) is a common estrogen-sensitive tumor that poses a serious threat to women 's health, and the mortality rate of EOC ranks first among malignant tumors in females. Studies have indicated a strong link between estrogen abnormality and EOC progression. We accidently found that 3-phosphoinositide-dependent protein kinase-1 (PDPK1) is highly expressed in EOC tissues. Further, estrogen also up-regulates the expression of PDPK1 in EOC cells. Notably, the expression of PDPK1 is controlled strictly, and its expression can determine the fate of cells. However, to date, the molecular mechanism by which estrogen elicits PDPK1 expression in EOC cells, and the role of PDPK1 in estrogen-driven EOC cells are not well defined. In this research, we found that a high expression of PDPK1 was associated with poor prognosis in patients with ovarian cancer. Further, estrogen stimulated the increase of PDPK1 protein expression through estrogen receptor ESR1. The depletion or overexpression of PDPK1 affected the inhibition or amplification of estrogen-driven EOC cell proliferation, and the knockdown of PDPK1 suppressed the migration of EOC cells by estrogen while promoting cell apoptosis. This suggests a critical functional association between estrogen and PDPK1 in the process of EOC. The expression of messenger RNA for cyclin A1, cyclin-dependent kinase 2 (CDK2), matrix metallopeptidase 2 (MMP2), and bcl-2 associated x protein (Bax) is regulated by PDPK1 under estrogen treatment. Our results indicated that PDPK1 plays a role as an oncogene in the development of EOC; hence, elucidating the mechanism by which estrogen promotes EOC progression by regulating PDPK1 expression.

Evaluating the health of river surface water is essential, as rivers support significant biological resources and serve as vital drinking water sources. While the Water Quality Index (WQI) is commonly employed to evaluate surface water quality, it fails to consider biodiversity and does not fully capture the ecological health of rivers. Here we show a comprehensive assessment of the ecological health of surface water in the lower Yangtze River (LYR), integrating chemical and biological metrics. According to traditional WQI metrics, the LYR's surface water generally meets China's Class II standards. However, it also contains 43 high-risk emerging contaminants; nitrobenzenes are found at the highest concentrations, representing 25–90% of total detections, while polycyclic aromatic hydrocarbons present the most substantial environmental risks, accounting for 81–93% of the total risk quotient. Notably, the plankton-based index of biological integrity (P-IBI) rates the ecological health of the majority of LYR water samples (59.7%) as ‘fair’, with significantly better health observed in autumn compared to other seasons (p

The concept of “enterotypes” in microbiome research has attracted substantial interest, particularly focusing on the abundance of Prevotella spp. in the human gut. In this study, the intricate dynamics of Prevotella spp. in the human gut microbiota was investigated, based on the metagenomic method. First, 239 fecal samples from individuals across four regions of China revealed a bimodal distribution, highlighting the abundance and variability in Prevotella spp. within the Chinese population. Second, the longitudinal cohort study included 184 fecal samples from 52 time points collected from seven individuals who demonstrated either the outbreaks or disappearances of Prevotella spp., emphasizing the transient nature of Prevotella abundance levels and suggesting shifts in Prevotella “enterotypes.” Furthermore, a turnover of the dominant Prevotella spp. was observed, indicating the potential presence of diverse subtypes of Prevotella enterotype. Notably, the genomic analysis demonstrated the persistence of specific Prevotella strains within individuals over extended periods, highlighting the enduring presence of Prevotella in the human gut. In conclusion, by integrating the temporal and geographical scales in our research, we gained deeper insights into the dynamics of Prevotella, emphasizing the importance of considering the dynamics at the time and species level in gut microbiota studies and their implications on human health.

Methamphetamine (Meth) abuse can cause serious mental disorders, including anxiety and depression. The gut microbiota is a crucial contributor to maintaining host mental health. Here, we aim to investigate if microbiota participate in Meth-induced mental disorders, and the potential mechanisms involved. Here, 15 mg/kg Meth resulted in anxiety- and depression-like behaviors of mice successfully and suppressed the Sigma-1 receptor (SIGMAR1)/BDNF/TRKB pathway in the hippocampus. Meanwhile, Meth impaired gut homeostasis by arousing the Toll-like receptor 4 (TLR4)-related colonic inflammation, disturbing the gut microbiome and reducing the microbiota-derived short-chain fatty acids (SCFAs). Moreover, fecal microbiota from Meth-administrated mice mediated the colonic inflammation and reproduced anxiety- and depression-like behaviors in recipients. Further, SCFAs supplementation optimized Meth-induced microbial dysbiosis, ameliorated colonic inflammation, and repressed anxiety- and depression-like behaviors. Finally, Sigmar1 knockout (Sigmar1−/−) repressed the BDNF/TRKB pathway and produced similar behavioral phenotypes with Meth exposure, and eliminated the anti-anxiety and -depression effects of SCFAs. The activation of SIGMAR1 with fluvoxamine attenuated Meth-induced anxiety- and depression-like behaviors. Our findings indicated that gut microbiota-derived SCFAs could optimize gut homeostasis, and ameliorate Meth-induced mental disorders in a SIGMAR1-dependent manner. This study confirms the crucial role of microbiota in Meth-related mental disorders and provides a potential preemptive therapy.

