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Abstract Background The aim of this study is to identify factors associated with the development of long-term severe tricuspid regurgitation (TR) following mitral valve replacement (MVR). Methods A retrospective analysis was conducted involving 308 patients who underwent single-valve MVR at Xuzhou Central Hospital between April 2017 and December 2022. Preoperative color Doppler ultrasound indicated that all patients had either no or mild to moderate tricuspid regurgitation. Postoperative follow-up was carried out over several years, and patients were categorized into two groups based on the severity of TR: 258 patients with non-severe TR (observation group) and 50 patients with severe TR (control group). Clinical data, medical history, the performance of tricuspid valvuloplasty during surgery, and echocardiographic parameters before and after the procedure were recorded. Comparative analysis between the two groups was performed, and logistic regression analysis was used to identify factors associated with the long-term development of severe TR post-MVR. Results Logistic regression analysis indicated that serum creatinine levels (OR = 1.023, P = 0.026), atrial fibrillation (OR = 2.780, P = 0.040), and a history of permanent pacemaker implantation (OR = 3.029, P = 0.039) were significantly associated with the development of severe TR over time. In contrast, concurrent intraoperative tricuspid valvuloplasty was associated with a reduced risk of TR (OR = 0.315, P = 0.002). Conclusions Elevated serum creatinine, atrial fibrillation, and a history of permanent pacemaker implantation were positively associated with the long-term occurrence of severe TR following MVR. In contrast, concurrent intraoperative tricuspid valvuloplasty was found to reduce the likelihood of severe TR development.

Abstract The access of distributed units leads to the rapid increase of power network information services, which brings great problems to the centralized dispatch of power system. To improve the efficiency of data processing and the flexibility of each unit dispatching, first, the areas are divided according to the load characteristics. An operating framework of distributed power system is presented based on offload strategy of mobile edge computing (MEC) and optimal allocation of computational quantity. Second, a novel hierarchical dispatching model is established based on the optimal configuration of MEC. In each area, the upper model takes the total energy consumption of the MEC server and the operating cost of the power system as the objective to calculate the output of each distributed unit and the computational quantity under the optimal offload strategy. The lower model ensures the complete accommodation of renewable energy and the optimal economic operation of the whole area through the introduction of electric vehicles (EVs) and secondary operation of energy storage systems under the constraint of MEC server computing delay. Third, the screening rules of the MEC system computing mode and the simulation strategies of EVs in different areas are proposed. Finally, the effectiveness and superiority of the model are verified by simulation experiments.

Eriocheir sinensis, commonly known as the Chinese mitten crab, is widely distributed in China from the Liaohe River in the north to the Pearl River in the south and in the shallow waters of the estuary into the sea, among which the population in the Yangtze River system has the largest yield and the most delicious taste, and is favored by domestic consumers. It is an important breeding species in the Chinese fishing industry. Since artificial breeding began in the 1980s, the production of Chinese mitten crabs has increased, and this species has become one of the most economically important crabs in the world and the most economically important freshwater crab in China. From the perspective of aquaculture areas, the Yangtze River Basin region accounts for over 80% of the total output in China, with Jiangsu and Anhui provinces ranking first and third, respectively. Therefore, the culture of Chinese mitten crabs in Jiangsu and Anhui plays a pivotal role in the country. After more than 30 years of development, China has established ecological and large-scale breeding systems for juvenile crabs. Therefore, artificial seedlings dominate the market but are mainly distributed in coastal areas such as Jiangsu. However, to reduce production costs, some breeding farms blindly introduce Chinese mitten crabs to one another, and do not perform germplasm detection during breeding, causing germplasm resources to be random and mixed, which directly affects the quality of juvenile crabs and results in the risk of germplasm decline. To evaluate the genetic background of cultured Chinese mitten crab populations in Jiangsu and Anhui in odd-number years, and to provide a scientific basis for subsequent genetic improvement and breeding of new varieties, 10 pairs of highly polymorphic microsatellite markers (simple sequence repeats) were used to analyze the genetic diversity and genetic structure of six cultured populations with 177 individuals in total. Each population contained 28–30 adult individuals with an approximate sex ratio. The leg muscle of the sampled crabs was extracted, and genomic DNA was extracted according to the instructions of the genome extraction kit (TianGen DP304). The microsatellite primers were modified using fluorescent labels (FAM and HEX) prior to PCR, and the PCR products were subjected to capillary electrophoresis. Genemarker 2.2 software was used to interpret typing results. The number of alleles (Na), effective number of alleles (Ne), expected heterozygosity (He), observed heterozygosity (Ho), inbreeding coefficient (Fis), and genetic distance (Dn) were calculated using Popgene 1.32 software, and Hardy-Weinberg equilibrium analysis was performed using the Markov chain method. PIC_CALC 0.6 software calculates polymorphism information content (PIC). Analysis of molecular variance (AMOVA) and the coefficient of genetic differentiation (Fst) were performed using Arlequin 3.5 software. A UPGMA tree was constructed based on inter-population genetic distance using MEGA 4.0 software. According to the frequency of alleles, mutation-drift equilibrium was detected using Bottleneck software. Genetic structure analysis was performed using the Structure 2.3.4 software. The results showed that the genetic diversity levels of the six cultured populations of E. sinensis were high and similar (Na=16.0–18.4, Ne=10.1–12.4, Ho=0.759–0.836, He=0.897–0.916, PIC=0.870–0.892). Genetic distance among populations (0.015–0.277) and the coefficient of genetic differentiation (Fst: 0.001–0.011) were low, and genetic variation among populations accounted for only 0.47% of the total variation in AMOVA. These analyses consistently indicated no significant genetic differentiation among the populations. The phylogenetic tree showed that the six cultured populations had a common ancestor and that the Gaochun population had further relationships with the other populations. Owing to its high genetic diversity, the Gaochun population can be used as a base population for mass selection. Genetic structure analysis showed that the genetic composition of each cultured population was diverse, and the proportions were similar. In this study, the inbreeding coefficient (Fis) of 10 loci in six populations had 43 positive values and 17 negative values, and there were both positive and negative values in each population, indicating that there was not only inbreeding to a certain extent but also a small amount of distant breeding in the six cultured populations of Chinese mitten crabs.The results of genetic structure analysis showed that the number of optimal genetic cluster groups was K=3. However, the chaotic genetic structures among the three groups failed to gather into a relatively independent group. Furthermore, each population had a genetic composition similar to those of the three genetic lineage sources. Considering the high level of genetic diversity in these populations, it is possible that the parental population sources are more complex. This indicated that the cultured population of Chinese mitten crabs had a large number of exogenous genetic hybrids.In conclusion, the genetic diversity of cultured Chinese mitten crab populations in the Jiangsu and Anhui areas is still high, which has potential development and utilization value, but there may be germplasm confounding. Therefore, it is necessary to conduct further studies on the breeding population during the subsequent breeding of improved varieties, such as using molecular markers with high sensitivity that can be used to identify different water systems to analyze the sources of mixed germplasm, and conducting germplasm detection before breeding to purify the germplasm and make reasonable and sustainable use of its germplasm resources.

