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Abstract Background A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting. Methods We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values. Results Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency. Conclusions Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed.

Abstract R-loops are prevalent three-stranded nucleic acid structures, comprising a DNA-RNA hybrid and a displaced single-stranded DNA, that frequently form during transcription and may be attributed to genomic stability and gene expression regulation. It was recently discovered that RNA modification contributes to maintain the stability of R-loops such as N6-methyladenosine (m6A). Yet, m6A-modified R-loops in regulating gene transcription remains poorly understood. Here, we demonstrated that insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs) recognize R-loops in an m6A-dependent way. Consequently, IGF2BPs overexpression leads to increased overall R-loop levels, cell migration inhibition, and cell growth retardation in prostate cancer (PCa) via precluding the binding of DNA methyltransferase 1(DNMT1) to semaphorin 3 F (SEMA3F) promoters. Moreover, the K homology (KH) domains of IGF2BPs are required for their recognition of m6A-containing R-loops and are required for tumor suppressor functions. Overexpression of SEMA3F markedly enhanced docetaxel chemosensitivity in prostate cancer via regulating Hippo pathway. Our findings point to a distinct R-loop resolution pathway mediated by IGF2BPs, emphasizing the functional importance of IGF2BPs as epigenetic R-loop readers in transcriptional genetic regulation and cancer biology. The manuscript summarizes the new role of N6-methyladenosine in epigenetic regulation, we introduce the distinct R-loop resolution mediated by IGF2BP proteins in an m6A-dependent way, which probably lead to the growth retardation and docetaxel chemotherapy resistance in prostate cancer. Moreover, our findings first emphasized the functional importance of IGF2BPs as epigenetic R-loop readers in transcriptional genetic regulation and cancer biology. In addition, our research provides a novel RBM15/IGF2BPs/DNMT1 trans-omics regulation m6A axis, indicating the new crosstalk between RNA m6A methylation and DNA methylation in prostate cancer. Graphical Abstract

Abstract Bioprinting that can synchronously deposit cells and biomaterials has lent fresh impetus to the field of tissue regeneration. However, the unavoidable occurrence of cell damage during fabrication process and intrinsically poor mechanical stability of bioprinted cell-laden scaffolds severely restrict their utilization. As such, on basis of heart-inspired hollow hydrogel-based scaffolds (HHSs), a mechanical-assisted post-bioprinting strategy is proposed to load cells into HHSs in a rapid, uniform, precise and friendly manner. HHSs show mechanical responsiveness to load cells within 4 s, a 13-fold increase in cell number, and partitioned loading of two types of cells compared with those under static conditions. As a proof of concept, HHSs with the loading cells show an enhanced regenerative capability in repair of the critical-sized segmental and osteoporotic bone defects in vivo. We expect that this post-bioprinting strategy can provide a universal, efficient, and promising way to promote cell-based regenerative therapy.

Abstract This paper studies the flexible double shop scheduling problem (FDSSP) that considers simultaneously job shop and assembly shop. It brings about the problem of scheduling association of the related tasks. To this end, a reinforcement learning algorithm with a deep temporal difference network is proposed to minimize the makespan. Firstly, the FDSSP is defined as the mathematical model of the flexible job-shop scheduling problem joined to the assembly constraint level. It is translated into a Markov decision process that directly selects behavioral strategies according to historical machining state data. Secondly, the proposed ten generic state features are input into the deep neural network model to fit the state value function. Similarly, eight simple constructive heuristics are used as candidate actions for scheduling decisions. From the greedy mechanism, optimally combined actions of all machines are obtained for each decision step. Finally, a deep temporal difference reinforcement learning framework is established, and a large number of comparative experiments are designed to analyze the basic performance of this algorithm. The results showed that the proposed algorithm was better than most other methods, which contributed to solving the practical production problem of the manufacturing industry.

