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Abstract Human society is facing increasingly serious problems of environmental pollution and energy shortage, and up to now, achieving high NH3-SCR activity at ultra-low temperatures (

ABSTRACT Aim New‐onset diabetes mellitus is a frequent and severe complication arising after liver transplantation (LT). We aimed to identify the risk factors for new‐onset diabetes mellitus after liver transplantation (NODALT) and to develop a risk prediction score system for relevant risks. Methods We collected and analyzed data from all recipients who underwent liver transplantation at the First Affiliated Hospital of Xi'an Jiaotong University. The OR derived from a multiple logistic regression predicting the presence of NODALT was used to calculate the risk prediction score. The performance of the risk prediction score was externally validated in patients who were from the CLTR (China Liver Transplant Registry) database. Results A total of 468 patients met the outlined criteria and finished the follow‐up. Overall, NODALT was diagnosed in 115 (24.6%) patients. Age, preoperative impaired fasting glucose (IFG), postoperative fasting plasma glucose (FPG), and the length of hospital stay were significantly associated with the presence of NODALT. The risk prediction score includes age, preoperative IFG, postoperative FPG, and the length of hospital stay. The risk prediction score of the area under the receiver operating curve was 0.785 (95% CI: 0.724–0.846) in the experimental population and 0.782 (95% CI: 0.708–0.856) in the validation population. Conclusions Age at the time of transplantation, preoperative IFG, postoperative FPG, and length of hospital stay were independent predictive factors of NODALT. The use of a simple risk prediction score can identify the patients who have the highest risk of NODALT and interventions may start early.

Abstract Filamentous fungi produce polysaccharide-degrading enzymes, which is controlled by poorly understood transcriptional circuits. Here we show that a circuit comprising RsrC-RsrA-RsrB (Rsr: production of raw-starch-degrading enzyme regulator) that positively regulates production of raw starch-degrading enzymes in Penicillium oxalicum. Transcription factor (TF) RsrA is essential for biosynthesis of raw starch-degrading enzymes. RsrB and RsrC containing Zn2Cys6- and C2H2-zinc finger domains, act downstream and upstream of RsrA, respectively. RsrA activates rsrB transcription, and three nucleotides (G-286, G-287 and G-292) of rsrB promoter region are required for RsrA, in terms of TF, for binding. RsrB165−271 binds to DNA sequence 5’-TCGATCAGGCACGCC-3’ in the promoter region of the gene encoding key raw-starch-degrading enzyme PoxGA15A. RsrC specifically binds rsrA promoter, but not amylase genes, to positively regulate the expression of rsrA and the production of raw starch-degrading enzymes. These findings expand complex regulatory network of fungal raw starch-degrading enzyme biosynthesis.

This study presents a cancer diagnostics method through the development of a graphitic carbon nitride (g-C3N4)-based electrochemical sensor for detecting circulating tumor cells (CTCs) in blood. Utilizing the unique properties of g-C3N4 nanosheets combined with gold nanoparticles functionalized with DNA aptamers, the sensor exhibits remarkable sensitivity and selectivity in CTC detection. The aptamers specifically target cell surface biomarkers, enabling the precise capture and quantification of CTCs. The sensor's detection limit is an impressive 5 cells/mL, with a broad detection range from 10 to 105 cells/mL. This high-performance sensing platform not only achieves rapid and accurate quantification of CTCs but also demonstrates robustness against interference from other cell types, making it highly suitable for clinical applications. The optimized conditions for aptamer-functionalized nanoparticle concentration and incubation time ensure the sensor's efficacy, as validated in spiked blood samples. This work provides a practical and efficient approach for non-invasive cancer diagnostics, offering significant improvements over existing methods in terms of simplicity, sensitivity, and specificity for early detection and monitoring of cancer progression.

Abstract Background Transition shock occurs at a vulnerable time in newly graduated registered nurses’ careers and has a clear impact on both newly graduated registered nurses’ productivity and patient recovery outcomes. Identifying classification features of transition shock and targeting interventions to support newly graduated registered nurses is imperative. The study aimed to explore potential transition shock subgroups of newly graduated registered nurses and further explore the impact of population characteristics and two indices of health on transition shock. Methods A descriptive, cross-sectional design was conducted. An online questionnaire was sent via WeChat to newly graduated registered nurses who started work in 2021 at seven hospitals between August and November 2021, and 331 nurses filled out the questionnaire. Latent class analysis was used to identify the potential class of the transition shock of newly graduated registered nurses, and multinomial logistic regression analyses were used to determine the factors of potential classification. Results The study identified four classes of transition shock in newly graduated registered nurses, namely, “high transition shock”, “physical fatigue-lack of knowledge”, “development adaptation” and “low transition shock-worry” groups. Newly graduated registered nurses who urinated less than 4 times per day (OR = 0.051, 95% CI = 0.005–0.502) were likely to be in the “high transition shock” group. Newly graduated registered nurses who did not delay urination (OR = 4.267, 95% CI = 1.162–11.236) were more likely to belong to the “low transition shock-worry” group. Newly graduated registered nurses without sleep disturbance were more likely to be in the “physical fatigue - lack of knowledge” (OR = 3.109, 95% CI = 1.283–7.532), “development adaptation” (OR = 8.183, 95% CI = 2.447–27.066), and “low transition shock-worry” (OR = 8.749, 95% CI = 1.619–47.288) groups than in the ‘high transition shock’ group. Conclusions This study highlights potential patterns of transition shock among newly graduated registered nurses. Two indices of health, namely, delayed urination and sleep disturbance, can predict the subgroups of newly graduated registered nurses with transition shock.

Abstract NF-κB signaling has been discovered for nearly 40 years. Initially, NF-κB signaling was identified as a pivotal pathway in mediating inflammatory responses. However, with extensive and in-depth investigations, researchers have discovered that its role can be expanded to a variety of signaling mechanisms, biological processes, human diseases, and treatment options. In this review, we first scrutinize the research process of NF-κB signaling, and summarize the composition, activation, and regulatory mechanism of NF-κB signaling. We investigate the interaction of NF-κB signaling with other important pathways, including PI3K/AKT, MAPK, JAK-STAT, TGF-β, Wnt, Notch, Hedgehog, and TLR signaling. The physiological and pathological states of NF-κB signaling, as well as its intricate involvement in inflammation, immune regulation, and tumor microenvironment, are also explicated. Additionally, we illustrate how NF-κB signaling is involved in a variety of human diseases, including cancers, inflammatory and autoimmune diseases, cardiovascular diseases, metabolic diseases, neurological diseases, and COVID-19. Further, we discuss the therapeutic approaches targeting NF-κB signaling, including IKK inhibitors, monoclonal antibodies, proteasome inhibitors, nuclear translocation inhibitors, DNA binding inhibitors, TKIs, non-coding RNAs, immunotherapy, and CAR-T. Finally, we provide an outlook for research in the field of NF-κB signaling. We hope to present a stereoscopic, comprehensive NF-κB signaling that will inform future research and clinical practice.

Anchoring the competitiveness diamond model, this study aims to reveal how aquaculture competitiveness formed in China in the past ten years. A concept model is constructed about aquaculture competitiveness based on a literature review. The data were obtained from China Fishery Statistical Yearbook from 2010 to 2021. After that, structural equation modeling with the partial least square method is employed to examine the influence and relationship of relevant constructs by calculating each model path's factor loads or path coefficients. The competitiveness of the Chinese aquaculture industry includes resources endowment, science technology environment, economic benefit, and development potential. The empirical results show that resources endowment positively influences economic benefit and development potential. The science and technology environment positively influences economic benefit and development potential. Finally, development potential has a positive influence on economic benefit. Therefore, development potential and economic benefit positively impact the competitiveness of aquaculture. As the field data were obtained from only China, future replication of the findings to other countries should consider country-specific factors. It is one of the first empirical attempts to explore the competitiveness formation mechanism in the aquaculture industry.