In Vacuum Induction Melting (VIM), reduction of defects such as porosity and cracking is critical to improve electrode integrity. Traditional simulation method ignores the temperature drop of liquid metal as it passes through the tundish, leading to inaccuracies in predicting the solidification process in the mold. Additionally, the crack of ingot may occur during demolding process, which is always overlooked. This paper presents an integrated simulation method that includes the flow model of liquid metal in the tundish, as well as the solidification model and the stress model of ingot in the mold. Based on these models, the criterion for demolding time is established based on First and Fourth Strength Theories. The entire VIM process from pouring to demolding can be analyzed comprehensively through this simulation method. The method is validated by 500 kg Inconel 718 VIM trial including the temperature measurement of outer mold wall, the height measurement of liquid metal in the tundish and longitudinal sectioned experiment of ingot. The suitable criteria for porosity of 500 kg Inconel 718 ingot, including shrinkage porosity and shrinkage cavity, have been found to be the Niyama criterion threshold of 15 K0.5s0.5cm−1 and Classical porosity model. Finally, the impact of each process parameter on porosity and demolding time is studied through this method for 500 kg Inconel 718 ingot. This method is not only applied to 500 kg ingot but also to larger ingot, thereby providing a basis for the VIM process optimization.

Abstract Background Regulatory T cells (Tregs) play a critical role in shaping the immunosuppressive microenvironment within tumors. Investigating the role of Tregs in Clear cell renal cell carcinoma (ccRCC) is crucial for identifying prognostic markers and therapeutic targets for ccRCC. Methods Weighted gene co-expression network analysis (WGCNA) was utilized to pinpoint modules related to Treg infiltration in TCGA-KIRC samples. Following this, consensus clustering was employed to derive two clusters associated with Treg infiltration in ccRCC. A prognostic model was then developed using the gene module associated with Treg infiltration. We then evaluated the ability of the prognostic model to predict ccRCC overall survival and demonstrated that RCN1 can be used as a target to predict ccRCC prognosis. Results We deduce that the two clusters associated with Treg infiltration exhibit distinct compositions of the immune microenvironment, pathway activations, prognosis, and drug sensitivities commonly utilized in ccRCC treatment. Furthermore, a 7-gene model risk score, developed based on ccRCC Treg infiltration, proved to be a reliable prognostic marker in both training and validation cohorts. Additionally, survival analysis indicated that RCN1 serves as a reliable prognostic factor for ccRCC. Single-cell sequencing analysis revealed that RCN1 is predominantly expressed in tumor cells. A pan-cancer analysis highlighted that RCN1 is linked with poor prognosis and the activation of inflammatory response pathways across various cancers. Conclusion We developed a prognostic model associated with Treg infiltration, which facilitates the clinical categorization of ccRCC progression. Moreover, our findings underscore the significant potential of RCN1 as a ccRCC biomarker.

A carbide strengthened wrought Ni-based superalloy is developed. The alloy depends on carbide dispersion strengthening. A high deformation plasticity in homogeneous alloy is shown in the 1100–1200 °C isothermal compression test and the improvement of microstructure can be achieved by recrystallization. After aging at 850–900 °C, the carbide strengthened wrought alloy appears excellent tensile strength. Carbide exists higher microstructure stability than γ′ in the same condition. The herein reported results reflect the potential of the economical wrought Ni-based superalloy to service above 800 °C.

Di(2-ethylhexyl) phthalate (DEHP) is recognised as a pollutant with multiple health risks. In this study, multi-omics approaches were used to examine the alterations in immunity, gut microbiota and metabolome, and liver transcriptome in the rats with DEHP-induced subacute liver injury. Following short-term subacute DEHP exposure, the rats exhibited decreased body weight, increased liver weight, impaired liver function and immunity, and signs of liver injury. DEHP exposure reduced the richness, diversity, and evenness of gut microbiota, resulting in elevated levels of Lactobacillus, Romboutsia, and Alistipes and decreased levels of unclassified Muribaculaceae, Oscillibacter, and Akkermansia in the intestine. Multiple gut metabolic pathways were altered by DEHP, among which sphingolipid metabolism was enriched with the most differentially expressed metabolites. In the liver tissues of rats exposed to DEHP, lipid metabolism-related pathways were altered, including downregulated steroid biosynthesis and upregulated fatty acid degradation. In conclusion, the relevant findings suggest that DEHP can cause immune alteration, gut microbiota dysbiosis, gut metabolome disruption, liver transcriptome dysregulation, and result in liver injury in rats. These results could benefit the clinical diagnosis of DEHP-induced subacute liver injury.

Two-dimensional (2D) MoTe2 shows great potential for future semiconductor devices, but the lab-to-fab transition is still in its preliminary stage due to the constraints in the crystal growth level. Currently, the chemical vapor deposition growth of 2D MoTe2 primarily relies on the tellurization process of Mo-source precursor (MSP). However, the target product 2H-MoTe2 from Mo precursor suffers from long growth time and suboptimal crystal quality, and MoOx precursor confronts the dilemma of unclear growth mechanism and inconsistent growth products. Here, we developed magnetron-sputtered MoO3 film for fast and high-mobility 2H-MoTe2 growth. The solid-to-solid phase transition growth mechanism of 2D MoTe2 from Mo and MoOx precursor was first experimentally unified, and the effect mechanism of MSPs on 2D MoTe2 growth was systematically elucidated. Compared with Mo and MoO2, the MoO3 precursor has the least Mo-unit lattice deformation and exhibits the optimal crystal quality of growth products. Meanwhile, the lowest Gibbs free energy change of the chemical reaction results in an impressive 2H-MoTe2 growth rate of 8.07 μm/min. The constructed 2H-MoTe2 field-effect transistor array from MoO3 precursor showcases record-high hole mobility of 85 cm2·V-1·s-1, competitive on-off ratio of 3×104, and outstanding uniformity. This scalable method not only offers efficiency but also aligns with industry standards, making it a promising guideline for diverse 2D material preparation towards real-world applications.

IntroductionOccupational stress is a significant issue among junior high school teachers in China, contributing to negative outcomes such as reduced mental health, impaired coping abilities, and decreased job satisfaction.MethodsThis quasi-experimental study investigates the impact of mindfulness-based interventions on occupational stress and mental health among junior high school teachers in China. A total of 118 teachers participated in the study, with a randomly assigned experimental group undergoing an 4-week mindfulness training program, while the control group received no intervention. Standardized measures of occupational stress, mental health, coping self-efficacy, and mindfulness were used to assess the outcomes before and after the intervention.FindingsThe findings revealed that teachers who participated in the mindfulness program experienced significant reductions in occupational stress and improvements in mental health and coping self-efficacy compared to the control group. Additionally mindfulness levels increased significantly among participants who underwent the training.DiscussionThe results suggest that mindfulness-based interventions can effectively alleviate occupational stress and enhance psychological wellbeing among junior high school teachers in China, highlighting the importance of implementing such programs to support educators in managing stress and maintaining mental health.

