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The present study aims to examine the process through which empowering leadership shapes employees’ work engagement and in-role performance by facilitating job-crafting behaviors, specifically seeking resources, seeking challenges, and reducing demands. Based on the extensive data from 733 Chinese employees across various organizations located predominantly in Chongqing and Xi’an, China, we carried out different types of statistical analysis such as confirmatory factor analysis (CFA) and structural equation modeling (SEM) to examine the relationships among empowering leadership, specific job-crafting behaviors, work engagement and in-role performance, test our hypothesis and our conceptual model. The results from structural equation modeling (SEM) suggested that empowering leadership was positively related to employees’ work engagement and in-role performance; empowering leadership was positively related to employees’ job crafting (seeking resources, seeking challenges and reducing demands); seeking resources, seeking challenges and reducing demands were positively related to in-role performance, and seeking challenges and reducing demands were positively related to work engagement. In the relationship between empowering leadership and in-role performance, seeking resources serves as a mediating factor. Similarly, seeking challenges mediates the association between empowering leadership and both work engagement and in-role performance. Furthermore, reducing demands mediates the links between empowering leadership and both work engagement and in-role performance. The implications of these findings are subsequently discussed.

(1) Background: HBV-DNA is an essential clinical indicator of primary hepatocellular carcinoma (HCC) prognosis. Our study aimed to investigate the prognostic implication of a low load of HBV-DNA in HCC patients who underwent local treatment. Additionally, we developed and validated a nomogram to predict the recurrence of patients with low (20–100 IU/mL) viral loads (L-VL). (2) Methods: A total of 475 HBV-HCC patients were enrolled, including 403 L-VL patients and 72 patients with very low (p = 0.024). The content of the nomogram included gender, BCLC stage, Glob, and MLR. The C-index (0.682 vs. 0.609); 1-, 3-, and 5-year AUCs (0.729, 0.784, and 0.783, vs. 0.631, 0.634, the 0.665); calibration curves; and decision curve analysis (DCA) curves of the training and validation cohorts proved the excellent predictive performance of the nomogram. There was a statistically significant difference in RFS between the low-, immediate-, and high-risk groups both in the training and validation cohorts (p < 0.001); (4) Conclusions: Patients with L-VL had a worse prognosis. The nomogram developed and validated in this study has the advantage of predicting patients with L-VL.

Subsurface drainage pipes covered with filters and geotextiles are the key to preventing clogging and ensuring efficient drainage. To improve the salt discharge efficiency of these subsurface drainage pipes, different layers of geotextiles were set outside the pipes with the aid of uniform gravel filters. This paper reports our findings from laboratory simulation of subsurface drainage pipes and experiments. The study examined the influence of different layers of geotextiles on the drainage efficiency, salt discharge effects of subsurface drainage pipes, and the effect of superimposed geotextiles on the salt drainage efficiency as well as the anti-clogging effect of subsurface drainage pipes. The results are as follows: (1) The geotextile and filter material wrapped around the subsurface pipe facilitated the movement of water towards the subsurface pipe, which could promote the salt discharge of the subsurface pipe. However, in the single leaching experiment, the reduction in soil pH was not significant for different scenarios. (2) The salt removal rate of the geotextile-wrapped subsurface pipes was more than 95%. The salt removal rate of the double-layer geotextile scenario was the highest (96.7%), and the total salt content of soil profiles was 8.3% and 31.3% lower than those of the single-layer and triple-layer geotextile scenarios, respectively. The drainage efficiency of the double-layer geotextile scenario was the highest, and the salt distribution in the 0–60 cm profile was relatively uniform, ranging from 2.3 to 3.0 g∙kg−1. (3) The clogging in the triple-layer geotextile scenario was caused by the geotextile, i.e., a dense filter cake layer formed on the surface of the geotextile. The clogging in the single-layer and double-layer geotextile scenarios was the clogging of the geotextile itself, i.e., soil particles retained in the fiber structure of geotextiles. (4) In the case of the single-layer and double-layer geotextile scenarios, the soil particles failed to completely clog the selected geotextiles, and there were still a large number of pores retained. The double-layer geotextiles integrate filtration, clogging prevention, and drainage promotion to provide the best salt drainage with the subsurface pipe. This study reveals the influence of the filter on soil water salt and salt discharge and provides a theoretical explanation and technical justification for the application of the subsurface pipes salt discharge technology in saline soil ameliorate.

Subsurface pipes covered with geotextiles and filters are essential for preventing clogging and ensuring efficient drainage. To address low salt discharge efficiency due to subsurface drainage pipes (SDPs) clogging easily, sand gravel, straw, and combined sand gravel–straw were set above SDPs, respectively, within a setting of uniform geotextiles. The influences of different filter materials on the drainage efficiency and salt discharge effect of the SDPs, as well as the effects of different filter materials on the salt drainage efficiency and anti-siltation effect of the SDPs were studied by performing simulation experiments in a laboratory. The results confirmed the following: (1) The salt removal rates of the SDPs externally wrapped with materials exceeded 95%. The subsurface pipe treated with the sand gravel filter material had the highest desalting rate (93.69%) and soil profiles with total salt contents that were 17.7% and 20.5% lower than those treated with the straw and combined sand gravel–straw materials, respectively. (2) The soil salinity of the sand gravel filter material around the SDPs was between 1.57 and 3.6 g/kg, and the drainage rate (R) was 0.97, so its salt-leaching effect was the best. (3) The sand gravel filter material increased the characteristic particle size of the soil above the SDP by 8.4%. It could effectively intercept coarse particles, release fine particles, and facilitate the formation of a highly permeable soil skeleton consisting of coarse particles, such as sand particles surrounding the soil. (4) The use of the straw filter material produced dense filter cake layers on the upstream surfaces of the geotextiles. When the sand gravel and combined sand gravel–straw filter materials were used, soil particles remained in the geotextile fiber structure, and a large number of pores were still retained. Therefore, the sand gravel filter material was the most suitable for the treatment of Yinbei saline–alkali soil in Ningxia Hui Autonomous Region.

Extracting relation quintuple and feature words from unstructured text is a prelude to the construction of the scientific knowledge base. At present, the prior works use explicit clues between entities to study this task but ignore the use and the association of the feature words. In this work, we propose a new method to generate self-adaptive feature words from the original text for every single sample. These words can add additional correlation information to the knowledge graph. We allow the model to generate a new word representation and apply it to the original sentence to judge the relation type and locate the head and tail of the relation quintuple. Compared with the previous works, the feature words increase the flexibility of relying on information and improve the explanatory ability. Extensive experiments on scientific field datasets illustrate that the self-adaptive feature words method (SAFW) is good at ferreting out the unique feature words and obtaining the core part for the quintuple. It achieves good performance on four public datasets and obtains a markable performance improvement compared with other baselines.

Two new phenylspirodrimanes, stachybotrins K and L (1 and 2), together with eight known analogues (3–10), were isolated from deep-sea-derived Stachybotrys sp. MCCC 3A00409. Their structures were determined by extensive NMR data and mass spectroscopic analysis. Absolute configurations of new compounds were determined through a comparison of their circular dichroism (CD) spectra with other reported compounds. The possible reversal effects of all compounds were assayed in the resistant cancer cell lines. Stachybotrysin B (8) can reverse multidrug resistance (MDR) in ABCB1-overexpression cells (KBv200, Hela/VCR) at the non-cytotoxic concentration. Doxorubicin accumulation assay and molecular-docking analysis reveal that the mechanism of its reversal MDR effect may be related to the increase in the intracellular concentration of substrate anticancer drugs.

Chronic hepatitis B virus (HBV) infection is a worldwide public health threat that results in huge morbidity and mortality. Late diagnosis and delayed treatment of HBV infections can cause irreversible liver damages and occurrence of cirrhosis and hepatocellular carcinoma (HCC). Detection of the presence and activity of HBV are the cornerstones of diagnosis and management in HBV related disease. Moreover, comprehensive knowledge of the mechanisms regulating HBV immunobiology is pivotal for managing diseases related with HBV. Here we tried to categorize and illustrate the classical and novel approaches used for diagnosis of HBV. Also, we reviewed our current knowledge on the immunobiology of HBV related HCC.