The incidence of ulcerative colitis (UC) is rapidly rising worldwide. Oral drug delivery system is a promising approach for treating UC, but it often fails to accumulate to the inflammatory lesions, thus, it is impressive to develop a colon-targeted oral delivery system for preventing systemic toxicity and maintaining UC therapeutics. Here, a negative-charged PLGA nanoparticle system was designed to encapsulate celastrol (Cel), and then chitosan and mannose were coated on the surface of the nanoparticles (MC@Cel-NPs) to endow these nanoparticles with the mucosal adsorption and macrophage targeting abilities. MC@Cel-NPs demonstrate excellent resist decomposition ability against the strong acidic gastrointestinal environment, and accumulates in the specific inflammatory sites through the affinity of electrostatic reaction. After releasing the payload, MC@Cel-NPs could remarkably alleviate the colon inflammation, which was evidenced by the decrease in pro-inflammatory cytokines TNF-α, IL-1β, and IL-6 in both blood and colon sections, and scavenging reactive oxygen species (ROS) in colon cells, including macrophage, neutrophil, T cell, and B cell. This nanoparticle system provided a new approach for treating UC through a Chinese herbal ingredient-related oral delivery manner.

This study explores the mechanism by which obstructive jaundice (OJ) induces liver damage through pyroptosis. We induced OJ in rats via bile duct ligation and assessed liver damage using serum biochemical markers and histological analysis of liver tissue. Pyroptosis was investigated through immunofluorescence, ELISA, Western blot, and quantitative RT-PCR techniques. Additionally, we examined intestinal function and fecal microbiota alterations in the rats using 16S rDNA sequencing. In vitro experiments involved co-culturing Kupffer cells and hepatocytes, which were then exposed to bile and lipopolysaccharide (LPS). Our findings indicated that OJ modified the gut microbiota, increasing LPS levels, which, in conjunction with bile, initiated a cycle of inflammation, fibrosis, and cell death in the liver. Mechanistically, OJ elevated necrotic markers such as ATP, which in turn activated pyroptotic pathways. Increased levels of pyroptosis-related molecules, including NLRP3, caspase-1, gasdermin D, and IL-18, were confirmed. In our co-cultured cell model, bile exposure resulted in cell death and ATP release, leading to the activation of the NLRP3 inflammasome and its downstream effectors, caspase-1 and IL-18. The combination of bile and LPS significantly intensified pyroptotic responses. This study is the first to demonstrate that LPS and bile synergistically exacerbate liver injury by promoting necrosis and pyroptosis, unveiling a novel mechanism of OJ-associated hepatic damage and suggesting avenues for potential preventive or therapeutic interventions.

The transformation of salvianolic acid B brought on by heat treatment recovery of ethanol eluent, which is a difficult problem in pharmaceutical technology, affects the purity of raw material when the medicinal raw material salvianolic acid B is purified by resin. Ultrasonic-assisted nanofiltration separation (UANS) was first employed to improve efficiency of resource utilization by regulating rejection and separating salvianolic acid B and rosmarinic acid from organic pharmaceutical wastewater. The rejection was related to three variables: ultrasonic power, pH, and ethanol concentration. But there were differences in the effects of variables on the rejections of salvianolic acid B and rosmarinic acid. The rejections of rosmarinic acid and salvianolic acid B showed a decreasing trend with an increase in ultrasonic power or a decrease in pH; however, when the concentration of ethanol was increased from 5 % to 35 %, the salvianolic acid B rejection increased from 84.96 % to 96.60 % and the rosmarinic acid rejection decreased from 35.09 % to 17.51 %. On the basis of response surface methodology (RSM), the optimal UANS parameters for solution conditions involving different ethanol concentrations are as follows: 10 % ethanol solution (ultrasonic power 500 W and pH 6.15), 20 % ethanol solution (ultrasonic power 500 W and pH 6.54), and 30 % ethanol solution (ultrasonic power 460 W and pH 6.34). The molecular proportions of salvianolic acid B were 10.75 %, 7.13 %, and 8.27 % in 10 %, 20 %, and 30 % ethanol wastewater, while the molecular proportions of rosmarinic acid were 40.52 %, 33.83 %, and 69.87 %, respectively. And the recoveries of salvianolic acid B in 10 %, 20 %, and 30 % ethanol wastewater were 93.56 %, 95.04 %, and 97.30 %, respectively, while the recoveries of rosmarinic acid were 3.19 %, 2.27 %, and 0.56 %. The molecular proportion and the rejection are correlated exponentially. In comparison with conventional nanofiltration separation (CNS), UANS is able to resolve the conflict between rosmarinic acid and salvianolic acid B in pharmaceutical wastewater, as well as enhance resource recycling and separation efficiency to prevent pollution of the environment from pharmaceutical wastewater. Experiments using UANS at different power intensities suggest that the ultrasonic at a power intensity of 46–50 W/L and the power density of 0.92–1.00 W/cm2 may resolve the separation conflict between rosmarinic acid and salvianolic acid B. This work suggests that UANS may be a significant advancement in the field of ultrasonic separation and has several potential uses in the water treatment industry.

Evodiamine (EVO), the main active alkaloid in Evodia rutaecarpa, was shown to exert various pharmacological activities, especially anti-tumor. Currently, it is considered a potential anti-cancer drug due to its excellent anti-tumor activity, which unfortunately has adverse reactions, such as the risk of liver and kidney injury, when Evodia rutaecarpa containing EVO is used clinically. In the present study, we aim to clarify the potential toxic target organs and toxicity mechanism of EVO, an active monomer in Evodia rutaecarpa, and to develop mitigation strategies for its toxicity mechanism. Transcriptome analysis and related experiments showed that the PI3K/Akt pathway induced by calcium overload was an important step in EVO-induced apoptosis of renal cells. Specifically, intracellular calcium ions were increased, and mitochondrial calcium ions were decreased. In addition, EVO-induced calcium overload was associated with TRPV1 receptor activation. In vivo TRPV1 antagonist and calcium chelator effects were observed to significantly reduce body weight loss and renal damage in mice due to EVO toxicity. The potential nephrotoxicity of EVO was further confirmed by an in vivo test. In conclusion, TRPV1-mediated calcium overload-induced apoptosis is one of the mechanisms contributing to the nephrotoxicity of EVO due to its toxicity, whereas maintaining body calcium homeostasis is an effective measure to reduce toxicity. These studies suggest that the clinical use of EVO-containing herbal medicines should pay due attention to the changes in renal function of patients as well as the off-target effects of the drugs.

