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Abstract Background Tumor morphology, immune function, inflammatory levels, and nutritional status play critical roles in the progression of intrahepatic cholangiocarcinoma (ICC). This multicenter study aimed to investigate the association between markers related to tumor morphology, immune function, inflammatory levels, and nutritional status with the prognosis of ICC patients. Additionally, a novel tumor morphology immune inflammatory nutritional score (TIIN score), integrating these factors was constructed. Methods A retrospective analysis was performed on 418 patients who underwent radical surgical resection and had postoperative pathological confirmation of ICC between January 2016 and January 2020 at three medical centers. The cohort was divided into a training set (n = 272) and a validation set (n = 146). The prognostic significance of 16 relevant markers was assessed, and the TIIN score was derived using LASSO regression. Subsequently, the TIIN-nomogram models for OS and RFS were developed based on the TIIN score and the results of multivariate analysis. The predictive performance of the TIIN-nomogram models was evaluated using ROC survival curves, calibration curves, and clinical decision curve analysis (DCA). Results The TIIN score, derived from albumin-to-alkaline phosphatase ratio (AAPR), albumin–globulin ratio (AGR), monocyte-to-lymphocyte ratio (MLR), and tumor burden score (TBS), effectively categorized patients into high-risk and low-risk groups using the optimal cutoff value. Compared to individual metrics, the TIIN score demonstrated superior predictive value for both OS and RFS. Furthermore, the TIIN score exhibited strong associations with clinical indicators including obstructive jaundice, CEA, CA19-9, Child–pugh grade, perineural invasion, and 8th edition AJCC N stage. Univariate and multivariate analysis confirmed the TIIN score as an independent risk factor for postoperative OS and RFS in ICC patients (p

BackgroundAlthough depression symptoms are commonly reported in patients with subcortical vascular mild cognitive impairment (svMCI), their impact on brain functions remains largely unknown, with diagnoses mainly dependent on behavioral assessments.MethodsIn this study, we analyzed resting-state fMRI data from a cohort of 34 svMCI patients, comprising 18 patients with depression symptoms (svMCI+D) and 16 patients without (svMCI-D), along with 34 normal controls (NC). The study used the fraction of the amplitude of low-frequency fluctuations (fALFF), resting-state functional connectivity, correlation analyses, and support vector machine (SVM) techniques.ResultsThe fALFF of the right cerebellum (CERE.R) differed among the svMCI+D, svMCI-D, and NC groups. Specifically, the regional mean fALFF of CERE. R was lower in svMCI-D patients compared to NC but higher in svMCI+D patients compared to svMCI-D patients. Moreover, the adjusted fALFF of CERE. R showed a significant correlation with Montreal Cognitive Assessment (MOCA) scores in svMCI-D patients. The fALFF of the right orbital part of the superior frontal gyrus was significantly correlated with Hamilton Depression Scale scores in svMCI+D patients, whereas the fALFF of the right postcingulate cortex (PCC.R) showed a significant correlation with MOCA scores in svMCI-D patients. Furthermore, RSFC between PCC. R and right precuneus, as well as between CERE. R and the right lingual gyrus (LING.R), was significantly reduced in svMCI-D patients compared to NC. In regional analyses, the adjusted RSFC between PCC. R and PreCUN. R, as well as between CERE. R and LING. R, was decreased in svMCI-D patients compared to NC but increased in svMCI+D patients compared to svMCI-D. Further SVM analyses achieved good performances, with an area under the curve (AUC) of 0.82 for classifying svMCI+D, svMCI-D, and NC; 0.96 for classifying svMCI+D and svMCI-D; 0.82 for classifying svMCI+D and NC; and 0.92 for classifying svMCI-D and NC.ConclusionThe study revealed disruptive effects of cognitive impairment, along with both disruptive and complementary effects of depression symptoms on spontaneous brain activity in svMCI. Moreover, these findings suggest that the identified features might serve as potential biomarkers for distinguishing between svMCI+D, svMCI-D, and NC, thereby guiding clinical treatments such as transcranial magnetic stimulation for svMCI.

To realize nanoscale manufacturing based on laser direct writing technology, objective lenses with high numerical apertures immersed in water or oil are necessary. The use of liquid medium restricts its application in semiconductors. Achieving nanoscale features on silicon by laser direct writing in a low refractive index medium has been a challenge. In this work, a microsphere assisted femtosecond laser far-field induced dewetting approach is proposed. A reduction in the full-width at half-maximum of the focused light spot is realized by modulating tightly focused light through microspheres and achieving a minimum feature size of 9 nm on silicon in ambient air with energy smaller than the ablation threshold. Theoretical analysis and numerical simulation of laser processing are performed based on a two-temperature model. Furthermore, we explored the potential of femtosecond laser-induced dewetting in nanolithography and demonstrated its ability to achieve an arbitrary structure on silicon. Our work enables laser-based far-field sub-10-nm feature etching on a large-scale, providing a novel avenue for nanoscale silicon manufacturing.

BackgroundBasement membranes (BMs) have recently emerged as significant players in cancer progression and metastasis, rendering them promising targets for potential anti-cancer therapies. Here, we aimed to develop a novel signature of basement membrane-related genes (BMRGs) for the prediction of clinical prognosis and tumor microenvironment in hepatocellular carcinoma (HCC).MethodsThe differentially expressed BMRGs were subjected to univariate Cox regression analysis to identify BMRGs with prognostic significance. A six-BMRGs risk score model was constructed using Least Absolute Shrinkage Selection Operator (LASSO) Cox regression. Furthermore, a nomogram incorporating the BMRGs score and other clinicopathological features was developed for accurate prediction of survival rate in patients with HCC.ResultsA total of 121 differentially expressed BMRGs were screened from the TCGA HCC cohort. The functions of these BMRGs were significantly enriched in the extracellular matrix structure and signal transduction. The six-BMRGs risk score, comprising CD151, CTSA, MMP1, ROBO3, ADAMTS5 and MEP1A, was established for the prediction of clinical prognosis, tumor microenvironment characteristics, and immunotherapy response in HCC. Kaplan-Meier analysis revealed that the BMRGs score-high group showed a significantly shorter overall survival than BMRGs score-low group. A nomogram showed that the BMRGs score could be used as a new effective clinical predictor and can be combined with other clinical variables to improve the prognosis of patients with HCC. Furthermore, the high BMRGs score subgroup exhibited an immunosuppressive state characterized by infiltration of macrophages and T-regulatory cells, elevated tumor immune dysfunction and exclusion (TIDE) score, as well as enhanced expression of immune checkpoints including PD-1, PD-L1, CTLA4, PD-L2, HAVCR2, and TIGIT. Finally, a multi-step analysis was conducted to identify two pivotal hub genes, PKM and ITGA3, in the high-scoring group of BMRGs, which exhibited significant associations with an unfavorable prognosis in HCC.ConclusionOur study suggests that the BMRGs score can serve as a robust biomarker for predicting clinical outcomes and evaluating the tumor microenvironment in patients with HCC, thereby facilitating more effective clinical implementation of immunotherapy.