Neurodevelopmental and neurodegenerative disorders are primarily characterized by serious structural and functional changes in excitatory glutamatergic synapses in the brain, resulting in many synaptic deficits and aberrant synapse loss. It is a big challenge to reverse these synaptic impairments as a treatment for neurological diseases in the field. Extensive research on glutamate receptors as therapeutic targets has been done but with little success shown in human trials. PSD-95-like MAGUK proteins perform a pivotal role in regulating the trafficking and stability of glutamate receptors that are important to postsynaptic structure and function. MAGUK and MAGUK-modulated synaptic pathways are becoming promising candidates for developing therapeutic targets. As a MAGUK protein, SAP102 is not understood well compared to PSD-95. Here, we review the current research on SAP102 including its synaptic functions and regulation, especially its expression and functions in the early stage of synaptogenesis and the association with neurodevelopmental disorders. This review presents valuable information for future structural and functional studies of SAP102 to reveal its roles in young and mature neurons. It provides clues for developing potential remedies to reverse synaptic impairments and strategies to grow new neurons.

Background We aimed to evaluate the relationships between the magnitude of systolic blood pressure (SBP) reduction and achieved SBP in the acute phase of ischemic stroke onset and subsequent clinical outcomes. Methods and Results This study was a secondary analysis of CATIS (China Antihypertensive Trial in Acute Ischemic Stroke), a multicenter randomized controlled trial of 4071 patients with acute ischemic stroke. SBP reduction was defined as the proportional SBP changes from baseline to 24 hours after randomization, and achieved SBP was the mean of SBP measurements at day 7. The study outcomes included functional outcome of death or major disability (modified Rankin Scale score ≥3), death, and cardiovascular events at 3 months after recruitment. Compared with the reference group of increase or no change in SBP within the first 24 hours, the odds ratios (95% CIs) of functional outcome of death or major disability were 0.62 (0.47–0.83) and 0.61 (0.42–0.87) for the reduction of 11% to 20% and >20%, respectively. Compared with participants in highest achieved SBP group (≥160 mm Hg) at day 7, odds ratios or hazard ratios of lower achieved SBP (

Background Chitinase‐3 like protein 1 (CHI3L1, YKL‐40) was reported to be implicated in the development of ischemic stroke, but whether the association between them was causal remained unclear. We conducted a 2‐sample Mendelian randomization study to explore the associations of genetically determined plasma YKL‐40 with ischemic stroke and its subtypes (large artery stroke, small vessel stroke, and cardioembolic stroke). Methods and Results Based on genome‐wide association study data of 3394 European‐descent individuals, we selected 13 single‐nucleotide polymorphisms associated with plasma YKL‐40 as genetic instruments. Summary data about ischemic stroke and its subtypes were obtained from the Multiancestry Genome‐wide Association Study of Stroke Consortium, involving 34 217 ischemic stroke cases and 406 111 controls of European ancestry. We used the inverse‐variance weighted method followed by a series of sensitivity analyses to assess the causal associations of plasma YKL‐40 with ischemic stroke and its subtypes. The primary analysis showed that genetically determined high YKL‐40 levels were associated with increased risks of large artery stroke (odds ratio [OR], 1.08 [95% CI, 1.04–1.12]; P=1.73×10−4) and small vessel stroke (OR, 1.05 [95% CI, 1.01–1.09]; P=7.96×10−3) but not with ischemic stroke or cardioembolic stroke. Sensitivity analyses further confirmed these associations, and Mendelian randomization‐Egger indicated no evidence of genetic pleiotropy. In addition, supplementary analysis based on the summary data from the Olink proximity extension assay cardiovascular I (Olink CVD‐I) panel showed that high YKL‐40 levels were positively associated with the risks of large artery stroke (OR, 1.15 [95% CI, 1.08–1.22]; P=4.16×10−6) but not with small vessel stroke. Conclusions Genetically determined high plasma YKL‐40 levels were causal associated with increased risks of large artery stroke.

Abstract. Background:. Cluster of differentiation 8 (CD8 T) cells play critical roles in eradicating human immunodeficiency virus (HIV)-1 infection, but little is known about the effects of T cells expressing CD8 at low levels (CD8low) or high levels (CD8high) on HIV-1 replication inhibition after HIV-1 invasion into individual. Methods:. Nineteen patients who had been acutely infected with HIV-1 (AHI) and 20 patients with chronic infection (CHI) for ≥2 years were enrolled in this study to investigate the dynamics of the quantity, activation, and immune responses of CD3+CD8low T cells and their counterpart CD3+CD8high T cells at different stages of HIV-1 infection. Results:. Compared with healthy donors, CD3+CD8low T cells expanded in HIV-1-infected individuals at different stages of infection. As HIV-1 infection progressed, CD3+CD8low T cells gradually decreased. Simultaneously, CD3+CD8high T cells was significantly reduced in the first month of AHI and then increased gradually as HIV-1 infection progressed. The classical activation of CD3+CD8low T cells was highest in the first month of AHI and then reduced as HIV-1 infection progressed and entered the chronic stage. Meanwhile, activated CD38−HLA-DR+CD8low T cells did not increase in the first month of AHI, and the number of these cells was inversely associated with viral load (r = −0.664, P = 0.004) but positively associated with the CD4 T-cell count (r = 0.586, P = 0.014). Increased programmed cell death protein 1 (PD-1) abundance on CD3+CD8low T cells was observed from the 1st month of AHI but did not continue to be enhanced, while a significant T cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibition motif (ITIM) domains (TIGIT) abundance increase was observed in the 12th month of infection. Furthermore, increased PD-1 and TIGIT abundance on CD3+CD8low T cells was associated with a low CD4 T-cell count (PD-1: r = −0.456, P = 0.043; TIGIT: r = −0.488, P = 0.029) in CHI. Nonetheless, the nonincrease in PD-1 expression on classically activated CD3+CD8low T cells was inversely associated with HIV-1 viremia in the first month of AHI (r = −0.578, P = 0.015). Notably, in the first month of AHI, few CD3+CD8low T cells, but comparable amounts of CD3+CD8high T cells, responded to Gag peptides. Then, weaker HIV-1-specific T-cell responses were induced in CD3+CD8low T cells than CD3+CD8high T cells at the 3rd and 12th months of AHI and in CHI. Conclusions:. Our findings suggest that CD3+CD8low T cells play an anti-HIV role in the first month of infection due to their abundance but induce a weak HIV-1-specific immune response. Subsequently, CD3+CD8low T-cell number decreased gradually as infection persisted, and their anti-HIV functions were inferior to those of CD3+CD8high T cells.

Abstract Background The triglyceride-glucose (TyG) index and triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, two simple surrogate indicators of insulin resistance, have been demonstrated to predict cardiovascular disease (CVD). However, very few studies have investigated their associations with CVD in European populations. Methods A total of 403,335 participants from the UK Biobank with data for TyG index and TG/HDL-C ratio and free from CVD at baseline were included. Cox models were applied to evaluate the association between TyG index and TG/HDL-C ratio and incident CVD. Mediation analyses were performed to evaluate the contribution of prevalent diabetes, hypertension, and dyslipidemia to observed associations. Results During a median follow-up of 8.1 years, 19,754 (4.9%) individuals developed CVD, including 16,404 (4.1%) cases of CHD and 3976 (1.0%) cases of stroke. The multivariable-adjusted hazard ratios of total CVD in higher quartiles versus the lowest quartiles were 1.05, 1.05, and 1.19, respectively, for TyG index, and 1.07, 1.13, and 1.29, respectively, for TG/HDL-C ratio. There were significant trends toward an increasing risk of CVD across the quartiles of TyG index and TG/HDL-C ratio. In mediation analyses, dyslipidemia, type 2 diabetes, and hypertension explained 45.8%, 27.0%, and 15.0% of TyG index’s association with CVD, respectively, and 40.0%, 11.8%, and 13.3% of TG/HDL-C ratio’s association with CVD, respectively. Conclusions Elevated baseline TyG index and TG/HDL-C ratio were associated with a higher risk of CVD after adjustment for the well-established CVD risk factors. These associations were largely mediated by greater prevalence of dyslipidemia, type 2 diabetes, and hypertension.