IntroductionAs an exceptional geographical entity, the vegetation of the Qinghai-Tibetan Plateau (QTP) exhibits high sensitivity to climate change. The Baima Snow Mountain National Nature Reserve (BNNR) is located in the south-eastern sector of the QTP, serving as a transition area from sub-tropical evergreen broadleaf forest to high-mountain vegetation. However, there has been limited exploration into predicting the temporal and spatial variability of vegetation cover using anti-interference methods to address outliers in long-term historical data. Additionally, the correlation between these variables and environmental factors in natural forests with complex terrain has rarely been analyzed.MethodsThis study has developed an advanced approach based on TS (Theil-Sen slope estimator) MK (Mann-Kendall test)-FVC (fractional vegetation cover) to accurately evaluate and predict the time and spatial shifts in FVC within the BNNR, utilizing the GEE (Google Earth Engine). The satellite data utilized in this paper consisted of Landsat images spanning from 1986 to2020. By integrating TS and MK methodologies to monitor and assess the FVC trend, the Hurst index was employed to forecast FVC. Furthermore, the association between FVC and topographic factors was evaluated, the partial correlation between FVC and climatic influences was analyzed at the pixel level (30×30m).Results and discussionHere are the results of this research: (1) Overall, the FVC of the BNNR exhibits a growth trend, with the mean FVC value increasing from 59.40% in 1986 to 68.67% in 2020. (2) The results based on the TS-MK algorithm showed that the percentage of the area of the study area with an increasing and decreasing trend was 59.03% (significant increase of 28.04%) and 22.13% (significant decrease of 6.42%), respectively. The coupling of the Hurst exponent with the Theil-Sen slope estimator suggests that the majority of regions within the BNNR are projected to sustain an upward trend in FVC in the future. (3) Overlaying the outcomes of TS-MK with the terrain factors revealed that the FVC changes were notably influenced by elevation. The partial correlation analysis between climate factors and vegetation changes indicated that temperature exerts a significant influence on vegetation cover, demonstrating a high spatial correlation.

Summary: Regulatory T (Treg) cells play a critical regulatory role in the immune system by suppressing excessive immune responses and maintaining immune balance. The effective migration of Treg cells is crucial for controlling the development and progression of inflammatory diseases. However, the mechanisms responsible for directing Treg cells into the inflammatory tissue remain incompletely elucidated. In this study, we identified BAF60b, a subunit of switch/sucrose nonfermentable (SWI/SNF) chromatin remodeling complexes, as a positive regulator of Treg cell migration that inhibits the progression of inflammation in experimental autoimmune encephalomyelitis (EAE) and colitis animal models. Mechanistically, transcriptome and genome-wide chromatin-landscaped analyses demonstrated that BAF60b interacts with the transcription factor RUNX1 to promote the expression of CCR9 on Treg cells, which in turn affects their ability to migrate to inflammatory tissues. Our work provides insights into the essential role of BAF60b in regulating Treg cell migration and its impact on inflammatory diseases.

Super-agile satellites with dynamic imaging capabilities can significantly improve the imaging efficiency of space-borne Earth observation. However, the image modulation transfer function (image MTF) of dynamic imaging varies dramatically with changes in the attitude maneuver status while improving observation efficiency. Therefore, both the observation efficiency and image MTF should be considered in the imaging mission planning of super-agile satellites. Existing imaging mission planning methods are mainly aimed at traditional agile satellites that are not capable of dynamic imaging, and the mainly optimization objectives are coverage revenue, spatial resolution, and task performance time, without considering the observation efficiency and image MTF as the optimization objectives. To overcome the problem of image MTF degradation caused by dynamic imaging, a mission planning method which considers the degradation of the image MTF and observation efficiency was proposed. Firstly, a mapping relationship between the angular velocity of the attitude maneuvering and the image MTF was constructed. On this basis, a Pareto multi-objective imaging mission planning model of partial order based was established. Considering the particularity of the model, the non-dominated sorting strategy of the NSGA-II algorithm was redesigned when solving the model using NSGA-II algorithm. Finally, the imaging tasks of different scales in single satellite and multi-satellite simulation scenes were set, and the proposed imaging mission planning method was verified. The planning results showed that the proposed method can achieve a balanced optimization of the image MTF and task efficiency under the premise of ensuing maximum observation coverage revenue.

This study aimed to investigate the effects of ultrasonic treatment at different powers on the physicochemical properties, microstructure and quercetin delivery capacity of fermentation-induced soy protein isolate emulsion gel (FSEG). The FSEG was prepared by subjecting soy protein isolate (SPI) emulsion to ultrasonic treatment at various powers (0, 100, 200, 300, and 400 W), followed by lactic acid bacteria fermentation. Compared with the control group (0 W), the FSEG treated with ultrasound had higher hardness, water holding capacity (WHC) and rheological parameters. Particularly, at an ultrasonic power of 300 W, the FSEG had the highest hardness (101.69 ± 4.67 g) and WHC (75.20 ± 1.07%) (p

BackgroundCuprizone (CPZ)-treated mice show significant demyelination, altered gut microbiome, and depressive-like behaviors. However, the effects of venlafaxine (Ven) on the gut microbiome and depressive-like behavior of CPZ-treated mice are largely unclear.MethodsMale C57BL/6J mice were fed a chow containing 0.2% cuprizone (w/w) for 5 weeks to induce a model of demyelination. Meanwhile, the gut microbiota and depressive-like behaviors were assessed after the mice were fed with Ven (20 mg/kg/day) or equal volumes of distilled water for 2 weeks by oral gavage from the third week onward during CPZ treatment.ResultsCPZ treatment decreased the sucrose preference rate in the sucrose preference test and increased the immobility time in the tail-suspension test, and it also induced an abnormality in β-diversity and changes in microbial composition. Ven alleviated the depressive-like behavior and regulated the composition of the gut microbiota, such as the increase of Lactobacillus and Bifidobacterium in CPZ-treated mice.ConclusionThe anti-depressant effects of Ven might be related to the regulation of gut microbiota in the CPZ-treated mice.

Objective: To investigate the spatial heterogeneity of nontuberculous mycobacterial pulmonary disease (NTM-PD) in Shanghai. Methods: A population-based retrospective study was conducted using presumptive pulmonary tuberculosis surveillance data of Shanghai between 2010 and 2019. The study described the spatial distribution of NTM-PD notification rates, employing hierarchical Bayesian mapping for high-risk areas and the Getis-Ord Gi* statistic to identify hot spots and explore associated factors. Results: Of 1652 NTM-PD cases, the most common species was Mycobacterium kansasii complex (MKC) (41.9%), followed by Mycobacterium avium complex (MAC) (27.1%) and Mycobacterium abscessus complex (MABC) (16.2%). MKC-PD patients were generally younger males with a higher incidence of pulmonary cavities, while MAC-PD patients were more often farmers or had a history of tuberculosis treatment. MKC-PD hot spots were primarily located in the areas alongside the Huangpu River, while MAC-PD hot spots were mainly in the western agricultural areas. Patients with MKC-PD and MAC-PD exhibited a higher risk of spatial clustering compared to those with MABC-PD. Conclusions: Different types of NTM-PD exhibit distinct patterns of spatial clustering and are associated with various factors. These findings underscore the importance of environmental and host factors in the epidemic of NTM-PD.

Abstract Background The purpose of this study was to investigate the influence of different residual meniscus volume on the biomechanics of tibiofemoral joint after discoid lateral meniscus (DLM) surgery by finite element analysis. Methods A knee joint model was established based on CT and MRI imaging data. The DLM model was divided into five regions according to conventional meniscectomy, with volumes of 15%, 15%, 15%, 15%, 15%, and 40% for each region. Additionally, the DLM model was divided into anterior and posterior parts to obtain ten regions. The DLM was resected according to the design scheme, and together with the intact discoid meniscus, a total of 15 models were obtained. Finite element analysis was conducted to assess shear and pressure trends on the knee joint. Results The study observed significant changes in peak shear stress and compressive stress in the lateral meniscus and lateral femur cartilage. As the meniscus volume decreased, there was an increase in these stresses. Specifically, when the meniscus volume reduced to 40%, there was a sharp increase in shear stress (302%) and compressive stress (152%) on the meniscus, as well as shear stress (195%) and compressive stress (157%) on the lateral femur cartilage. Furthermore, the model grouping results showed that preserving a higher frontal volume in the meniscus model provided better biomechanical advantages. Conclusion The use of finite element analysis has demonstrated that preserving more than 55% of the meniscus volume is necessary to prevent a significant increase in joint stress, which can potentially lead to joint degeneration. Additionally, it is crucial to preserve the front volume of the DLM in order to achieve improved knee biomechanical outcomes.