Objective The size of Neogene reservoir formation in rifted basins is closely linked to deep oil and gas accumulation and three-dimensional transport systems. Methods This study examines the differential oil and gas charging issues associated with target traps in Neogene fault basins. Using the eastern steep slope of the Miaoxibei Uplift in the Bohai Sea as an example, we analyze the components of the oil and gas accumulation system in steep slope zones by evaluating fault conduction capability and dividing the dominant injection segments. Subsequently, oil and gas migration simulations are conducted under the control of the fault injection section. Results The research findings are as follows: ① The accumulation system in the steep slope zone consists of deep hydrocarbon accumulative sand bodies, large boundary faults, and late shallow faults. ② The dominant hydrocarbon sinks in the three parts of the accumulation system interact with each other, forming a dominant migration path that is reflected in the overlapping fault charging section with the target trap. The middle section of the main migration fault on the east side of the Miaoxibei Uplift is a strong charging area, while the northern section is a medium charging area. Among the secondary migration faults, faults 4, 6, and 8 have developed strong charging sections, while faults 1, 2, and 11 have developed medium charging sections. ③ Structural migration simulations reveal that the oil and gas accumulation area develops in the middle of the steep slope zone in the east of the Miaoxibei Uplift, with two main migration routes in the east and one in the south. The typical sand traps in fault No. 3 have developed four accumulation zones, with accumulation zone C being the most significant. Conclusion In conclusion, these research findings can serve as a reference for well deployment in target areas, and the technical methods employed can provide support for hydrocarbon accumulation analysis.

Abstract Background Regulatory T cells (Tregs) are involved in the maintenance of immune homeostasis and immune regulation. Clinical trials on the adoptive transfer of Tregs have been ongoing for > 10 years. However, many unresolved issues remain in the production of readymade Treg products and selection of patients. Hence, this study aimed to develop a method to expand off-the-shelf Tregs derived from umbilical cord blood (UCB-Tregs) in vitro without changing their phenotype and inhibitory function. In addition, the study intended to design an approach to precisely select patients who are more likely to benefit from the adoptive Treg transfer therapy. Methods UCB-Tregs were isolated and cultured in a medium containing human recombinant IL-2 and rapamycin and then multiply restimulated with human T-activator CD3/CD28 dynabeads. The phenotype and suppressive capacity of Tregs were assessed on days 18 and 42. The relationship between the suppressive function of UCB-Tregs in vitro and clinical indicators was analyzed, and the ability of the in vitro suppressive capacity to predict the in vivo therapeutic effects was evaluated. Results UCB-Tregs expanded 123-fold and 5,981-fold at 18 and 42 days, respectively. The suppressive function of UCB-Tregs on the proliferation of immune cells at 42 days was not significantly different compared with that of UCB-Tregs obtained at 18 days. The suppression rate of UCB-Tregs to PBMCs was negatively correlated with the course of diabetes. Moreover, the high-suppression group exhibited a better treatment response than the low-suppression group during the 12-month follow-up period. Conclusions Multiply restimulated UCB-Tregs expanded at a large scale without any alterations in their classical phenotypic features and inhibitory functions. The suppressive function of Tregs in vitro was negatively correlated with the disease duration. The present study revealed the possibility of predicting the in vivo therapeutic effects via the in vitro inhibition assay. Thus, these findings provided a method to obtain off-the-shelf Treg products and facilitated the selection of patients who are likely to respond to the treatment, thereby moving toward the goal of precision treatment.

Abstract Background Specific pathogen-free ducks are a valuable laboratory resource for waterfowl disease research and poultry vaccine development. High throughput sequencing allows the systematic identification of structural variants in genomes. Copy number variation (CNV) can explain the variation of important duck genetic traits. Herein, the genome-wide CNVs of the three experimental duck species in China (Jinding ducks (JD), Shaoxing ducks (SX), and Fujian Shanma ducks (SM)) were characterized using resequencing to determine their genetic characteristics and selection signatures. Results We obtained 4,810 CNV regions (CNVRs) by merging 73,012 CNVs, covering 4.2% of the duck genome. Functional analysis revealed that the shared CNVR-harbored genes were significantly enriched for 31 gene ontology terms and 16 Kyoto Encyclopedia of Genes and Genomes pathways (e.g., olfactory transduction and immune system). Based on the genome-wide fixation index for each CNVR, growth (SPAG17 and PTH1R), disease resistance (CATHL3 and DMBT1), and thermoregulation (TRPC4 and SLIT3) candidate genes were identified in strongly selected signatures specific to JD, SM, and SX, respectively. Conclusions In conclusion, we investigated the genome-wide distribution of experimental duck CNVs, providing a reference to establish the genetic basis of different phenotypic traits, thus contributing to the management of experimental animal genetic resources.

It has been shown that deep neural networks can be easily fooled by adversarial examples, which are samples delicately crafted by adding small imperceptible perturbations to the input. Most optimization-based white-box attacks generate adversarial examples by formulating a constrained optimization problem and then solving it using gradient-based iterative methods. During each iteration, the search point is projected back to satisfy the constraints if it falls out of the feasible region. However, this breaks the continuity of the search process, negatively impacting the attacking performance. Additionally, existing methods often employ an identical step size for all dimensions. In this work, to address these problems and improve the performance of constructing adversarial examples, we propose a novel white-box attack capable of generating $\ell _{\infty } $ adversarial examples based on the feasible direction method. In our attack, the step size of each dimension is carefully adjusted to preserve the feasibility and to accelerate the convergence. The efficiency of the proposed method is evaluated on three widely used datasets(MNIST, CIFAR10, and ImageNet). The experimental results show that our method generates adversarial examples at a higher success rate and a faster convergence rate than existing methods. To facilitate reproducing the experiment results presented, we make the source code of our implementation publicly accessible at https://github.com/sjysjy1/Feasible_Direction_Method_Attack.