Abstract Background Hyalomma ticks are widely distributed in semi-arid zones in Northwest China. They have been reported to harbor a large number of zoonotic pathogens. Methods In this study, a total of 334 Hyalomma asiaticum ticks infesting domestic animals were collected from four locations in Xinjiang, Northwest China, and the bacterial agents in them were investigated. Results A putative novel Borrelia species was identified in ticks from all four locations, with an overall positive rate of 6.59%. Rickettsia sibirica subsp. mongolitimonae, a human pathogen frequently reported in Europe, was detected for the second time in China. Two Ehrlichia species (Ehrlichia minasensis and Ehrlichia sp.) were identified. Furthermore, two Anaplasma species were characterized in this study: Candidatus Anaplasma camelii and Anaplasma sp. closely related to Candidatus Anaplasma boleense. It is the first report of Candidatus Anaplasma camelii in China. Conclusions Six bacterial agents were reported in this study, many of which are possible or validated pathogens for humans and animals. The presence of these bacterial agents may suggest a potential risk for One Health in this area. Graphical Abstract

Dishevelled 2 (Dvl2) is a key mediator of the Wingless/Wnt signaling pathway that regulates cell proliferation, migration, and immune function. However, little is known about the role of macrophage Dvl2 in modulating NOD1-mediated pyroptosis and hepatocyte death in oxidative stress-induced inflammatory liver injury. In a mouse model of oxidative stress-induced liver inflammation, mice with myeloid-specific Dvl2 knockout (Dvl2M−KO) displayed exacerbated ischemia/reperfusion (IR) stress-induced hepatocellular damage with increased serum ALT levels, oxidative stress, and proinflammatory mediators. Unlike in Dvl2FL/FL controls, Dvl2M−KO enhanced NOD1, caspase-1, GSDMD, and NF-κB activation in liver macrophages after IR. Interestingly, IR stress enhanced YAP colocalized with HSF1 in Dvl2FL/FL macrophages, while macrophage Dvl2 deficiency reduced YAP and HSF1 colocalization in the nucleus under inflammatory conditions. Importantly, Dvl2 deletion diminished nuclear YAP interacted with HSF1 and augmented NOD1/caspase-1 and GSDMD activation in response to inflammatory stimulation. However, Dvl2 activation increased YAP interaction with HSF1 and activated HSF1 target gene eEF2, inhibiting NOD1/caspase-1, GSDMD, and NF-κB activity. Moreover, macrophage eEF2 deletion increased the NOD1-caspase-1 interaction, GSDMD activation, HMGB1 release, and hepatocyte LDH release after macrophage/hepatocyte co-culture. Adoptive transfer of eEF2-expressing macrophages in Dvl2M−KO mice alleviated IR-triggered liver inflammation and hepatocellular damage. Therefore, macrophage Dvl2 deficiency promotes NOD1-mediated pyroptosis and exacerbates IR-induced hepatocellular death by disrupting the YAP-HSF1 axis. eEF2 is crucial for modulating NOD1-driven pyroptosis, inflammatory response, and hepatocyte death. Our findings underscore a novel role of macrophage Dvl2 in modulating liver inflammatory injury and imply the therapeutic potential in organ IRI and transplant recipients.

The widespread use of plasticizers like phthalate esters (PAEs) has led to environmental and health concerns. The neurobehavioral toxicity of these compounds in marine environments, particularly regulated by the “brain-gut” axis, remains unclear, especially concerning wild demersal fish of high ecological value. Our investigation into the behavioral effects of three common PAEs, i.e., dimethyl phthalate (DMP), di-n-butyl phthalate (DBP), and di(2-ethylhexyl) phthalate (DEHP), and their molecular mechanisms on juvenile Sebastes schlegelii, revealed alarming results from molecular to population levels. After a 20-day foodborne exposure at a low marine environmental concentration (1.0 μg g−1), we observed that all three PAEs significantly increased the thigmotaxis (behavioral tendency to stay close to physical boundaries) and mobility of juvenile fish by 28.2–59.4 % and 23.3–74.5 %, respectively, indicating anxiety-like behavior of fish. DEHP exhibited the most pronounced effects, followed by DBP and DMP. PAEs accumulated in the juvenile fish in the order of brain > liver > gut > muscle, with DEHP showing the highest brain concentrations (23.2 ± 2.98 μg g−1). This accumulation led to oxidative damage, inflammatory responses, and neurodegenerative changes in the optic tectum, resulting in cholinergic system dysfunction. In the gut, PAEs caused inflammatory lesions, disrupted the gut barrier, and altered the gut microbiome, exacerbating the neurotoxicity via “brain-gut” communication. These findings underscore the significant neurobehavioral toxicity of PAEs, emphasizing their critical impact on fish behavior. We also stress the crucial need for further research on fish and other marine species beyond the laboratory scale to fully understand the broader implications of PAE exposure in marine ecosystems and to guide future conservation efforts.