AbstractBarnacles are crustaceans that are critical model organisms in intertidal ecology and biofouling research. In this study, we present the first mitochondrial genome of Striatobalanus tenuis which is a circular molecule of 15,067 bp in length. Consistent with most barnacles, the mitochondrial genome of S. tenuis encodes 37 genes, including 13 PCGs, 22 tRNAs and 2 rRNAs. A novel insight into the phylogenetic analysis based on the nucleotide data of 13 PCGs showed that the S. tenuis clusters with Striatobalanus amaryllis (bootstrap value = 100) of the same genus, then groups with other Balanoidea species, the Chelonibiidae, Austrobalanidae and Tetraclitidae cluster together forming superfamily Coronuloidea. The result can help us to understand the novel classification within Balanomorpha.

Abstract Background Hepatitis B virus (HBV) remains a substantial public health safety concern drawing considerable attention in China and globally. The detection of HBV serological markers can enable the assessment of HBV infection and replication status in vivo and evaluate the body’s protection against HBV. Therefore, this study aims to identify the epidemiological and clinical characteristics of HBV infection in children to prevent and control HBV infection in Wuhan areas. Methods We conducted an extensive retrospective cohort analysis of 115,029 individuals aged 0–18 years who underwent HBV serological markers detection for HBV infection in hospital between 2018 and 2021 using Electrochemiluminescence immunoassay. We generated descriptive statistics and analysed HBV infection’s epidemiological and clinical characteristics between different sex and age groups. Results The overall positive detection rates of HBsAg, HBsAb, HBeAg, HBeAb, and HBcAb in all participants were 0.13%, 79.09%, 0.17%, 2.81%, and 5.82%, respectively. The positive rate of HBeAb and HBcAb in males was significantly lower than that in females (2.64% vs. 3.13%, 5.56% vs. 6.29%) (P

Abstract Background and purpose Chronic gastritis, especially that caused by helicobacter pylori (HP) infection, has been associated with increased risk of ischemic stroke. But the relationship between chronic gastritis and cerebral small vessel disease (CSVD) remains largely undetermined. This study aimed to determine the potential predictors for CSVD, with chronic gastritis and its proxies as alternatives. Method Patients aged 18 years or older with indications for electronic gastroscopy were enrolled. Presence of CSVD was evaluated with brain magnetic resonance imaging (MRI) results. Degree of CSVD was scored according to established criteria. Logistic regression analysis was used for identifying possible risk factors for CSVD. Results Of the 1191 enrolled patients, 757 (63.6%) were identified as with, and 434 (36.4%) as without CSVD. Multivariate analysis indicated that patients with chronic atrophic gastritis had an increased risk for CSVD than those without (adjusted odds ratio = 1.58; 95% CI, 1.08–2.32; P

Cross-border electricity trade can promote the sustainable development of regional multi-country economies by alleviating the uneven distribution of global energy resources. Hence, designing a reasonable and effective mechanism contributes toward the development of cross-border electricity market. This study established a non-cooperative game model for cross-border electricity trading. Central to our approach is the analysis of multi-participants trading modes influenced by cross-border trading centers. The model distinctively incorporates trading rules and service fees, providing a realistic simulation framework. The results reveal a direct correlation between strategic scope and the dependency of trading strategies on electricity pricing set by trading centers. This research advances the theoretical understanding of game theory application in electricity markets and offers practical insights for policymakers and market operators, particularly in strategizing for price setting and managing cross-border transactions.

Heterosigma akashiwo is a harmful algal bloom species that causes significant detrimental effects on marine ecosystems worldwide. The algicidal bacterium Pseudalteromonas sp. LD-B1 has demonstrated potential effectiveness in mitigating these blooms. However, the molecular mechanisms underlying LD-B1’s inhibitory effects on H. akashiwo remain poorly understood. In this study, we employed the comprehensive methodology, including morphological observation, assessment of photosynthetic efficiency (Fv/Fm), and transcriptomic analysis, to investigate the response of H. akashiwo to LD-B1. Exposure to LD-B1 resulted in a rapid decline of H. akashiwo's Fv/Fm ratio, with cells transitioning to a rounded shape within 2 hours, subsequently undergoing structural collapse and cytoplasmic leakage. Transcriptomic data revealed sustained downregulation of photosynthetic genes, indicating impaired functionality of the photosynthetic system. Additionally, genes related to the respiratory electron transfer chain and antioxidant defenses were consistently downregulated, suggesting prolonged oxidative stress beyond the cellular antioxidative capacity. Notably, upregulation of autophagy-related genes was observed, indicating autophagic responses in the algal cells. This study elucidates the molecular basis of LD-B1's algicidal effects on H. akashiwo, advancing our understanding of algicidal mechanisms and contributing to the development of effective strategies for controlling harmful algal blooms.

AimThis study comprehensively assesses the incidence and profiles of treatment-related adverse events (trAEs) of immune checkpoint inhibitor (ICI)-based therapies across cancer at various sites.MethodsWe systematically searched the PubMed, Embase, and Cochrane databases for trials investigating ICI-based therapies published between their inception and August 2023.ResultsIn total, 147 studies involving 45,855 patients met the inclusion criteria. Among them, patients treated with ICIs reported 39.8% and 14.9% of all-grade and grade ≥3 immune-related adverse events (irAEs), respectively. The most common all-grade irAEs were dermatological and gastrointestinal issues, diarrhea, and pruritus, whereas patients who received ICIs showed most common grade ≥3 irAEs, including gastrointestinal events, diarrhea, increased aspartate aminotransferase and alanine transaminase levels, and hepatic and dermatological events. The overall trAE incidence in patients treated with ICIs was 83.2% for all-grade trAEs and 38.2% for grade ≥3 trAEs. TrAE incidence was highest for patients treated with cytotoxic T lymphocyte antigen-4 inhibitors for all-grade and grade ≥3 trAEs, with incidences of 86.4% and 39.2%, respectively. ICIs combined with targeted therapy showed the highest all-grade and grade ≥3 trAEs, with incidences of 96.3% and 59.4%, respectively. The most common all-grade trAEs were anemia, decrease in white blood cell count, decrease in neutrophil count, nausea, fatigue, diarrhea, and alopecia; patients who received ICIs presented relatively high incidences of grade ≥3 trAEs.ConclusionThis study provided comprehensive data regarding irAEs and trAEs in patients receiving ICIs. These results should be applied in clinical practice to provide an essential reference for safety profiles of ICIs.Systematic review registrationINPLASY platform, identifier INPLASY202380119.

The low carbon park islanded microgrid faces operational challenges due to the high variability and uncertainty of distributed renewable energy sources. These sources cause severe random disturbances that impair the frequency control performance and increase the regulation cost of the islanded microgrid, jeopardizing its safety and stability. This paper presents a data-driven intelligent load frequency control (DDI-LFC) method to address this problem. The method replaces the conventional LFC controller with an intelligent agent based on a deep reinforcement learning algorithm. To adapt to the complex islanded microgrid environment and achieve adaptive multi-objective optimal frequency control, this paper proposes the quantum-inspired maximum entropy actor-critic (QIS-MEAC) algorithm, which incorporates the quantum-inspired principle and the maximum entropy exploration strategy into the actor-critic algorithm. The algorithm transforms the experience into a quantum state and leverages the quantum features to improve the deep reinforcement learning’s experience replay mechanism, enhancing the data efficiency and robustness of the algorithm and thus the quality of DDI-LFC. The validation on the Yongxing Island isolated microgrid model of China Southern Grid (CSG) demonstrates that the proposed method utilizes the frequency regulation potential of distributed generation, and reduces the frequency deviation and generation cost.

