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The Changbaishan Tianchi intraplate volcano is one of the most active and hazardous volcanoes of NE Asia, characterized by a summit caldera formed after the 946 CE ‘Millennium’ Plinian eruption. From December 2020 to June 2021, the frequency and magnitude of earthquakes at Tianchi were significantly higher than during background periods, with hundreds of earthquakes (46 events per month in average) and reaching a local magnitude of ML 3.1. This study reports a comprehensive deformation analysis and geophysical inversion scheme aimed to unveil the dynamics of this period. Multi-temporal InSAR analysis results of 32 ALOS-2 images from 2018 to 2022 show that the surface deformation is a combination of seasonal fluctuations (± 25 mm in average, with a maximum ± 45 mm) and a long-term positive component. The least squares linear regression of the deformation time series and temperature data, isolates the seasonal fluctuations, revealing a clear uplift-subsidence process from June 2020 to July 2021 in the caldera area. To constrain the Tianchi plumbing system dynamics, a combined inversion scheme consisting of three deformation sources is designed. The inversion results and the seismic records indicate that Tianchi volcano has experienced a low-level unrest episode from December 2020 to June 2021. The shallower plumbing system, located at about 5–9 km depth and modelled by pressurized spheroids, underwent a cumulative volume increase of 26 × 106 m3 from November 2018 to April 2021, followed by a volume decrease of 9 × 106 m3 from April to July 2021. This suggests magma uprising from the 14 km deep storage zone to the shallower plumbing system, followed by depressurization of the plumbing system due to the escape of fluids. This research provides a comprehensive understanding of the magma and fluid migration dynamics within the Tianchi multi-level plumbing system for the first time.

Accurate power consumption assessment is of critical importance in the fast-evolving world of cloud and edge computing. These technologies enable rapid data processing and storage but they also require huge amounts of energy. This energy requirement directly impacts operational costs, as well as environmental responsibility. We are conducting research to develop a specialized cloud-edge power measurement and security model. This model delivers reliable power usage data from these systems while maintaining security for the data they process and store. A combination of simulation-based analysis and real-world experimentation helped us to deliver these results. Monte Carlo based simulations produced power usage predictions under various conditions and Load Testing validated their real-world performance. A Threat Modeling-based security study identified potential vulnerabilities and suggested protection protocols. A collaborative approach enhances power measurements accuracy and encourages secure operation of the combined cloud-edge systems. By fusing these metrics, a more efficient and secure operation of computing resources becomes possible. This research underscores the critical importance of developing advanced techniques for power metering and security in cloud-edge computing systems. Future research may focus on both expanding the model’s use to an array of larger, more complex networks, as well as the inclusion of AI driven predictive analytics to amplify accuracy of power management.

BackgroundAdvanced schistosomiasis is the most serious outcome of infection and has a negative impact on both physical fitness and mental health of patients, the latter of which has long been overlooked. Therefore, we performed this systematic review and meta-analysis to estimate the overall prevalence of depressive symptoms, one of the most common mental problems, in patients with advanced schistosomiasis in China.MethodsSix electronic databases were searched for studies reporting the prevalence of depressive symptoms in the targeted patients. Assessments were pooled using a fixed- or random-effects model based on heterogeneity test. Subgroup analyses were further performed and differences between/among groups were examined using the chi-squared test. The protocol had previously been registered in PROSPERO (CRD42023406708).ResultsA total of 11 studies with 1,673 participants were included. The pooled prevalence of depressive symptoms in advanced schistosomiasis in China was 62.01% (95% CI: 51.30% - 72.72%), with a significant heterogeneity among studies. Depressive symptoms were more prevalent in patients with complications and more than half of the patients suffered a mild- or moderate-level of depression. No publication bias was found, and sensitivity analysis showed a stable result.ConclusionsThe overall prevalence of depressive symptoms in advanced schistosomiasis in China was high enough to warrant psychotherapeutic interventions, especially for patients with complications. This would greatly prevent or/and reduce depression and improve their quality of life.

Abstract The integrity of the intestinal mucosal barrier is crucial for protecting the intestinal epithelium against invasion by commensal bacteria and pathogens, thereby combating colitis. The investigation revealed that the absence of TSP50 compromised the integrity of the intestinal mucosal barrier in murine subjects. This disruption facilitated direct contact between intestinal bacteria and the intestinal epithelium, thereby increasing susceptibility to colitis. Mechanistic analysis indicated that TSP50 deficiency in intestinal stem cells (ISCs) triggered aberrant activation of the TGF‐β signaling pathway and impeded the differentiation of goblet cells in mice, leading to impairment of mucosal permeability. By inhibiting the TGF‐β pathway, the functionality of the intestinal mucosal barrier is successfully restored and mitigated colitis in TSP50‐deficient mice. In conclusion, TSP50 played a crucial role in maintaining the intestinal mucosal barrier function and exhibited the preventive effect against the development of colitis by regulating the TGF‐β signaling pathway.

The incidence of ischemic stroke (IS) is rising in tandem with the global aging population. There is an urgent need to delve deeper into the pathological mechanisms and develop new neuroprotective strategies. In the present review, we discuss the latest advancements and research on various nanodrug delivery systems (NDDSs) for targeting microglial polarization in IS treatment. Furthermore, we critically discuss the different strategies. NDDSs have demonstrated exceptional qualities to effectively permeate the blood–brain barrier, aggregate at the site of ischemic injury, and target specific cell types within the brain when appropriately modified. Consequently, NDDSs have considerable potential for reshaping the polarization phenotype of microglia and could be a prospective therapeutic strategy for IS. The treatment of IS remains a challenge. However, this review provides a new perspective on neuro-nanomedicine for IS therapies centered on microglial polarization, thereby inspiring new research ideas and directions.