In recent years, AI and deep learning (DL) methods have been widely used for object classification, recognition, and segmentation of high-resolution multispectral remote sensing images. These DL-based solutions perform better compared with the traditional spectral algorithms but still suffer from insufficient optimization of global and local features of object context. In addition, failure of code-data isolation and/or disclosure of detailed eigenvalues cause serious privacy and even secret leakage due to the sensitivity of high-resolution remote sensing data and their processing mechanisms. In this article, class feature modules have been presented in the decoder part of an attention-based CNN network to distinguish between building and nonbuilding (background) area. In this way, context features of a focused object can be extracted with more details being processed while the resolution of images is maintained. The reconstructed local and global feature values and dependencies in the proposed model are maintained by reconfiguring multiple effective attention modules with contextual dependencies to achieve better results for the eigenvalue. According to quantitative results and their visualization, the proposed model has depicted better performance over others' work using two large-scale building remote sensing datasets. The F1-score of this model reached 87.91 and 89.58 on WHU Buildings Dataset and Massachusetts Buildings Dataset, respectively, which exceeded the other semantic segmentation models.

Abstract Background Breast cancer is the most common cancer among women with limited treatment options. To identify promising drug targets for breast cancer, we conducted a systematical Mendelian randomization (MR) study to screen blood metabolome for potential causal mediators of breast cancer and further predict target-mediated side effects. Methods We selected 112 unique blood metabolites from 3 large-scale European ancestry-based genome-wide association studies (GWASs) with a total of 147,827 participants. Breast cancer data were obtained from a GWAS in the Breast Cancer Association Consortium (BCAC), involving 122,977 cases and 105,974 controls of European ancestry. We conducted MR analyses to systematically assess the associations of blood metabolites with breast cancer, and a phenome-wide MR analysis was further applied to ascertain the potential on-target side effects of metabolite interventions. Results Two blood metabolites were identified as the potential causal mediators for breast cancer, including high-density lipoprotein cholesterol (HDL-C) (odds ratio [OR], 1.09; 95% confidence interval [CI], 1.06–1.12; P = 9.67 × 10−10) and acetate (OR, 1.24; 95% CI, 1.13–1.37; P = 1.35 × 10−5). In the phenome-wide MR analysis, lowering HDL-C might have deleterious effects on the risk of the circulatory system and foreign body injury, while lowering acetate had deleterious effects on mental disorders disease. Conclusions The present systematic MR analysis revealed that HDL-C and acetate may be the causal mediators in the risk of developing breast cancer. Side-effect profiles were characterized to help inform drug target prioritization for breast cancer prevention. HDL-C and acetate might be promising drug targets for preventing breast cancer, but they should be applied under weighting advantages and disadvantages.

Accurate tropical cyclone (TC) intensity and size estimation are key in disaster management and prevention. While great breakthroughs have been made in TC intensity estimation research, there is currently a lack of research on TC size reflecting TC influence radius. Therefore, we propose a lightweight multi-task learning model (TC-MTLNet) with adaptive loss balance to simultaneously estimate TC intensity and size. Adaptive loss balance is utilized to solve the problem of inconsistent convergence speed of TC intensity and size estimation tasks. The model based on four 2-D convolutions, four 3-D convolutions and three fully connected layers takes up less computational and storage space and improves the accuracy of TC intensity and size estimation by sharing knowledge among multiple tasks. In addition, due to the imbalanced distribution of TC samples, with significantly few low-intensity and high-intensity TC satellite data, this phenomenon poses a great challenge to TC intensity and size estimation. So, we utilize the influence of nearby samples to calibrate the sample density to weight the loss function to enable the model to be generalized to all samples. The result shows that the root-mean-square error (RMSE) of TC intensity estimation is $\text{8.40}\,\text{kts}$, which is 33.5% lower than that of the Advanced Dvorak Technique (ADT) and 11.4% lower than that of the deep learning method (3DAttentionTCNet). The mean absolute error (MAE) of the TC size estimation is $\text{20.89}\,\text{nmi}$, which is a 16% reduction compared to the Multi-Platform Tropical Cyclone Surface Winds Analysis (MTCSWA).

Abstract Background Subcutaneous panniculitis T-cell lymphoma (SPTCL) is a rare, cytotoxic T-cell lymphoma with which some patients have accompanying hemophagocytic syndrome (HPS). There is currently no standard treatment regimen. In the past, the most commonly used treatment was multidrug chemotherapy. In contrast, numerous case reports or small series suggest that immunosuppressive drugs could also be effective for some patients. Since this NHL subtype is extremely rare in children and adolescents, to improve the understanding of this disease and standardize its rational treatment, we retrospectively summarized the treatment regimens of 18 pathologically diagnosed children with SPTCL to compare the clinical efficacy of multidrug chemotherapy and immunomodulatory therapy. Results The median age of onset was 11.1 years. Painless subcutaneous nodules or skin patchy lesions were found in all patients, most commonly involving the lower extremities and/or trunk. Before January 1, 2019, the treatment was mainly chemotherapy, and 10 patients were initially treated with chemotherapy, among whom was one patient who progressed during initial treatment, was voluntarily discharged and was subsequently lost to follow-up, one patient who died of disease progression, and the remaining 8 patients who all achieved sustained remission, with a complete remission (CR) rate of 80% (8/10). Corticosteroids combined with cyclosporine A or ruxolitinib were the most common initial immunosuppressive agents at our center after January 1, 2019 and had a CR rate of 71.4% (5/7). In addition, 1 patient achieved partial remission (PR) during follow-up, and one had autologous hematopoietic stem cell transplantation (AHSCT) after 4 months of drug withdrawal. There were 7 patients (38.9%, one case in chemotherapy group and six cases in immunotherapy group) with HPS and 4/5 screened patients (80%) with positive HAVCR2 gene mutations. The median follow-up was 17 months. Conclusion The prognosis of SPTCL is relatively good. Previous multi-drug and long-term chemotherapy treatment has clear efficacy, and recent immunomodulatory therapy as pre-chemotherapy therapy can also benefit patients.

Background High plasma prekallikrein was reported to be associated with increased risks of stroke, but the causality for these associations remains unclear. We aimed to investigate the associations of genetically predicted plasma prekallikrein concentrations with all‐cause stroke, ischemic stroke, 3 ischemic stroke subtypes, and intracerebral hemorrhage (ICH) using a 2‐sample Mendelian randomization approach. Methods and Results Seven independent prekallikrein‐related single‐nucleotide polymorphisms were identified as genetic instruments for prekallikrein based on a genome‐wide association study with 1000 European individuals. The summary statistics for all‐cause stroke, ischemic stroke, and ischemic stroke subtypes were obtained from the Multiancestry Genome‐wide Association Study of Stroke Consortium with 40 585 cases and 406 111 controls of European ancestry. The summary statistics for ICH were obtained from the ISGC (International Stroke Genetics Consortium) with 1545 ICH cases and 1481 controls of European ancestry. In the main analysis, the inverse‐variance weighted method was applied to estimate the associations of plasma prekallikrein concentrations with all‐cause stroke, ischemic stroke, ischemic stroke subtypes, and ICH. Genetically predicted high plasma prekallikrein levels were significantly associated with elevated risks of all‐cause stroke (odds ratio [OR] per SD increase, 1.04 [95% CI, 1.02–1.06]; P=5.44×10−5), ischemic stroke (OR per SD increase, 1.05 [95% CI, 1.03–1.07]; P=1.42×10−5), cardioembolic stroke (OR per SD increase, 1.08 [95% CI, 1.03–1.12]; P=3.75×10−4), and small vessel stroke (OR per SD increase, 1.11 [95% CI, 1.06–1.17]; P=3.02×10−5). However, no significant associations were observed for genetically predicted prekallikrein concentrations with large artery stroke and ICH. Conclusions This Mendelian randomization study found that genetically predicted high plasma prekallikrein concentrations were associated with increased risks of all‐cause stroke, ischemic stroke, cardioembolic stroke, and small vessel stroke, indicating that prekallikrein might have a critical role in the development of stroke.