Volatile components are one of the main active components of Ligusticum chuanxiong Hort and are important indicators for evaluating the medicinal quality of Ligusticum chuanxiong. To explore the effects of 60Co-γ irradiation on the volatile components of Ligusticum chuanxiong, the samples were treated with different irradiation doses, and the changes of the volatile components before and after irradiation were analyzed using an electronic nose combined with headspace solid-phase microextraction and gas chromatography-mass spectrometry. Principal component analysis (PCA), linear discriminant analysis (LDA), orthogonal partial least squares discriminant analysis (OPLS-DA), and cluster statistical analysis were used to elucidate changes in the volatile components of Ligusticum chuanxiong before and after irradiation. The electronic nose detection results and gas chromatography–mass spectrometry detection results indicated that ketone alkanes, alcohols, aldehydes, and ketones contributed to the odor of Ligusticum chuanxiong. Irradiation treatments at doses ≤10 kGy had no significant effect on the odor of Ligusticum chuanxiong. The results demonstrated that after irradiation at 0 kGy (control group), 3 kGy, 7 kGy, and 10 kGy, 60 compounds were identified in Ligusticum chuanxiong, including 23 hydrocarbons, 12 alcohols, 10 lipids, and 4 aldehydes or ketones, and 11 others. There were mainly 21 volatile substances that changed after irradiation, accounting for approximately 12.92% of the volatile components in Ligusticum chuanxiong; however, they were not the main volatile components of Ligusticum chuanxiong. No new compounds were identified in Ligusticum chuanxiong after irradiation treatment within a dose of 10 kGy. The results provide a theoretical basis and reference for the influence of 60Co-γ irradiation on the quality of Ligusticum chuanxiong samples and also lay a certain foundation for the application of irradiation in Ligusticum chuanxiong pieces and traditional Chinese medicine and simple preparation resources. The results indicate that the treatment of 60Co-γ irradiation on the Ligusticum chuanxiong samples with doses ˂10 kGy does not affect its main volatile components.

Abstract Hepatocellular carcinoma (HCC) is a widely prevalent type of primary liver cancer. However, strategies for pretumor intervention are still limited. In this study, a liver‐specific Zbtb7b knockout mouse model was used to evaluate the role of Zbtb7b in metabolic dysfunction‐associated steatotic liver disease (MASLD)‐related HCC development. We revealed that Zbtb7b was compensatively increased and restricted lipid deposition in the liver during MASLD progression, which protects against MASLD‐related HCC initiation. Mechanistically, Zbtb7b suppresses the expression of the long noncoding RNA H19 to attenuate hepatic de novo lipogenesis and increase fatty acid oxidation, thereby preventing lipid accumulation in hepatocytes. As a result, the proliferation and migration abilities of HCC cells are reduced. Overall, we demonstrated that Zbtb7b serves as a tumor suppressor at an early stage of HCC, thus providing a promising target for the treatment of HCC at a premalignant stage.

ABSTRACTThe gut commensal bacteria Christensenellaceae species are negatively associated with many metabolic diseases, and have been seen as promising next-generation probiotics. However, the cultured Christensenellaceae strain resources were limited, and their beneficial mechanisms for improving metabolic diseases have yet to be explored. In this study, we developed a method that enabled the enrichment and cultivation of Christensenellaceae strains from fecal samples. Using this method, a collection of Christensenellaceae Gut Microbial Biobank (ChrisGMB) was established, composed of 87 strains and genomes that represent 14 species of 8 genera. Seven species were first described and the cultured Christensenellaceae resources have been significantly expanded at species and strain levels. Christensenella strains exerted different abilities in utilization of various complex polysaccharides and other carbon sources, exhibited host-adaptation capabilities such as acid tolerance and bile tolerance, produced a wide range of volatile probiotic metabolites and secondary bile acids. Cohort analyses demonstrated that Christensenellaceae and Christensenella were prevalent in various cohorts and the abundances were significantly reduced in T2D and OB cohorts. At species level, Christensenellaceae showed different changes among healthy and disease cohorts. C. faecalis, F. tenuis, L. tenuis, and Guo. tenuis significantly reduced in all the metabolic disease cohorts. The relative abundances of C. minuta, C. hongkongensis and C. massiliensis showed no significant change in NAFLD and ACVD. and C. tenuis and C. acetigenes showed no significant change in ACVD, and Q. tenuis and Geh. tenuis showed no significant change in NAFLD, when compared with the HC cohort. So far as we know, this is the largest collection of cultured resource and first exploration of Christensenellaceae prevalences and abundances at species level.

Alcohol-related liver disease (ALD) is a major cause of morbidity and mortality worldwide. It encompasses conditions such as fatty liver, alcoholic hepatitis, chronic hepatitis with liver fibrosis or cirrhosis, and hepatocellular carcinoma. Numerous recent studies have demonstrated the critical role of oxidative stress, abnormal lipid metabolism, endoplasmic reticulum stress, various forms of cell death (including apoptosis, necroptosis, and ferroptosis), intestinal microbiota dysbiosis, liver immune response, cell autophagy, and epigenetic abnormalities in the pathogenesis of ALD. Currently, abstinence, corticosteroids, and nutritional therapy are the traditional therapeutic interventions for ALD. Emerging therapies for ALD mainly include the blockade of inflammatory pathways, the promotion of liver regeneration, and the restoration of normal microbiota. Summarizing the advances in animal models of ALD will facilitate a more systematic investigation of the pathogenesis of ALD and the exploration of therapeutic targets. This review summarizes the latest insight into the pathogenesis and molecular mechanisms of ALD, as well as the pros and cons of ALD rodent models, providing a basis for further research on therapeutic strategies for ALD.

BackgroundAlcoholic hepatitis is a severe inflammatory liver disease. In recent years, the incidence of AH has been on the rise, leading to an increasingly severe disease burden. Currently, there is a lack of specific biomarkers for the diagnosis and prognosis of AH in clinical practice. Therefore, the main objective of this study is to identify biomarkers closely associated with the progression of AH, to address the shortcomings in pathological diagnosis, and to identify potential therapeutic targets.MethodsBioinformatics and machine learning methods were used to comparatively study the differentially expressed genes (DEGs) between AH patients and healthy individuals by analyzing four mRNA microarray data sets obtained from the GEO database. Subsequently, the role of potential biomarkers in AH and their mechanism of action were further confirmed by AH patients and in vitro and in vivo experiments.ResultsUsing differential analysis and WGCNA of the data set, a total of 167 key genes that may be related to AH were obtained. Among 167 genes, the LASSO logistic regression algorithm identified four potential biomarkers (KCNJ10, RPL21P23, ADRB2, and AC025279.1). Notably, ADRB2 showed biomarker potential in GSE28619, GSE94397, and E-MTAB-2664 datasets, and clinical liver samples. Furthermore, AH patients and in vivo experiments demonstrated ADRB2 inhibition and suppression of SIRT1/PPARα/PGC-1α signaling pathways, accompanied by elevated inflammatory factors and lipid deposition. In vitro experiments showed that ADRB2 overexpression mitigated the inhibition of the SIRT1/PPARα/PGC-1α signaling pathway, reversing the decrease in mitochondrial membrane potential, cell apoptosis, oxidative stress, and lipid deposition induced by alcohol exposure. Besides, the results also showed that ADRB2 expression in AH was negatively correlated with the levels of inflammatory factors (e.g., CCL2, CXCL8, and CXCL10).ConclusionThis study points to ADRB2 as a promising biomarker with potential diagnostic and prognostic value in clinical cohort data. In addition, in AH patients, in vivo and in vitro experiments confirmed the key role of ADRB2 in the progression of AH. These findings suggest that ADRB2 may alleviate AH by activating the SIRT1/PPARα/PGC-1α pathway. This finding provides a new perspective for the diagnosis and treatment of AH.