BackgroundThymus mandschuricus is an aromatic and medicinal plant with notable antibacterial and antioxidant properties. However, traditional breeding methods rely on phenotypic selection due to a lack of molecular resources. A high-quality reference genome is crucial for marker-assisted breeding, genome editing, and molecular genetics.ResultsWe utilized PacBio and Hi-C technologies to generate a high-quality chromosome-level reference genome for T. mandschuricus, with a size of 587.05 Mb and an N50 contig size of 8.41 Mb. The assembled genome contained 29,343 predicted protein-coding genes, and evidence of two distinct whole-genome duplications in T. mandschuricus was discovered. Comparative genomic analysis revealed rapid evolution of genes involved in phenylpropanoid biosynthesis and the CYP450 gene family in T. mandschuricus. Additionally, we reconstructed the gene families of terpenoid biosynthesis structural genes, such as TPS, BAHD, and CYP, and identified regulatory networks controlling the expression of aroma-synthesis genes by integrating transcriptome data from various organs and developmental stages. We discovered that hormones and transcription factors may collaborate in controlling aroma-synthesis gene expression.ConclusionThis study provides the first high-quality genome sequence and gene annotation for T. mandschuricus, an indigenous thyme species unique to China. The genome assembly and the comprehension of the genetic basis of fragrance synthesis acquired from this research could potentially serve as targets for future breeding programs and functional studies.

Accurately predicting key features in WWTPs is essential for optimizing plant performance and minimizing operational costs. This study assesses the potential of various machine learning models for predicting the inflow to anoxic sludge reactors. Firstly, it conducts a comprehensive evaluation of diverse machine learning models, including k-Nearest Neighbors (kNN), Random Forest (RF), XGBoost, CatBoost, LightGBM, and Decision Tree Regression (DTR), for predicting the flow into the Anoxic section under various weather conditions (dry, rainy, and stormy). Secondly, the study introduces parsimonious models guided by variable importance from the XGBoost algorithm. Furthermore, the study employs SHAP (SHapley Additive exPlanations) to elucidate model predictions, providing insights into the contribution of each feature. Data from the COST Benchmark Simulation Model (BSM1) is used to verify the investigated models' effectiveness. Each dataset consists of 14 days of influent data at 15-minute intervals, with 80% of the data used for model training. Results show that ensemble learning methods, particularly CatBoost and XGBoost, demonstrate satisfactory predictive results for Anoxic section flow in the presence of increased variability under rainy and stormy conditions. Notably, the CatBoost and XGBoost models achieve average Mean Absolute Percentage Error values of 1.33% and 1.59%, outperforming the other methods.

The accurate modeling and forecasting of Battery State of Health (SOH) is crucial for ensuring reliable performance and longevity of lithium-ion batteries. This article introduces a data-driven approach for SOH prediction using Gaussian Process Regression (GPR), selected for its ability to model complex data relationships and capture prediction uncertainty without relying on future load information. Recognizing the effect of reversible capacity recoveries on prediction accuracy, this work employs the ISEA-RWTH 48 Li-ion Cells dataset, deliberately devoid of such recoveries prior to training the GPR model. The GPR model was evaluated and compared with Support Vector Regression (SVR) using the publicly available dataset. First and second End of Life (EOL) scenarios were considered, relevant to primary and secondary battery applications. The results demonstrated the GPR model's superior performance. Particularly, mid-life and late-life predictions displayed better accuracy with GPR, showcasing higher R2 values and lower MAPE values (e.g., mid-life prediction: GPR's average R2 = 0.99, SVR's = 0.9789; GPR's average MAPE = 0.1916, SVR's = 1.3028). Moreover, GPR exhibited the ability to quantify uncertainty in capacity degradation and forecast first and second EOL instances effectively (e.g., mid-life predictions had 1.7 cycle error at 1st EOL and 8.9 cycle error at 2nd EOL). The research also offers valuable insights into the application of machine learning methods for predicting the health degradation of lithium-ion batteries.

One of the malignant tumors with a high occurrence rate worldwide is gastric carcinoma, which is an epithelial malignant tumor emerging from the stomach. Natural product polysaccharides are a kind of natural macromolecular polymers, which have the functions of regulating immunity, anti-oxidation, anti-fatigue, hypoglycemia, etc. Natural polysaccharides have remarkable effectiveness in preventing the onset, according to studies, and development of gastric cancer at both cellular and animal levels. This paper summarizes the inhibitory mechanisms and therapeutic significance of plant polysaccharides, fungi polysaccharides, and algal polysaccharides in natural product polysaccharides on the occurrence and development of gastric cancer in recent years, providing a theoretical basis for the research, development, and medicinal value of polysaccharides.

Solar photovoltaic (PV) systems have become a vital renewable energy source, witnessing rapid global demand. Nevertheless, these systems are susceptible to faults and anomalies that can deteriorate performance and yield significant consequences. Hence, this paper is dedicated to reviewing recent advancements in monitoring, modeling, and fault detection methods for PV systems. It encompasses diverse PV system types, including grid-connected, stand-alone, and hybrid configurations, and delves into the latest data acquisition and monitoring techniques. The review also discusses various performance modeling approaches, including empirical, analytical, and numerical models, highlighting the significance of model validation and calibration. Furthermore, it provides a comprehensive analysis of model-based fault detection techniques. Overall, this paper underscores the pivotal role of fault detection in PV systems and offers a thorough comprehension of available techniques vital for enhancing system management and maintenance.