BackgroundSerum alpha-fetoprotein (AFP) is an important clinical indicator for screening, diagnosis, and prognosis of primary hepatocellular carcinoma (HCC). Our team’s previous study showed that patients with negative AFP at baseline and positive AFP at relapse had a worse prognosis (N-P). Therefore, the aim of our study was to develop and validate a nomogram for this group of patients.MethodsA total of 513 patients with HCC who received locoregional treatments at Beijing You’an Hospital, Capital Medical University, from January 2012 to December 2019 were prospectively enrolled. Patients admitted from 2012 to 2015 were assigned to the training cohort (n = 335), while 2016 to 2019 were in the validation cohort (n =183). The clinical and pathological features of patients were collected, and independent risk factors were identified using univariate and multivariate Cox regression analysis as a basis for developing a nomogram. The performance of the nomogram was evaluated by C-index, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) curves in the training and validation cohorts.ResultsThe content of the nomogram includes gender, tumor number, tumor size, lymphocyte, direct bilirubin (DBIL), gamma-glutamyl transferase (GGT), and prealbumin. The C-index (0.717 and 0.752) and 1-, 3-, and 5-year AUCs (0.721, 0.825, 0.845, and 0.740, 0.868, 0.837) of the training and validation cohorts proved the good predictive performance of the nomogram. Calibration curves and DCA curves suggested accuracy and net clinical benefit rates. The nomogram enabled to classify of patients with dynamic changes in AFP into three groups according to the risk of recurrence: low risk, intermediate risk, and high risk. There was a statistically significant difference in RFS between the three groups in the training and validation cohorts (P

The 5-year recurrence rate of thermal ablation for hepatocellular carcinoma (HCC) is high, and whether this treatment strategy induces systemic immune response remains elusive. This study aimed to investigate the effects of thermal ablation on HCC patients’ cytokine profiles and to explore the correlation of cytokine profiles with tumor recurrence after ablation. A total of 22 HCC patients were included in this prospective study. The levels of 27 cytokines in the peripheral blood of HCC patients were measured before ablation (baseline), week 1, and week 4 after ablation using a Bio-Plex Pro Human Cytokine 27-plex Assay kit. Cytokines showed different dynamic changing trends after ablation treatment. It was found that the level of IL-6 was significantly elevated at week 1 and returned to the baseline level at week 4 after ablation. The level of IL-10 was slightly reduced at week 1 and significantly decreased at week 4. The levels of MCP-1, macrophage inflammatory protein-1β (MIP-1β), and TNF-α were similarly reduced at week 1 and increased at week 4. The levels of IL-17, platelet-derived growth factor-BB (PDGF-BB), and regulated upon activation, normal T cell expressed and secreted (RANTES) showed little to no change at week 1 while an observable increase at week 4. Patients with a high IL-10 level (2.99 pg/ml) at baseline and low levels of TNF-α (20.4 pg/ml), PDGF-BB (107.78 pg/ml), and RANTES (2303.94 pg/ml) at week 4 were at risk of tumor recurrence during 1-year follow-up. The results suggested that thermal ablation activated systemic immune responses by changing the levels of cytokines. The results also demonstrated that measurement of IL-10 at baseline, TNF-α, PDGF-BB, and RANTES at week 4 after ablation might predict the risk of tumor recurrence.

Background We examined whether the relationship between baseline platelet count and clinical outcomes is modulated by HS‐CRP (high‐sensitivity C‐reactive protein) in patients with ischemic stroke. Methods and Results A total of 3267 patients with ischemic stroke were included in the analysis. The primary outcome was a combination of death and major disability at 1 year after ischemic stroke. Secondary outcomes included major disability, death, vascular events, composite outcome of vascular events or death, and an ordered 7‐level categorical score of the modified Rankin Scale at 1 year. Multivariate logistic regression and Cox proportional hazards regression models were used to assess the association between the baseline platelet count and clinical outcomes stratified by HS‐CRP levels when appropriate. There was an interaction effect of platelet count and HS‐CRP on the adverse clinical outcomes after ischemic stroke (all Pinteraction

IntroductionPlacental trophoblasts contribute to regulatory T (Treg) function via the programmed cell death-1 (PD-1)/PD-1 ligand 1 (PD-L1) pathway during normal pregnancy. Decreased expression of PD-L1 in trophoblasts was closely associated with Treg deficiency in the development of pregnancy failure. Thus, targeting PD-L1 might be a novel therapy to prevent pregnancy loss. However, the mechanisms for modulating the expression of PD-L1 in trophoblasts are an enigma.MethodsThe proportion of decidual Treg cells, and the profile of decidual macrophages (DMs) sampled from women with normal pregnancy (NP) and recurrent miscarriage (RM) were evaluated by flow cytometry. The expression of Yin and Yang 1 protein (YY1) and PD-L1 in human villous were measured by Immunohistochemistry (IHC), qRT-PCR and western blot. The determination of soluble PD-L1 (sPD-L1) in serum from NP and RM, and trophoblast conditioned media (TCM) was performed by the PD-L1 SimpleStep ELISA kit. Knockdown of YY1 was processed in the human trophoblast derived cell lines, HTR-8 and Bewo, with siYY1 transfection. Peripheral naïve CD4+ T cells were isolated from women with NP for the in vitro culture. The percentages of Treg cells differentiated from peripheral naïve CD4+ T cells were measured by flow cytometry. The interaction between YY1 and CD274 was proved by CHIP. The expression of inducible nitric oxide synthase (iNOS) in decidua was evaluated by IHC. The level of NO in serum from women with NP and RM was determined by the Griess reagent system. The effects of NO on YY1 were determined by the in vitro culture of HTR-8 cells with the NO donor, SNAP. The in vivo model comprising twelve pregnant mice and underwent different treatment. The percentages of Treg cells in murine uterus were measured by flow cytometry. Similarly, Western blot and IHC were performed to determine the expression of YY1 and PD-L1 in murine placenta.ResultsDecreased expression of YY1 and PD-L1 in trophoblasts and lower proportion of decidual Treg cells were observed in patients with RM. Knockdown of YY1 contributes to a lower expression of YY1 and PD-L1. Soluble PD-L1 in the supernatant from HTR-8 cells was also decreased with siYY1 administration. Lower Treg differentiation was observed in the presence of supernatant from HTR-8 cells treated with siYY1. CHIP analysis revealed that endogenous YY1 directly occupied the promoter region of the CD274 (PD-L1) gene. Accompanied with increased M1 DMs, higher NO was observed in serum sampled from patients with RM. In the presence of Reduced expression of YY1 and PD-L1 was observed in HTR-8 cells with the treatment of SNAP. Furthermore, less Treg differentiation was observed with SNAP treated TCM. Moreover, our in vivo data found that YY1 deficiency was associated with decreased PD-L1, which further resulting in less Treg differentiation and Treg deficiency at the maternal-fetal interface and increased embryo loss.DiscussionOur work found the modulatory capacity of YY1 on PD-L1 in trophoblasts during early pregnancy. Furthermore, reduced YY1 was supposed resulting from higher levels of NO produced from the M1 DMs in RM.

A successful human pregnancy requires the maternal immune system to recognize and tolerate the semi-allogeneic fetus, allowing for appropriate trophoblasts invasion and protecting the fetus from invading pathogens. Therefore, maternal immunity is critical for the establishment and maintenance of pregnancy, especially at the maternal-fetal interface. Anatomically, the maternal-fetal interface has both maternally- and fetally- derived cells, including fetal originated trophoblasts and maternal derived immune cells and stromal cells. Besides, a commensal microbiota in the uterus was supposed to aid the unique immunity in pregnancy. The appropriate crosstalk between fetal derived and maternal originated cells and uterine microbiota are critical for normal pregnancy. Dysfunctional maternal-fetal interactions might be associated with the development of pregnancy complications. This review elaborates the latest knowledge on the interactions between trophoblasts and decidual immune cells, highlighting their critical roles in maternal-fetal tolerance and pregnancy development. We also characterize the role of commensal bacteria in promoting pregnancy progression. Furthermore, this review may provide new thought on future basic research and the development of clinical applications for pregnancy complications.