Abstract Background Progressive hepatitis B virus (HBV) infection can result in cirrhosis, hepatocellular cancer, and chronic hepatitis. While antiviral drugs that are now on the market are efficient in controlling HBV infection, finding a functional cure is still quite difficult. Identifying host factors involved in regulating the HBV life cycle will contribute to the development of new antiviral strategies. Zinc finger proteins have a significant function in HBV replication, according to earlier studies. Zinc finger protein 148 (ZNF148), a zinc finger transcription factor, regulates the expression of various genes by specifically binding to GC-rich sequences within promoter regions. The function of ZNF148 in HBV replication was investigated in this study. Methods HepG2-Na+/taurocholate cotransporting polypeptide (HepG2-NTCP) cells and Huh7 cells were used to evaluate the function of ZNF148 in vitro. Northern blotting and real-time PCR were used to quantify the amount of viral RNA. Southern blotting and real-time PCR were used to quantify the amount of viral DNA. Viral protein levels were elevated, according to the Western blot results. Dual-luciferase reporter assays were used to examine the transcriptional activity of viral promoters. ZNF148’s impact on HBV in vivo was investigated using an established rcccDNA mouse model. Results ZNF148 overexpression significantly decreased the levels of HBV RNAs and HBV core DNA in HBV-infected HepG2-NTCP cells and Huh7 cells expressing prcccDNA. Silencing ZNF148 exhibited the opposite effects in both cell lines. Furthermore, ZNF148 inhibited the activity of HBV ENII/Cp and the transcriptional activity of cccDNA. Mechanistic studies revealed that ZNF148 attenuated retinoid X receptor alpha (RXRα) expression by binding to the RXRα promoter sequence. RXRα binding site mutation or RXRα overexpression abolished the suppressive effect of ZNF148 on HBV replication. The inhibitory effect of ZNF148 was also observed in the rcccDNA mouse model. Conclusions ZNF148 inhibited HBV replication by downregulating RXRα transcription. Our findings reveal that ZNF148 may be a new target for anti-HBV strategies.

Abstract Background Intrahepatic cholangiocarcinoma (ICC) is a highly malignant tumor with a poor prognosis. This study aimed to investigate whether Hemoglobin, Albumin, Lymphocytes, and Platelets (HALP) score and Tumor Burden Score (TBS) serves as independent influencing factors following radical resection in patients with ICC. Furthermore, we sought to evaluate the predictive capacity of the combined HALP and TBS grade, referred to as HTS grade, and to develop a prognostic prediction model. Methods Clinical data for ICC patients who underwent radical resection were retrospectively analyzed. Univariate and multivariate Cox regression analyses were first used to find influencing factors of prognosis for ICC. Receiver operating characteristic (ROC) curves were then used to find the optimal cut-off values for HALP score and TBS and to compare the predictive ability of HALP, TBS, and HTS grade using the area under these curves (AUC). Nomogram prediction models were constructed and validated based on the results of the multivariate analysis. Results Among 423 patients, 234 (55.3%) were male and 202 (47.8) were aged ≥ 60 years. The cut-off value of HALP was found to be 37.1 and for TBS to be 6.3. Our univariate results showed that HALP, TBS, and HTS grade were prognostic factors of ICC patients (all P

Abstract Persistent transcription of HBV covalently closed circular DNA (cccDNA) is critical for chronic HBV infection. Silencing cccDNA transcription through epigenetic mechanisms offers an effective strategy to control HBV. Long non‐coding RNAs (lncRNAs), as important epigenetic regulators, have an unclear role in cccDNA transcription regulation. In this study, lncRNA sequencing (lncRNA seq) is conducted on five pairs of HBV‐positive and HBV‐negative liver tissue. Through analysis, HOXA‐AS2 (HOXA cluster antisense RNA 2) is identified as a significantly upregulated lncRNA in HBV‐infected livers. Further experiments demonstrate that HBV DNA polymerase (DNA pol) induces HOXA‐AS2 after establishing persistent high‐level HBV replication. Functional studies reveal that HOXA‐AS2 physically binds to cccDNA and significantly inhibits its transcription. Mechanistically, HOXA‐AS2 recruits the MTA1‐HDAC1/2 deacetylase complex to cccDNA minichromosome by physically interacting with metastasis associated 1 (MTA1) subunit, resulting in reduced acetylation of histone H3 at lysine 9 (H3K9ac) and lysine 27 (H3K27ac) associated with cccDNA and subsequently suppressing cccDNA transcription. Altogether, the study reveals a mechanism to self‐limit HBV replication, wherein the upregulation of lncRNA HOXA‐AS2, induced by HBV DNA pol, can epigenetically suppress cccDNA transcription.