Abstract Gut microbiota dysbiosis has been implicated in rheumatoid arthritis (RA) and influences disease progression. Although molecular and culture‐independent studies revealed RA patients harbored a core microbiome and had characteristic bacterial species, the lack of cultured bacterial strains had limited investigations on their functions. This study aimed to establish an RA‐originated gut microbial biobank (RAGMB) that covers and further to correlates and validates core microbial species on clinically used and diagnostic inflammation and immune indices. We obtained 3200 bacterial isolates from fecal samples of 20 RA patients with seven improved and 11 traditional bacterial cultivation methods. These isolates were phylogenetically identified and selected for RAGMB. The RAGMB harbored 601 bacterial strains that represented 280 species (including 43 novel species) of seven bacterial phyla. The RAGMB covered 93.2% at species level of medium‐ and high‐abundant (relative abundances ≥0.2%) RA gut microbes, and included four rare species of the phylum Synergistota. The RA core gut microbiome was defined and composed of 20 bacterial species. Among these, Mediterraneibacter tenuis and Eubacterium rectale were two species that statistically and significantly correlated with clinically used diagnostic indices such as erythrocyte sedimentation rate (ESR) and IL‐10. Thus, M. tenuis and E. rectale were selected for experimental validation using DSS‐treated and not DSS‐treated mice model. Results demonstrated both M. tenuis and E. rectale exacerbated host inflammatory responses, including shortened colon length and increased spleen weight, decreased IL‐10 and increased IL‐17A levels in plasma. Overall, we established the RAGMB, defined the RA core microbiome, correlated and demonstrated core microbial species effected on host inflammatory and immune responses. This work provides diverse gut microbial resources for future studies on RA etiology and potential new targets for new biomedical practices.

Chinese calligraphy and Suzhou classical gardens exhibit unique and distinctive formal attributes and layout styles. This paper examines the interrelationships from a spatial perspective, using classical gardens such as the Humble Administrators’ Garden, the Lingering Garden, and the Master of Nets Garden, alongside Yan Zhenqing’s Three Manuscripts (颜公三稿), as illustrative examples. From the theoretical stance of “Heterogeneous Homology”, this investigation assesses the comparability between calligraphy and garden design. It highlights the shared spatial features of “Emptiness-Substance” and “Denseness-Sparseness”, analyzing their specific applications within each realm. Furthermore, the “Correspondence and Guidance” is fulfilled to effectively integrate the spatial boundary within their respective domains. The findings reveal profound similarities in spatial construction between calligraphy and garden design, highlighting the traditional Chinese aesthetic pursuits of emptiness, distance, and externality. These findings affirm the ancient Chinese pursuit of the natural philosophical concept of “the unity of nature and human”. Consequently, it is proposed that future design and urban spatial planning should emphasize the application of the spatial techniques and cultural meanings embedded in these arts. This approach aims to provide a multidimensional and detailed interdisciplinary perspective on future research concerning Asian architectural culture and art history.

Due to the strong chemical toxicity and radiological hazard, uranium poses long-term threat to both environment and living organisms. However, soluble UO22+ ions with the mobility leads to difficulties in effectively capturing uranium from complex radioactive wastewater. Herein, the efficient U(VI) adsorption is achieved by MQ2-collagen fibers (MoS2-CF; M = Mo, W; Q = S, Se) composite prepared via co-ball milling MQ2 and CF, which exhibit higher uranium adsorption performance with the saturated adsorption capacity (qe) of 301 mg g−1 than pristine MQ2 due to their better hydrophilicity and the advantage of fibrous structure for better UO22+ transfer. The adsorption mechanism is revealed to be the synergistic interaction of abundant S2− sites from MoS2 and amino and carboxyl groups from CF towards UO22+. This work proposes a universal preparation method for low-cost and eco-friendly composite materials combining transition metal dichalcogenide with CF by co-ball milling for efficient uranium adsorption.

Heart failure (HF) is an increasingly prevalent disease in humans; it induces multiple symptoms and damages health. The animal gut microbiota has critical roles in host health, which might be related to HF symptoms. Currently, several options are used to treat HF, including non-invasive ventilation (NIV). However, studies on gut microbiota responses to acute HF and associated treatments effects on gut communities in patients are scarce. Here, short-term (1 week after treatments) and long-term (3 months after treatment) variations in gut microbiota variations in rats with acute HF treated were examined NIV through high-throughput sequencing of the bacterial 16S rRNA gene. Through comparison of gut microbiota alpha diversity, it was observed lower gut microbiota richness and diversity in animals with acute HF than in normal animals. Additionally, beta-diversity analysis revealed significant alterations in the gut microbiota composition induced by acute HF, as reflected by increased Firmicutes/Bacteroidetes (F/B) ratios and Proteobacteria enrichment. When network analysis results were combined with the null model, decreased stability and elevated deterministic gut microbiota assemblies were observed in animals with acute HF. Importantly, in both short- and long-term periods, NIV was found to restore gut microbiota dysbiosis to normal states in acute HF rats. Finally, it was shown that considerable gut microbiota variations existed in rats with acute HF, that underlying microbiota mechanisms regulated these changes, and confirmed that NIV is suitable for HF treatment. In future studies, these findings should be validated with different model systems or clinical samples.

With the growing concern for the environment, sustainable development centred on a low-carbon economy has become a unifying pursuit for the energy industry. Integrated energy systems (IES) that combine multiple energy sources such as electricity, heat and gas are essential to facilitate the consumption of renewable energy and the reduction of carbon emission. In this paper, gas turbine (GT), carbon capture and storage (CCS) and power-to-gas (P2G) device are introduced to construct a new carbon capture coupling device model, GT-CCS-P2G (GCCP), which is applied to the integrated electrical and gas system (IEGS). Multi-agent soft actor critic (MASAC) applies historical trajectory representations, parameter spatial techniques and deep densification frameworks to reinforcement learning for reducing the detrimental effects of time-series data on the decisional procedure. The energy scheduling problem of IEGS is redefined as a Markov game, which is addressed by adopting a low carbon economic control framework based on MASAC with minimum operating cost and minimum carbon emission as the optimization objectives. To validate the rationality and effectiveness of the proposed low-carbon economy scheduling model of IEGS based on MASAC, this paper simulates and analyses in integrated PJM-5 node system and seven nodes natural gas system.

Smart materials, which exhibit shape memory behavior in response to external stimuli, have shown great potential for use in biomedical applications. In this study, an energetic composite was fabricated using a UV-assisted DIW 3D printing technique and a shape memory material (SMP) as the binder. This composite has the ability to reduce the impact of external factors and adjust gun propellant combustion behavior. The composition and 3D printing process were delineated, while the internal structure and shape memory performance of the composite material were studied. The energetic SMP composite exhibits an angle of reversal of 18 s at 70°, with a maximum elongation typically reaching up to 280% of the original length and a recovery length of approximately 105% during ten cycles. Additionally, thermal decomposition and combustion behavior were also demonstrated for the energetic SMP composite.

Abstract Accurate indel calling plays an important role in precision medicine. A benchmarking indel set is essential for thoroughly evaluating the indel calling performance of bioinformatics pipelines. A reference sample with a set of known-positive variants was developed in the FDA-led Sequencing Quality Control Phase 2 (SEQC2) project, but the known indels in the known-positive set were limited. This project sought to provide an enriched set of known indels that would be more translationally relevant by focusing on additional cancer related regions. A thorough manual review process completed by 42 reviewers, two advisors, and a judging panel of three researchers significantly enriched the known indel set by an additional 516 indels. The extended benchmarking indel set has a large range of variant allele frequencies (VAFs), with 87% of them having a VAF below 20% in reference Sample A. The reference Sample A and the indel set can be used for comprehensive benchmarking of indel calling across a wider range of VAF values in the lower range. Indel length was also variable, but the majority were under 10 base pairs (bps). Most of the indels were within coding regions, with the remainder in the gene regulatory regions. Although high confidence can be derived from the robust study design and meticulous human review, this extensive indel set has not undergone orthogonal validation. The extended benchmarking indel set, along with the indels in the previously published known-positive set, was the truth set used to benchmark indel calling pipelines in a community challenge hosted on the precisionFDA platform. This benchmarking indel set and reference samples can be utilized for a comprehensive evaluation of indel calling pipelines. Additionally, the insights and solutions obtained during the manual review process can aid in improving the performance of these pipelines.