As an important research direction of swarm intelligence algorithm, particle swarm optimization (PSO) has become a popular evolutionary method and received extensive attention in the past decades. Despite many PSO variants have been proposed, how to maintain a good balance between the exploration and exploitation abilities, and how to jump out of the local optimal position are still challenges. In this article, based on empirical balance strategy, a new particle swarm optimization (EBPSO) algorithm is presented. Firstly, based on an adaptive adjustment mechanism, the algorithm can choose a better strategy from two search equations, which can maintain the balance between the exploration and exploitation abilities. Secondly, to utilize the information of individual historical optimal solution and the optimal solution of the current population, a weight for adjusting their influence is introduced into the search equation. Thirdly, by introducing the diversity of population, a moving equation for dynamically adjusting the search ability of the algorithm is proposed. Finally, to avoid falling into local optimum and to search the potential location, a dynamic random search mechanism is proposed, which is designed by using the information of the current optimal solution. Compared with some state-of-the-art algorithms, the experimental results show that EBPSO has excellent solution quality and convergence characteristic on almost all test problems.

To optimize the utilization of fermented maize stover (FMS) feed during the fattening phase of Xianghai flying geese (XFG), a total of 300 XFG at 125 days of age were randomly assigned to four dietary treatment groups with three replicates of 25 in each set. Group A was fed the basal fattening diet, while the B, C, and D groups were fed the basic fattening diet and diets supplemented with 5%, 10% or 15% FMS, respectively. The findings indicate that the production performance indicators (especially the dressed, eviscerated and breast muscle yield) of Group D closely resembled Group A more than Groups B and C. Intestinal morphometry found that the jejunal villus height and the villus height/crypt depth were significantly increased in Group D compared to Group A. Next, 16S rRNA amplicon sequencing of the extracted DNA revealed that beneficial microbiota (Coprococcus and Victivallis) showed increased abundance in Group D. Cecal flora function analysis further revealed that some amino acid and glycerol biosynthesis were found to be associated with growth performance in geese. These findings suggest that incorporating 15% FMS as a substitute for a portion of the feed during the fattening phase of XFG can effectively sustain their production performance, optimize the gut microbial community and morphometrical traits, provide new insight into using non-conventional feed resources to reduce feed cost and improve economic benefits in the breeding industry.

The drum rotor of an aero-engine is connected by one or multiple mounting edges through bolts, and their dynamics are significantly influenced by the preload state of the bolts. Long working hours in challenging environments can result in the deterioration of bolt pre-tightening during assembly or service, which impacts the rotor’s dynamic stability and overall performance. Currently, there are no available methods for detecting the dynamic characteristics of the drum connection components. This paper analyzes the impact of the natural characteristics of the drum composite structure of a high-pressure aero-engine turbine based on the refined finite element method when the preloading state changes. Two conditions of deviation and uneven stiffness distribution were applied to the connected components of the drum. The analysis focused on the impact of the pre-tightening state on its natural frequency. After analyzing the feasibility of identifying the pre-tightening state, two methods are proposed. These methods focus on changes in natural frequency and mode shape, specifically the sensitive natural frequency change method and the mode step change method. The methods proposed in this paper can serve as a reference for evaluating the quality of assembling complex disc–drum structures with multiple bolt connections.

The issue of nitrogen fertilizer contamination resulting from high-protein diets can be effectively solved by adopting low-protein diets. The objective of this study was to investigate the effects of inorganic zinc supplementation in low-protein diets on 42-day-old broilers across a multitude of parameters. To determine the optimal dose of inorganic zinc in broiler diets with a 1.5% reduction in crude protein, 1-day-old Arbor Acres broilers (n = 270) were randomly assigned to five groups, each containing 54 broilers. Our results revealed that inorganic zinc supplementation at levels of 130 mg/kg elevated growth performance and carcass traits (p < 0.05). It also significantly increased the ratio of intestinal villi heights to crypt depths (p < 0.001), changed intestinal morphology, and significantly increased albumin content in serum (p < 0.05). Furthermore, analysis of mRNA expression showed that 130 mg/kg and 150 mg/kg of inorganic zinc improved the myogenic differentiation involved in muscle development, as well as intestinal tight junction and liver metallothionein capacity (p < 0.001). Additionally, these groups exhibited lower zinc excretion compared with other treatments (p < 0.001). In summary, our findings suggest that inorganic zinc supplementation in low-protein diets holds the potential to support muscle and intestinal development in broilers, presenting a viable nutritional strategy.

Representation-based classification methods (RBCM) have recently garnered notable attention in the field of pattern classification. Diverging from conventional methods reliant on ℓ1 or ℓ2-norms, the nonnegative representation-based classifier (NRC) enforces a nonnegative constraint on the representation vector, thus enhancing the representation capabilities of positively correlated samples. While NRC has achieved substantial success, it falls short in fully harnessing the discriminative information associated with the training samples and neglects the locality constraint inherent in the sample relationships, thereby limiting its classification power. In response to these limitations, we introduce the locality-constraint discriminative nonnegative representation (LDNR) method. LDNR extends the NRC framework through the incorporation of a competitive representation term. Recognizing the pivotal role played by the estimated samples in the classification process, we include estimated samples that involve discriminative information in this term, establishing a robust connection between representation and classification. Additionally, we assign distinct local weights to different estimated samples, augmenting the representation capacity of homogeneous samples and, ultimately, elevating the performance of the classification model. To validate the effectiveness of LDNR, extensive comparative experiments are conducted on various pattern classification datasets. The findings demonstrate the competitiveness of our proposed method.

Abstract Background Genome-wide association studies (GWASs) have identified hundreds of loci for body mass index (BMI), but functional variants in these loci are less known. The purpose of this study was to identify RNA modification-related SNPs (RNAm-SNPs) for BMI in GWAS loci. BMI-associated RNAm-SNPs were identified in a GWAS of approximately 700,000 individuals. Gene expression and circulating protein levels affected by the RNAm-SNPs were identified by QTL analyses. Mendelian randomization (MR) methods were applied to test whether the gene expression and protein levels were associated with BMI. Results A total of 78 RNAm-SNPs associated with BMI (P

Tetrabromobisphenol A (TBBPA), Tetrachlorobisphenol A (TCBPA), Tetrabromobisphenol S (TBBPS) and their derivatives as the most widely used halogenated flame retardants (HFR), had been employed in the manufacturing industry to raise fire safety. HFRs have been shown to be developmentally toxic to animals and also affect plant growth. However, little was known about the molecular mechanism responded by when plants were treated with these compounds. In this study, when Arabidopsis was exposed to four HFRs (TBBPA, TCBPA, TBBPS-MDHP, TBBPS), the stress of these compounds had different inhibitory effects on seed germination and plant growth. Transcriptome and metabolome analysis showed that all four HFRs could influence the expression of transmembrane transporters to affect ion transport, Phenylpropanoid biosynthesis, Plant-pathogen interaction, MAPK signalling pathway and other pathways. In addition, the effects of different kinds of HFR on plants also have variant characteristics. It is very fascinating that Arabidopsis shows the response of biotic stress after exposure to these kinds of compounds, including the immune mechanism. Overall, the findings of the mechanism recovered by methods of transcriptome and metabolome analysis supplied a vital insight into the molecular perspective for Arabidopsis response to HFRs stress.