BackgroundMechanical ventilation (MV) is often required in critically ill patients. However, prolonged mechanical ventilation can lead to Ventilator-induced diaphragmatic dysfunction (VIDD), resulting in difficulty in extubation after tracheal intubation, prolonged ICU stay, and increased mortality. At present, the incidence of diabetes is high in the world, and the prognosis of diabetic patients with mechanical ventilation is generally poor. Therefore, the role of diabetes in the development of VIDD needs to be discovered.MethodsMV modeling was performed on C57 mice and DB mice, and the control group was set up in each group. After 12 h of mechanical ventilation, the muscle strength of the diaphragm was measured, and the muscle fiber immunofluorescence staining was used to verify the successful establishment of the MV model. RNA sequencing (RNA-seq) method was used to detect mRNA expression levels of the diaphragms of each group, and then differential expressed gene analysis, Heatmap analysis, WGCNA analysis, Venn analysis, GO and KEGG enrichment analysis were performed. qRT-PCR was used to verify the expression of the selected mRNAs.ResultsOur results showed that, compared with C57 control mice, the muscle strength and muscle fiber cross-sectional area of mice after mechanical ventilation decreased, and DB mice showed more obvious in this respect. RNA-seq showed that these differential expressed (DE) mRNAs were mainly related to genes such as extracellular matrix, collagen, elastic fiber and Fbxo32. GO and KEGG enrichment analysis showed that the signaling pathways associated with diabetes were mainly as follows: extracellular matrix (ECM), protein digestion and absorption, PI3K-Akt signaling pathway, calcium signaling pathway, MAPK signaling pathway and AGE-RAGE signaling pathway in diabetic complications, etc. ECM has the closest relationship with VIDD in diabetic mice. The key genes determined by WGCNA and Venn analysis were validated by quantitative real-time polymerase chain reaction (qRT-PCR), which exhibited trends similar to those observed by RNA-seq.ConclusionVIDD can be aggravated in diabetic environment. This study provides new evidence for mRNA changes after mechanical ventilation in diabetic mice, suggesting that ECM and collagen may play an important role in the pathophysiological mechanism and progression of VIDD in diabetic mice, and provides some clues for the research, diagnosis, and treatment of VIDD in diabetic context.

BackgroundNormal hepatic functional reserve is the key to avoiding liver failure after liver surgery. This study investigated the assessment of hepatic functional reserve using liver shear wave velocity (LSWV) combined with biochemical indicators, tumor volume, and portal vein diameter.MethodsIn this single-center prospective study, a total of 123 patients with hepatocellular carcinoma (HCC) were divided into a test group (n=92) and a validation group (n=31). All patients were Child-Pugh grade A. The indocyanine green retention rate at 15 min (ICG-R15), liver shear wave velocity (LSWV), portal vein diameter (Dpv), alanine aminotransferase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), γ-glutamyl transpeptidase (γ-GGT), albumin (ALB), prothrombin time (PT), and also liver tumor volume (maximum diameter ≤5 cm) were measured. In the test group, multiple parameters were used to evaluate hepatic functional reserve, and the multiparametric model was established. Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic performance of the multiparametric model. In the validation group, the predictive effectiveness of the multiparametric model was analyzed using consistency tests.ResultsIt was revealed that LSWV, ALB, and PT were statistically significant in evaluation of the hepatic functional reserve (P

Accounting for over 40% of the total energy consumption, the global building sector is pivotal for achieving carbon peak and neutrality objectives. The intricate nature of building carbon emissions, influenced by spatial, temporal, and multifactor coupling, poses challenges on implementing carbon-neutral technologies and conservation strategies. This study focuses on nearly zero energy buildings in China and employs system dynamics to predict energy consumption and carbon emissions according to various scenarios, unveiling influencing patterns and viable emission reduction pathways. The results highlight the substantial impact of enhancing energy conservation awareness as this leads to a 36.4% reduction in energy consumption and a 44.2% reduction in carbon emissions. To attain energy efficiency and carbon reduction goals, a comprehensive approach is essential, encompassing improved building performance, heightened resident energy awareness, increased renewable energy use, and energy landscape adjustments. These findings inform future building energy and carbon emission regulations and offer valuable policy insights.

Abstract Flexible pressure sensors based on micro‐/nanostructures can be integrated into robots to achieve sensitive tactile perception. However, conventional symmetric structures, such as pyramids or hemispheres, can sense only the magnitude of a force and not its direction. In this study, a capacitive flexible tactile sensor inspired by skin structures and based on an asymmetric microhair structure array to perceive directional shear force is designed. Asymmetric microhair structures are obtained by two‐photon polymerization (TPP) and replication. Owing to the features of asymmetric microhair structures, different shear force directions result in different deformations. The designed device can determine the directions of both static and dynamic shear forces. Additionally, it exhibits large response scales ranging from 30 Pa to 300 kPa and maintains high stability even after 5000 cycles; the final relative capacitive change (ΔC/C0) is

Summary: Gestational diabetes mellitus (GDM), the most prevalent metabolic disorder during pregnancy, has long-term risks of metabolic diseases in offspring. However, the underlying mechanisms remain unclear. Here, we analyzed single-cell transcriptional data of cord blood mononuclear cells (CBMCs) from fetuses of healthy and GDM mothers, peripheral blood mononuclear cells from children and adolescents, and coronary plaques myeloid cells from atherosclerosis. Our results demonstrated that monocytes in cord blood were characterized with down-regulated proinflammatory-related pathways and up-regulated proliferation-related pathways. And monocytes in cord blood from GDM mothers were featured with expanded CXCL8+IL1B+ subclusters, enhanced crosstalk with neutrophil granulocytes and augmented adhesive and phagocytic abilities. Interestingly, CXCL8+IL1B+ monocytes influenced by GDM had transcriptome similarity with those of coronary plaques myeloid cells from individuals with atherosclerotic cardiovascular disease. Collectively, our data reveal adverse impact of maternal GDM environment on fetal monocytes and propose potential mechanisms between maternal GDM and offspring atherosclerosis.

Amidst escalating global policy uncertainties and the painful transformation phase of the Chinese economy, studying the time-varying characteristics of risk spillover among the real economy, real estate market, and financial system holds substantial practical relevance for preventing and resolving significant systemic risks. This paper employs the TVP-VAR-DY model, selects indices from the real sectors to construct a risk spillover index for the real economy, and incorporates indices from the real estate and financial sectors to develop a trivariate SV-TVP-VAR model for empirically analyzing the time-varying nature of risk spillover relationships among these variables. This study reveals that risk spillover among different sectors of the real economy exhibits asymmetry and volatility, with the industrial sector experiencing the highest degree of risk spillover. The prosperity of the real estate market consistently aligns with that of the financial system; however, shocks during periods of risk accumulation in the real estate market significantly amplify risks in the real economy. The financial system serves the real economy, which suffers lesser impacts. Nonetheless, post-2008, the financial system’s support for the real estate market has gradually diminished. Crises exacerbate the extent of risk spillover, but the causative factors and socio-economic context create heterogeneity in fluctuations. Based on these findings, in response to the current real estate shock, the Chinese government should discuss the real economy, the real estate industry, and the financial system within the same research framework. Policies should primarily focus on fiscal measures to promote the recovery of the real economy more rapidly. Additionally, by allowing local governments to implement tailored policies based on local conditions, potential homebuying demand has been effectively stimulated.