Abstract Purpose The contouring of organs at risk (OARs) in head and neck cancer radiation treatment planning is a crucial, yet repetitive and time-consuming process. Recent studies have applied deep learning (DL) algorithms to automatically contour head and neck OARs. This study aims to conduct a systematic review and meta-analysis to summarize and analyze the performance of DL algorithms in contouring head and neck OARs. The objective is to assess the advantages and limitations of DL algorithms in contour planning of head and neck OARs. Methods This study conducted a literature search of Pubmed, Embase and Cochrane Library databases, to include studies related to DL contouring head and neck OARs, and the dice similarity coefficient (DSC) of four categories of OARs from the results of each study are selected as effect sizes for meta-analysis. Furthermore, this study conducted a subgroup analysis of OARs characterized by image modality and image type. Results 149 articles were retrieved, and 22 studies were included in the meta-analysis after excluding duplicate literature, primary screening, and re-screening. The combined effect sizes of DSC for brainstem, spinal cord, mandible, left eye, right eye, left optic nerve, right optic nerve, optic chiasm, left parotid, right parotid, left submandibular, and right submandibular are 0.87, 0.83, 0.92, 0.90, 0.90, 0.71, 0.74, 0.62, 0.85, 0.85, 0.82, and 0.82, respectively. For subgroup analysis, the combined effect sizes for segmentation of the brainstem, mandible, left optic nerve, and left parotid gland using CT and MRI images are 0.86/0.92, 0.92/0.90, 0.71/0.73, and 0.84/0.87, respectively. Pooled effect sizes using 2D and 3D images of the brainstem, mandible, left optic nerve, and left parotid gland for contouring are 0.88/0.87, 0.92/0.92, 0.75/0.71 and 0.87/0.85. Conclusions The use of automated contouring technology based on DL algorithms is an essential tool for contouring head and neck OARs, achieving high accuracy, reducing the workload of clinical radiation oncologists, and providing individualized, standardized, and refined treatment plans for implementing "precision radiotherapy". Improving DL performance requires the construction of high-quality data sets and enhancing algorithm optimization and innovation.

Abstract Objective Pregnant women experience enormous psychological pressure, particularly during the late trimester. Symptoms of depression in late pregnancy may persist postpartum, increasing the incidence of postpartum depression. This study is aimed to investigate the factors influencing depressive symptoms among pregnant women in their third trimester at a Chinese tertiary hospital and provide information for effective intervention. Methods Pregnant women in their third trimester who visited the Ningbo Women and Children’s Hospital between January 1, 2020 and June 30, 2022 participated in this study. A score of ≥ 13 on the Edinburgh Postnatal Depression Scale (EPDS) was considered as positive for depressive symptom. Potential influencing factors were examined by using an online questionnaire and analyzed using multivariate logistic regression. Results A total of 1196 participants were recruited. The mean EPDS score was 7.12 ± 4.22. The positive screening rate for depressive symptom was 9.9%. Univariate analysis showed that living with partner, annual family income, planned pregnancy, sleep quality, and partner’s drinking habits were related to positive screening for depression(P

【Objective】In modern vegetable facility cultivation, the quality of vegetable seedlings plays a very important role in the economic benefits of subsequent agricultural production. Continuous light is a common special light mode in artificial light plant factory. Exploring the effect of continuous light combined with light quality on the growth and development of pepper seedlings could provide an important technical reference for efficiently improving the resistance of pepper seedlings.【Method】The pepper backbone parent '6421' was used as the test material, and 6 light treatment groups were set up: normal white light irradiation group (CW), normal blue light irradiation group (CB), normal red light irradiation group (CR), continuous white light irradiation group (TW), continuous blue light irradiation group (TB) and continuous red light irradiation group (TR). The effects of continuous photoperiod treatment combined with red and blue light on the growth and physiological characteristics of pepper seedlings were studied.【Result】(1) TR significantly increased the plant height and stem diameter of pepper seedlings by 20.5% and 10.6%, respectively, compared with the CW group. After TR treatment, the seedling index increased significantly by 2.38 times, while TB significantly reduced the plant height and stem diameter of pepper seedlings by 17.1% and 14.3%, and the root-shoot ratio increased significantly by 2.62 times. (2) There was no significant difference in Pn and Gs of pepper seedling leaves between TR and TB, but Tr and Ci of TB were significantly lower than those of TR. Compared with CW, Tr and Ci of TB were significantly reduced by 62.5% and 51.1%. The chlorophyll fluorescence parameters of pepper seedling leaves showed opposite results after different light treatments. The Fv/Fm, Fv/Fo, NPQ and qP values of pepper seedling leaves in TB group were significantly higher than those in TR group. The qP of TB and TR was significantly higher than that of CW, increasing by 36.1% and 26.1%, respectively. (3) The antioxidant enzyme activity and osmotic substances of pepper seedlings were significantly different after continuous red light treatment and continuous blue light treatment. TB significantly increased SOD, POD and CAT in leaves of pepper seedlings. The POD and CAT activities of pepper seedling leaves were also significantly increased after TR treatment, while the MDA content of pepper leaves after TB and TR treatments was significantly reduced by 55%-56% compared with that of CW.【Conclusion】Continuous light conditions have a positive effect on the growth and development of pepper seedlings at the seedling stage, and the antioxidant enzyme activity and osmotic substances of pepper seedlings under continuous light irradiation combined with monochromatic red and monochromatic blue light treatments increase to different degrees to better counteract the light stress environment and improve the adaptability of pepper seedlings.

Abstract Activating transcription factor 6 (ATF6) is an endoplasmic reticulum stress responsive gene. We previously reported that conditional knockout of hepatic ATF6 exacerbated liver metabolic damage by repressing autophagy through mTOR pathway. However, the mechanism by which ATF6 influence liver metabolism has not been well established. Hydrogen sulfide (H2S) is a gaseous signaling molecule that plays an important role in regulating inflammation, and suppress nonalcoholic fatty liver in mice. Based on the previous study, we assumed that ATF6 may regulate H2S production to participate in liver metabolism. In order to clarify the mechanism by which ATF6 regulates H2S synthesis to ameliorate liver steatosis and inflammatory environment, we conducted the present study. We used the liver specific ATF6 knockout mice and fed on high-fat-diet, and found that H2S level was significantly downregulated in hepatic ATF6 knockout mice. Restoring H2S by the administration of slow H2S releasing agent GYY4137 ameliorated the hepatic steatosis and glucose tolerance. ATF6 directly binds to the promoter of cystathionine β synthetase (CBS), an important enzyme in H2S synthesis. Thus, ATF6 could upregulate H2S production through CBS. Sulfhydrated Sirtuin-1 (SIRT1) was downregulated in ATF6 knockout mice. The expression of pro-inflammatory factor IL-17A was upregulated and anti-inflammatory factor IL-10 was downregulated in ATF6 knockout mice. Our results suggest that ATF6 can transcriptionally enhance CBS expression as well as H2S synthesis. ATF6 increases SIRT1 sulfhydration and ameliorates lipogenesis and inflammation in the fatty liver. Therefore, ATF6 could be a novel therapeutic strategy for high-fat diet induced fatty liver metabolic abnormalities.