BackgroundOur study aimed to explore the potential association of CYP4F2 gene polymorphisms with lung cancer (LC) risk.MethodsThe five variants in CYP4F2 were genotyped using Agena MassARRAY in 507 cases and 505 controls. Genetic models and haplotypes based on logistic regression analysis were used to evaluate the potential association between CYP4F2 polymorphisms and LC susceptibility.ResultsThis study observed that rs12459936 was linked to an increased risk of LC in no-smoking participants (allele: OR = 1.38, p = 0.035; homozygote: OR = 2.00, p = 0.035; additive: OR = 1.40, p = 0.034) and females (allele: OR = 1.64, p = 0.002; homozygote: OR = 2.57, p = 0.006; heterozygous: OR = 2.56, p = 0.001; dominant: OR = 2.56, p < 0.002; additive: OR = 1.67, p = 0.002). Adversely, there was a significantly decreased LC risk for rs3093110 in no-smoking participants (heterozygous: OR = 0.56, p = 0.027; dominant: OR = 0.58, p = 0.035), rs3093193 (allele: OR = 0.66, p = 0.016; homozygote: OR = 0.33, p = 0.011; recessive: OR = 0.38, p = 0.021; additive: OR = 0.64, p = 0.014), rs3093144 (recessive: OR = 0.20, p = 0.045), and rs3093110 (allele: OR = 0.54, p = 0.010; heterozygous: OR = 0.50, p = 0.014; dominant: OR = 0.49, p = 0.010; additive: OR = 0.54, p = 0.011) in females.ConclusionsThe study demonstrated that CYP4F2 variants were associated with LC susceptibility, with evidence suggesting that this connection may be affected by gender and smoking status.

BackgroundThe aim of this study was to investigate the association between pathologic markers and prognosis in patients with hepatocellular carcinoma who received transcatheter chemoembolization combined with locoregional ablation therapy.MethodsThis retrospective study included 111 hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC). All patients underwent transcatheter arterial chemoembolization (TACE) combined with locoregional ablation therapy, and received core needle biopsy before therapy in Beijing You ‘an Hospital affiliated to Capital Medical University from January 1, 2013 to December 31, 2016. Demographic, pathological indicators and clinical laboratory data were collected. The cumulative recurrence-free survival (RFS) and overall survival (OS) were calculated and compared by Kaplan-Meier method and Log-rank test, and Cox proportional risk model was used to screen for independent predictors of recurrence and long-term prognosis in HCC patients.ResultsThere was a correlation between HBsAg expression in liver tissue and prognosis of HCC patients. Patients with negative HBsAg expression had longer 1-,3- and 5-year RFS rates than positive HBsAg expression (78.3%, 43.5%, 30.4% and 58.5%, 24.5%, 17.0%, P=0.018). Meanwhile,the postoperative 1-,3-and 5-year OS rates of HCC patients in the negative HBsAg expression group were significantly higher than those of HCC patients in the positive HBsAg expression group (100%, 89.1%, 80.4% and 100%, 75.5%, 58.5%, P=0.008).ConclusionsThe prognosis of patients with hepatocellular carcinoma with negative HBsAg expression was better than that with positive HBsAg expression. Accordingly, the expression of the liver HBsAg before combined therapy was a prognostic indicator for OS and RFS. For patients with liver HBsAg positive, follow-up should be strengthened and corresponding intervention measures should be taken to improve prognosis.

BackgroundCurrently, locoregional therapies, such as transarterial chemoembolization (TACE) and ablation, play an important role in the treatment of Hepatocellular carcinoma (HCC). However, an easy-to-use scoring system that predicts recurrence to guide individualized management of HCC with varying risks of recurrence remains an unmet need.MethodsA total of 483 eligible HCC patients treated by TACE combined with ablation from January 1, 2017, to December 31, 2019, were included in the temporal external validation cohort and then used to explore possibilities for refinement of the original scoring system. We investigated the prognostic value of baseline variables on recurrence-free survival (RFS) using a Cox model and developed the easily applicable YA score. The performances of the original scoring system and YA score were assessed according to discrimination (area under the receiver operating curve [AUROC] and Harrell's concordance index [C-statistic]), calibration (calibration curves), and clinical utility [decision curve analysis (DCA) curves]. Finally, improvement in the ability to predict in the different scoring systems was assessed using the Net Reclassification Index (NRI). The YA score was lastly compared with other prognostic scores.ResultsDuring the median follow-up period of 35.6 months, 292 patients experienced recurrence. In the validation cohort, the original scoring system exhibited high discrimination (C-statistic: 0.695) and calibration for predicting the prognosis in HCC. To improve the prediction performance, the independent predictors of RFS, including gender, alpha-fetoprotein (AFP) and des-γ-carboxyprothrombin (DCP), tumor number, tumor size, albumin-to-prealbumin ratio (APR), and fibrinogen, were incorporated into the YA score, an improved score. Compared to the original scoring system, the YA score has better discrimination (c-statistic: 0.712VS0.695), with outstanding calibration and the clinical net benefit, both in the training and validation cohorts. Moreover, the YA score accurately stratified patients with HCC into low-, intermediate- and high-risk groups of recurrence and mortality and outperformed other prognostic scores.ConclusionYA score is associated with recurrence and survival in early- and middle-stage HCC patients receiving local treatment. Such score would be valuable in guiding the monitoring of follow-up and the design of adjuvant treatment trials, providing highly informative data for clinical management decisions.

A novel low-cost hematite–silicon mesoporous composite (HSMC) was synthesized in situ from coal gasification coarse slag (CGCS) via acid modification and its potential for phosphate removal from wastewater was studied. Calcium, aluminum and iron in CGCS were activated by hydrochloric acid, and formed crystalline hematite on the quartz and silicates substrates. Compared with traditional methods of preparing hematite, this in-situ preparation method effectively utilized the iron in CGCS instead of requiring added iron salts, which is highly cost-effective. The specific surface area increased from 4 m2/g for CGCS to 67 m2/g for HSMC, greatly enhancing the phosphate removal ability of HSMC. The maximum adsorption capacity of HSMC for phosphate was 28.62 mg/g, which is more than 28 times higher than that of CGCS. The HSMC had a high point of zero charge (pHPZC) of 7.5, providing good phosphate removal performance over a wide pH range. The phosphate removal mechanism of HSMC mainly involves ligand exchange induced by the large number of hydroxyl groups, inner-sphere complexation induced by the presence of major metal (hydr)oxides, the precipitation of calcium and aluminum with phosphate groups, and some electrostatic adsorption induced by the positively charged surface. The contribution of precipitation to the phosphate removal ability was approximately 27 %. This study provides a new method for the development of phosphate adsorbents while recycling CGCS.

Abstract Background Soluble triggering receptor expressed on myeloid cells 2 (sTREM2), which reflects microglia activation, has been reported closely associated with neuronal injury and neuroinflammation. We aimed to prospectively investigate the associations between plasma sTREM2 and clinical outcomes in acute ischemic stroke (AIS) patients. Methods Study participants were from the China Antihypertensive Trial in Acute Ischemic Stroke, plasma sTREM2 levels in the acute phase of AIS were measured in 3285 participants. The study outcomes were death, cardiovascular events and severe disability at 1 year after AIS. Cox proportional hazards models or logistic regression models were performed to examine the associations of plasma sTREM2 and clinical outcomes. Results After 1-year follow-up, 288 participants (8.8%) experienced cardiovascular events or died. Multivariable-adjusted hazard ratios or odds ratios (95% confidence intervals) for the highest quartile of sTREM2 were 1.57 (1.11–2.21) for the composite outcome of death and cardiovascular events, 1.68 (1.09–2.60) for death, and 1.53 (1.08–2.18) for death or severe disability compared to the lowest quartile. Moreover, incorporation sTREM2 into traditional risk factors model significantly improved risk prediction of the composite outcome of death and cardiovascular events as evidenced by net reclassification index and integrated discrimination improvement (all p values