Learning from work failures is not only beneficial for individual development but also crucial for improving organizational performance and achieving sustainable development. We hypothesize that leader bottom-line mentality, which is commonly used by leaders to prevent profit and performance losses, may reduce subordinates learning from work failures. Drawing on social information processing theory, this paper examines how and when leader bottom-line mentality negatively affects subordinates learning from work failures. We tested our hypotheses through a three-wave survey of 245 employees from several high-tech companies in China. For data analysis, we used SPSS 26.0 and Mplus 8.0 to test the theoretical model and research hypotheses. The results indicated that leader bottom-line mentality has a negative indirect effect on subordinates learning from work failures through the mediating role of subordinates’ psychological availability. In addition, subordinate self-compassion can mitigate this negative mediating mechanism. The present study has several theoretical and practical implications for the current literature.

We developed the Stem Cell Educator therapy among multiple clinical trials based on the immune modulations of multipotent cord blood-derived stem cells (CB-SCs) on different compartments of immune cells, such as T cells and monocytes/macrophages, in type 1 diabetes and other autoimmune diseases. However, the effects of CB-SCs on the B cells remained unclear. To better understand the molecular mechanisms underlying the immune education of CB-SCs, we explored the modulations of CB-SCs on human B cells. CB-SCs were isolated from human cord blood units and confirmed by flow cytometry with different markers for their purity. B cells were purified by using anti-CD19 immunomagnetic beads from human peripheral blood mononuclear cells (PBMCs). Next, the activated B cells were treated in the presence or absence of coculture with CB-SCs for 7 days before undergoing flow cytometry analysis of phenotypic changes with different markers. Reverse transcription-polymerase chain reaction (RT-PCR) was utilized to evaluate the levels of galectin expressions on CB-SCs with or without treatment of activated B cells in order to find the key galectin that was contributing to the B-cell modulation. Flow cytometry demonstrated that the proliferation of activated B cells was markedly suppressed in the presence of CB-SCs, leading to the downregulation of immunoglobulin production from the activated B cells. Phenotypic analysis revealed that treatment with CB-SCs increased the percentage of IgD+CD27− naïve B cells, but decreased the percentage of IgD−CD27+ switched B cells. The transwell assay showed that the immune suppression of CB-SCs on B cells was dependent on the galectin-9 molecule, as confirmed by the blocking experiment with the anti-galectin-9 monoclonal antibody. Mechanistic studies demonstrated that both calcium levels of cytoplasm and mitochondria were downregulated after the treatment with CB-SCs, causing the decline in mitochondrial membrane potential in the activated B cells. Western blot exhibited that the levels of phosphorylated Akt and Erk1/2 signaling proteins in the activated B cells were also markedly reduced in the presence of CB-SCs. CB-SCs displayed multiple immune modulations on B cells through the galectin-9-mediated mechanism and calcium flux/Akt/Erk1/2 signaling pathways. The data advance our current understanding of the molecular mechanisms underlying the Stem Cell Educator therapy to treat autoimmune diseases in clinics.

The recovery of the ozone layer relies on decreasing atmospheric mixing ratios of ozone-depleting substances (ODSs), including chlorofluorocarbons (CFCs). A significant decline in the mixing ratio of trichlorofluoromethane (CFC-11 or $\mathrm{CCl_3F}$ ), the second most abundant CFC, has been observed since the mid-1990s. However, a slowdown in the decline after 2012 indicates a rise in emissions, particularly in Eastern Asia. Ground-based observations are lacking in southeastern China, limiting a thorough evaluation of CFC-11 levels and emissions in this region. A new Advanced Global Atmospheric Gases Experiment background station was established at Xichong (XCG), Shenzhen, China, to provide high-frequency continuous in situ observations. The annual mean CFC-11 mixing ratio, recorded from May 2022 to April 2023, is 221.64 ± 2.29 ppt. When compared with a monthly (MHD) or daily (MLO) observation, this value is found to be 0.45% to 5.36% higher than the northern hemispheric background. With the inverse modeling and interspecies correlation method, we estimate CFC-11 emissions in southeastern China between 1.23 ± 0.25 Gg yr ^−1 and 1.58 ± 0.21 Gg yr ^−1 , in line with the bottom-up estimation of 1.50 Gg yr ^−1 . Results indicate that CFC-11 emissions in the Pearl River Delta region have returned to levels before 2010, aligning with regional and global trends. Observations from XCG would compensate for the deficiency of CFC-11 measurements in southeastern China, paving the road for ODS studies in this region and beyond.

Background: Basement membranes (BMs) have recently emerged as significant players in cancer progression and metastasis, rendering them promising targets for potential anti-cancer therapies. Here, we aimed to develop a novel signature of basement membrane-related genes (BMRGs) for the prediction of clinical prognosis and tumor microenvironment in hepatocellular carcinoma (HCC). Methods: The differentially expressed BMRGs were subjected to univariate Cox regression analysis to identify BMRGs with prognostic significance. A six-BMRGs risk score model was constructed using Least Absolute Shrinkage Selection Operator (LASSO) Cox regression. Furthermore, a nomogram incorporating the BMRGs score and other clinicopathological features was developed for accurate prediction of survival rate in patients with HCC. Results: A total of 121 differentially expressed BMRGs were screened from the TCGA HCC cohort. The functions of these BMRGs were significantly enriched in the extracellular matrix structure and signal transduction. The six-BMRGs risk score, comprising CD151, CTSA, MMP1, ROBO3, ADAMTS5 and MEP1A, was established for the prediction of clinical prognosis, tumor microenvironment characteristics, and immunotherapy response in HCC. Kaplan-Meier analysis revealed that the BMRGs score-high group showed a significantly shorter overall survival than BMRGs score-low group. A nomogramshowed that the BMRGs score could be used as a new effective clinical predictor and can be combined with other clinical variables to improve the prognosis of patients with HCC. Furthermore, the high BMRGs score subgroup exhibited an immunosuppressive state characterized by infiltration of macrophages and T-regulatory cells, elevated tumor immune dysfunction and exclusion (TIDE) score, as well as enhanced expression of immune checkpoints including PD-1, PD-L1, CTLA4, PD-L2, HAVCR2, and TIGIT. Finally, a multi-step analysis was conducted to identify two pivotal hub genes, PKM and ITGA3, in the high-scoring group of BMRGs, which exhibited significant associations with an unfavorable prognosis in HCC. Conclusion: Our study suggests that the BMRGs score can serve as a robust biomarker for predicting clinical outcomes and evaluating the tumor microenvironment in patients with HCC, thereby facilitating more effective clinical implementation of immunotherapy. [ABSTRACT FROM AUTHOR]