Abstract This experiment aimed to study the effects of straw return combined with potassium fertilizer on stem lodging resistance, grain quality, and yield of spring maize. The objective was to provide a scientific basis for the rational utilization of Inner Mongolia spring maize straw and potassium fertilizer resources. The test material used was ‘Xianyu 335’, and the study was conducted in three ecological regions from east to west of Inner Mongolia (Tumochuan Plain Irrigation Area, Hetao Plain Irrigation Area, and Lingnan Warm Dry Zone). A split-plot design was employed, with the straw return method as the main plot and potassium fertilizer dosage as the secondary plot. We determined the stem resistance index, grain quality, and yield. The results showed that both straw return and potassium application improved stem lodging resistance, grain quality, and maize yield. Combining straw return with the reasonable application of potassium fertilizer enhanced the effectiveness of potassium fertilizer, increased lodging resistance, maize yield, and improved grain quality and yield stability. Under the straw return treatment, with potassium application compared to no potassium application, significant increases were observed in maize plant height, stem diameter, dry weight of stems, stem compressive strength, stem bending strength, grain protein content, yield, straw potassium accumulation content, and soil available potassium content. These increases were up to 30.79 cm, 2.63 mm, 15.40 g, 74.93 N/mm2, 99.65 N/mm2, 13.68%, 3142.43 kg/hm2, 57.97 kg/hm2, and 19.80 mg/kg, respectively. Therefore, the interaction of straw return and potassium fertilizer was found to be the most effective measure for maintaining high-yield and stress-resistant cultivation, improving grain quality, and optimizing the management of straw and potassium fertilizer resources. This approach is suitable for promotion and application in the spring maize growing areas of Inner Mongolia.

Abstract Background The establishment of a robust gut microbiota in piglets during their early developmental stage holds the potential for long-term advantageous effects. However, the optimal timeframe for introducing probiotics to achieve this outcome remains uncertain. Results In the context of this investigation, we conducted a longitudinal assessment of the fecal microbiota of 63 piglets at three distinct pre-weaning time points. Simultaneously, we gathered vaginal and fecal samples from 23 sows. Employing 16S rRNA gene and metagenomic sequencing methodologies, we conducted a comprehensive analysis of the fluctuation patterns in microbial composition, functional capacity, interaction networks, and colonization resistance within the gut microbiota of piglets. As the piglets progressed in age, discernible modifications in intestinal microbial diversity, composition, and function were observed. A source-tracking analysis unveiled the pivotal role of fecal and vaginal microbiota derived from sows in populating the gut microbiota of neonatal piglets. By D21, the microbial interaction network displayed a more concise and efficient configuration, accompanied by enhanced colonization resistance relative to the other two time points. Moreover, we identified three strains of Ruminococcus sp. at D10 as potential candidates for improving piglets' weight gain during the weaning phase. Conclusions The findings of this study propose that D10 represents the most opportune juncture for the introduction of external probiotic interventions during the early stages of piglet development. This investigation augments our comprehension of the microbiota dynamics in early-life of piglets and offers valuable insights for guiding forthcoming probiotic interventions.

Abstract Acute kidney injury (AKI) is a clinical syndrome with high morbidity and mortality but no specific therapy. Microsomal prostaglandin E synthase-2 (mPGES-2) is a PGE2 synthase but can metabolize PGH2 to malondialdehyde by forming a complex with heme. However, the role and mechanism of action of mPGES-2 in AKI remain unclear. To examine the role of mPGES-2, both global and tubule-specific mPGES-2-deficient mice were treated with cisplatin to induce AKI. mPGES-2 knockdown or overexpressing HK-2 cells were exposed to cisplatin to cause acute renal tubular cell injury. The mPGES-2 inhibitor SZ0232 was used to test the translational potential of targeting mPGES-2 in treating AKI. Additionally, mice were subjected to unilateral renal ischemia/reperfusion to further validate the effect of mPGES-2 on AKI. Interestingly, both genetic and pharmacological blockage of mPGES-2 led to decreased renal dysfunction and morphological damage induced by cisplatin and unilateral renal ischemia/reperfusion. Mechanistic exploration indicated that mPGES-2 deficiency inhibited ferroptosis via the heme-dependent regulation of the p53/SLC7A11/GPX4 axis. The present study indicates that mPGES-2 blockage may be a promising therapeutic strategy for AKI.

Abstract Background Sodium-glucose cotransporter 2 (SGLT2) inhibitors have shown promise in reducing the risk of atrial fibrillation (AF). However, the results are controversial and the underlying metabolic mechanism remains unclear. Emerging evidence implied that SGLT2 inhibitors have extra beneficial metabolic effects on circulating metabolites beyond glucose control, which might play a role in reducing the risk of AF. Hence, our study aimed to investigate the effect of circulating metabolites mediating SGLT2 inhibition in AF by Mendelian randomization (MR). Methods A two-sample and two-step MR study was conducted to evaluate the association of SGLT2 inhibition with AF and the mediation effects of circulating metabolites linking SGLT2 inhibition with AF. Genetic instruments for SGLT2 inhibition were identified as genetic variants, which were both associated with the expression of SLC5A2 gene and glycated hemoglobin level (HbA1c). Positive control analysis on type 2 diabetes mellitus (T2DM) was conducted to validate the selection of genetic instruments. Results Genetically predicted SGLT2 inhibition (per 1 SD decrement in HbA1c) was associated with reduced risk of T2DM (odds ratio [OR] = 0.63 [95% CI 0.45, 0.88], P = 0.006) and AF (0.51 [0.27, 0.97], P = 0.039). Among 168 circulating metabolites, two metabolites were both associated with SGLT2 inhibition and AF. The effect of SGLT2 inhibition on AF through the total concentration of lipoprotein particles (0.88 [0.81, 0.96], P = 0.004) and the concentration of HDL particles (0.89 [0.82, 0.97], P = 0.005), with a mediated proportion of 8.03% (95% CI [1.20%, 14.34%], P = 0.010) and 7.59% ([1.09%, 13.34%], P = 0.011) of the total effect, respectively. Conclusions This study supported the association of SGLT2 inhibition with a reduced risk of AF. The total concentration of lipoprotein particles and particularly the concentration of HDL particles might mediate this association. Further mechanistic and clinical studies research are needed to understand the mediation effects of circulating metabolites especially blood lipids in the association between SGLT2 inhibition and AF.