BackgroundStaffing policies are critical in healthcare facilities. However, problems from a mismatch between staff numbers requirements and offers are frequently encountered. This research examines the joint effects of quantitative and qualitative staff mismatch in a healthcare organization in China to understand how staffing management policies affect staffing adequacy and how staffing adequacy leads to important human resource (HR) outcomes.MethodsIn a previous study, we identified four dimensions of staffing management policies, namely decision-making, data management, productivity optimization, and title vs. competency. Based on this categorization, an 11-item scale was generated and evaluated for psychometric quality. A quantitative study was conducted with 1,323 healthcare professionals (including clinical and administrative staff) working at the hospital, matched by dyads and teams. A conceptual model with work engagement as a mediator between quantitative staffing adequacy interactions and qualitative staffing adequacy was tested with structural equations.ResultsThe findings indicate that staffing policies do exert effects on staffing adequacy. These findings further indicate that quantitative and qualitative staffing adequacy interact in explaining work engagement and team performance and that the moderated mediation occurs as hypothesized.ConclusionOur findings indicate that both types of staffing adequacies contribute to higher team performance via a heightened sense of work engagement from healthcare professionals. Furthermore, a modulation is observed between the two types of staffing adequacies during the promotion of higher team performance. The supported model is helpful in improving staffing management policies and increasing staffing fit so as to improve hospital performance.

BackgroundThe prevalence of cardiovascular disease has increased sharply in the Asian population, and evaluation of the risk of cardiovascular events with stable coronary heart disease remains challenging. The role of white blood cell (WBC) count in assisting clinical decision-making in this setting is still unclear.ObjectivesThis study sought to evaluate the prognostic meaning of WBC count among patients with stable coronary heart disease.MethodsThis study included Asian participants (n = 1,933) from the prospective STABILITY (Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy) trial, which involved 15,828 patients with stable coronary heart disease with 3–5 years of follow-up on optimal secondary preventive treatment. WBC count was measured at baseline. Associations between WBC count and cardiovascular outcomes were evaluated by Cox regression analyses with multivariable adjustments. Hematologic emergencies in patients may introduce potential bias.ResultsIn the lower WBC count quartiles, patients had lower-risk clinical profiles. Higher WBC counts were associated with greater event probabilities for cardiovascular death, major cardiovascular events, or all-cause death. In Cox regression models, WBC counts were an independent predictor of major adverse cardiovascular events (OR = 2.445, 95% CI 1.427–4.190, P = 0.001) for the primary outcomes. For the secondary outcomes, including the composite of all-cause death, cardiovascular death, myocardial infarction, stroke, and hospitalization for heart failure, WBC counts were significantly predictive of events with similar magnitude (OR = 1.716, 95% CI 1.169–2.521, P = 0.006).ConclusionsIn patients with stable coronary heart disease, higher WBC counts were associated with a heightened risk for the primary or secondary outcomes. Registrationhttps://clinicaltrials.gov/; Unique identifier NCT00799903.