【Objective】In recent years, grape industry has developed rapidly in Guangdong Province, which has been a high-profit grape production region where two crops of grape berry can be harvested in a year. However, the short day photoperiod and chilling temperatures in autumn and winter induce systematic leaf senescence, which is unfavorable for over-winter berry development and quality formation in grape. In the study, the effect of artificial supplementary lighting on leaf senescence and berry development in 'Shine Muscat' grape were explored, with an aim to provide technical basis for maintaining leaf function and berry development in winter.【Method】From mid-October, 8-year-old 'Shine Muscat' plants on rootstock of '5BB' were treated with 3 μmol/m2·s red and blue LED light (5∶1) belts, which were placed above the leaves at the fruit cluster node. Light supplementary was carried out from 18:00 to 24:00 until the berries became mature. Changes in chlorophyll index (SPAD value), photosynthetic parameters (Pn) of the leaves at the fruit cluster node and horizontal and vertical diameters of berries were traced, and single berry weight, cluster weight and total soluble solid (TSS) content were collected at mature period.【Result】After 6 weeks of supplementary lighting treatment, leaves at the cluster node in the control plants became yellowing with decreasing SPAD value. While artificial lighting treatment was effective to suppress leaf chlorosis in winter, with significantly lower SPAD decreasing range. After 10 weeks of treatment, leaves at various nodes in supplementary lighting treatment were higher than those at corresponding nodes in the control plants, suggesting that artificial lighting suppressed systematic leaf senescence in winter. The Pn of both lighting treatment and the control plants decreased dramatically from mid-November to late December. However, the decreasing range of Pn was smaller in the lighting treatment. Pn had no significant correlation with stomatal conductance (Gs), but was extremely negatively correlated to mesophyll CO2 concentration (Ci), indicating the reduction of Pn during leaf senescence in winter was mainly caused by non-stomatal limitation. Supplementary lighting treatment maintained Pn via overcoming both stomatal and non-stomatal limitations. the supplementary lighting treatment, significantly increased single berry weight (10.8 g VS 8.8 g), promoted berry horizontal diameter, slightly increased single cluster weight, but significantly reduced total soluble solids (15.0% VS 16.7%).【Conclusion】The results show that supplementary lighting treatment is effective to delay systematic leaf senescence in winter and promote berry growth. It is recommended to use supplementary LED lighting during over-winter grape cultivation in Guangzhou or in regions with similar climate. However, measures should be taken to promote TSS accumulation in the berry.

Abstract Background Depression among adolescents is a seriously disabling public health problem with an extremely high prevalence. Identifying risk factors of depression at an early stage is important to reduce the disease burden. Childhood maltreatment (CM) is one of the major risk factors for depression. The key mediating processes that how CM affects the development of depression, however, still need further clarification. The present study tested the mediating effect of self-esteem, internalizing problems, and externalizing problems between CM and depressive symptoms. Potential sex differences in the foregoing associations were also explored. Methods A three-wave longitudinal study was carried out among 1,957 middle and high school students from 69 classes in 10 public schools in the Guangdong province of China. Data collection started when students were in grades 7 and 10 (median age: 13.0, range: 11–18) between January and April 2019, and the students were followed up once a year thereafter. Self-reported CM, depressive symptoms, self-esteem, internalizing and externalizing problems, and other demographics were collected. The multiple serial mediation analysis was conducted. Results We found that CM was positively related to subsequent internalizing and externalizing problems, as well as depressive symptoms, while self-esteem was negatively related to depressive symptoms. Serial mediation analysis indicated that self-esteem (mediator 1) and internalizing problems (mediator 2) sequentially mediated the path from CM to depressive symptoms in the overall and male population. Moreover, with externalizing problems as mediator 2, self-esteem (mediator 1) acted as a partial mediator in the association between CM and depressive symptoms in males, whereas externalizing problems played a complete mediating role in females. Conclusion Findings revealed that self-esteem and internalizing problems sequentially mediated the influence of CM on depressive symptoms whereas externalizing problems played an independent mediating role. In addition, sex differences need to be taken into consideration when designing prevention and intervention strategies, given the different psychosocial processes between boys and girls.

Abstract Background Previous researches have not distinguished the between-person effects from the within-person effects when exploring the relationship between self-esteem, coping styles, and anxiety symptoms among adolescents. To address this gap, this study investigated reciprocal associations among self-esteem, coping styles, and anxiety symptoms in a three-wave longitudinal panel survey, using an analytical strategy that disaggregates the within-person and the between-person variance. Methods Data was drawn from the Longitudinal Study of Adolescents’ Mental and Behavioral Well-being Research study conducted in 10 public schools in the Guangdong province of China. All participants had a baseline visit (N = 1957, mean age 13.6, grades 7 and 10) and follow-up interviews at 1-year intervals for 3 years. A random intercept cross-lagged panel model combined with mediation analysis was performed. Results At the within-person level, the following results were observed. (1) Low self-esteem and anxiety symptoms bidirectionally predicted each other. (2) Low self-esteem and negative coping style bidirectionally predicted each other. (3) Anxiety symptoms predicted subsequent negative coping style but not vice versa. At the between-person level, we obtained the following main results. (1) Significant predictive effects on the random intercept were found among all three study constructs. (2) There were sex differences regarding the association between self-esteem and anxiety symptoms and the correlation of females was stronger than that of males. (3) Self-esteem mediated the reciprocal relations between coping styles and anxiety symptoms. Conclusions Overall, findings revealed a reciprocal relationship between low self-esteem and anxiety symptoms for both females and males. Besides, anxiety symptoms predict subsequent negative coping style but not vice versa. We also highlighted the mediating role of self-esteem in the reciprocal relations between coping styles and anxiety symptoms. Thus, interventions targeted at promoting self-esteem and cultivating positive coping style may help reduce adolescent anxiety.