Thioredoxin reductase 1 (TrxR1) has emerged as a promising target for cancer therapy. In our previous research, we discovered several new TrxR1 inhibitors and found that they all have excellent anti-tumor activity. At the same time, we found these TrxR1 inhibitors all lead to an increase in AKT phosphorylation in cancer cells, but the detailed role of AKT phosphorylation in TrxR1 inhibitor-mediated cell death remains unclear. In this study, we identified the combination of AKT and TrxR1 inhibitor displayed a strong synergistic effect in colon cancer cells. Furthermore, we demonstrated that the synergistic effect of auranofin (TrxR1 inhibitor) and MK-2206 (AKT inhibitor) was caused by ROS accumulation. Importantly, we found that ATM inhibitor KU-55933 can block the increase of AKT phosphorylation caused by auranofin, and exhibited a synergistic effect with auranofin. Taken together, our study demonstrated that the activation of ATM/AKT pathway is a compensatory mechanism to cope with ROS accumulation induced by TrxR1 inhibitor, and synergistic targeting of TrxR1 and ATM/AKT pathway is a promising strategy for treating colon cancer.

BackgroundIsoniazid-resistant, rifampicin-susceptible tuberculosis (Hr-TB) globally exhibits a high prevalence and serves as a potential precursor to multidrug-resistant tuberculosis (MDR-TB). Recognizing the spatial distribution of Hr-TB and identifying associated factors can provide strategic entry points for interventions aimed at early detection of Hr-TB and prevention of its progression to MDR-TB. This study aims to analyze spatial patterns and identify socioeconomic, demographic, and healthcare factors associated with Hr-TB in Shanghai at the county level.MethodWe conducted a retrospective study utilizing data from TB patients with available Drug Susceptible Test (DST) results in Shanghai from 2010 to 2016. Spatial autocorrelation was explored using Global Moran’s I and Getis-Ord Gi∗ statistics. A Bayesian hierarchical model with spatial effects was developed using the INLA package in R software to identify potential factors associated with Hr-TB at the county level.ResultsA total of 8,865 TB patients with DST were included in this analysis. Among 758 Hr-TB patients, 622 (82.06%) were new cases without any previous treatment history. The drug-resistant rate of Hr-TB among new TB cases in Shanghai stood at 7.20% (622/8014), while for previously treated cases, the rate was 15.98% (136/851). Hotspot areas of Hr-TB were predominantly situated in southwestern Shanghai. Factors positively associated with Hr-TB included the percentage of older adult individuals (RR = 3.93, 95% Crl:1.93–8.03), the percentage of internal migrants (RR = 1.35, 95% Crl:1.15–1.35), and the number of healthcare institutions per 100 population (RR = 1.17, 95% Crl:1.02–1.34).ConclusionWe observed a spatial heterogeneity of Hr-TB in Shanghai, with hotspots in the Songjiang and Minhang districts. Based on the results of the models, the internal migrant population and older adult individuals in Shanghai may be contributing factors to the emergence of areas with high Hr-TB notification rates. Given these insights, we advocate for targeted interventions, especially in identified high-risk hotspots and high-risk areas.

The limitations of current drug-eluting stent technologies in selectively inhibiting vascular smooth muscle cell proliferation, which often leads to inflammation, call for innovative approaches in coronary artery disease treatment. In the present work, we propose a revolutionary solution: a three-in-one platform for vascular stents, combining arsenic trioxide (ATO) and tacrolimus (TAC) to address anti-proliferation, pro-endothelialization, and anti-inflammation aspects. Our findings demonstrate that the synergistic action of ATO and TAC effectively suppresses aberrant vascular smooth muscle cell proliferation and mitigates endothelial cell inflammation. Remarkably, the combination treatment of TAC/ATO enhances endothelial cell migration and adhesion abilities. Moreover, our TAC/ATO-eluting stent exhibits superior re-endothelialization and anti-restenosis effects in a rabbit and porcine stent implantation model. Both in vitro and in vivo results solidify the notion that the TAC/ATO-eluting stent ensures rapid re-endothelialization and significantly reduces the incidence of in-stent restenosis. Overall, this study represents a promising and novel multifunctional platform with immense potential in the therapy of coronary artery disease.

Lactococcus lactis subsp. lactis (L. lactis subsp. lactis) is a commonly used starter cultures in fermented dairy products, contributing distinct flavor and texture characteristics with high application value. However, the strains from different isolates have different contributions to milk fermentation. Therefore, this study aimed to investigate the influence of L. lactis subsp. lactis isolated from various sources on the volatile metabolites present in fermented milk. In this study, L. lactis subsp. lactis from different isolation sources (yogurt, koumiss and goat yogurt) was utilized as a starter culture for fermentation. The volatile metabolites of fermented milk were subsequently analyzed by headspace solid phase microextraction gas chromatography-mass spectrography (HS-SPME-GC-MS). The results indicated significant differences in the structure and abundance of volatile metabolites in fermented milk produced with different isolates (R2Y = 0.96, Q2 = 0.88). Notably, the strains isolated from goat yogurt appeared to enhance the accumulation of ketones (goat yogurt vs yogurt milk: 50 %; goat yogur vs koumiss: 27.3 %)and aldehydes (goat yogurt vs yogurt milk: 21.4 %; goat yogurt vs koumiss: 54.5 %) in fermented milk than strains isolated from koumiss and yogurt milk. It significantly promoted the production of 8 flavor substances (1 substance with OAV ≥ 1 and 6 substances with OAV > 0.1) and enhanced the biosynthesis of valine, leucine, and isoleucine. This study provides valuable insights for the application of Lactococcus lactis subsp. lactis isolated from different sources in fermented dairy production and screening of potential starter cultures.

Alumina is considered as one of the most promising candidates for tritium permeation barrier. Coating preparation parameters such as the thickness and the surface coverage both affect the hydrogen isotope resistant performance of TPBs. Alumina coatings with thickness in the nanometric scale are considered in this work. Reduced thickness in the coatings leads to an improvement in the thermal conductivity and the reduction of mismatch problems with the substrate due to differences in the thermal expansion coefficients. Alumina coatings with different thickness were prepared on differentiated manufactured substrate by radio frequency magnetron sputtering with varying sputtering time. Deposited alumina layers are maximal 104.2 nm in thickness. Gas-driven permeation experiments have been performed to investigate the deuterium permeation behavior of the coating samples. It is noted that the alumina coating with only approximately 100 nm in thickness whose permeation reduction factor could achieve 1784 at 823 K and maintain its excellent performance at elevated temperatures, which indicates that the coating at nanometer scale with high surface coverage is capable of possessing extraordinary hydrogen permeation resistance property.