ABSTRACT Nitrogen (N)-fixing organisms, also known as diazotrophs, play a crucial role in N-limited ecosystems by controlling the production of bioavailable N. The carbon-dominated cold-seep ecosystems are inherently N-limited, making them hotspots of N fixation. However, the knowledge of diazotrophs in cold-seep ecosystems is limited compared to other marine ecosystems. In this study, we used multi-omics to investigate the diversity and catabolism of diazotrophs in deep-sea cold-seep bottom waters. Our findings showed that the relative abundance of diazotrophs in the bacterial community reached its highest level in the cold-seep bottom waters compared to the cold-seep upper waters and non-seep bottom waters. Remarkably, more than 98% of metatranscriptomic reads aligned on diazotrophs in cold-seep bottom waters belonged to the genus Sagittula, an alphaproteobacterium. Its metagenome-assembled genome, named Seep-BW-D1, contained catalytic genes (nifHDK) for nitrogen fixation, and the nifH gene was actively transcribed in situ. Seep-BW-D1 also exhibited chemosynthetic capability to oxidize C1 compounds (methanol, formaldehyde, and formate) and thiosulfate (S2O32−). In addition, we observed abundant transcripts mapped to genes involved in the transport systems for acetate, spermidine/putrescine, and pectin oligomers, suggesting that Seep-BW-D1 can utilize organics from the intermediates synthesized by methane-oxidizing microorganisms, decaying tissues from cold-seep benthic animals, and refractory pectin derived from upper photosynthetic ecosystems. Overall, our study corroborates that carbon-dominated cold-seep bottom waters select for diazotrophs and reveals the catabolism of a novel chemosynthetic alphaproteobacterial diazotroph in cold-seep bottom waters.IMPORTANCEBioavailable nitrogen (N) is a crucial element for cellular growth and division, and its production is controlled by diazotrophs. Marine diazotrophs contribute to nearly half of the global fixed N and perform N fixation in various marine ecosystems. While previous studies mainly focused on diazotrophs in the sunlit ocean and oxygen minimum zones, recent research has recognized cold-seep ecosystems as overlooked N-fixing hotspots because the seeping fluids in cold-seep ecosystems introduce abundant bioavailable carbon but little bioavailable N, making most cold seeps inherently N-limited. With thousands of cold-seep ecosystems detected at continental margins worldwide in the past decades, the significant role of cold seeps in marine N biogeochemical cycling is emphasized. However, the diazotrophs in cold-seep bottom waters remain poorly understood. Through multi-omics, this study identified a novel alphaproteobacterial chemoheterotroph belonging to Sagittula as one of the most active diazotrophs residing in cold-seep bottom waters and revealed its catabolism.

The stress response of pig herds poses a significant challenge in the pig breeding industry, and investigating strategies to mitigate this stress is of paramount importance. The objective of this study was to investigate the impacts of supplemental feeding of Chinese herbal mixtures to perinatal sows on antioxidant capacity and gut microbiota of sows and their offspring piglets. A total of 60 healthy sows (Large white) at fourth parity were randomly assigned to five treatment groups. The control group received a basal diet, while the TRT1 group received a basal diet supplemented with 2kg/t Bazhen powder (BZP). The TRT2, TRT3, and TRT4 groups were fed a basal diet supplemented with 1kg/t, 2kg/t, and 3kg/t Qi-Zhu- Gui-Shao soothing liver and replenishing blood powder (QZGSP), respectively. The trial lasted for 5weeks, starting from day 100 of gestation until day 21 of delivery. The results demonstrated that the inclusion of 2kg/t and 3kg/t QZGSP significantly enhanced the antioxidant capacity of sows and their offspring piglets to different degrees, thereby effectively alleviating oxidative stress. Analysis of gut microbiota revealed that QZGSP influenced the composition of gut microbiota in both sows and their offspring piglets. Specifically, at the genus level, the abundance of Christensenellaceae_R-7_group in the gut microbiota of sows in the TRT4 group was significantly lower than that in the TRT1 group (p < 0.05), while the relative abundance of Lactobacillus in the gut microbiota of sows in the TRT4 group was significantly higher than that in the CON group (p < 0.05). Furthermore, at the genus level, compared to those in the TRT1 group, piglets from the TRT4 group exhibited a significant decrease in relative abundance of Escherichia-Shigella, Parabacteroides, and Methanobrevivacter (p < 0.05), but a significant increase in Phascolarctobacterium (p < 0.05). Spearman correlation analysis indicated a positive correlation between relative abundance of Christensenellaceae_R-7_group and serum contents of T-AOC and CAT (p < 0.05), as well as a negative correlation with serum concentration MDA (p < 0.05). Additionally, there was a positive correlation between relative abundance Lactobacillus and serum levels SOD (p < 0.01) and GSH-Px (p < 0.05). Therefore, supplementation of 3kg/t QZGSP in the periparturient sow diet significantly augmented antioxidant capacity in both sows and offspring piglets, while concurrently modulating the composition and structure of their intestinal microflora. The findings from this study demonstrate that QZGSP represents a beneficial feed additive for perinatal sows.