Aging with dysregulated metabolic and immune homeostasis stimulates pyroptosis, neuroinflammation, and cellular senescence, thus contributing to etiopathogenesis of Alzheimer's disease. GATA-binding protein 4 (GATA4) functions as a transcriptional factor in response to DNA damage, and is associated with neuroinflammation and cellular senescence. The role of GATA4 in Alzheimer's disease was investigated. GATA4 was elevated in hippocampus of Aβ1–42 fibril-infused rats. Injection with shRNA targeting GATA4 reduced escape latency with increase of time in target quadrant and number of platform crossings in Aβ1–42 fibril-infused rats. Moreover, knockdown of GATA4 ameliorated morphological changes of hippocampus and reduced amyloid plaque deposition in Aβ1–42 fibril-infused rats. Silence of GATA4 repressed neuroinflammation and apoptosis in Aβ1–42 fibril-infused rats. Loss of GATA4 in Aβ1–42 fibril-infused rats reduced the expression of specificity protein 1 (Sp1) to downregulate long noncoding RNA small nucleolar RNA host gene 1 (SNHG1) and upregulated miR-361-3p. Loss of SNHG1 ameliorated learning and memory impairments in Aβ1–42 fibril-infused rats. Overexpression of Sp1 attenuated GATA4 silence-induced decrease of escape latency, increase of time in target quadrant, and number of platform crossings in Aβ1–42 fibril-infused rats. In conclusion, silence of GATA4 ameliorated cognitive dysfunction and inhibited hippocampal inflammation and cell apoptosis through regulation of Sp1/SNHG1/miR-361-3p.

A study for human gut microbiota composition in 7 healthy Chinese adult subjects across several years provides a valuable perspective on the dynamics of microbiota composition over time.

Abstract Background Depressive symptoms among adolescents are a serious health concern around the world. Altered DNA methylation in the FK506 binding protein 5 (FKBP5) gene has been reported to regulate stress response, which has been reported to be closely associated with depressive symptoms. However, most of the contributing studies have been conducted among adults and relatively few studies have considered the effect of disparate social influences and sex differences on the DNA methylation of FKBP5 in persons with depressive symptoms. The present study aimed to test the associations of FKBP5 DNA methylation and depressive symptoms among adolescents and explore possible sex differences in the foregoing associations. Methods This study was conducted using a nested case-control design within a longitudinal cohort study from January 2019 to December 2019. Adolescents aged 12 to 17 years from 69 classes in 10 public high schools located in Guangdong province of China participated in this research. Students with persistent depressive symptoms that reported having depressive symptoms at both baseline and follow-up were treated as the case group, and those without depressive symptoms were randomly selected as the control group. Our study finally included 87 cases and 151 controls. Quantitative methylation analyses of the selected gene were carried out by MassARRAY platform System. Results The overall DNA methylation trend of FKBP5 CpG sites in the case group was lower in comparison to the control group. Compared to healthy controls, lower methylation percentage of FKBP5-12 CpG 1 was observed in adolescents with persistent depressive symptoms after adjusting for covariates (case: 0.94 ± 2.00, control: 0.47 ± 0.92; F = 5.41, P = 0.021), although the statistical significance of the difference was lost after false discovery rate correction (q > 0.05). In addition, the hypomethylation of FKBP5-12 CpG 1 was approaching significance after adjustment for social-environmental factors (aOR = 0.77; P = 0.055), which indicated that no independent association was detected between hypomethylation of FKBP5 CpG sites and persistent depressive symptoms. Furthermore, in the present study, we were unable to identify sex differences in the association of FKBP5 gene methylation with depressive symptoms. Conclusion The decreased methylation level of FKBP5 was observed in adolescents with persistent depressive symptoms, albeit non-significant after correction for multiple testing. Our results presented here are preliminary and underscore the complex gene-environment interactions relevant to the risk for depressive symptoms.

In the recent study, we described a novel iron nanoparticles green-mediated by arabic coffee as a novel anticancer agent (FeNPs). The recent nanoparticles were analyzed by Fourier transformed infrared spectroscopy (FT-IR), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDS), elemental mapping, X-ray diffraction (XRD) and ultraviolet–visible spectroscopy (UV–Vis). The iron nanoparticles showed the best antioxidant activities against DPPH. The IC50 of iron nanoparticles and BHT against DPPH free radicals were 165 and 62 µg/mL, respectively. In the oncological part of the recent study, the treated cells with iron nanoparticles were assessed by MTT assay for 48 h about the cytotoxicity and anticancer properties on normal (HUVEC) and lung cancer cell lines. The IC50 of iron nanoparticles were 273, 216, and 250 µg/mL against HT144, SKMEL2, and WM266-4 cell lines, respectively. The viability of malignant cell lines reduced dose-dependently in the presence of iron nanoparticles.

Monitoring forest species diversity is essential for biodiversity conservation and ecological management. Currently, unmanned aerial vehicle (UAV) remote sensing technology has been increasingly used in biodiversity monitoring due to its flexibility and low cost. In this study, we compared two methods for estimating forest species diversity indices, namely the spectral angle mapper (SAM) classification approach based on the established species-spectral library, and the self-adaptive Fuzzy C-Means (FCM) clustering algorithm by selected biochemical and structural features. We conducted this study in two complex subtropical forest areas, Mazongling (MZL) and Gonggashan (GGS) National Nature Forest Reserves using UAV-borne hyperspectral and LiDAR data. The results showed that the classification method performed better with higher values of R2 than the clustering algorithm for predicting both species richness (0.62 > 0.46 for MZL and 0.55 > 0.46 for GGS) and Shannon-Wiener index (0.64 > 0.58 for MZL, 0.52 > 0.47 for GGS). However, the Simpson index estimated by the classification method correlated less with the field measurements than the clustering algorithm (R2 = 0.44 and 0.83 for MZL and R2 = 0.44 and 0.62 for GGS). Our study demonstrated that the classification method could provide more accurate monitoring of forest diversity indices but requires spectral information of all dominant tree species at individual canopy scale. By comparison, the clustering method might introduce uncertainties due to the amounts of biochemical and structural inputs derived from the hyperspectral and LiDAR data, but it could acquire forest diversity patterns rapidly without distinguishing the specific tree species. Our findings underlined the advantages of UAV remote sensing for monitoring the species diversity in complex forest ecosystems and discussed the applicability of classification and clustering methods for estimating different individual tree-based species diversity indices.