Abstract Ceramic membranes are a promising alternative to polymeric membranes for selective separations, given their ability to operate under harsh chemical conditions. However, current fabrication technologies fail to construct ceramic membranes suitable for selective molecular separations. Herein, we demonstrate a molecular-level design of ceramic thin-film composite membranes with tunable subnanometer pores for precise molecular sieving. Through burning off the distributed carbonaceous species of varied dimensions within hybrid aluminum oxide films, we created membranes with tunable molecular sieving. Specifically, the membranes created with methanol showed exceptional selectivity toward monovalent and divalent salts. We attribute this observed selectivity to the dehydration of the large divalent ions within the subnanometer pores. As a comparison, smaller monovalent ions can rapidly permeate with an intact hydration shell. Lastly, the flux of neutral solutes through each fabricated aluminum oxide membrane was measured for the demonstration of tunable separation capability. Overall, our work provides the scientific basis for the design of ceramic membranes with subnanometer pores for molecular sieving using atomic layer deposition.

ObjectiveTo investigate the incidence and severity of COVID-19 reinfection.MethodsWe searched relevant studies on COVID-19 reinfection， including cohort study， case report， and cross-sectional study in PubMed， Embase， CNKI and Wanfang databases. Revman5.3.0 was used for statistical analysis.ResultsA total of 52 studies in 19 countries were included. These literatures showed moderate and high quality. Furthermore， the pooled incidence of COVID-19 reinfection was estimated to be 1.9%（95%CI： 0.9%‒4.7%， P

The emergence of distributed energy and prosumers has greatly promoted the reform of the energy market. Blockchain technology provides a very potent solution for distributed energy transactions, however, blockchain technology still develops slowly in the energy field due to the unstable performance of the imperfect system. This paper aims to narrow this gap by the following steps. First, a function-driven integration method is proposed to combine the merit of blockchain distributed ledger and traditional centralized databases. Then a hybrid energy blockchain system architecture is designed, including the blockchain layer, smart contract layer, database layer, and client layer. Further, a peer-to-peer market mechanism considering energy storage arbitrage and fully automated matchmaking is developed on the hybrid blockchain system. The case study proves the effectiveness and safety of the system. The proposed architecture of combined blockchain and database technologies effectively paves the way for constructing a more reasonable and feasible distributed energy trading platform.

Abstract Colon cancer is a major cause of cancer-related death. Despite recent improvements in the treatment of colon cancer, new strategies to improve the overall survival of patients are urgently needed. Heat shock protein 90 (HSP90) is widely recognized as a promising target for treating various cancers, including colon cancer. However, no HSP90 inhibitor has been approved for clinical use due to limited efficacy. In this study, we evaluated the antitumor activities of HSP90 inhibitors in combination with piperlongumine in colon cancer cells. We show that combination treatment with HSP90 inhibitors and piperlongumine displayed strong synergistic interaction in colon cancer cells. These agents synergize by promoting ER stress, JNK activation, and DNA damage. This process is fueled by oxidative stress, which is caused by the accumulation of reactive oxygen species. These studies nominated piperlongumine as a promising agent for HSP90 inhibitor-based combination therapy against colon cancer.

Urban waterfronts are important gateways that reflect a city's image and characteristics. Evaluating waterfront vitality and its influencing factors is critical for guiding urban waterfront planning and redevelopment. Hourly human movement data, provided by the Baidu Heatmap, were used to explore the weekday and weekend urban vitality spatial distribution characteristics of the waterfronts of the Qinhuai River in Nanjing. Global (ordinary least squares) and local (multiscale geographically weighted regression) models revealed the influence of physical–environmental characteristics (objective) and spatial experience evaluation factors (subjective) on urban vitality. (1) The Qinhuai River waterfront urban vitality agglomeration characteristics were similar between weekdays and weekends, and the core vitality areas were distributed in the dense tourism, commercial, and residential areas along the river. (2) The evaluation of catering experience had the strongest positive correlation with vitality, whereas the waterfront distance had the strongest negative correlation. (3) The influence of each factor on waterfront vitality in the study area exhibited considerable spatial differences, with attenuation trends observed from the east-to-west river sections. This study shows the urban vitality distribution characteristics of the Qinhuai River waterfront spaces. Exploring the influence of physical–environmental and spatial evaluation factors on the vitality distribution can provide a scientific basis and reference for urban waterfront planning and redevelopment focusing on cultivating vitality.

Biodegradable magnesium (Mg) alloys are expected to be promising materials for cardiovascular stents (CVS), which can avoid the long-term clinical problems of current CVS, such as in-stent restenosis, late stent thrombosis, etc. Mg alloy stents exhibit superior biocompatibility and tunable biodegradability, compared with conventional permanent metallic stents. However, the poor formability and non-uniform corrosion of Mg alloy stents hinder their clinical application of CVS. This review focuses on the development of Mg alloys for CVS in recent years. According to the results of bibliometric analysis, we analyzed different biodegradable Mg alloy systems. Moreover, the structural design strategies for Mg alloy stents that can reduce the stress concentration, as well as the surface modification methods to control the corrosion behavior and biological performance of Mg alloy stents are also highlighted. At last, this review systematically discussed the potential directions and challenges of biodegradable magnesium stents (BMgS) in cardiovascular fields.

Organic room temperature afterglow (ORTA) can be categorized into two key mechanisms: continuous thermally activated delayed fluorescence (TADF) and room-temperature phosphorescence (RTP), both of which involve a triplet excited state. However, triplet excited states are easily quenched by non-radiative transitions due to oxygen and molecular vibrations. Solid-phase systems provide a conducive environment for triplet excitons due to constrained molecular motion and limited oxygen permeation within closely packed molecules. The stimulated triplet state tends to release energy through radiative transitions. Despite numerous reports on RTP in solid-phase systems in recent years, the complexity of these systems precludes the formulation of a universal theory to elucidate the underlying principles. Several strategies for achieving ORTA luminescence in the solid phase have been developed, encompassing crystallization, polymer host-guest doping, and small molecule host-guest doping. Many of these systems exhibit luminescent responses to various physical stimuli, including light stimulation, mechanical stimuli, and solvent vapor exposure. The appearance of these intriguing luminescent phenomena in solid-phase systems underscores their significant potential applications in areas such as light sensing, biological imaging, and information security.

Post-traumatic stress disorder (PTSD) is a persistent psychiatric condition that arises following exposure to traumatic events such as warfare, natural disasters, or other catastrophic incidents, typically characterized by heightened anxiety, depressive symptoms, and cognitive dysfunction. In this study, animals subjected to single prolonged stress (SPS) were administered evodiamine (EVO) and compared to a positive control group receiving sertraline. The animals were then assessed for alterations in anxiety, depression, and cognitive function. Histological analysis was conducted to examine neuronal changes in the hippocampus. In order to predict the core targets and related mechanisms of evodiamine intervention in PTSD, network pharmacology was used. The metabolic markers pre- and post-drug administration were identified using nontargeted serum metabolomics techniques, and the intersecting Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were screened. Finally, the core targets were validated through molecular docking, enzyme-linked immunosorbent assays, and immunofluorescence staining to confirm the anti-PTSD effects and mechanisms of these targets. As well as improving cognitive impairment, evodiamine reversed anxiety- and depression-like behaviors. It also inhibited the reduction in the number of hippocampal neuronal cells and Nissl bodies in SPS mice inhibited angiotensin converting enzyme (ACE) levels in the hippocampus of SPS mice, and modulated the renin angiotensin pathway and its associated serum metabolites in brain tissue. Evodiamine shows promise as a potential candidate for alleviating the symptoms of post-traumatic stress disorder.