Drought has a significant impact on crop growth and productivity, highlighting the critical need for precise and timely soil moisture estimation to mitigate agricultural losses. This study focuses on soil moisture retrieval in northern Hebei Province during July 2012, utilizing eight widely employed remote sensing drought indices derived from MODIS satellite data. These indices were cross-referenced with measured soil moisture levels for analysis. Based on their correlation coefficients, a composite remote sensing drought index set comprising six indices was identified. Furthermore, a radial basis function neural network (RBFNN) was employed to estimate soil relative humidity. The accuracy evaluation of the soil moisture estimation model, which integrates multiple remote sensing drought indices and the RBFNN, demonstrated clear superiority over models relying on single drought indices. The model achieved an average estimation accuracy of 87.54 % for soil relative humidity at a depth of 10 cm (SM10) and 87.36 % for a 20 cm depth (SM20). The root mean square errors (RMSE) for the test sets were 0.093 and 0.092, respectively. Validation results for July 2013 indicated that the inversion accurately reflected the actual soil moisture conditions, effectively capturing dynamic moisture changes. These results fully verify the reliability and practicability of the model. These findings introduce a novel approach to local agricultural soil moisture estimation, with significant implications for enhancing agricultural water resource management and decision-making processes.

Meniscus is an important structure within the knee to maintain stability and load gravity distribution. Compared with meniscectomy, timely meniscal repair can reduce the risk of knee regression and laxity. Various methods have been studied to repair the meniscus. Among them, the outside-in technique is appropriate to repair anterior and middle segments of the meniscus. A number of modifications of this technique have been described in previous literatures. However, it still has disadvantages, such as complex intra-articular maneuvers, requiring extra devices sometimes. Therefore, we have developed the modified outside-in technique using thin steel wire to introduce the suture from the outside to the inside and then to the outside. We then make a knot outside the capsule. The advantages of our technique are that it is easy to perform, is reproducible, and avoids making multiple intra-articular suture loops.

Resource utilization of tail vegetables has raised increasing concerns in the modern agriculture. However, the effect and related mechanisms of flue-cured tobacco leaves on the product quality, phytotoxicity and bacterially-mediated nitrogen (N) transformation process of tail vegetable composting were poorly understood. Amendments of high-dosed (5% and 10% w/w) tobacco leaves into the compost accelerated the heating process, prolonged the time of thermophilic stage, increased the peak temperature, thereby improving maturity and shortening composting duration. The tobacco leaf amendments at the 10% (w/w) increased the N conservation (TN and NH4-N content) of compost, due to the supply of N-containing nutrient and promotion of organic matter degradation by tobacco leaves. Besides, tobacco leaf amendments promoted the seed germination and root development of wild soybean, exhibiting the feasibility of composting product for promoting the growth of salt-tolerant plants, but no dose-dependent effect was found for tobacco leaf amendments. Addition of high dosed (5% and 10% w/w) tobacco leaves shifted the bacterial community towards lignocellulosic and N-fixing bacteria, contributing to increasing the compost maturity and N retention. PICRUSt 2 functional prediction revealed that N-related bacterial metabolism (i.e., hydroxylamine oxidation and denitrifying process) was enhanced in the tobacco leaf treatments, which contributed to N retention and elevated nutrient quality of composting. To the best knowledge, this was the first study to explore the effect of tobacco waste additives on the nutrient transformation and halophyte growth promotion of organic waste composting. These findings will deepen the understanding of microbially-mediated N transformation and composting processes involving flue-cured tobacco leaves.

ObjectiveIdentifying the status of caring behavior and its influencing factors in nurses is crucial for improving the quality of care for patients. However, there is a lack of studies on this in Sierra Leone. This study explored the status of caring behavior and associated factors in nurses working in Sierra Leone.Study designA cross-sectional descriptive survey was conducted from October 3 to December 15, 2022, with clinical nurses recruited through convenience sampling.MethodsThe participants included 360 nurses from various nursing departments from 12 hospitals in Sierra Leone. Measurements included a general information questionnaire, the Caring Behavior Inventory, Connor-Davidson Resilience Scale, McCloskey/Mueller Satisfaction Scale and Zung’s Self-Rating Anxiety Scale. Descriptive statistics, one-way analysis of variance and independent-sample t-tests, Pearson’s correlation analyses, and multiple regression analyses were performed.ResultsCaring behavior score was 128.97 (SD 11.967); it significantly and positively correlated with job satisfaction and resilience and negatively correlated with anxiety. Linear regression analysis showed that resilience, job satisfaction, anxiety, daily working time, and position were the main predictors of caring behavior.ConclusionThe level of caring behavior in nurses in Sierra Leone was moderate. Resilience and job satisfaction significantly and positively predicted nurses’ caring behavior. Anxiety, daily working time, and position are important factors of caring behaviors.Implications for practiceIt is suggested to create a conducive working environment, reduce the excessive workload of nurses, enhance their positive psychological state, and their job satisfaction by providing recognition and rewards to improve the level of nurses’ caring behavior.