Grassland canopy height is a crucial trait for indicating functional diversity or monitoring species diversity. Compared with traditional field sampling, light detection and ranging (LiDAR) provides new technology for mapping the regional grassland canopy height in a time-saving and cost-effective way. However, the grassland canopy height based on unmanned aerial vehicle (UAV) LiDAR is usually underestimated with height information loss due to the complex structure of grassland and the relatively small size of individual plants. We developed canopy height correction methods based on scan angle to improve the accuracy of height estimation by compensating the loss of grassland height. Our method established the relationships between scan angle and two height loss indicators (height loss and height loss ratio) using the ground-measured canopy height of sample plots with 1×1m and LiDAR-derived heigh. We found that the height loss ratio considering the plant own height had a better performance (R2 = 0.71). We further compared the relationships between scan angle and height loss ratio according to holistic (25–65cm) and segmented (25–40cm, 40–50cm and 50–65cm) height ranges, and applied to correct the estimated grassland canopy height, respectively. Our results showed that the accuracy of grassland height estimation based on UAV LiDAR was significantly improved with R2 from 0.23 to 0.68 for holistic correction and from 0.23 to 0.82 for segmented correction. We highlight the importance of considering the effects of scan angle in LiDAR data preprocessing for estimating grassland canopy height with high accuracy, which also help for monitoring height-related grassland structural and functional parameters by remote sensing.

BackgroundThe presence of heterogenous somatic symptoms frequently obscures the recognition of depression in primary care. We aimed to explore the association between somatic symptoms and subthreshold depression (SD) and Major Depressive Disorder (MDD), as well as to determine the predictive potential of somatic symptoms in identifying SD and MDD in primary care.MethodsData were derived from the Depression Cohort in China study (ChiCTR registry number: 1900022145). The Patient Health Questionnaire-9 (PHQ-9) was used to assess SD by trained general practitioners (GPs), and the Mini International Neuropsychiatric Interview depression module was used to diagnose MDD by professional psychiatrists. Somatic symptoms were assessed using the 28-item Somatic Symptoms Inventory (SSI).ResultsIn total of 4,139 participants aged 18–64 years recruited from 34 primary health care settings were included. The prevalence of all 28 somatic symptoms increased in a dose-dependent manner from non-depressed controls to SD, and to MDD (P for trend

ABSTRACT In this study, we aimed to understand the characteristics of the gut microbial composition in a healthy Chinese population and to evaluate if they differed across different regions. In addition, we aimed to understand the changes in the gut microbial composition over time. We collected 239 fecal samples from healthy Chinese adults living in four regions and performed a 1-year time cohort study in a small population in Beijing. The Chinese gut microbiota share 34 core bacterial genera and 39 core bacterial species, which exist in all collected samples. Several disease-related microorganisms (DRMs), virulence factors, and antibiotic resistance genes were found in one or more healthy Chinese samples. Differences in gut microbiota were observed in samples from different regions, locations, individuals, and time points. Compared to other factors, time was associated with a lower degree of change in the gut microbiota. Our findings revealed spatial and temporal changes in the gut microbiota of healthy Chinese individuals. Compared to fecal microbiomes of 152 samples in the publicly released the Human Microbiome Project (HMP) project from the United States, samples in this study have higher variability in the fecal microbiome, with higher richness, Shannon diversity indices, and Pielou evenness indexes, at both the genus and species levels. The microbiota data obtained in this study will provide a detailed basis for further understanding the composition of the gut microbiota in the healthy Chinese population. IMPORTANCE China accounts for approximately 1/5th of the world’s total population. Differences in environment, ethnicity, and living habits could impart unique features to the structure of the gut microbiota of Chinese individuals. In 2016, we started to investigate healthy Chinese people and their gut microbiomes. Phase I results for 16S rRNA amplicons have been released. However, owing to the limitations of 16S rRNA amplicon sequencing, the gut microbiome of a healthy Chinese population could not be examined thoroughly at the species level, and the detailed changes in the gut microbiota over time need to be investigated. To address these knowledge gaps, we started a phase II study and investigated the basis for variations in the gut microbiome composition in a healthy Chinese population at the species level using shotgun metagenomics technology. In the phase II study, we also conducted a time scale analysis of fecal samples from healthy Chinese subjects, as a pioneered study, which quantitatively clarified the changes in the gut microbiota at both the spatial and temporal levels and elucidated the distribution pattern of DRMs in healthy Chinese individuals.

Green Human Resource Management (HRM) supports promoting and incorporating sustainable development with regard to their resources. Managers and customers actively utilize the limited resources efficiently and effectively to accomplish environment-friendly goals and objectives. The study focuses on investigating the moderating role of diffidence between Green HRM, among eco-friendly behavior and Employee Performance of frontline employees of the hospitality sector. Two hundred ten individuals particapted in the research from hospitality sector with regard to examine green HRM policies of employees along with their influence on consumer buying behvaiour. Frontline employees incorporated the data on HRM performance, eco-friendly behavior, and diffidence. Besides, consumers gave their opinion on consumer buying behavior. The study’s findings revealed that Green HRM, aka Green HRM, directly impacts consumer behavior. In addition to this diffidence moderates the relationship between Green HRM and employee performance and employee eco-friendly behavior. Besides, future studies can explore the clothing and banking sector as the current study was conducted in fast food sector.