Abstract Background Monocyte to lymphocyte ratio (MLR) represents a pro-inflammatory immune microenvironment. The aim of this study was to elucidate the effect of MLR and subsequent MLR when relapse occurred (R-MLR) on prognosis for hepatocellular carcinoma (HCC) after transcatheter arterial chemoembolization (TACE) combined with ablation. Methods A prospective analysis was conducted on 606 patients with HCC who were treated with TACE combined with local ablation in Beijing You’an Hospital affiliated to Capital Medical University from January 1, 2012 to December 31, 2016. MLR or R-MLR were stratified according to the optimal cut-off values. The cumulative recurrence-free survival (RFS), overall survival (OS) , and recurrence-death survival (RDS) rates were calculated by Kaplan–Meier method. The Cox proportion hazard model and logistic regression analysis was conducted to screen for independent predictive factors for indicating early relapse and long-term prognosis. Results High MLR was significantly associated with relapse, early recurrence, and overall survival. After a median follow-up of 59.4 months, The cumulative 1-, 3-, 5-year RFS rates of low MLR were 74.6%, 43.8%, and 34.0%; while 66.1%, 32.2%, and 22.6% for high group (P

The rising issue of an aging population has intensified the focus on the health concerns of the elderly. Among these concerns, falls have emerged as a predominant health threat for this demographic. The YOLOv5 family represents the forefront of techniques for human fall detection. However, this algorithm, although advanced, grapples with issues such as computational demands, challenges in hardware integration, and vulnerability to occlusions in the designated target group. To address these limitations, we introduce a pioneering lightweight approach named CGNS-YOLO for human fall detection. Our method incorporates both the GSConv module and the GDCN module to reconfigure the neck network of YOLOv5s. The objective behind this modification is to diminish the model size, curtail floating-point computations during feature channel fusion, and bolster feature extraction efficacy, thereby enhancing hardware adaptability. We also integrate a normalization-based attention module (NAM) into the framework, which concentrates on salient fall-related data and deemphasizes less pertinent information. This strategic refinement augments the algorithm’s precision. By embedding the SCYLLA Intersection over Union (SIoU) loss function, our model benefits from faster convergence and heightened detection precision. We evaluated our model using the Multicam dataset and the Le2i Fall Detection dataset. Our findings indicate a 1.2% enhancement in detection accuracy compared with the conventional YOLOv5s framework. Notably, our model realized a 20.3% decrease in parameter tally and a 29.6% drop in floating-point operations. A comprehensive instance analysis and comparative assessments underscore the method’s superiority and efficacy.

Fine spatiotemporal resolution snow monitoring at the watershed scale is crucial for the management of snow water resources. This research proposes a cloud removal algorithm via snow grain size (SGS) gap-filling based on a space–time extra tree, which aims to address the issue of cloud occlusion that limits the coverage and time resolution of long-time series snow products. To fully characterize the geomorphic characteristics and snow duration time of the Kaidu River Basin (KRB), we designed dimensional data that incorporate spatiotemporal information. Combining other geographic and snow phenological information as input for estimating SGS. A spatiotemporal extreme tree model was constructed and trained to simulate the nonlinear mapping relationship between multidimensional inputs and SGS. The estimation results of SGS can characterize the snow cover under clouds. This study found that when the cloud cover is less than 70%, the model’s estimation of SGS meets expectations, and snow cover reconstruction achieves good results. In specific cloud removal cases, compared to traditional spatiotemporal filtering and multi-sensor fusion, the proposed method has better detail characterization ability and exhibits better performance in snow cover reconstruction and cloud removal in complex mountainous environments. Overall, from 2000 to 2020, 66.75% of snow products successfully removed cloud coverage. This resulted in a decrease in the annual average cloud coverage rate from 52.46% to 34.41% when compared with the MOD10A1 snow product. Additionally, there was an increase in snow coverage rate from 21.52% to 33.84%. This improvement in cloud removal greatly enhanced the time resolution of snow cover data without compromising the accuracy of snow identification.

Viral hepatitis is a global health concern mostly caused by hepatitis B virus (HBV) and hepatitis C virus (HCV). The late diagnosis and delayed treatment of HBV and HCV infections can cause irreversible liver damage and the occurrence of cirrhosis and hepatocellular carcinoma. Detecting the presence and activity of HBV and HCV is the cornerstone of the diagnosis and management of related diseases. However, the traditional method shows limitations. The utilization of nanomaterials has been of great significance in the advancement of virus detection technologies due to their unique mechanical, electrical, and optical properties. Here, we categorized and illustrated the novel approaches used for the diagnosis of HBV and HCV.

Differentiating between snow and clouds presents a formidable challenge in the context of mapping snow cover over the Qinghai–Tibetan Plateau (QTP). The frequent presence of cloudy conditions severely complicates the discrimination of snow cover from satellite imagery. To accurately monitor the spatiotemporal evolution of snow cover, it is imperative to address these challenges and enhance the segmentation schemes employed for snow cover assessment. In this study, we devised a pixel-wise classification algorithm based on Support Vector Machine (SVM) called the 3-D Orientation Gradient algorithm (3-D OG), which captures the variations of the gradient direction of snow and clouds in spatiotemporal dimensions based on geostationary satellite “Fengyun-4A” (FY-4A) multi-spectral and multi-temporal optical imagery. This algorithm assumes that the speed and direction of clouds and snow are different in the process of movement leading to their discrepancy of gradient characteristics in time and space. Therefore, in this algorithm, the gradient of the images in the spatiotemporal dimensions is calculated first, and then the movement angle and trend are obtained based on that. Finally, the feature space is composed of the multi-spectral image, gradient image, and movement feature maps, which are used as the input of the SVM. Our results demonstrate that the proposed algorithm can identify snow and clouds more accurately during snowfall by utilizing the FY-4A’s high temporal resolution image. Weather station data, which was collected during snowstorms in the QTP, were used for evaluating the accuracy of our algorithm. It is demonstrated that the overall accuracy of snow cover segmentation by using the 3-D OG algorithm is improved by at least 12% and 10% as compared to snow products of Fengyun-2 and MODIS, respectively. Overall, the proposed algorithm has overcome the axial swing errors existing in Geostationary satellites and is successfully applied to cloud and snow segmentation in QTP. Furthermore, our study underscores that the visible and near-infrared bands of Fengyun-4A can be used for near real-time snow cover monitoring with high performance using the 3-D OG algorithm.

The Qinghai–Tibet Plateau is one of the regions with the highest snow accumulation in China. Although the Fengyun-4A (FY4A) satellite is capable of monitoring snow-covered areas in real time and on a wide scale at high temporal resolution, its spatial resolution is low. In this study, the Qinghai–Tibet Plateau, which has a harsh climate with few meteorological stations, was selected as the study area. We propose a deep learning model called the Dual-Branch Super-Resolution Semantic Segmentation Network (DSRSS-Net), in which one branch focuses with super resolution to obtain high-resolution snow distributions and the other branch carries out semantic segmentation to achieve accurate snow recognition. An edge enhancement module and coordinated attention mechanism were introduced into the network to improve the classification performance and edge segmentation effect for cloud versus snow. Multi-task loss is also used for optimization, including feature affinity loss and edge loss, to obtain fine structural information and improve edge segmentation. The 1 km resolution image obtained by coupling bands 1, 2, and 3; the 2 km resolution image obtained by coupling bands 4, 5, and 6; and the 500 m resolution image for a single channel, band 2, were inputted into the model for training. The accuracy of this model was verified using ground-based meteorological station data. Snow classification accuracy, false detection rate, and total classification accuracy were compared with the MOD10A1 snow product. The results show that, compared with MOD10A1, the snow classification accuracy and the average total accuracy of DSRSS-Net improved by 4.45% and 5.1%, respectively. The proposed method effectively reduces the misidentification of clouds and snow, has higher classification accuracy, and effectively improves the spatial resolution of FY-4A satellite snow cover products.