Forest canopy height is a fundamental parameter of forest structure, and plays a pivotal role in understanding forest biomass allocation, carbon stock, forest productivity, and biodiversity. Spaceborne LiDAR (Light Detection and Ranging) systems, such as GEDI (Global Ecosystem Dynamics Investigation), provide large-scale estimation of ground elevation, canopy height, and other forest parameters. However, these measurements may have uncertainties influenced by topographic factors. This study focuses on the calibration of GEDI L2A and L1B data using an airborne LiDAR point cloud, and the combination of Sentinel-2 multispectral imagery, 1D convolutional neural network (CNN), artificial neural network (ANN), and random forest (RF) for upscaling estimated forest height in the Guangxi Gaofeng Forest Farm. First, various environmental (i.e., slope, solar elevation, etc.) and acquisition parameters (i.e., beam type, Solar elevation, etc.) were used to select and optimize the L2A footprint. Second, pseudo-waveforms were simulated from the airborne LiDAR point cloud and were combined with a 1D CNN model to calibrate the L1B waveform data. Third, the forest height extracted from the calibrated L1B waveforms and selected L2A footprints were compared and assessed, utilizing the CHM derived from the airborne LiDAR point cloud. Finally, the forest height data with higher accuracy were combined with Sentinel-2 multispectral imagery for an upscaling estimation of forest height. The results indicate that through optimization using environmental and acquisition parameters, the ground elevation and forest canopy height extracted from the L2A footprint are generally consistent with airborne LiDAR data (ground elevation: R2 = 0.99, RMSE = 4.99 m; canopy height: R2 = 0.42, RMSE = 5.16 m). Through optimizing, ground elevation extraction error was reduced by 45.5% (RMSE), and the canopy height extraction error was reduced by 30.3% (RMSE). After training a 1D CNN model to calibrate the forest height, the forest height information extracted using L1B has a high accuracy (R2 = 0.84, RMSE = 3.13 m). Compared to the optimized L2A data, the RMSE was reduced by 2.03 m. Combining the more accurate L1B forest height data with Sentinel-2 multispectral imagery and using RF and ANN for the upscaled estimation of the forest height, the RF model has the highest accuracy (R2 = 0.64, RMSE = 4.59 m). The results show that the extrapolation and inversion of GEDI, combined with multispectral remote sensing data, serve as effective tools for obtaining forest height distribution on a large scale.

Intercropping has the potential to enhance yields and nutrient availability in resource-limited agricultural systems. However, the effects on crop yield nutrients and soil properties can vary considerably depending on the specific plant combinations and intercropping ratios used. In this study, the advantages and impacts of intercropping C. esculentus with legumes were investigated by measuring their biomass, nutrient content, and soil properties. The experiment included five intercropping treatments: monoculture of C. esculentus (MC), intercropping of C. esculentus with Medicago sativa L. (alfalfa) at row spacing ratios of 4:4 (4:4CM) and 8:4 (8:4CM), and intercropping of C. esculentus with Glycine max (L.) Merr. (soybean), also at row spacing ratios of 4:4 (4:4CG) and 8:4 (8:4CG). Our results demonstrated that all four intercropping treatments (4:4CM, 4:4CG, 8:4CM, and 8:4CG) significantly increased the biomass of C. esculentus by approximately 41.05%, 41.73%, 16.08%, and 18.43%, respectively, compared with monoculture cultivation alone, among which the 4:4CG treatment was optimum. However, no significant differences were observed in alfalfa or soybean biomass across different intercropping ratios. A notable increase was found in the total nitrogen (TN) and total phosphorus (TP) contents in the leaves, roots, and tubers of C. esculentus under intercropping, along with increased soil organic carbon (SOC), alkaline-hydrolyzed nitrogen (AN), available phosphorus (AP), microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), and soil water content (SWC), and significantly reduced the soil pH. Among the intercropping treatments, the 4:4CG treatment also exhibited the most favorable soil properties. In particular, compared with MC, the 4:4CG treatment resulted in significant increases of 163.8%, 394.6%, and 716.8% in SOC, AN, and AP contents, respectively. The same treatment also led to significant increases of 48.34%, 46.40%, and 208.65% in MBC, MBN, and SWC, respectively. Overall, the findings suggest that the use of 4:4CG intercropping is an effective approach for sustainable farming management in Xinjiang.

As industrial technology continues to advance through integration, society's demand for electricity is rapidly increasing. To meet the requirements of refined grid management and address the elevated challenges arising from the increased electrical load, this paper delves into the investigation of distribution vehicle scheduling for the practical scenario of batch rotation of smart meters. Initially, based on the practical distribution task requirements of a provincial metrology verification center, a multi-level optimization model is constructed for the batch rotation and distribution vehicle scheduling of smart meters. The primary objective is to maximize the enhancement of smart meter distribution efficiency while minimizing the overall distribution cost. Moreover, this paper introduces a refined Grey Wolf Optimization algorithm (OLC-GWO) based on Opposition-based Learning, Levy flight strategy, and Cauchy mutation to solve the model. By generating an opposite population to improve the quality of initial feasible solutions and further harnessing the global search capabilities of Levy flight and Cauchy mutation operators, the algorithm's effectiveness is enhanced. The algorithm is subjected to testing using multiple benchmark functions and its performance is compared with variants of GWO, as well as several cutting-edge intelligent optimization algorithms including Particle Swarm Optimization (PSO), Harris Hawks Optimization (HHO), and Honey Bee Algorithm (HBA). The results indicate that OLC-GWO exhibits excellent performance in terms of convergence speed and optimization capability. Finally, the improved algorithm is subjected to simulation experiments by incorporating order data from the practical distribution operations of a provincial metrology verification center. The outcomes verify the efficiency of the proposed algorithm, reinforcing the practical significance of the established model in addressing the real-world challenge of batch rotation and distribution vehicle scheduling for smart meters.

BackgroundsThe diagnostic delay of tuberculosis (TB) contributes to further transmission and impedes the implementation of the End TB Strategy. Therefore, we aimed to describe the characteristics of patient delay, health system delay, and total delay among TB patients in Shanghai, identify areas at high risk for delay, and explore the potential factors of long delay at individual and spatial levels.MethodThe study included TB patients among migrants and residents in Shanghai between January 2010 and December 2018. Patient and health system delays exceeding 14 days and total delays exceeding 28 days were defined as long delays. Time trends of long delays were evaluated by Joinpoint regression. Multivariable logistic regression analysis was employed to analyze influencing factors of long delays. Spatial analysis of delays was conducted using ArcGIS, and the hierarchical Bayesian spatial model was utilized to explore associated spatial factors.ResultsOverall, 61,050 TB patients were notified during the study period. Median patient, health system, and total delays were 12 days (IQR: 3–26), 9 days (IQR: 4–18), and 27 days (IQR: 15–43), respectively. Migrants, females, older adults, symptomatic visits to TB-designated facilities, and pathogen-positive were associated with longer patient delays, while pathogen-negative, active case findings and symptomatic visits to non-TB-designated facilities were associated with long health system delays (LHD). Spatial analysis revealed Chongming Island was a hotspot for patient delay, while western areas of Shanghai, with a high proportion of internal migrants and industrial parks, were at high risk for LHD. The application of rapid molecular diagnostic methods was associated with reduced health system delays.ConclusionDespite a relatively shorter diagnostic delay of TB than in the other regions in China, there was vital social-demographic and spatial heterogeneity in the occurrence of long delays in Shanghai. While the active case finding and rapid molecular diagnosis reduced the delay, novel targeted interventions are still required to address the challenges of TB diagnosis among both migrants and residents in this urban setting.