Summary: Many acute and chronic diseases affect the distal lung alveoli. Alveolar epithelial cell (AEC) lines are needed to better model these diseases. We used de-identified human remnant transplant lungs to develop a method to establish AEC lines. The lines grow well in 2-dimensional (2D) culture as epithelial monolayers expressing lung progenitor markers. In 3-dimensional (3D) culture with fibroblasts, Matrigel, and specific media conditions, the cells form alveolar-like organoids expressing mature AEC markers including aquaporin 5 (AQP5), G-protein-coupled receptor class C group 5 member A (GPRC5A), and surface marker HTII280. Single-cell RNA sequencing of an AEC line in 2D versus 3D culture revealed increased cellular heterogeneity and induction of cytokine and lipoprotein signaling in 3D organoids. Our approach yields lung progenitor lines that retain the ability to differentiate along the alveolar cell lineage despite long-term expansion and provides a valuable system to model and study the distal lung in vitro.

With population aging, diabetes mellitus and cognitive function decline are common health problems among older adults worldwide. This longitudinal study is aimed at estimating the longitudinal associations of newly diagnosed prediabetes and diabetes status with cognitive function among Chinese adults aged 45 years and older and evaluating the clinical risk factors associated with cognitive function. Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS). A total of 8716 participants meeting the inclusion criteria were enrolled between 2011 and 2012 at baseline, and 6125 participants completed the follow-up survey in 2018. Cognitive function, newly diagnosed diabetic status, depression, body mass index, and clinical and biochemical measurements were collected. At baseline, the mean age of the participants was 58.93 (SD: 9.76) years, 3987 (45.7%) were males, 1802 (20.7%) participants were newly diagnosed with prediabetes, and 935 (10.7%) were diabetes patients. After adjusting for control variables, diabetes was a significant risk factor for subsequent cognitive decline (unstandardized βestimate=−0.50, 95%CI=−0.98~−0.02). Subgroup analyses found that the association of diabetes with cognitive decline was significant in females. Stratification analyses found that among prediabetes patients, triglyceride concentrations were negatively associated with cognitive function; among diabetes patients, high-sensitivity C-reactive protein was significantly associated with cognitive decline. The newly diagnosed diabetes status at baseline was associated with subsequent cognitive decline among middle-aged and elderly Chinese, especially in females. The management of triglycerides through lifestyle modification for prediabetes and specific adjunctive anti-inflammatory therapy for diabetes might benefit cognitive performance.

Non-invasive detection of unstable angina (UA) patients with different severity of coronary lesions remains challenging. This study aimed to identify plasma lipoproteins (LPs) that can be used as potential biomarkers for assessing the severity of coronary lesions, determined by the Gensini score (GS), in UA patients. We collected blood plasma from 67 inpatients with angiographically normal coronary arteries (NCA) and 230 UA patients, 155 of them with lowGS (GS ≤ 25.4) and 75 with highGS (GS > 25.4), and analyzed it using proton nuclear magnetic resonance spectroscopy to quantify 112 lipoprotein variables. In a logistic regression model adjusted for four well-known risk factors (age, sex, body mass index and use of lipid-lowering drugs), we tested the association between each lipoprotein and the risk of UA. Combined with the result of LASSO and PLS-DA models, ten of them were identified as important LPs. The discrimination with the addition of selected LPs was evaluated. Compared with the basic logistic model that includes four risk factors, the addition of these ten LPs concentrations did not significantly improve UA versus NCA discrimination. However, thirty-two selected LPs showed notable discrimination power in logistic regression modeling distinguishing highGS UA patients from NCA with a 14.9% increase of the area under the receiver operating characteristics curve. Among these LPs, plasma from highGS patients was enriched with LDL and VLDL subfractions, but lacked HDL subfractions. In summary, we conclude that blood plasma lipoproteins can be used as biomarkers to distinguish UA patients with severe coronary lesions from NCA patients.

Ticks carry and transmit a variety of pathogens, which are very harmful to humans and animals. To characterize the microbial interactions in ticks, we analysed the microbiota of the hard ticks, Dermacentor silvarum, Ixodes persulcatus, and Haemaphysalis concinna, using 16S rRNA, showing that microbial interactions are underappreciated in terms of shaping arthropod microbiomes. The results show that the bacterial richness and microbiota structures of these three tick species had significant differences. Interestingly, the bacterial richness (Chao1 index) of all ticks decreased significantly after they became engorged. All the operational taxonomic units (OTUs) were assigned to 26 phyla, 67 classes, 159 orders, 279 families, and 627 genera. Microbial interactions in D. silvarum demonstrated more connections than in I. persulcatus and H. concinna. Bacteria with a high abundance were not important families in microbial interactions. Positive interactions of Bacteroidaceae and F_Solibacteraceae Subgroup 3 with other bacterial families were detected in all nine groups of ticks. This study provides an overview of the microbiota structure and interactions of three tick species and improves our understanding of the role of the microbiota in tick physiology and vector capacity, thus being conducive to providing basic data for the prevention of ticks and tick-borne diseases.