Summary: Metabolic reprogramming is crucial for activating innate immunity in macrophages, and the accumulation of immunometabolites is essential for effective defense against infection. The NAD+/NADH (ratio of nicotinamide adenine dinucleotide and its reduced counterpart) redox couple serves as a critical node that integrates metabolic pathways and signaling events, but how this metabolite couple engages macrophage activation remains unclear. Here, we show that the NAD+/NADH ratio serves as a molecular signal that regulates proinflammatory responses and type I interferon (IFN) responses divergently. Salmonella Typhimurium infection leads to a decreased NAD+/NADH ratio by inducing the accumulation of NADH. Further investigation shows that an increased NAD+/NADH ratio correlates with attenuated proinflammatory responses and enhanced type I IFN responses. Conversely, a decreased NAD+/NADH ratio is linked to intensified proinflammatory responses and restrained type I IFN responses. These results show that the NAD+/NADH ratio is an essential cell-intrinsic factor that orchestrates innate immunity, which enhances our understanding of how metabolites fine-tune innate immunity.

With the wide application of the Internet of Things (IoT), storing large amounts of IoT data and protecting data privacy has become a meaningful issue. In general, the access control mechanism is used to prevent illegal users from accessing private data. However, traditional data access control schemes face some non-ignorable problems, such as only supporting coarse-grained access control, the risk of centralization, and high trust issues. In this paper, an attribute-based data access control scheme using blockchain technology is proposed. To address these problems, attribute-based encryption (ABE) has become a promising solution for encrypted data access control. Firstly, we utilize blockchain technology to construct a decentralized access control scheme, which can grant data access with transparency and traceability. Furthermore, our scheme also guarantees the privacy of policies and attributes on the blockchain network. Secondly, we optimize an ABE scheme, which makes the size of system parameters smaller and improves the efficiency of algorithms. These optimizations enable our proposed scheme supports large attribute universe requirements in IoT environments. Thirdly, to prohibit attribute impersonation and attribute replay attacks, we design a challenge-response mechanism to verify the ownership of attributes. Finally, we evaluate the security and performance of the scheme. And comparisons with other related schemes show the advantages of our proposed scheme. Compared to existing schemes, our scheme has more comprehensive advantages, such as supporting a large universe, full security, expressive policy, and policy hiding.

The naked mole rat (NMR), Heterocephalus glaber, is known as the longest-lived rodent and is extraordinarily resistant to hypoxia and cancer. Here, both NMR embryonic fibroblasts (NEFs) and their mouse counterparts (MEFs) were subjected to anoxic conditions (0% O2, 5% CO2). A combination of comparative transcriptomics and proteomics was then employed to identify differentially expressed genes (DEGs). Notably, we observed distinct levels of histone H1.2 (encoded by HIST1H1C) accumulation between NEFs and MEFs. Subsequent mechanistic analyses showed that higher H1.2 expression in NEFs was associated with the lower expression of its inhibitor, PARP1. Additionally, we discovered that H1.2 can directly interact with HIF-1α PAS domains, thereby promoting the expression of HIF-1α through facilitating the dimerization with HIF-1β. The overexpression of H1.2 was also found to trigger autophagy and to suppress the migration of cancer cells, as well as the formation of xenograft tumors, via the NRF2/P62 signaling pathway. Moreover, an engineered H1.2 knock-in mouse model exhibited significantly extended survival in hypoxic conditions (4% O2) and showed a reduced rate of tumor formation. Collectively, our results indicate a potential mechanistic link between H1.2 and the dual phenomena of anoxic adaptation and cancer resistance.