Abstract Background Important roles of INHBB in various malignancies are increasingly identified. The underlying mechanisms in gastric cancer (GC) microenvironment are still greatly unexplored. Methods The clinical significance of INHBB and the correlation between INHBB and p-p65 in GC were assessed through analyzing publicly available databases and human paraffin embedded GC tissues. The biological crosstalk of INHBB between GC cells and fibroblasts was explored both in vitro and in vivo. RNA-seq analyses were performed to determine the mechanisms which regulating fibroblasts reprogramming. Luciferase reporter assay and chromatin immunoprecipitation (CHIP) assay were used to verify the binding relationship of p65 and INHBB in GC cells. Results Our study showed that INHBB level was significantly higher in GC, and that increased INHBB was associated with poor survival. INHBB positively regulates the proliferation, migration, and invasion of GC cells in vitro. Also, activin B promotes the occurrence of GC by reprogramming fibroblasts into cancer-associated fibroblasts (CAFs). The high expression of INHBB in GC cells activates the NF-κB pathway of normal gastric fibroblasts by secreting activin B, and promotes fibroblasts proliferation, migration, and invasion. In addition, activin B activates NF-κB pathway by controlling TRAF6 autoubiquitination to induce TAK1 phosphorylation in fibroblasts. Fibroblasts activated by activin B can induce the activation of p65 phosphorylation of GC cells by releasing pro-inflammatory factors IL-1β. p65 can directly bind to the INHBB promoter and increase the INHBB transcription of GC cells, thus establishing a positive regulatory feedback loop to promote the progression of GC. Conclusions GC cells p65/INHBB/activin B and fibroblasts p65/IL-1β signal loop led to the formation of a whole tumor-promoting inflammatory microenvironment, which might be a promising therapeutic target for GC.

Abstract Background The psychological impact of the COVID-19 pandemic has been understudied among vulnerable populations. This study aimed to examine the immediate and longer-term changes in the mental health of children with parent–child separation experiences during the COVID-19 pandemic, and identify potential buffering opportunities for mental health. Methods This longitudinal cohort study used data from 723 rural Chinese children who provided data before (Oct. 2019) the COVID-19 pandemic and during the following 2 years. Changes in the probability of depressive symptoms, anxiety symptoms, non-suicide self-injurious (NSSI), suicidal ideation, suicide plan, and suicide attempt were tested across four waves using generalized estimating models (GEE). Results Compared with children who never experienced parent–child separation, children persistently separated from parents since birth experienced greater deterioration in all mental health in the 2-year follow-up (average change: depressive symptoms: β = 0.59, 95% CI [0.26, 0.93]; anxiety symptoms: β = 0.45, 95% CI [0.10, 0.81]; NSSI: β = 0.66, 95% CI [0.31, 1.01]; suicide ideation: β = 0.67, 95% CI [0.38, 0.96]; suicide plan: β = 0.77, 95% CI [0.38, 1.15]; suicide attempt: β = 1.12, 95% CI [0.63, 1.62]). However, children with childhood separation from their parents but reunited with them during the transition to adolescence showed similar even lower changes to counterparts who never experienced parent–child separation (all ps > 0.05). Conclusion These results indicating improvements in supportiveness of the caregiving environment during the transition to adolescence may provide the opportunity to buffer the adverse impact of COVID-19 on mental health. Translating such knowledge to inform intervention and prevention strategies for youths exposed to adversity is a critical goal for the field.

Purposes Speech emotion recognition allows computers to understand the emotional information contained in human speech, and is an important part of intelligent human-computer interaction. Feature extraction and fusion are key parts in speech emotion recognition systems, and have an important impact on recognition results. Aiming at the problem of insufficient emotional information contained in traditional acoustic features, a deep feature extraction method based on multi-task learning for optimization of acoustic features is proposed in this paper. Methods The proposed acoustic depth feature can better characterize itself and has more emotional information. Then, on the basis of the complementarity between acoustic features and spectrogram features, spectrogram features through convolutional neural network are extracted. Then, the multi-kernel principal component analysis method is used to perform feature fusion and dimension reduction on these two features, and the obtained fusion features can effectively improve the system recognition performance. Findings Experiments are carried out on the EMODB and the CASIA speech databases. When the DNN classifier is used, the multi-kernel fusion feature of the acoustic depth feature and the spectrogram feature achieve the highest recognition rates of 92.71% and 88.25%, respectively. Compared with direct feature splicing, this method increased the recognition rate by 2.43% and 2.83%, respectively.