Combined application of biochar and nitrogen (N) fertilizer has the potential to reduce N losses from soil. However, the effectiveness of biochar amendment on N management can vary with biochar types with different physical and chemical properties. This study aimed to assess the effect of two types of hardwood biochar with different ash contents and cation exchange capacity (CEC) on soil N mineralization and nitrous oxide (N2O) production when applied alone and in combination with N fertilizer. Soil samples collected from a temperate pasture system were amended with two types of biochar (B1 and B2), urea, and urea plus biochar, and incubated for 60 days along with soil control (without biochar or urea addition). Soil nitrate N, ammonium N, ammonia-oxidizing bacteria amoA gene transcripts, and N2O production were measured during the experiment. Compared to control, addition of B1 (higher CEC and lower ash content) alone decreased nitrate N concentration by 21% to 45% during the incubation period while the addition of B2 (lower CEC and higher ash content) alone increased the nitrate N concentration during the first 10 days. Biochar B1 also reduced the abundance of amoA transcripts by 71% after 60 days. Compared to B1 + urea, B2 + urea resulted in a significantly greater initial increase in soil ammonium and nitrate N concentrations. However, B2 + urea had a significantly lower 60-day cumulative N2O emission compared to B1 + urea. Overall, when applied with urea, the biochar with higher CEC reduced ammonification and nitrification rates, while biochar with higher ash content reduced N N2O production. Our study demonstrated that biochar has the potential to enhance N retention in soil and reduce N2O emission when it is applied with urea, but the specific effects of the added biochar depend on its physical and chemical properties.

Pathogenic microorganism analysis based on next-generation sequencing technology is an important tool for clinical diagnosis, public health surveillance, and outbreak investigation. However, scientific researchers without the relevant background lack the time, training, or infrastructure to use large data sets or install and use command line tools. Therefore, the bioinformatic team at the Chinese Center for Disease Control and Prevention developed the Microbial Data Analysis Cloud Platform (MDACP) as a safe, professional, and efficient pathogen genetic data analysis platform for rapid microbial data mining, such as for candidate pathogen detection, genome typing, and traceability. MDACP is a web service system based on the Docker platform and can be used for data analysis on various operating systems. The platform focuses on pathogen analysis and continuously develops new analysis processes according to the analysis needs of the users. This platform has a friendly user interface and is easy to operate, allowing users to submit data through data pages or graphical clients, flexibly control parameters according to data conditions, and analyze data in parallel with multiple tasks. Researchers can quickly carry out bioinformatic analyses without coding work, promote follow-up research and information mining of projects, and improve the utilization of big data in the field of disease control. MDACP enables research personnel to conduct data analysis and management and assists clinicians and disease control personnel with mining information, such as pathogen identification, classification, and traceability.

Background Extracellular superoxide dismutase (Ec‐SOD) is a major scavenger of reactive oxygen species. However, its relationships with abnormal left ventricular (LV) geometry patterns and heart failure (HF) are still unknown in patients with cardiovascular disease. Methods and Results A cross‐sectional study was carried out to evaluate the association of serum Ec‐SOD activity with LV geometry, as well as HF in 1047 patients with cardiovascular disease. All participants underwent standard echocardiography examination and measurement of serum Ec‐SOD activity. Overall, we found a significantly decreased trend of serum Ec‐SOD activity from subjects with normal geometry (147.96±15.94 U/mL), subjects with abnormal LV geometry without HF (140.19±20.12 U/mL), and subjects with abnormal LV geometry and overt HF (129.32±17.92 U/mL) after adjustment for potential confounders (P for trend

Abstract Background Pathogen detection in clinical samples based on 16S metagenomic sequencing technology in microbiology laboratories is an important strategy for clinical diagnosis, public health surveillance, and investigations of outbreaks. However, the implementation of the technology is limited by its accuracy and the time required for bioinformatics analysis. Therefore, a simple, standardized, and rapid analysis pipeline from the receipt of clinical samples to the generation of a test report is needed to increase the use of metagenomic analyses in clinical settings. Results We developed a comprehensive bioinformatics analysis pipeline for the identification of pathogens in clinical samples based on 16S metagenomic sequencing data, named 16SPIP. This pipeline offers two analysis modes (fast and sensitive mode) for the rapid conversion of clinical 16S metagenomic data to test reports for pathogen detection. The pipeline includes tools for data conversion, quality control, merging of paired-end reads, alignment, and pathogen identification. We validated the feasibility and accuracy of the pipeline using a combination of culture and whole-genome shotgun (WGS) metagenomic analyses. Conclusions 16SPIP may be effective for the analysis of 16S metagenomic sequencing data for real-time, rapid, and unbiased pathogen detection in clinical samples.

The aim of this article is to establish sufficient conditions for the approximate controllability of fractional control systems with time delay in Hilbert spaces. By the technique of sequential approach, we prove that the fractional control systems with time delay are approximately controllable. Finally, an example is provided to illustrate our main results.

In this study, natural manganese oxides (MnOx), an environmental material with high redox potential, were used as a promising low-cost oxidant to degrade the widely used dyestuff methylene blue (MB) in aqueous solution. Although the surface area of MnOx was only 7.17 m2 g−1, it performed well in the degradation of MB with a removal percentage of 85.6% at pH 4. It was found that MB was chemically degraded in a low-pH reaction system and the degradation efficiency correlated negatively with the pH value (4–8) and initial concentration of MB (10–50 mg l−1), but positively with the dosage of MnOx (1–5 g l−1). The degradation of MB fitted well with the second-order kinetics. Mathematical models were also built for the correlation of the kinetic constants with the pH value, the initial concentration of MB and the dosage of MnOx. Furthermore, several transformation products of MB were identified with HPLC-MS, which was linked with the bond energy theory to reveal that the degradation was initiated with demethylation.

The goal of this paper is to study approximate controllability for control systems driven by abstract second order nonlinear evolution hemivariational inequalities in Hilbert spaces. First, the concept of a mild solution of our problem is defined by using the cosine operator theory and the generalized Clarke subdifferential. Next, the existence and the approximate controllability of mild solutions are formulated and proved by means of the fixed points strategy. Finally, an example is provided to illustrate our main results.