PurposeWith the rapid advancement of time-lapse culture and artificial intelligence (AI) technologies for embryo screening, pregnancy rates in assisted reproductive technology (ART) have significantly improved. However, clinical pregnancy rates in fresh cycles remain dependent on the number and type of embryos transferred. The selection of embryos with the highest implantation potential is critical for embryologists and influences transfer strategies in fertility centers. The superiority of AI over traditional morphological scoring for ranking cleavage-stage embryos based on their implantation potential remains controversial.MethodsThis retrospective study analyzed 105 fresh embryo transfer cycles at the Centre for Reproductive Medicine from August 2023 to March 2024, following IVF/ICSI treatment at the cleavage stage. All embryos were cultured using time-lapse technology and scored using an automated AI model (iDAScore V2.0). Embryos were categorized into three groups based on the iDAScore V2.0: Group A (8 cells, iDA: 1.0-5.7); Group B (8 cells, iDA: 5.8-8.0); and Group C (>8 cells, iDA: 5.8-8.0). Clinical treatment outcomes, embryonic development, and pregnancy outcomes were analyzed and compared across the groups.ResultsBaseline characteristics such as patient age, AMH levels, AFC, and basal sex hormones showed no significant differences among the three groups (p > 0.05). The iDAscores were significantly higher in Group C (7.3 ± 0.5) compared to Group B (6.7 ± 0.5) and the iDAscores were significantly higher in Group B (6.7 ± 0.5) compared to Group A (4.8 ± 1.0) (p < 0.001).The mean number of high-quality embryos was highest in Group C (4.7 ± 3.0), followed by Group B (3.6 ± 1.7) and Group A (2.1 ± 1.2) (p < 0.001). There was no statistical difference (p = 0.392) in the ongoing pregnancy rate for single cleavage-stage transfers between Group B (54.5%, 30/55) and Group A (38.1%, 8/21), although there was a tendency for Group B to be higher.ConclusionCombining time-lapse culture with AI scoring may enhance ongoing pregnancy rates in single cleavage-stage fresh transfer cycles.

BackgroundMycoplasma pneumoniae pneumonia (MPP) is a prevalent respiratory infectious disease in children. Given the increasing resistance of M. pneumoniae (MP) to macrolide antibiotics, the identification of new therapeutic agents is critical. Yinqin Qingfei granules (YQQFG), a Chinese patent medicine formulated specifically for pediatric MPP, lacks a clear explanation of its mechanism.MethodsThe primary components of YQQFG were identified using LC-MS/MS. In vitro, RAW264.7 cells infected with MP underwent morphological examination via scanning electron microscopy. Drug-containing serum was prepared, and its intervention concentration was determined using the CCK-8 assay. The active components of YQQFG were molecularly docked with NLRP3 protein using Autodock Vina software. A RAW264.7 cell line overexpressing NLRP3 was created using lentivirus to pinpoint the target of YQQFG. In vivo, MPP model mice were established via nasal instillation of MP. Lung damage was assessed by lung index and H&E staining. Pyroptosis-associated protein levels in cells and lung tissue were measured by western blot, while interleukin (IL)-1β and IL-18 levels in cell supernatants and mouse serum were quantified using ELISA. Immunofluorescence double staining of lung tissue sections was conducted to assess the correlation between NLRP3 protein expression and macrophages. The expression of the community-acquired respiratory distress syndrome toxin (CARDS TX) was evaluated by qPCR.Results25 effective components with favorable oral bioavailability were identified in YQQFG. Both in vitro and in vivo studies demonstrated that YQQFG substantially reduced the expression of the NLRP3/Caspase-1/GSDMD pathway, decreasing the release of IL-1β and IL-18, and inhibited MP exotoxin. Molecular docking indicated strong affinity between most YQQFG components and NLRP3 protein. Lentivirus transfection and immunofluorescence double staining confirmed that YQQFG significantly suppressed NLRP3 expression in macrophages, outperforming azithromycin (AZM). The combination of YQQFG and AZM yielded the optimal therapeutic effect for MPP.ConclusionYQQFG mitigates inflammatory responses by suppressing NLRP3 inflammasome-mediated macrophage pyroptosis, thereby ameliorating MP-induced acute lung injury. YQQFG serves as an effective adjunct and alternative medication for pediatric MPP treatment.

This paper presents the results, insights and challenges of a small-scale laboratory implementation of a virtual storage plant (VSP) and the distributed control of its portfolio for frequency restoration services. The proposed framework has been experimentally validated using a controller-hardware-in-the-loop setup consisting of 5 battery storage systems, a hydraulic turbine-generator and a real-time digital simulator. The results show that the performance of the VSP whose assets are controlled by the proposed framework is compliant with the grid code requirements regarding manual and automatic frequency restoration service. Furthermore, this paper reveals novel insight into the practical implementation challenges of consensus-based distributed control due to time delays and communication synchronization.