Abstract Value at risk (VaR) and expected shortfall (ES) have emerged as standard measures for detecting the market risk of financial assets and play essential roles in investment decisions, external regulations, and risk capital allocation. However, existing VaR estimation approaches fail to accurately reflect downside risks, and the ES estimation technique is quite limited owing to its challenging implementation. This causes financial institutions to overestimate or underestimate investment risk and finally leads to the inefficient allocation of financial resources. The main purpose of this study is to use machine learning to improve the accuracy of VaR estimation and provide an effective tool for ES estimation. Specifically, this study proposes a VaR estimator by combining quantile regression with “Mogrifier” recurrent neural networks to capture the “long memory” and “clustering” properties of financial assets; while for estimating ES, this study directly models the quantile of assets and employs generative adversarial networks to generate future tail risk scenarios. In addition to the typical properties of financial assets, the model design is also consistent with heterogeneous market theory. An empirical application to four major global stock indices shows that our model is superior to other existing models.

The high resolution range profile (HRRP) of radar targets is commonly used for target recognition, and the recognition of non-cooperative targets is one of the urgent problems to be solved in radar target recognition. In order to address the noise impact and small sample issues in non-cooperative target recognition, this paper proposes a radar target HRRP recognition method based on SDAE-WACGAN. This method combines Stacked Denoising Auto-encoders (SDAE) and Weighted Auxiliary Classifier Generative Adversarial Networks (WACGAN). In this networks, the decoder of SDAE is used as the generator of WACGAN and the weight coefficients is introduced on the basis of ACGAN, so that the network can generate high-quality data that is more consistent with the real sample distribution, and can be more robust to noise. Experimental results show that compared with other commonly used models, the proposed method achieves higher recognition accuracy in scenarios with small samples and high noise, and demonstrates certain advantages in different SNRs and different number of sample sets.

With the increasing emphasis on environmental issues, the utilization of renewable energy has been recognized as a feasible solution to address the energy crisis and reduce environmental pollution. In view of this, this article proposes a multi-modal renewable energy hybrid power supply optimization model based on heterogeneous cloud wireless access. The model innovatively combines heterogeneous cloud wireless access technology and various intelligent optimization algorithms, including k-clustering algorithm, particle swarm optimization algorithm, and whale optimization algorithm, forming a hybrid optimization algorithm. In order to comprehensively evaluate the actual performance of the model, this study recruited 20 experts to provide detailed ratings on four core dimensions: cost-benefit ratio, reliability, robustness, and user satisfaction. The results showed that the model scored 95.1, 96.4, 95.6, and 96.2 in the four dimensions of cost-benefit ratio, reliability indicators, robustness, and user satisfaction, respectively. This series of significant data not only confirms the theoretical superiority of the model, but also demonstrates its strong potential and practical value in practical applications. In summary, this study provides a promising and innovative solution for the field of renewable energy supply.

The Chinese mitten crab (Eriocheir sinensis) is an economically important crustacean. With the development of the E. sisnensis industry, precocity has become a significant challenge in juvenile crab culturing. In this study, the eyestalks of female E. sinensis from precocious (PE) and normal juvenile (NE) groups were used for proteome and metabolome analyses. In total, 731 up-regulated and 657 down-regulated differentially expressed proteins (DEPs) were identified in the PE and NE groups. In addition, 110 differentially expressed metabolites (DMs) were up-regulated and 256 were down-regulated in the PE group. An integrated analysis showed 5667 significant correlations between the metabolites and proteins and 109 common pathways in the proteome and metabolome. The proteins were mostly associated with the mechanistic target of rapamycin (mTOR) pathway, longevity regulation, autophagy, and the pyrimidine and purine metabolism pathways. The metabolites were primarily enriched in amino acid and lipid metabolisms. These results demonstrated the differences in the PE and NE groups at two omics levels and will be useful for the E. sinensis industry.

For the current wearable devices in the application of cross-diversified user groups, it is common to face the technical difficulties of static sign language recognition accuracy attenuation, weak anti-noise ability, and insufficient system robustness due to the differences in the use of users. This paper proposes a novel static sign language recognition method enhanced by a self-attention mechanism. The key features of sign language gesture classification are highlighted by the weight function, and then the self-attention mechanism is combined to pay more attention to the key features, and the convolutional neural network is used to extract the features and classify them, which realizes the accurate recognition of different types of static sign language under standard gestures and non-standard gestures. Experimental results reveal that the proposed method achieves an average accuracy of 99.52% in the standard static sign language recognition task when tested against the standard 36 static gestures selected within the reference American Sign Language dataset. By imposing random angular bias conditions of ±(0°–9°] and ±(9°–18°], the average recognition rates in this range were 98.63% and 86.33%. These findings indicate that, compared to existing methods, the proposed method not only maintains a high recognition rate for standard static gestures but also exhibits superior noise resistance and robustness, rendering it suitable for static sign language recognition among diverse user populations.

The rapidly developed Unmanned Aerial Vehicles (UAV) and artificial intelligence technology has prompted the real-time and accurate observation measurements of tidal bore, the basis of which is tidal bore propagation velocity. In this article, we construct a tidal observation system framework based on UAV and computer vision in order to obtain the tidal bore propagating velocity datasets. Firstly, we focus on the identification of tidal headlines based on the Sobel edge detection, the improved Otsu image segmentation algorithm and the edge connection algorithm with an accuracy of 91%. And then, the detected tidal headlines could be used to control the flight parameters of UAV in order to stably track tidal bore on the specified route with the deviation range below 0.5, and finally to acquire the tidal bore propagation velocity datasets. Comparing with the propagation velocity of the tidal line measured on site, the error of the results is maintained within 0.1 m/s, which demonstrates the effectiveness of our proposed observation method.

Abstract Exploiting multi‐scale features is one of the most effective methods to recognize objects of different scales in object detection. Since image pyramid is time‐consuming, Feature Pyramid Network (FPN) becomes the most popular component used for obtaining pyramidal features. Despite its effectiveness, there still exist some intrinsic defects. In this work, it is attributed to insufficient information flow and a Deformable Cross‐scale Interaction Feature Pyramid Network (DCIFPN) is proposed, which aims to promote the information transfer process with content‐aware sampling and dynamic aggregation weights. More specifically, Deformable Semantic Enhancement Module (DSEM) is designed that can construct accurate information flow with dynamic aggregation weights. In addition, Deformable Spatial Refinement Module (DSRM) is proposed to enhance high‐level features with low‐level location details. When DCIFPN is deployed on RetinaNet and FCOS with ResNet‐50, the performance is improved by 1.6 AP and 1.1 AP, respectively, on the challenging MS COCO benchmark. Apart from one‐stage detectors, DCIFPN is also applicable to two‐stage methods such as Faster R‐CNN and Mask R‐CNN. Further experiments on Pascal VOC and CrowdHuman datasets can verify the effectiveness and generalization of the method.