In this study, the differences in the aroma substances, major flavor substances and sensory quality of different grades of charcoal-baked and electrically baked white tea were studied by gas chromatography-mass spectrometry (GC-MS) and high performance liquid chromatography (HPLC) combined with chemometrics methods. The results showed that a total of 262 volatile compounds were detected, with terpenes, heterocyclic compounds, alcohols, esters and ketones being the major components, and 2-phenyl ethanol, linalool, geraniol, methyl salicylate, laurene, and (E)-linalool oxide accounting for a higher proportion of the total amount of volatile compounds. Compared with electrically baked white tea, 77, 16 and 93 differential volatile substances were identified from charcoal-baked Yinzhen, Baimudan and Shoumei tea, respectively. Odor activity value (OAV) analysis showed that linallinol, geraniol, 2-phenyl ethanol and laurene were important aroma substances of charcoal-baked white tea, which contribute to natural refreshing, floral and fruity or sweet aromas. Analysis of non-volatile compounds showed that there were significant differences in the content of total and individual catechins, tea polyphenols, caffeine and water extract between charcoal-baked and electrically baked white tea. The results of sensory evaluation were consistent with those of volatile and non-volatile substances. This study is helpful to understand the aroma and flavor quality of charcoal-baked white tea and provides theoretical support for improving the quality of white tea.

Abstract Influenza H7N9 virus causes human infections with about 40% case fatality rate. The severe cases usually present with pneumonia; however, some present with central nervous system complications. Pneumonia syndrome is attributed to the cytokine storm after infection with H7N9, but the pathogenic mechanism of central nervous system complications has not been clarified. This study used immortalized human brain microvascular endothelial cells hCMEC/D3 to simulate the blood-brain barrier. It demonstrated that H7N9 virus could infect brain microvascular endothelial cells and compromise the blood-brain barrier integrity and permeability by down-regulating the expression of cell junction-related proteins, including claudin-5, occludin, and vascular endothelial (VE)-cadherin. These results suggested that H7N9 could infect the blood-brain barrier in vitro and affect its functions, which could be a potential mechanism for the pathogenesis of H7N9 viral encephalopathy.

Abstract Background Neutralizing antibody plays a key role in protecting hosts from invasive pathogens and their virulent components. Current high-throughput assays for antibody screening are based on binding activities. However, those antibodies with high affinity may not have neutralizing activities. Subsequent functionality assays are necessary to identify neutralizing antibodies from binders with high affinity to their target antigens, which is laborious and time-consuming. Therefore, a versatile platform that can rapidly identify antibodies with both high binding affinity and neutralizing activity is desired to curb future pandemics like COVID-19. Results In this proof-of-concept study, we adapted Saccharomyces cerevisiae to either display human antibodies on the yeast surface or secrete soluble antibodies into the cultivation supernatant under a controllable ‘switch’ through different carbon source induced promoters. Initially, an engineered chimeric-bispecific Fab antibody, derived from humanized nanobodies against both Clostridioides difficile toxin A and B (TcdA and TcdB), was successfully expressed either on the yeast cell surface or in the culture medium with intact bioactivity, suggesting the applicability of our system in antibody display and secretion. Next, a combinatorial Fab library was constructed from B cells isolated from a convalescent patient with a high serological neutralizing titer against TcdB. Following three rounds of magnetic bead enrichment and one round of flow cytometry sorting, antibodies against TcdB were enriched efficiently. We then sorted out single binders with high binding affinity and induced them to express soluble antibodies in culture medium. The neutralizing activity of culture supernatant was analyzed using cell-based assay immediately. This way, we rapidly identified two unique neutralizers (out of seven binders) that can neutralize the cytotoxicity of TcdB. Conclusion The antibody screening platform described here simplifies the neutralizing antibody discovery procedure and will be an attractive alternative for screening functional antibodies against infectious diseases.

Objective: Objective: To explore and analyze the clinical features and chest thin-slice non-enhanced computed tomography (CT) imaging features of patients with coronavirus disease 2019 (COVID-19) at initial diagnosis in a fever clinic. Methods: A retrospective analysis was performed on 140 patients with COVID-19 at initial diagnosis in a fever clinic, including 101 and 39 cases in the moderate and severe and critical groups , respective-ly. Baseline, clinical characteristics, complete blood count + C-reactive protein (CBC+CRP), and chest thin-slice non-enhanced CT imaging characteristics of the patients were analyzed. Results: (1) The comparison between the moderate and severe and criti-cal groups showed that there were statistically significant differences in age (66.05±14.38 vs. 77.90±13.12,), course of initial diagnosis (5.40±3.81 vs. 3.97±3.12), SPO2 (97.88±1.73 vs. 92.92±4.01), and Tmax (38.32±0.66 vs. 38.68±0.63).(2) CT features between the two groups showed statistically significant differences in semi-quantitative volume (18.85±13.51 vs. 34.41±19.34). (3) The comparison between the moderate and severe and critical groups showed that there were statistically significant differ-ences in CRP (29.42±26.93 vs. 80.67±48.01), LYM (1.64±0.68 vs. 0.95±0.64), and NLR (3.48±2.46 vs. 9.36±10.42). (4) Six indicators, namely age, the course of initial diagnosis, SPO2, semi-quantitative volume, CRP, and LYM, were screened for multivariate logistic regression analysis. The result show that age (OR=1.090, 95%CI 1.006 ~ 1.181), semi-quantitative (OR=1.086, 95%CI 1.086 ~ 1.019), and SPO2 (OR=0.261, 95%CI 0.089 ~ 0.762), are related to the occurrence of severe and critical COVID-19 infection, and the difference is statistically significant; CRP (OR=1.054, 95%CI 1.023 ~ 1.087) and LYM (OR=0.039, 95%CI 0.04 ~ 0.391) are related to the occurrence of severe and critical COVID-19 infection, and the difference is significant statistically significant. Conclusion: Age, lower SPO2 and LYM, a shorter course; a higher Tmax, semi-quantitative volume, CRP, and NLR are associ-ated with severe and critical cases and required early identification.