Abstract Background Preclinical and epidemiological studies indicate a potential chemopreventive role of low-density lipoprotein cholesterol (LDL-C) -lowering drugs in the risks of breast cancer and prostate cancer, but the causality remains unclear. We aimed to evaluate the association of genetically proxied inhibition of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase, Niemann-Pick C1-Like 1 (NPC1L1), and proprotein convertase subtilisin/kexin type 9 (PCSK9) with risks of breast cancer and prostate cancer using a two-sample Mendelian randomization (MR) method. Methods Single-nucleotide polymorphisms (SNPs) in HMGCR, NPC1L1, and PCSK9 associated with LDL-C in a genome-wide association study (GWAS) meta-analysis from the Global Lipids Genetics Consortium (GLGC; up to 188,577 European individuals) were used to proxy inhibition of HMG-CoA reductase, NPC1L1, and PCSK9. Summary statistics with outcomes were obtained from a GWAS meta-analysis of the Breast Cancer Association Consortium (BCAC; 228,951 European females) and a Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL; 140,254 European males) consortium. SNPs were combined into multiallelic models and MR estimates representing lifelong inhibition of targets were generated using the inverse-variance weighted method. Results Genetically proxied inhibition of HMG-CoA reductase (OR: 0.84; 95% CI 0.74–0.95; P = 0.005) and NPC1L1 (OR: 0.72; 95% CI 0.58–0.90; P = 0.005) equivalent to a 1-mmol/L (38.7 mg/dL) reduction in LDL-C was associated with reduced breast cancer risk. There were no significant associations of genetically proxied inhibition of PCSK9 with breast cancer. In contrast, genetically proxied inhibition of PCSK9 (OR: 0.81; 95% CI 0.73–0.90; P

Abstract. Background:. Sweat secreted by eccrine sweat glands is transported to the skin surface through the lumen. The eccrine sweat gland develops from the initial solid bud to the final gland structure with a lumen, but how the lumen is formed and the mechanism of lumen formation have not yet been fully elucidated. This study aimed to investigate the mechanism of lumen formation of eccrine gland organoids (EGOs). Methods:. Human eccrine sweat glands were isolated from the skin for tissue culture, and the primary cultured cells were collected and cultured in Matrigel for 14 days in vitro. EGOs at different development days were collected for hematoxylin and eosin (H&E) staining to observe morphological changes and for immunofluorescence staining of proliferation marker Ki67, cellular motility marker filamentous actin (F-actin), and autophagy marker LC3B. Western blotting was used to detect the expression of Ki67, F-actin, and LC3B. Moreover, apoptosis was detected using a terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) apoptosis assay kit, and the expression of poly (ADP-ribose) polymerase and Caspase-3 was detected by Western blot. In addition, 3-methyladenine (3MA) was used as an autophagy inhibitor to detect whether the formation of sweat glands can be effectively inhibited. Results:. The results showed that a single gland cell proliferated rapidly and formed EGOs on day 4. The earliest lumen formation was observed on day 6. From day 8 to day 14, the rate of lumen formation in EGOs increased significantly. The immunofluorescence and Western blot analyses showed that the expression of Ki67 gradually decreased with the increase in days, while the F-actin expression level did not change. Notably, the expression of autophagy marker LC3B was detected in the interior cells of EGOs as the apoptosis signal of EGOs was negative. Compared with the control group, the autophagy inhibitor 3MA can effectively limit the formation rate of the lumen and reduce the inner diameter of EGOs. Conclusion:. Using our model of eccrine gland 3D-reconstruction in Matrigel, we determined that autophagy rather than apoptosis plays a role in the lumen formation of EGOs.

Change detection based on multi-temporal synthetic aperture radar (SAR) images plays a significant role in environmental and earth observations. With the advancement in deep neural networks, existing work in the literature mainly concentrates on developing self-supervised methods to generate pseudo-labeled samples to guide the subsequent deep learning based detection. However, this way of selecting sample inevitably introduces erroneous labels and imbalance between unchanged and changed classes, thus causing deterioration in change detection performance. To mitigate these issues, we have proposed a SAR change detection network based on visual saliency and multi-hierarchical fuzzy clustering. Specifically, with multi-dimensional difference feature representations, a visual saliency based difference map is constructed for accurate difference feature extraction. By integrating neighborhood information and hierarchical clustering, the multi-hierarchical fuzzy local information C-means clustering algorithm has been developed to identify potential changed regions for sample selection. A class-balanced adaptive focal loss has further been incorporated into the network training to obtain accurate predictions. Extensive experiments and comparisons on five datasets have been performed. The proposed method has achieved averaged accuracy of 99.07% and Kappa coefficient of 79.87%, outperforming other state-of-the-art algorithms both visually and quantitatively.

The human immunodeficiency virus (HIV) is still a global pandemic and despite the successful use of anti-retroviral therapy, a well-established cure remains to be identified. Viral modulation of cell death has a significant role in HIV pathogenesis. Here we sought to understand the major mechanisms of HIV-induced death of lymphocytes and the effects on viral transmission. Flow cytometry analysis of lymphocytes from five latent HIV-infected patients, and HIV IIIB-infected MT2 cells demonstrated both necrosis and apoptosis to be the major mechanisms of cell death in CD4+ and CD4-/CD8- lymphocytes. Significantly, pro-apoptotic tumor necrosis factor (TNF) peptide (P13) was found to inhibit HIV-related cell death and reduced viral transmission. Whereas pro-necrotic TNF peptide (P16) had little effect on HIV-related cell death and viral transmission. Understanding mechanisms by which cell death can be manipulated may provide additional drug targets to reduce the loss of CD4+ cells and the formation of a viral reservoir in HIV infection.

In Remote Sensing(RS) data analysis, Remote Sensing Change Detection(CD) is an important technology. The existing Remote Sensing Change Detection(RS-CD) methods do not fully consider the advantages and disadvantages of Convolution and Transformer in feature extraction, which will restrict the overall performance of the network to a certain extent. Therefore, this paper proposes a Dual Branch Feature Guided Aggregation Network composed of convolutional neural network(CNN) and Transformer. In the encoding stage, based on the respective characteristics of Convolution and Transformer, a dual-branch backbone network is constructed to extract the spatial information and semantic information of the image respectively; And through the Feature Guidance Aggregation Module, the two branches can guide each other for feature mining, so as to avoid the occurrence of false detection and missed detection of change areas due to insufficient fusion to the greatest extent. Finally, in the decoding stage, the different levels of features extracted by the two branches are fully used for fusion and decoding. And the experiment shows that compared with the existing methods, the mean intersection over union(MIoU) index on the four public datasets are improved by 1.25%, 1.55%, 1.38% and 1.71%.

This paper addresses the issue of dynamic instability in quadrotor caused by changes in load mass during flight. To tackle this problem, the Lyapunov exponent method is adopted to study the dynamics and motion stability of the system. This approach resolves the challenge of constructing system eigenvalues due to the nonlinearity and high order of the quadrotor. To enhance the reliability of stability analysis, a quantitative relationship between system dynamics parameters and motion stability is established by combining the dynamic model with the Lyapunov exponent method. This approach compensates for inaccuracies in theoretical modeling analysis caused by factors such as load mass changes. The experiments demonstrate that changing the wheelbase and load mass improves flight motion stability, ensuring the reliability of the quadrotor flight system. Overall, this paper provides an in-depth analysis of the motion stability of a quadrotor and proposes a reliable method for stability analysis that accounts for changes in load mass during flight.

ABSTRACT Introduction Primary central nervous system lymphoma (PCNSL) is extremely rare in pediatric population. We reported a case of PCNSL in a 3‐year‐old girl and reviewed the literature in the past three decades. Case presentation A 3‐year‐old girl presented with gait disturbance. A contrast‐enhanced magnetic resonance image of the brain showed a solitary bulky mass in the left cerebellar hemisphere, hydrocephalus and cerebellar tonsillar hernia. Surgical resection was performed and the patient was diagnosed with primary central nervous system lymphoblastic B cell lymphoma. Then the patient received regular chemotherapy, including 6 cycles of chemotherapy containing high‐dose methotrexate (HD‐MTX). The patient remains alive 15 months after the diagnosis with no evidence of active disease, but suffered twice chronic subdural hematoma, which was treated by burr hole drainage. Conclusion Lymphoblastic B cell lymphoma is a rare histologic subtype of pediatric PCNSL. Chemotherapy containing HD‐MTX remains the most effective treatment. The patient should avoid head impact after surgical resection of the tumor to prevent chronic subdural hematoma.