In order to study the influence of the vacuum arc remelting process (VAR) on the grain structure of the ingot and provide initial condition for the prediction and analysis of the subsequent process such as homogenization and billet forging, an efficient and accurate three-dimensional (3D) cellular automata method was developed for the VAR process, and all parts of the algorithm were rigorously verified, and it can be combined with the MeltFlow-VAR. An ingot of 718 alloy was smelted through experiment for calculation verification and proved the accuracy of the predictions. A new method for discretization of Euler angles to obtain orientation index is proposed and verified, which is more flexible and higher computationally efficient than previous algorithms. Aiming at the problem of a large number of cells and calculation time on large-scale VAR ingot in the future, a hybrid parallel scheme is designed, and it is expected to realize large-scale calculations on the supercomputer system. Finally, the effect of different cell sizes on the calculation results was also studied, and the grain size at the edge of the ingot was not affected by the cell size.

To enhance the performance of super-resolution models, neural networks frequently employ module stacking. However, this approach inevitably results in an excessive proliferation of parameter counts and information redundancy, ultimately constraining the deployment of these models on mobile devices. To surmount this limitation, this study introduces the application of Dual-path Large Kernel Learning (DLKL) to the task of image super-resolution. Within the DLKL framework, we harness a multiscale large kernel decomposition technique to efficiently establish long-range dependencies among pixels. This network not only maintains excellent performance but also significantly mitigates the parameter burden, achieving an optimal balance between network performance and efficiency. When compared with other prevalent algorithms, DLKL exhibits remarkable proficiency in generating images with sharper textures and structures that are more akin to natural ones. It is particularly noteworthy that on the challenging texture dataset Urban100, the network proposed in this study achieved a significant improvement in Peak Signal-to-Noise Ratio (PSNR) for the ×4 upscaling task, with an increase of 0.32 dB and 0.19 dB compared with the state-of-the-art HAFRN and MICU networks, respectively. This remarkable result not only validates the effectiveness of the present model in complex image super-resolution tasks but also highlights its superior performance and unique advantages in the field.

Obesity is a complex and multifactorial disease with global epidemic proportions, posing significant health and economic challenges. Whilst diet and lifestyle are well-established contributors to the pathogenesis, the gut microbiota’s role in obesity development is increasingly recognized. Blautia, as one of the major intestinal bacteria of the Firmicutes phylum, is reported with both potential probiotic properties and causal factors for obesity in different studies, making its role controversial. To summarize the current understanding of the Blautia–obesity correlation and to evaluate the evidence from animal and clinical studies, we used “Blautia” AND “obesity” as keywords searching through PubMed and SpringerLink databases for research articles. After removing duplicates and inadequate articles using the exclusion criteria, we observed different results between studies supporting and opposing the beneficial role of Blautia in obesity at the genus level. Additionally, several studies showed probiotic effectiveness at the species level for Blautia coccoides, B. wexlerae, B. hansenii, B. producta, and B. luti. Therefore, the current evidence does not demonstrate Blautia’s direct involvement as a pathogenic microbe in obesity development or progression, which informs future research and therapeutic strategies targeting the gut Blautia in obesity management.

Feature extraction plays a pivotal role in the context of single image super-resolution. Nonetheless, relying on a single feature extraction method often undermines the full potential of feature representation, hampering the model’s overall performance. To tackle this issue, this study introduces the wide-activation feature distillation network (WFDN), which realizes single image super-resolution through dual-path learning. Initially, a dual-path parallel network structure is employed, utilizing a residual network as the backbone and incorporating global residual connections to enhance feature exploitation and expedite network convergence. Subsequently, a feature distillation block is adopted, characterized by fast training speed and a low parameter count. Simultaneously, a wide-activation mechanism is integrated to further enhance the representational capacity of high-frequency features. Lastly, a gated fusion mechanism is introduced to weight the fusion of feature information extracted from the dual branches. This mechanism enhances reconstruction performance while mitigating information redundancy. Extensive experiments demonstrate that the proposed algorithm achieves stable and superior results compared to the state-of-the-art methods, as evidenced by quantitative evaluation metrics tests conducted on four benchmark datasets. Furthermore, our WFDN excels in reconstructing images with richer detailed textures, more realistic lines, and clearer structures, affirming its exceptional superiority and robustness.

IntroductionGut microbes form complex networks that significantly influence host health and disease treatment. Interventions with the probiotic bacteria on the gut microbiota have been demonstrated to improve host well-being. As a representative of next-generation probiotics, Christensenella minuta (C. minuta) plays a critical role in regulating energy balance and metabolic homeostasis in human bodies, showing potential in treating metabolic disorders and reducing inflammation. However, interactions of C. minuta with the members of the networked gut microbiota have rarely been explored.MethodsIn this study, we investigated the impact of C. minuta on fecal microbiota via metagenomic sequencing, focusing on retrieving bacterial strains and coculture assays of C. minuta with associated microbial partners.ResultsOur results showed that C. minuta intervention significantly reduced the diversity of fecal microorganisms, but specifically enhanced some groups of bacteria, such as Lactobacillaceae. C. minuta selectively enriched bacterial pathways that compensated for its metabolic defects on vitamin B1, B12, serine, and glutamate synthesis. Meanwhile, C. minuta cross-feeds Faecalibacterium prausnitzii and other bacteria via the production of arginine, branched-chain amino acids, fumaric acids and short-chain fatty acids (SCFAs), such as acetic. Both metagenomic data analysis and culture experiments revealed that C. minuta negatively correlated with Klebsiella pneumoniae and 14 other bacterial taxa, while positively correlated with F. prausnitzii. Our results advance our comprehension of C. minuta’s in modulating the gut microbial network.ConclusionsC. minuta disrupts the composition of the fecal microbiota. This disturbance is manifested through cross-feeding, nutritional competition, and supplementation of its own metabolic deficiencies, resulting in the specific enrichment or inhibition of the growth of certain bacteria. This study will shed light on the application of C. minuta as a probiotic for effective interventions on gut microbiomes and improvement of host health.

L-theanine, a non-protein amino acid in tea, has been widely studied as an immune enhancer in poultry, livestock, and rodents. However, no studies have been performed on the application of L-theanine in aquaculture feed. To fill this research gap, we investigated the effects of L-theanine as a feed additive on the growth performance, immune function, antioxidant capacity, and intestinal flora of female Chinese mitten crab (Eriocheir sinensis) using biochemical assays, real-time polymerase chain reaction, and 16 S rRNA gene sequencing. In total, 300 one-year-old female Chinese mitten crabs were randomly divided into treatment groups supplemented with 0 (control), 0.5%, 1.0%, 1.5%, and 2.0% L-theanine (L0–L4, respectively; n = 4 replicates per group with 15 crabs per replicate). After eight weeks, the total edible yield was significantly higher in all treatment groups than in the L0 group (P

Background The presence of sudden onset to maximal deficit (SOTMD) in patients with acute basilar artery occlusion often results in more severe outcomes. However, the effect of endovascular therapy on SOTMD and whether the outcome is affected by onset‐to‐puncture time remain unclear. Methods and Results This retrospective analysis was conducted using data from the prospective BASILAR (Endovascular Treatment for Acute Basilar Artery Occlusion Study Registry). Consecutive patients with basilar artery occlusion receiving endovascular therapy were dichotomized into SOTMD and non‐SOTMD cohorts. The primary outcomes included a favorable outcome (modified Rankin scale 0–3), recanalization, and mortality at 90 days. The outcomes of patients with SOTMD were analyzed using multivariable logistic regression. In the multivariate analysis, a favorable outcome was similar between the two cohorts (odds ratio [OR], 0.88 [95% CI, 0.58–1.34]; P=0.5), although the mortality of patients with SOTMD was higher than that of patients with non‐SOTMD (OR, 1.67 [95% CI, 1.14–2.44]; P=0.008). The probability of mortality increased from 40.0% at 1 hour to 70.0% at 6 hours in the SOTMD cohort, and favorable outcomes of patients with non‐SOTMD declined from 38.0% at 1 hour to 18.0% at 8 hours. Conclusions No significant difference was observed in favorable outcomes between the SOTMD and non‐SOTMD groups, although mortality was higher in the SOTMD cohort. The patients with SOTMD had a stronger time dependence for endovascular therapy in terms of mortality, while the time dependency regarding favorable outcome in the NSOTMD group was even higher. Registration URL: https://www.chictr.org.cn; Unique identifier: ChiCTR1800014759.