Rolling plays an important role in shaping the characteristic quality of black tea. However, the dynamic alterations in volatile compounds during the rolling process remain unclear, which hampers the quality control of black tea. In this study, the dynamic changes of volatile compounds in Congou black tea throughout the rolling process were explored by a combination of GC-E-Nose and GC–MS analysis. The results of PCA and PLS-DA by GC-E-Nose revealed significant alterations in the volatile profiles, particularly at the 15-min rolling stage. A total of 82 volatile compounds including eight categories were identified in Congou black tea during the rolling process. The most abundant volatiles were aldehydes, alcohols, and esters. Through the integration of variable importance in the projection >1 and p

Aroma plays a pivotal role in the quality of black tea. However, the acceptability of black tea is greatly limited by the green off-flavor (GOF) resulting from the inappropriate processing control. In this study, the key odorants causing GOF were investigated by volatolomics, and their dynamic changes and formation pathways were in-depth understood. Significant alterations in volatile metabolites were observed in the withering stage. A total of 14 key odorants were identified as contributors to GOF, including 2-methylpropanal, 3-methylbutanal, 1-hexanol, nonanal, (E, E)-2,4-heptadienal, benzaldehyde, linalool, (E, E)-3,5-octadiene-2-one, β-cyclocitral, phenylacetaldehyde, (E, E)-2,4-nonadienal, methyl salicylate, geraniol, and β-ionone. Among them, (E, E)-2,4-heptadienal (OAV = 3913), characterized by fatty, green, and oily aromas, was considered to be the most important contributor causing GOF. Moreover, it was found that lipid degradation served as the primary metabolic pathway for GOF. This study provides a theoretical foundation for off-flavor control and quality improvement of black tea.

Cold stress causes considerable damage to tender tea seedlings. Previous studies have explored changes in the physiological and biochemical factors of tea in response to cold stress; however, the mechanisms of cold resistance in ancient tea tree plants are unclear. The aim of this study was to analyze the effects of 0 °C cold stress for 15 days and 24 °C ambient temperature recovery for 5 days on the physiological and biochemical characteristics of two representative old tea varieties: Dali tea and Siqiu tea. The results revealed significant changes in antioxidant, photosynthetic efficiency, and physiological and biochemical indicators in response to cold stress, with the two species exhibiting different patterns. Cold stress decreased chlorophyll and carotene content, Fv/Fm, Y(II), non-photochemical quenching coefficient, photochemical quenching, and superoxide dismutase (SOD) activity, and increased intercellular CO2 concentration and ascorbate peroxidase activity. Siqiu tea showed a higher increase in soluble sugar content and antioxidant enzyme activity and a lower accumulation of malondialdehyde and minimal fluorescence (F0) than Dali, indicating a greater tolerance to cold stress. Based on partial least-squares discriminant analysis, six key differential physiological indicators of cold resistance—water-soluble sugar, F0, peroxidase, catalase, SOD, and gas conductance—were identified. Our findings provide technical support for identifying ways to protect ancient tea trees from extreme weather conditions.

We search for an optimal filter design for the estimation of stellar metallicity, based on synthetic photometry from Gaia XP spectra convolved with a series of filter-transmission curves defined by different central wavelengths and bandwidths. Unlike previous designs based solely on maximizing metallicity sensitivity, we find that the optimal solution provides a balance between the sensitivity and uncertainty of the spectra. With this optimal filter design, the best precision of metallicity estimates for relatively bright ( G ∼ 11.5) stars is excellent, σ _[Fe/H] = 0.034 dex for FGK dwarf stars, superior to that obtained utilizing custom sensitivity-optimized filters (e.g., SkyMapper v ). By selecting hundreds of high-probability member stars of the open cluster M67, our analysis reveals that the intrinsic photometric-metallicity scatter of these cluster members is only 0.036 dex, consistent with this level of precision. Our results clearly demonstrate that the internal precision of photometric-metallicity estimates can be extremely high, even providing the opportunity to perform chemical tagging for very large numbers of field stars in the Milky Way. This experiment shows that it is crucial to take into account uncertainty alongside the sensitivity when designing filters for measuring the stellar metallicity and other parameters.

Aroma is an indispensable factor that substantially impacts the quality assessment of black tea. This study aims to uncover the dynamic alterations in the sweet and floral aroma black tea (SFABT) throughout various manufacturing stages using a comprehensive analytical approach integrating gas chromatography electronic nose, gas chromatography–ion mobility spectrometry (GC-IMS), and gas chromatography–mass spectrometry (GC-MS). Notable alterations in volatile components were discerned during processing, predominantly during the rolling stage. A total of 59 typical volatile compounds were identified through GC-IMS, whereas 106 volatile components were recognized via GC-MS throughout the entire manufacturing process. Among them, 14 volatile compounds, such as linalool, β-ionone, dimethyl sulfide, and 1-octen-3-ol, stood out as characteristic components responsible for SFABT with relative odor activity values exceeding one. This study serves as an invaluable theoretical platform for strategic controllable processing of superior-quality black tea.

Gaia DR3 photometry and Blue Photometer (BP) and Red Photometer (RP) spectra have been widely used as reference in photometric calibrations. In this work, we check the spatial uniformity of Gaia DR3 photometry and BP/RP spectra by comparing the BP, RP, and G -band photometry with the synthetic ones from the BP/RP spectra. The discrepancies have a small dispersion of 1.07, 0.55, and 1.02 mmag for the BP, RP, and G bands, respectively. However, the discrepancies exhibit obvious spatial patterns, which are clearly associated with Gaia’s scanning law. The patterns observed in the BP and G bands are similar, with discrepancies between photometry and spectra being more pronounced in these bands compared to the RP band. A further independent test with the Dark Energy Survey DR2 photometry reveals that the spatial patterns are more likely attributed to the Gaia DR3 BP/RP spectra, particularly in the BP band. On one hand, our results confirm the high spatial uniformity of Gaia data at the mmag level. On the other hand, our results suggest that the spatial uniformity of Gaia DR3 BP/RP spectra is not as good as that of Gaia DR3 photometry, and could be further improved in the future.