Background: Qing-Jin-Hua-Tan decoction (QJHTD) is a classic traditional Chinese medicine (TCM) prescription that first appeared in the ancient book Yi-Xue-Tong-Zhi. QJHTD has shown effectiveness for treating chronic obstructive pulmonary disease (COPD), although its mechanisms of action are still perplexing. The molecular mechanisms underlying the curative effects of QJHTD on COPD is worth exploring. Methods: In vitro antiapoptotic and antiinflammatory activities of QJHTD were evaluated using cell viability, proliferation, apoptosis rate, and expression of IL-1β and TNF-α in BEAS-2B and RAW264.7 cells challenged with cigarette smoke (CS) extract (CSE) and lipopolysaccharide (LPS). In vivo therapeutic activities of QJHTD were evaluated using respiratory parameters (peak inspiratory flow (PIFb) and peak expiratory flow (PEFb) values), histopathology (mean linear intercept, MLI), and proinflammatory cytokine (IL-1β and TNF-α) and cleaved caspase-3 (c-Casp3) levels in the lung tissue of CS–LPS-exposed BALB/c mice. Network pharmacology-based prediction, transcriptomic analysis, and metabolic profiling were employed to investigate the signaling molecules and metabolites pertinent to the anti-COPD action of QJHTD. Results: Increased cell viability and proliferation with decreased apoptosis rate and proinflammatory cytokine expression were noted after QJHTD intervention. QJHTD administration elevated PEFb and PIFb values, reduced MLI, and inhibited IL-1β, TNF-α, and c-Casp3 expression in vivo. Integrated network pharmacology–transcriptomics revealed that suppressing inflammatory signals (IL-1β, IL-6, TNF, IκB–NF-κB, TLR, and MAPK) and apoptosis contributed to the anti-COPD property of QJHTD. Metabolomic profiling unveiled prominent roles for the suppression of apoptosis and sphingolipid (SL) metabolism and the promotion of choline (Ch) metabolism in the anti-COPD effect of QJHTD. Integrative transcriptomics–metabolomics unraveled the correlation between SL metabolism and apoptosis. In silico molecular docking revealed that acacetin, as an active compound in QJHTD, could bind with high affinity to MEK1, MEK2, ERK1, ERK2, Bcl2, NF-κB, and alCDase target proteins. Conclusion: The therapeutic effect of QJHTD on COPD is dependent on regulating inflammatory signals and apoptosis-directed SL metabolism. These findings provide deeper insights into the molecular mechanism of action of QJHTD against COPD and justify its theoretical promise in novel pharmacotherapy for this multifactorial disease.

As global temperatures rise and climate change becomes more severely. People realize that air conditioning systems as a controllable resource and play an increasingly important role in reducing carbon emissions. In the past, the operation optimization of air conditioning systems was mainly oriented to user comfort and electricity costs ignoring the long-term impact on the environment. This article aims to establish a multi-objective model of air-conditioning load to ensure user temperature comfort performance and reduce the total cost (i.e., electricity cost and carbon emission cost) simultaneously. Multi Sand Cat Swarm Optimization (MSCSO) algorithm combined with gray target decision-making (GTD) is used to explore optimal solution. Meanwhile four competitive strategies are applied to validate the effectiveness of the proposed method, i.e., genetic algorithm (GA), MSCSO-comfort objective, MSCSO-total electricity cost objective and unoptimization. The simulation results show that the MSCSO-GTD based objective method can significantly reduce total costs while taking into account appropriate indoor temperature comfort.

Barnacles have demonstrated adaptability to a range of habitats, spanning from shallow water to the deep sea. Given the harsh conditions present in hydrothermal vents, hydrothermal vent barnacles serve as the model organism for investigating the interplay between evolution and adaptability. In order to gain insights into barnacle adaptive characteristics, particularly within hydrothermal vents, we conducted a comprehensive analysis of the mitogenomes and transcriptome in a deep-sea barnacle (Neolepas marisindica), in comparison to its shallow-water related species. The mitogenomes with the same genetic skews and the non-synonymous/synonymous mutation ratios (Ka/Ks) of the mitogenomes indicate that the protein-coding genes (COIII, ND2, and ND6) of N. marisindica are under positive selection. Meanwhile, the functional annotation shows that distinctly positive selected orthologs in N. marisindica are predominately related to neural signal transduction, immunity, antiapoptotic, and energy metabolism. These results indicate that the mitogenomes and key genes found in transcriptomic analysis are under high-temperature and high-pressure conditions, and which may contribute N. marisindica to have evolved to adapt to the extreme hydrothermal vent environments. The findings shed light on the mitogenome and transcriptome of N. marisindica, which lays a foundation for the in-depth understanding of the adaptation mechanism of sessile invertebrates to the deep-sea environment.

IntroductionThe deep-sea environment is always characterized by high hydrostatic pressure, fluctuating temperatures, heavy metals, darkness, and others. The Vesicomyidae inhabit cold seep zones, hydrothermal vents, and other chemically reduced environments.MethodsTo enhance the understanding of the adaptation mechanisms of clams in extreme environments, a comprehensive proteomic study was conducted on the cold seep clam Archivesica marissinica and shallow water clam Ruditapes philippinarum.ResultsA total of 4,557 proteins were identified from the comparative groups. The Gene Ontology results indicated that the differentially expressed proteins (DEP) for the comparative group Rpgill vs. Amgill were enriched in the nitrogen compound metabolic process, and others. The comparative analysis for Amfoot vs. Amgill and Ammantle vs. Amgill revealed significant enrichment of the differential proteins that were involved in metal ion transport, divalent inorganic cation transport, and so on. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis for the comparative group Rpgill vs. Amgill was significantly enriched in the regulation of actin cytoskeleton, lysosome, and others. The proteins that exhibited differential expression in the cold seep clam’ different tissues were also enriched in important pathways, such as lysosome, fatty acid degradation, nitrogen metabolism.DiscussionThe further analysis identified crucial response proteins involved in various biological pathways. For example, the pattern recognition receptors, such as galectin and peptidoglycan recognition protein, participated in recognition of symbiotic microorganisms. The lysosome pathway members, such as cathepsin and saposins, were engaged in the degradation process of symbiont proteins during symbiont digestion. Profilin and gelsolin from actin cytoskeleton pathway might be pressure-related proteins. Furthermore, carbonic anhydrases from nitrogen metabolism KEGG pathway provide inorganic carbon for symbiotic bacteria. Additionally, Mn superoxide dismutase plays a role in the scavenging of superoxide anion radicals and antioxidant activity. Then, arginine kinases facilitate the low temperature adaptation of deep-sea shellfish with its cold adaptation characters. These findings offer novel perspectives on the proteins that are implicated in A. marisica’s response to cold seep environments, thereby contributing to the understanding of deep-sea biological adaptation and the preservation of deep-sea ecosystems.

Abstract Macrophage efferocytosis of apoptotic osteoblasts (apoOBs) is a key osteoimmune process for bone homeostasis. However, apoOBs frequently accumulate in aged bone marrow, where they may mount proinflammatory responses and progressive bone loss. The reason why apoOBs are not cleared during aging remains unclear. In this study, it is demonstrated that aged apoOBs upregulate the immune checkpoint molecule CD47, which is controlled by SIRT6‐regulated transcriptional pausing, to evade clearance by macrophages. Using osteoblast‐ and myeloid‐specific gene knockout mice, SIRT6 is further revealed to be a critical modulator for apoOBs clearance via targeting CD47‐SIRPα checkpoint. Moreover, apoOBs activate SIRT6‐mediated chemotaxis to recruit macrophages by releasing apoptotic vesicles. Two targeting delivery strategies are developed to enhance SIRT6 activity, resulting in rejuvenated apoOBs clearance and delayed age‐related bone loss. Collectively, the findings reveal a previously unknown linkage between immune surveillance and bone homeostasis and targeting the SIRT6‐regulated mechanism can be a promising therapeutic strategy for age‐related bone diseases.