Mating plugs in animals are ubiquitous and are commonly interpreted to be products of mating strategies. In spiders, however, mating plugs may also take on functions beyond female remating prevention. Due to the vagaries of female genital (spermathecal) anatomy, most spiders face the problem of having to secure additional, non-anatomical, protection for transferred sperm. Here, we test the hypothesis that mating plugs, rather than (or in addition to) being adaptations for mating strategies, may serve as sperm protection mechanism. Based on a comparative study on 411 epigyna sampled from 36 families, 187 genera, 330 species of entelegyne spiders, our results confirm the necessity of a sperm protection mechanism. We divided the entelegyne spermathecae into four types: SEG, SED, SCG and SCD. We also studied detailed morphology of epigynal tracts in the spider Diphya wulingensis having the SEG type spermathecae, using 3D-reconstruction based on semi thin histological series section. In this species, we hypothesize that two distinct types of mating plug, the sperm plug and the secretion plug, serve different functions. Morphological details support this: sperm plugs are formed on a modified spermathecal wall by the spilled sperm, and function as a temporary protection mechanism to prevent sperm from leaking and desiccating, while secretion plugs function in postcopulation both as a permanent protection mechanism, and to prevent additional mating. Furthermore, with the modified spermathecal wall of S2 stalk, the problem of shunt of sperm input and output, and the possibility of female multiple mating have been resolved. Variation in spermathecal morphology also suggests that the problem of sperm protection might be resolved in different ways in spiders. Considering mating plugs of varying shapes and origins in the vast morphospace of spiders, we conclude that mating plugs might serve different purposes that relate both to mating strategies, as well as to sperm protection.

Abstract Public health service is an important guarantee by the government to safeguard the health rights of rural migrant women. This not only concerns the health status of rural migrant women and their willingness to stay in the urban area but can also affect their fertility intention. This study systematically examined the impact of public health services on the fertility intentions of rural migrant women as well as the mechanisms, underlying these intentions based on the data from the 2018 China Migration Dynamics Monitoring Survey. Urban public health services, including health records management and health education, could effectively enhance the fertility intentions of rural migrant women. Furthermore, their health status and willingness to stay in urban areas were important mechanisms, by which, the public health services could influence the fertility intentions of rural migrant women. Additionally, urban public health services have a better effect on improving the fertility desire of rural migrant women who have no pregnancy experience, a low income level, and a short residence time in the inflow area. This study contributed to the examination and clarification of the policy effects of public health services on the fertility intentions of rural migrant women. Additionally, it also provided important evidence to support the government policies related to the optimization of the public health service system, improvement of the health status, citizenship, and fertility intentions of the rural migrant women, as well as the development of the uniform public health services.

Increasing service temperature of wrought Ni-based superalloy by increasing alloying degree and fraction of γ′ phase has come to a bottleneck. In present work, an attempt is made to make maximum use of carbide to strengthen Ni-based alloy with a simpler chemical composition. Multiple morphology characterization methods and high temperature tensile test show that the newly designed Ni(bal.)-20Cr-0.80C–12Ta (wt%) alloy can be strengthened by TaC and Cr-rich M7C3 carbide and shows good ductility at 800 °C. Phase transformation characteristics detected by differential scanning calorimetry (DSC) and high-temperature confocal laser scanning microscopy (CLSM) images shows that there is a potential for dispersive precipitation of carbide in the alloy to get better mechanical property.

At present, visual saliency prediction algorithms have been developed more and more mature, but most of the current saliency prediction algorithms are aimed at natural images. Due to the inconsistency of elements and features between natural images and advertising images, the existing saliency prediction algorithms show poor robustness and low inference speed to advertising images, which severely limits its commercial application in advertising design and evaluation. In view of this, a saliency prediction algorithm for advertisement images is proposed in this paper. In the feature extraction stage, two text candidate regions based on intensity feature and improved MESR algorithm are first obtained and further integrated to produce a two-dimensional text confidence score. Meanwhile, a saliency confidence score is also obtained by an improved natural image saliency prediction network. Then, the score level fusion strategy was adopted to fuse the two confidence scores to get the final saliency prediction map. The experimental results show that the proposed model has good accuracy and robustness in advertising images, as well as the most remarkable inference speed, which can meet the demand for real-time performance of advertising image saliency prediction, leading to great practical and commercial value.

Deep convolutional neural networks have significantly enhanced the performance of single image super-resolution in recent years. However, the majority of the proposed networks are single-channel, making it challenging to fully exploit the advantages of neural networks in feature extraction. This paper proposes a Multi-attention Fusion Recurrent Network (MFRN), which is a multiplexing architecture-based network. Firstly, the algorithm reuses the feature extraction part to construct the recurrent network. This technology reduces the number of network parameters, accelerates training, and captures rich features simultaneously. Secondly, a multiplexing-based structure is employed to obtain deep information features, which alleviates the issue of feature loss during transmission. Thirdly, an attention fusion mechanism is incorporated into the neural network to fuse channel attention and pixel attention information. This fusion mechanism effectively enhances the expressive power of each layer of the neural network. Compared with other algorithms, our MFRN not only exhibits superior visual performance but also achieves favorable results in objective evaluations. It generates images with sharper structure and texture details and achieves higher scores in quantitative tests such as image quality assessment.

Background: Dental pulp stem cells (DPSCs) have self-renewal and multidirectional differentiation potentials. As such, DPSCs have a wide range of clinical applications. Low-level laser therapy (LLLT) has positive photobiostimulatory effects on cell proliferation, angiogenesis, osteogenic differentiation, bone regeneration, and fracture healing. However, there have been few studies on the effect of low-energy lasers on DPSC proliferation. Methods: DPSCs were obtained from dental pulp tissue. The effects of LLLT on the proliferation of DPSCs and the associated mechanisms were investigated by in vitro culture and laser irradiation. Results: LLLT with energy densities of 3.5 J/cm2 and 14 J/cm2promoted the proliferation of DPSCs. Differential protein expression studies suggested the stimulation of DPSC proliferation by LLLT involved the PI3K-Akt and Rap1 signaling pathways, as well as the apoptosis-related pathway. Conclusion: This preliminary study demonstrated that low-energy lasers have a pro-proliferative effect on DPSCs, and identified possible associated mechanisms. Our findings provide a theoretical basis for the clinical application of DPSCs and suggest novel strategies for the treatment of related diseases.