We present a direct measurement of extinction curves using corrected Gaia XP spectra of the common sources in Gaia DR3 and LAMOST DR7. Our analysis of approximately 370,000 high-quality samples yielded a high-precision average extinction curve for the Milky Way. After incorporating infrared photometric data from Two Micron All Sky Survey and Wide-field Infrared Survey Explorer, the extinction curve spans wavelengths from 0.336 to 4.6 μ m. We determine an average R _55 of 2.730 ± 0.007, corresponding to R _V = 3.073 ± 0.009, and a near-infrared power-law index α of 1.935 ± 0.037. Our study confirmed some intermediate-scale structures within the optical range. One new feature was identified at 540 nm, and its intensity exhibited a correlation with extinction. This extinction curve can be used to investigate the characteristics of dust and enhance the extinction correction of Milky Way stars. A Python package for this extinction curve is available.

Photometric stellar surveys now cover a large fraction of the sky, probe to fainter magnitudes than large-scale spectroscopic surveys, and are relatively free from the target selection biases often associated with such studies. Photometric-metallicity estimates that include narrow/medium-band filters can achieve comparable accuracy and precision to existing low-resolution spectroscopic surveys such as Sloan Digital Sky Survey/SEGUE and LAMOST. Here we report on an effort to identify likely members of the Galactic disk system among the very metal-poor (VMP; [Fe/H] ≤ −2) and extremely metal-poor (EMP; [Fe/H] ≤ −3) stars. Our analysis is based on an initial sample of ∼11.5 million stars with full space motions selected from the SkyMapper Southern Survey (SMSS) and Stellar Abundance and Galactic Evolution Survey (SAGES). After applying a number of quality cuts to obtain the best available metallicity and dynamical estimates, we analyze a total of ∼5.86 million stars in the combined SMSS/SAGES sample. We employ two techniques that, depending on the method, identify between 876 and 1476 VMP stars (6.9%−11.7% of all VMP stars) and between 40 and 59 EMP stars (12.4%−18.3% of all EMP stars) that appear to be members of the Galactic disk system on highly prograde orbits ( v _ϕ > 150 km s ^−1 ). The total number of candidate VMP/EMP disklike stars is 1496, the majority of which have low orbital eccentricities, ecc ≤ 0.4; many have ecc ≤ 0.2. The large fractions of VMP/EMP stars associated with the Milky Way disk system strongly suggest the presence of an early-forming “primordial” disk.

Utilizing high-cadence and continuous g - and r -band data over three nights acquired from the 3.6 m Canada–France–Hawaii Telescope, aiming to find short-duration microlensing events, we conduct a systematic search for variables, transients, and asteroids across a ∼1° field of view of the Andromeda galaxy (M31). We present a catalog of 5859 variable stars, yielding the most extensive compilation of short-period variable sources of M31. We also detected 19 flares, predominantly associated with foreground M dwarfs in the Milky Way. In addition, we discovered 17 previously unknown asteroid candidates, and we subsequently reported them to the Minor Planet Center. Lastly, we report a microlensing event candidate C-ML-1 and present a preliminary analysis.

During the early merger of the Milky Way, intermediate-mass black holes (BHs) in merged dwarf galaxies may have been ejected from the center of their host galaxies due to gravitational waves, carrying some central stars along. This process can lead to the formation of hypercompact star clusters, potentially hosting BHs in the mass range of 10 ^4 –10 ^5 solar masses. These clusters are crucial targets for identifying and investigating intermediate-mass BHs. However, no hypercompact star clusters in the Milky Way have been identified so far. In this paper, taking advantage of the high spatial resolution power of Gaia, we used data from Gaia Early Data Release (EDR) 3 and Large-Area Multi-Object Fiber Optic Spectroscopic Telescope Data Release 7, along with additional data from Pan-STARRS and the Sloan Digital Sky Survey, to conduct an initial screening of 6,138,049 sources using various parameters of Gaia EDR3. A total of 4786 sources were selected for in-depth analysis. Each of these sources was meticulously scrutinized by examining their images, spectra, and nearby celestial objects to exclude various false positives, such as contaminations, galaxies, wide binaries, or wrong matches. We finally identified one likely hypercompact star cluster candidate in the Milky Way, laying the foundation for further high-resolution imaging and spectral verification.

We present a comprehensive recalibration of narrowband/medium-band and broadband photometry from the Southern Photometric Local Universe Survey (S-PLUS) by leveraging two approaches: an improved Gaia XP synthetic photometry (XPSP) method with corrected Gaia XP spectra, and the stellar color regression (SCR) method with corrected Gaia Early Data Release 3 photometric data and spectroscopic data from LAMOST Data Release 7. Through the use of millions of stars as standards per band, we demonstrate the existence of position-dependent systematic errors, up to 23 mmag for the main survey region, in the S-PLUS iDR4 photometric data. A comparison between the XPSP and SCR methods reveals minor differences in zero-point offsets, typically within the range of 1–6 mmag, indicating the accuracy of the recalibration, and a twofold to threefold improvement in the zero-point precision. During this process, we also verify and correct for systematic errors related to CCD position. The corrected S-PLUS iDR4 photometric data will provide a solid data foundation for conducting scientific research that relies on high-precision calibration. Our results underscore the power of the XPSP method in combination with the SCR method, showcasing their effectiveness in enhancing calibration precision for wide-field surveys when combined with Gaia photometry and XP spectra, to be applied for other S-PLUS subsurveys.