The aim of the present study was to evaluate the soft tissue bond strength of a newly developed, monomeric, biomimetic, tissue adhesive called phosphoserine modified cement (PMC). Two types of PMCs were evaluated using lap shear strength (LSS) testing, on porcine skin: a calcium metasilicate (CS1), and alpha tricalcium phosphate (αTCP) PMC. CS1 PCM bonded strongly to skin, reaching a peak LSS of 84, 132, and 154 KPa after curing for 0.5, 1.5, and 4 h, respectively. Cyanoacrylate and fibrin glues reached an LSS of 207 kPa and 33 kPa, respectively. αTCP PMCs reached a final LSS of ≈110 kPa. In soft tissues, stronger bond strengths were obtained with αTCP PMCs containing large amounts of amino acid (70–90 mol%), in contrast to prior studies in calcified tissues (30–50 mol%). When αTCP particle size was reduced by wet milling, and for CS1 PMCs, the strongest bonding was obtained with mole ratios of 30–50% phosphoserine. While PM-CPCs behave like stiff ceramics after setting, they bond to soft tissues, and warrant further investigation as tissue adhesives, particularly at the interface between hard and soft tissues.

The influence of the cellulose nanocrystal (CNC) aspect ratio (L/d) distribution and ionic strength of different salts on the L/d estimation by viscosity measurement were investigated. The L/d distribution was controlled by mixing two CNC, with different L/d, which were prepared by acid hydrolysis from wood and bacterial cellulose. The results demonstrated that the L/d distribution did not affect the accuracy of the CNC L/d estimated by viscosity measurements using the Batchelor equation, and the calculated L/d was the number-average L/d. Moreover, monovalent (NaCl), divalent (CaCl2), and trivalent (AlCl3) salts were chosen to study the influence of ionic strength on the CNC L/d estimation by viscosity measurement. It was found that NaCl and CaCl2 could be added to the CNC suspension to screen the electro-viscous effect and estimate the actual physical CNC L/d by viscosity measurement, and the content of NaCl and CaCl2 can be predicted by the Debye−Hückel theory. However, a small amount of AlCl3 induced CNC aggregation and increased intrinsic viscosity and predicted L/d.

This paper is concerned with the distributed field estimation problem using a sensor network, and the main purpose is to design a local filter for each sensor node to estimate a spatially-distributed physical process using the measurements of the whole network. The finite element method is employed to discretize the infinite dimensional process, which is described by a partial differential equation, and an approximate finite dimensional linear system is established. Due to the sparsity on the spatial distribution of the source function, the ℓ 1 -regularized H ∞ filtering is introduced to solve the estimation problem, which attempts to provide better performance than the classical centralized Kalman filtering. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed method.

BACKGROUND:Leptospirosis is one of the most important neglected tropical infectious diseases worldwide. Icterohaemorrhagiae has been throughout recent history, and still is, the predominant serogroup of this pathogen in China. However, very little in detail is known about the serovars or genotypes of this serogroup. METHODOLOGY/PRINCIPAL FINDINGS:In this study, 120 epidemic strains from five geographically diverse regions in China collected over a 50 year period (1958~2008), and 8 international reference strains characterized by 16S rRNA sequencing and MLST analysis. 115, 11 and 2 strains were identified as L. interrogans, L. borgpetersenii, and L. kirschneri, respectively. 17 different STs were identified including 69 ST1 strains, 18 ST17, 18 ST128, 9 ST143 and 2 ST209. The remaining 12 strains belonged to 12 different STs. eBURST analysis demonstrated that, among the clonal complexes isolated (CCs), CC1 accounted for 73.3% (88/120) strains representing three STs: ST1, ST128 and ST98. ST1 was the most likely ancestral strain of this CC, followed by singleton CC17 (17/120) and CC143 (11/120). Further analysis of adding 116 serogroup Icterohaemorrhagiae strains in the MLST database and studies previously described using global eBURST analysis and MST dendrogram revealed relatively similar ST clustering patterns with five main CCs and 8 singletons among these 244 strains. CC17 was found to be the most prevalent clone of pathogenic Leptospira circulating worldwide. This is the first time, to our knowledge, that ST1 and ST17 strains were distributed among 4 distinct serovars, indicating a highly complicated relationship between serovars and STs. CONCLUSIONS/SIGNIFICANCE:Our studies demonstrated a high level of genetic diversity in the serogroup Icterohaemorrhagiae strains. Distinct from ST17 or ST37 circulating elsewhere, ST1 included in CC1, has over the past 50 years or so, proven to be the most prevalent ST of pathogenic leptospires isolated in China. Moreover, the complicated relationship between STs and serovars indicates an urgent need to develop an improved scheme for Leptospira serotyping.

We consider the control systems governed by semilinear differential equations with Riemann-Liouville fractional derivatives in Banach spaces. Firstly, by applying fixed point strategy, some suitable conditions are established to guarantee the existence and uniqueness of mild solutions for a broad class of fractional infinite dimensional control systems. Then, by using generally mild conditions of cost functional, we extend the existence result of optimal controls to the Riemann-Liouville fractional control systems. Finally, a concrete application is given to illustrate the effectiveness of our main results.