Objective: To investigate the clinical value of thin-section chest computed tomography (CT) in the typing of coronavirus disease 2019 (COVID-19). Methods: A retrospective analysis was performed on 134 patients diagnosed with COVID-19 in our hospital’s Department of Infectious Diseases from December 20, 2022, to December 31, 2022. All patients underwent thin-section chest CT scan with complete clinical data. According to clinical classification, patients were divided into the non-severe and severe groups. Clinical data and imaging features of the two groups were compared and analyzed, and statistical analysis was conducted. Results: There was a statistically significant difference with respect to diabetes mellitus between the two groups, and the incidence of diabetes mellitus in the severe group (45.8%) was higher than that in the non-severe group (25.5%); There were no significant differences in sex, age, average course of disease, and clinical symptoms between the two groups; There were significant differences in the number of lesions, symmetrical distribution, predominant peripheral distribution, diffuse distribution, blurred edge, morphology of large flake and band, vascular bundle thickening, paving stone sign, arcade sign, and fried egg sign between the two groups, the number of lesions >10, diffuse distribution, morphology of large flake and band, vascular bundle thickening, paving stone sign, and arcade sign were more common in the severe group than in the non-severe group, while predominant peripheral distribution, blurred edge, and fried egg sign were more common in the non-severe group than in the severe group. Conclusions: Thin-section chest CT scan can identify the abnormal imaging manifestations of the lung in patients with COVID-19 and evaluate the number, distribution range, and morphological characteristics of the lesions. Combined background diseases, number, distribution characteristics, blurred edge, large flake and band morphology, vascular bundle thickening, paving stone sign, arcade sign, and fried egg sign can effectively indicate the classification of patients with COVID-19. This can provide imaging evidence for the diagnosis and treatment of COVID-19.

In this paper, Fe−8.5Mn−1.5Al light−weight medium Mn steel is used as the research object, and the hot compression test is conducted by Gleeble−3500 thermal simulation tester. The dynamic reversion and dynamic recrystallization (DRX) processes are analyzed according to the true stress−strain curve; the θ−σ work−hardening rate curve is plotted by P−J double differential method to analyze the influence law between work−hardening and dynamic reversion and recrystallization softening effect of the material; the DRX critical strain model is established to analyze the influence law of deformation parameters on DRX; Based on the dynamic material model theory, the hot working diagram and three−dimensional power dissipation diagram are constructed, and the best hot working area is determined by combining the microstructure of the material. Finally, based on the above research content, a systematic overview of the dynamic softening effects of DRX and dynamic recovery (DRV) will be provided.

Abstract HMGB1, a nucleoprotein, is expressed in almost all eukaryotic cells. During cell activation and cell death, HMGB1 can function as an alarm protein (alarmin) or damage-associated molecular pattern (DAMP) and mediate early inflammatory and immune response when it is translocated to the extracellular space. The binding of extracellular HMGB1 to Toll-like receptors (TLRs), such as TLR2 and TLR4 transforms HMGB1 into a pro-inflammatory cytokine, contributing to the occurrence and development of autoimmune diseases. TLRs, which are members of a family of pattern recognition receptors, can bind to endogenous DAMPs and activate the innate immune response. Additionally, TLRs are key signaling molecules mediating the immune response and play a critical role in the host defense against pathogens and the maintenance of immune balance. HMGB1 and TLRs are reported to be upregulated in several autoimmune diseases, such as rheumatoid arthritis, systemic lupus erythematosus, type 1 diabetes mellitus, and autoimmune thyroid disease. The expression levels of HMGB1 and some TLRs are upregulated in tissues of patients with autoimmune diseases and animal models of autoimmune diseases. The suppression of HMGB1 and TLRs inhibits the progression of inflammation in animal models. Thus, HMGB1 and TLRs are indispensable biomarkers and important therapeutic targets for autoimmune diseases. This review provides comprehensive strategies for treating or preventing autoimmune diseases discovered in recent years.

Abstract In island mode, voltage source inverter (VSI) supports the frequency and voltage of microgrid. After the complex load is connected, the VSI control performance is degraded, and the output voltage has deviation, negative sequence, waveform distortion and other problems, which further deteriorate the power quality of the microgrid. Different from the traditional strategy that only focus on a single problem, the strategy proposed in this paper can deal with these three power quality problems simultaneously. In this paper, a self‐learning sliding mode control strategy is proposed. First, a nonlinear smooth function is used to design an expansion observer, which can estimate the expansion state of the internal uncertainties and external disturbances of the control system. Second, the extended observer is combined with the self‐learning synovial control technology to realize the self‐learning synovial disturbance rejection control of VSI control strategy. This strategy can improve the stability of voltage control under various working conditions without precise mathematical model. The simulation results show that, compared with the traditional control strategy, this strategy has good robustness under different working conditions.

With the development of society, the idea of healthy diet and the green sustainable development are widely recognized. Compared with traditional meat product, with advantages of rich nutrition and environment-friendly factors of production, plant-based protein meat substitutes has become the research focus. In this report, both domestic and overseas research status and development process of plant-based protein meat substitutes in recent years are briefly analyzed, it also systematically introduced the raw materials needed, extrusion technology and quality evaluation methods. In the end of this report, the existing main problems are summarized, and corresponding expectations are putted forward based on the actual research process. In the future, the appearance, flavour, texture and other sensory attributes should be deeply studied, while taking the nutrition and food safety into account. As the development trend in the future, in addition to water content adjustment, extrusion temperature and other process parameters, high moisture extrusion technology should also focus on the improvement of cooling die.

This article investigated whether crossmodal correspondence, as a sensory translation phenomenon, can mediate crossmodal transfer from visual to auditory stimuli in category learning and whether multimodal category learning can influence the crossmodal correspondence between auditory and visual stimuli. Experiment 1 showed that the category knowledge acquired from elevation stimuli affected the categorization of pitch stimuli when there were robust crossmodal correspondence effects between elevation and size, indicating that crossmodal transfer occurred between elevation and pitch stimuli. Experiments 2 and 3 revealed that the size category knowledge could not be transferred to the categorization of pitches, but interestingly, size and pitch category learning determined the direction of the pitch-size correspondence, suggesting that the pitch-size correspondence was not stable and could be determined using multimodal category learning. Experiment 4 provided further evidence that there was no crossmodal transfer between size and pitch, due to the absence of a robust pitch-size correspondence. These results demonstrated that crossmodal transfer can occur between audio-visual stimuli with crossmodal correspondence, and multisensory category learning can change the corresponding relationship between audio-visual stimuli. These findings suggest that crossmodal transfer and crossmodal correspondence share similar abstract representations, which can be mediated by semantic content such as category labels.