The Gaia Data Release 3 (DR3) mission has identified and provided about 440,000 binary systems with orbital solutions, offering a valuable resource for searching binaries including a compact component. By combining the Gaia DR3 data with radial velocities from the LAMOST spectroscopic survey, we identify three wide binaries possibly containing a compact object. For two of these sources with a main-sequence companion, no obvious excess is observed in the blue/red band of the Gaia DR3 XP spectra, and the LAMOST medium-resolution spectra exhibit clear single-lined features. The absence of an additional component from spectral disentangling analysis further suggests the presence of compact objects within these systems. On the other hand, the visible star of the third source is a stripped giant star. In contrast to most binaries including stripped stars, no emission line is detected in the optical spectra. The unseen star could potentially be a massive white dwarf or neutron star, but the possibility of an F-type dwarf star scenario cannot be ruled out. An examination of about 10 binaries containing white dwarfs or neutron stars using both kinematic and chemical methods suggests most of these systems are located in the thin disk of the Milky Way.

The upcoming Chinese Space Station Telescope (CSST) slitless spectroscopic survey poses a challenge of flux calibration, which requires a large number of flux-standard stars. In this work, we design an uncertainty-aware residual attention network, the UaRA-net, to derive the CSST spectral energy distributions (SEDs) with a resolution of R = 200 over the wavelength range of 2500–10000 Å using LAMOST normalized spectra with a resolution of R = 2000 over the wavelength range of 4000–7000 Å. With the special structure and training strategy, the proposed model provides accurate predictions not only of SEDs, but also of their corresponding errors. The precision of the predicted SEDs depends on the effective temperature ( T _eff ), wavelength, and the LAMOST spectral signal-to-noise ratios (S/Ns), particularly in the GU band. For stars with T _eff = 6000 K, the typical SED precisions in the GU band are 4.2%, 2.1%, and 1.5% at S/N values of 20, 40, and 80, respectively. As T _eff increases to 8000 K, the precision increases to 1.2%, 0.6%, and 0.5%, respectively. The precision is higher at redder wavelengths. In the GI band, the typical SED precisions for stars with T _eff = 6000 K increase to 0.3%, 0.1%, and 0.1% at S/N values of 20, 40, and 80, respectively. We further verify our model using empirical MILES spectra and find a good performance. The proposed method will open up new possibilities for the optimal use of slitless spectra of the CSST and other surveys.

We combine photometric data from GALEX GR6+7 All-Sky Imaging Survey and Gaia Early Data Release 3 with stellar parameters from the SAGA and PASTEL catalogs to construct high-quality training samples for dwarfs (0.4 < BP − RP < 1.6) and giants (0.6 < BP − RP < 1.6). We apply careful reddening corrections using empirical temperature- and extinction-dependent extinction coefficients. Using the two samples, we establish a relationship between stellar loci (near-ultraviolet (NUV)−BP versus BP − RP colors), metallicity, and M _G . For a given BP − RP color, a 1 dex change in [Fe/H] corresponds to an approximately 1 magnitude change in NUV − BP color for solar-type stars. These relationships are employed to estimate metallicities based on NUV − BP, BP − RP, and M _G . Thanks to the strong metallicity dependence in the GALEX NUV band, our models enable a typical photometric-metallicity precision of approximately σ _[Fe/H] = 0.11 dex for dwarfs and σ _[Fe/H] = 0.17 dex for giants, with an effective metallicity range extending down to [Fe/H] = −3.0 for dwarfs and [Fe/H] = −4.0 for giants. We also find that the NUV-band-based photometric-metallicity estimate is not as strongly affected by carbon enhancement as previous photometric techniques. With the GALEX and Gaia data, we have estimated metallicities for about 5 million stars across almost the entire sky, including approximately 4.5 million dwarfs and 0.5 million giants. This work demonstrates the potential of the NUV band for estimating photometric metallicities, and sets the groundwork for utilizing the NUV data from space telescopes such as the upcoming Chinese Space Station Telescope.

By combining spectra from the CALSPEC and NGSL, as well as spectroscopic data from the LAMOST Data Release 7 (DR7), we have analyzed and corrected the systematic errors of the Gaia DR3 BP/RP (XP) spectra. The errors depend on the normalized spectral energy distribution (simplified by two independent “colors”) and G magnitude. Our corrections are applicable in the range of approximately −0.5 < BP − RP < 2, 3 < G < 17.5, and E ( B − V ) < 0.8. To validate our correction, we conduct independent tests by comparisons with the MILES and LEMONY spectra. The results demonstrate that the systematic errors of BP − RP and G have been effectively corrected, especially in the near-ultraviolet. The consistency between the corrected Gaia XP spectra and the MILES and LEMONY is better than 2% in the wavelength range of 336–400 nm and 1% in redder wavelengths. A global absolute calibration is also carried out by comparing the synthetic Gaia photometry from the corrected XP spectra with the corrected Gaia DR3 photometry. Our study opens up new possibilities for using XP spectra in many fields. A Python package is publicly available to do the corrections (doi: https://doi.org/10.12149/101375 or https://github.com/HiromonGON/GaiaXPcorrection ).

Using integral field spectroscopy (IFS) from MaNGA, we study the resolved microstructures in a shocked region in the Criss-cross Nebula (CCN), with an unprecedentedly high resolution of ≲1000 au. We measure surface brightness maps for 34 emission lines, which can be broadly divided into three categories: (1) the [O iii ] λ 5007-like group including seven high-ionization lines and two [O ii ] auroral lines that uniformly present a remarkable lane structure, (2) the H α λ 6563-like group, including 23 low-ionization or recombination lines that present a clump-like structure, and (3) [O ii ] λ 3726 and [O ii ] λ 3729 showing high densities at both the [O iii ] λ 5007 lane and the H α clump. We use these measurements to constrain resolved shock models implemented in MAPPINGS V . We find our data can be reasonably well fitted by a model that includes a plane-parallel shock with a velocity of 133 ± 5 km s ^−1 , plus an isotropic two-dimensional Gaussian component, which is likely another clump of gas ionized by photons from the shocked region, and a constant background. We compare the electron density and temperature profiles as predicted by our model with those calculated using observed emission-line ratios. We find different line ratios to provide inconsistent temperature maps, and the discrepancies can be attributed to observational effects caused by limited spatial resolution and projection of the shock geometry, as well as contamination of the additional Gaussian component. Implications on shock properties and perspectives on future IFS-based studies of the CCN are discussed.