Candesartan is an antihypertensive agent that acts on an angiotensin II receptor. Candesartan cilexetil is a prodrug that is converted into the active form of candesartan during intestinal absorption. This study aimed to assess the pharmacokinetics and bioequivalence of a reference and a test formulation of candesartan cilexetil tablets in healthy Chinese volunteers. A randomized, open-label, single-dose, crossover study was conducted with two treatment periods. Forty-eight healthy Chinese volunteers participated under fasted conditions. Qualified subjects were randomly divided into two groups (1:1 ratio) to receive either the test or reference formulation first. A washout period of 14 days separated the administration of the two formulations. Blood samples were collected at specific time points and analyzed for candesartan concentration using Ultra High-Performance Liquid Chromatography Tandem Mass Spectrometry (UPLC-MS/MS). The maximum concentration (Cmax), the AUC from time zero to the last measured time point (AUC0-t) and the AUC from time zero to infinity (AUC0-∞) fell within the bioequivalence range of 80% to 125%. These results suggest that the test and reference formulations of candesartan cilexetil tablets are bioequivalent, meaning they have similar rates and extents of absorption in healthy Chinese volunteers. No serious adverse events or side effects were reported throughout the study. [ABSTRACT FROM AUTHOR]

In this paper, we are concerned with a generalized evolution dynamical system, called fractional differential variational-hemivariational inequality (FDVHVI, for short), which is composed of a nonlinear fractional evolution inclusion and a time-dependent mixed variational-hemivariational inequality in the framework of Banach spaces. The objective of this paper is four fold. The first one is to investigate the nonemptiness as well as the compactness of the mild solutions set to the FDVHVI. The second aim is to study the optimal control problems described by the FDVHVI. The third goal is to establish the well-posedness results of the FDVHVI, including the existence, uniqueness, and stability. Furthermore, the sensitivity analysis of a perturbed problem associated to the FDVHVI with respect to the initial state and the two parameters is also obtained. Finally, a comprehensive fractional model is given to illustrate the validity of our main results. [ABSTRACT FROM AUTHOR]

Deep neural networks have recently made remarkable achievements in computer vision applications. However, the high computational requirements needed to achieve accurate inference results can be a significant barrier to deploying DNNs on resource-constrained computing devices, such as those found in the Internet-of-things. In this work, we propose a fresh approach called adaptive channel skipping (ACS) that prioritizes the identification of the most suitable channels for skipping and implements an efficient skipping mechanism during inference. We begin with the development of a new gating network model, ACS-GN, which employs fine-grained channel-wise skipping to enable input-dependent inference and achieve a desirable balance between accuracy and resource consumption. To further enhance the efficiency of channel skipping, we propose a dynamic grouping convolutional computing approach, ACS-DG, which helps to reduce the computational cost of ACS-GN. The results of our experiment indicate that ACS-GN and ACS-DG exhibit superior performance compared to existing gating network designs and convolutional computing mechanisms, respectively. When they are combined, the ACS framework results in a significant reduction of computational expenses and a remarkable improvement in the accuracy of inferences. [ABSTRACT FROM AUTHOR]

Abstract Background Idiopathic acute transverse myelitis (IATM) is a focal inflammatory disorder of the spinal cord that results in motor, sensory, and autonomic dysfunction. However, the comparative analysis of MRI-negative and MRI-positive in IATM patients were rarely reported. Objectives The purpose of this study was to compare MRI-negative with MRI-positive groups in IATM patients, analyze the predictors for a poor prognosis, thus explore the relationship between MRI-negative and prognosis. Methods We selected 132 patients with first-attack IATM at the First Affiliated Hospital of Nanchang University from May 2018 to May 2022. Patients were divided into MRI-positive and MRI-negative group according to whether there were responsible spinal MRI lesions, and good prognosis and poor prognosis based on whether the EDSS score ≥ 4 at follow-up. The predictive factors of poor prognosis in IATM patients was analyzed by logistic regression models. Results Of the 132 patients, 107 first-attack patients who fulfilled the criteria for IATM were included in the study. We showed that 43 (40%) patients had a negative spinal cord MRI, while 27 (25%) patients were identified as having a poor prognosis (EDSS score at follow-up ≥ 4). Compared with MRI-negative patients, the MRI-positive group was more likely to have back/neck pain, spinal cord shock and poor prognosis, and the EDSS score at follow-up was higher. We also identified three risk factors for a poor outcome: absence of second-line therapies, high EDSS score at nadir and a positive MRI result. Conclusions Compared with MRI-negative group, MRI-positive patients were more likely to have back/neck pain, spinal cord shock and poor prognosis, with a higher EDSS score at follow-up. The absence of second-line therapies, high EDSS score at nadir, and a positive MRI were risk factors for poor outcomes in patients with first-attack IATM. MRI-negative patients may have better prognosis, an active second-line immunotherapy for IATM patients may improve clinical outcome.

The recent proliferation of Fifth-Generation (5G) networks and Sixth-Generation (6G) networks has given rise to Vehicular Crowd Sensing (VCS) systems which solve parking collisions by effectively incentivizing vehicle participation. However, instead of being an isolated module, the incentive mechanism usually interacts with other modules. Based on this, we capture this synergy and propose a Collision-free Parking Recommendation (CPR), a novel VCS system framework that integrates an incentive mechanism, a non-cooperative VCS game, and a multi-agent reinforcement learning algorithm, to derive an optimal parking strategy in real time. Specifically, we utilize an LSTM method to predict parking areas roughly for recommendations accurately. Its incentive mechanism is designed to motivate vehicle participation by considering dynamically priced parking tasks and social network effects. In order to cope with stochastic parking collisions, its non-cooperative VCS game further analyzes the uncertain interactions between vehicles in parking decision-making. Then its multi-agent reinforcement learning algorithm models the VCS campaign as a multi-agent Markov decision process that not only derives the optimal collision-free parking strategy for each vehicle independently, but also proves that the optimal parking strategy for each vehicle is Pareto-optimal. Finally, numerical results demonstrate that CPR can accomplish parking tasks at a 99.7% accuracy compared with other baselines, efficiently recommending parking spaces.