Ionizing radiation exposure can cause damage to diverse tissues and organs, with the hematopoietic system being the most sensitive. However, limited information is available regarding the radiosensitivity of various hematopoietic cell populations in the bone marrow due to the high heterogeneity of the hematopoietic system. In this study, we observed that granulocyte–macrophage progenitors, hematopoietic stem/progenitor cells, and B cells within the bone marrow showed the highest sensitivity, exhibiting a rapid decrease in cell numbers following irradiation. Nonetheless, neutrophils, natural killer (NK) cells, T cells, and dendritic cells demonstrated a certain degree of radioresistance, with neutrophils exhibiting the most pronounced resistance. By employing single-cell transcriptome sequencing, we investigated the early responsive genes in various cell types following irradiation, revealing that distinct gene expression profiles emerged between radiosensitive and radioresistant cells. In B cells, radiation exposure led to a specific upregulation of genes associated with mitochondrial respiratory chain complexes, suggesting a connection between these complexes and cell radiosensitivity. In neutrophils, radiation exposure resulted in fewer gene alterations, indicating their potential for distinct mechanisms in radiation resistance. Collectively, this study provides insights into the molecular mechanism for the heterogeneity of radiosensitivity among the various bone marrow hematopoietic cell populations.

Phenolic environmental endocrine-disrupting chemicals (PEDCs) are persistent EDCs that are widely found in food packaging materials and environmental media and seriously threaten human health and ecological security. Human estrogen-related receptor γ (hERRγ) has been proposed as a mediator for the low-dose effects of many environmental PEDCs; however, the atomic-level descriptions of dynamical structural features and interactions of hERRγ and PEDCs are still unclarified. Herein, how three PEDCs, 4-(1-methylpropyl)phenol (4-sec-butylphenol), 5,6,7,8-tetrahydro-2-naphthol (tetrahydro-2-napthol), and 2,2-bis(4-hydroxy-3,5-dimethoxyphenyl)propane (BP(2,2)(Me)), interact with hERRγ to produce its estrogenic disruption effects was studied. Molecular docking and multiple molecular dynamics (MD) simulations were first conducted to distinguish the detailed interaction pattern of hERRγ with PEDCs. These binding structures revealed that residues around Leu271, Leu309, Leu345, and Phe435 are important when binding with PEDCs. Furthermore, the binding energies of PEDCs with hERRγ were also characterized using the molecular mechanics/Poisson Boltzmann surface area (MM-PBSA) and solvated interaction energy (SIE) methods, and the results showed that the interactions of CH-π, π-π, and hydrogen bonds are the major contributors for hERRγ binding to these three PEDCs. What is striking is that the methoxide groups of BP(2,2)(Me), as hydrophobic groups, can help to reduce the binding energy of PEDCs binding with hERRγ. These results provide important guidance for further understanding the influence of PEDCs on human health problems.

In the context of increasing energy demands and the integration of renewable energy sources, this review focuses on recent advancements in energy storage control strategies from 2016 to the present, evaluating both experimental and simulation studies at component, system, building, and district scales. Out of 426 papers screened, 147 were assessed for eligibility, with 56 included in the final review. As a first outcome, this work proposes a novel classification and taxonomy update for advanced storage control systems, aiming to bridge the gap between theoretical research and practical implementation. Furthermore, the study emphasizes experimental case studies, moving beyond numerical analyses to provide practical insights. It investigates how the literature on energy storage is enhancing building flexibility and resilience, highlighting the application of advanced algorithms and artificial intelligence methods and their impact on energy and financial savings. By exploring the correlation between control algorithms and the resulting benefits, this review provides a comprehensive analysis of the current state and future perspectives of energy storage control in smart grids and buildings.

Based on the characteristics of space particle radiation in the Sun-synchronous orbit (SSO), a space particle radiation effect comprehensive measuring instrument (SPRECMI) was installed on the orbital platform of the upper stage of the Chinese CZ-4C carrier rocket, which can acquire the high-energy proton energy spectra, linear energy transfer (LET) spectra of particles, and radiation dose rate. The particle radiation detection data were obtained at 1000 km altitude for the first time, which can be used mainly for scientific research of the space environment, in-orbit fault analysis, and the operational control management of spacecraft, and can also serve as reference data for component validation tests. After SPRECMI’s development, accelerator calibration and simulations were conducted, and the results demonstrated that all the measured indicators, including the high-energy proton spectra (energy range: 21.8–275.0 MeV, precision: 6 rad, sensitivity: 6.2 µrad/h), and the LET spectra (range: 0.001–37.20 MeV/(mg/cm2), >37.2 MeV/(mg/cm2)), met the relevant requirements. Furthermore, the in-orbit flight test revealed that the detection results of the load components were consistent with the physical characteristics of the particle radiation environment of the spacecraft’s orbit.

A novel three-dimensional isolation system consisting of thick rubber bearing (TNRB), disc spring bearing (DSB), and laminated rubber bearing (LRB) in series combination was designed, and its composition, principle, and isolation effect were comprehensively analyzed. By combining numerical examples, the whole structure method is used to compare and analyze the dynamic characteristics, dynamic response, and structural damage of large-span isolation structures containing new three-dimensional systems, large-span horizontal isolation structures based on LRB, and corresponding non-isolation structures under multi-dimensional seismic excitation. The results show that compared with the horizontal isolation structure based on LRB, the structure of the new three-dimensional isolation system has a 33% longer vertical natural vibration period, a 17.85% attenuation in the overall damage index, and a 36.86% increase in vertical energy dissipation capacity. It can achieve good isolation effects in both horizontal and vertical directions, which can form a favorable complement to the horizontal isolation structure based on LRB in terms of vertical isolation and energy dissipation.