Lacticaseibacillus rhamnosus is applied as a probiotic to alleviate various metabolic, gastrointestinal, and psychological symptoms and diseases, and its probiotic effectiveness is strain-specific. In this study, we obtained 21 strains of Ls. rhamnosus, and their genomes were sequenced. We defined the pan- and core-genomes of Ls. rhamnosus. Phenotypes such as the assimilation of carbohydrates and antibiotic resistance were experimentally characterized and associated with genome annotations. Nine strains were selected and tested for growth rates, tolerance to acidity/alkalinity and bile acids, the production of short-chain fatty acids, and competition with pathogenic microbes. Strains WL11 and WL17 were targeted as potential probiotics and were applied in mouse model tests for the alleviation of chronic fatigue syndrome (CFS) and irritable bowel syndrome (IBS). The results showed that WL11 and WL17 effectively alleviated slow body weight gain, anxiety, poor memory, and cognitive impairment in CFS mouse models. They also reduced the expression of pro-inflammatory factors, such as TNF-α and IL-6, and alleviated intestinal peristalsis, visceral hypersensitivity, and anxiety-like behavior in IBS mouse models. This study reports new Ls. rhamnosus strain resources and their effect on alleviation of both IBS and CFS symptoms with mouse models; the probiotic functions of those strains in human patients remain to be further tested.

So as to decrease those cacoethic impact of a huge amount of wind energy generation systems associated with the electric power system and improve the utilization rate and the budgetary profits of wind power era, this paper raises a neural network in view of CEEMDAN-LSTM-TCN. Firstly, CEEMDAN is used to break down the wind velocity arrangement to decrease the sway of arbitrariness Furthermore variance about wind velocity. Secondly, the ultra-short-term wind power forecast depend upon LSTM and TCN is built to realize the real-time prediction for wind energy. Finally, the simulation results show that LSTM-TCN can deal with multi time order characteristics and predict ultra-short period wind energy with effect, which is better than LSTM and TCN. It also has a scientific reference for local power dispatching.

In view of the problem that load frequency fluctuation of the electrical power systems with energy storage when it is disturbed, a load frequency control (LFC) model is constructed, furthermore, a load frequency controller which bottom on disturbance observer is devised, the accommodate reaching law is used to improve the system performance. These actions have improved the immunity and robustness of the system. It is verified by MATLAB simulation that the control strategy can decrease load frequency deflection under conditions of load fluctuation with effect, and the Lyapunov principle is used to analyze the stability. The analysis shows the method proposed can effectively ameliorate the robustness and operational stability of power systems with energy storage.

ABSTRACTGlycogen storage disease type Ia (GSD-Ia) is caused by a deficiency in the glucose-6-phosphatase (G6Pase, G6pc) enzyme, which catalyses the final step of gluconeogenesis and glycogenolysis. Accumulation of G6pc can lead to an increase in glycogen and development of fatty liver. Ductular reactions refer to the proliferation of cholangiocytes and hepatic progenitors, which worsen fatty liver progress. To date, however, ductular reactions in GSD-Ia remain poorly understood. Here, we studied the development and potential underlying mechanism of ductular reactions in GSD-Ia in mice. We first generated GSD-Ia mice using CRISPR/Cas9 to target the exon 3 region of the G6pc gene. The typical GSD-Ia phenotype in G6pc−/− mice was then analysed using biochemical and histological assays. Ductular reactions in G6pc−/− mice were tested based on the expression of cholangiocytic markers cytokeratin 19 (CK19) and epithelial cell adhesion molecule (EpCAM). Yes-associated protein 1 (Yap) signalling activity was measured using western blot (WB) analysis and quantitative real-time polymerase chain reaction (qRT-PCR). Verteporfin was administered to the G6pc−/− mice to inhibit Yap signalling. The CRISPR/Cas9 system efficiently generated G6pc−/− mice, which exhibited typical GSD-Ia characteristics, including retarded growth, hypoglycaemia, and fatty liver disease. In addition, CK19- and EpCAM-positive cells as well as Yap signalling activity were increased in the livers of G6pc−/− mice. However, verteporfin treatment ameliorated ductular reactions and decreased Yap signalling activity. This study not only improves our understanding of GSD-Ia pathophysiology, but also highlights the potential of novel therapeutic approaches for GSD-Ia such as drug targeting of ductular reactions.

This paper introduces a novel control strategy that merges integral sliding mode control with fuzzy adaptive PI control. This hybrid approach maximizes the benefits of both techniques to ensure voltage stability in DC microgrid. Firstly, a mathematical model characterizes the DC–DC boost converter. Subsequently, a sliding surface, incorporating an integral term, is employed to regulate the converter’s output voltage and current errors. To address uncertainties stemming from factors like input inductance and output capacitance, a dynamic sliding mode controller is formulated. The proposed sliding mode control scheme significantly reduces the time required for voltage stability, curbs system oscillations, and showcases robustness. Furthermore, the inclusion of fuzzy adaptive PI control aids in refining the voltage deviation signal and droop resistance. This enhancement improves the precision of the error tracking system. Finally, the effectiveness of this strategy is demonstrated through MATLAB simulations, supported by experimental validation and analysis. The findings reveal that this control strategy efficiently accelerates the convergence of DC microgrid voltage to a stable state.

Summary: Background: Ground-glass opacity (GGO)-like lung adenocarcinoma (LUAD) has been detected increasingly in the clinic and its inert property and superior survival indicate unique biological characteristics. However, we do not know much about them, which hampers identification of key reasons for the inert property of GGO-like LUAD. Methods: Using whole-exome sequencing and RNA sequencing, taking into account both radiological and pathological classifications of the same 197 patients concomitantly, we systematically interrogate genes driving the progression from GGO to solid nodule and potential reasons for the inertia of GGO. Using flow cytometry and IHC, we validated the abundance of immune cells and activity of cell proliferation. Findings: Identifying the differences between GGO and solid nodule, we found adenocarcinoma in situ/minimally invasive adenocarcinoma (AIS/MIA) and GGO-like LUAD exhibited lower TP53 mutation frequency and less active cell proliferation-related pathways than solid nodule in LUAD. Identifying the differences in GGO between AIS/MIA and LUAD, we noticed that EGFR mutation frequency and CNV load were significantly higher in LUAD than in AIS/MIA. Regulatory T cell was also higher in LUAD, while CD8+ T cell decreased from AIS/MIA to LUAD. Finally, we constructed a transcriptomic signature to quantify the development from GGO to solid nodule, which was an independent predictor of patients’ prognosis in 11 external LUAD datasets. Interpretation: Our results provide deeper insights into the indolent nature of GGO and provide a molecular basis for the treatment of GGO-like LUAD. Funding: This study was supported in part by the National Natural Science Foundation of China (32170657), the National Natural Science Foundation of China (82203037), and Shanghai Sailing Program (22YF1408900).

In order to control the influence of wind power generation incorporated into the power grid and keep the original power grid stable, this paper investigates the Takagi–Sugeno fuzzy model and the nonlinear switched system for permanent magnet synchronous generator in wind power generation system. By introducing fuzzy sliding mode control method, the stability of power system can be guaranteed. To do this, the integral sliding mode surface and fuzzy sliding mode control law are designed to reduce the influence of nonlinear disturbance on power system. In addition, the appropriate Lyapunov function is selected for derivation and proof. At the same time, the gain matrix is solved by linear matrix inequalities, which makes the model globally asymptotically stable. Finally, the stability of the system model is verified by simulation results.