The present study involves the preparation of continuous carbon fiber samples treated with epoxy-based sizing agent (EP) and vinyl ester resin-based sizing agent (VE), alongside untreated fibers, aiming to explore the influence pattern of interfacial differences caused by these sizing agents on the compressive properties of carbon fiber composites. Surface analysis, including Scanning Electron Microscope (SEM), Atomic Force Microscope (AFM), and X-ray Photoelectron Spectroscopy (XPS), followed by testing the mechanical properties of carbon fibers and the composite materials. Results indicate that, compared to unsized carbon fibers, EP and VE increase the O atom content on the carbon fiber surface by 13.0% and 18.1%, respectively, and enhance the proportion of active C atoms by 11.3% and 20.3%, respectively. The interlaminar shear strength (GB/T) of carbon fibers is improved by 9.3% and 20.0%, respectively. Given the compatibility between the sizing agent and the matrix resin, VE improves the open-hole compressive strength of composites by 6.7% compared to EP. This improvement in interface bonding performance positively impacts the open-hole compressive properties of the composites, though it has limited effect on the 0° compressive and post-impact compressive strengths. Following EP and VE sizing, the 0° compressive strength increases by 11.8% and 13.6%, respectively, with VE only resulting in a marginal 1.6% improvement over EP. The enhancements in both interlaminar shear strength and open-hole compressive strength are attributed to the increased number of active functional groups at the fiber-resin interface, facilitated by sizing agents, which promote stronger chemical bonding and thus improved load transfer between the fibers and the matrix. VE demonstrates superior performance over EP in regulating the interface state of carbon fibers.The presence or absence of a sizing agent has a more significant impact on the compressive properties of carbon fiber composites than the type of sizing agent used. These findings provide valuable insights for optimizing the preparation and enhancing the compressive performance of carbon fiber composite materials.

IntroductionEnterobacter chengduensis was defined as a novel species in the genus. Enterobacter in 2019, however, antimicrobial resistance, such as carbapenem resistance, has rarely been described in E. chengduensis. This study described the molecular features of four carbapenem-resistant E. chengduensis strains collected from a tertiary health care hospital in Southwest China.MethodsWhole genome sequencing (WGS) was used to determine the genome sequence of four E. chengduensis strains. The precise species of strains were identified by average nucleotide identity (ANI) and in silico DNA-DNA hybridization (isDDH). The clonal relatedness of four E. chengduensis strains and additional 15 ones from NCBI were examined through phylogenetic analysis. The molecular features of E. chengduensis and genetic structure of carbapenemase- encoding plasmids were characterized through genomic annotation and analysis.ResultsThe results revealed the emergence of blaNDM–1-carrying E. chengduensis strains in China. Multilocus sequence typing (MLST) analysis showed that all 19 E. chengduensis belonged to the same sequence type of ST414. Core SNP analysis suggested the potential intrahospital clonal transmission of ST414 E. chengduensis. The carbapenemase-encoding gene blaNDM–1 was harbored by an IncC-type plasmid, which was experimentally confirmed to be able to conjugate.DiscussionThis study reports the first emergence and potential clonal transmission of blaNDM–1-carrying E. chengduensis. Further surveillance should be advocated to monitor the dissemination of carbapenem-resistant E. chengduensis and blaNDM–1-harboring IncC-type plasmids in China.

The thin film composite (TFC) membrane possesses the highest commercial application potential among all types of forward osmosis (FO) membranes. The support layer of the membrane plays a crucial role in both bearing mechanical loads and facilitating the active layer formation. Herein, we addressed the issues of low permeability and poor mechanical strength of the conventional TFC FO membrane by selecting suitable fabrics and optimizing membrane design and preparation. Polyester (PS) woven fabric, with its high strength, low thickness, and high porosity, served as an excellent material for reinforcing the strength of the FO membrane. We employed a novel double-blade casting method to address the defect issue associated with the conventional single-blade casting method. The influencing factors and quality control strategies of the fabric-reinforced substrate were systematically investigated. Furthermore, membrane characterization techniques, including scanning electron microscopy (SEM), liquid-liquid displacement porometer, and cross-flow FO system, were used to reveal the influences of different substrates, including polysulfone (PSU), polyacrylonitrile (PAN), and polyetherimide (PEI), on the structure and performance of the fabric-reinforced TFC-FO membrane. Compared to commercial FO membranes, the TFC/PSU membrane exhibited superior FO performance, with a water flux of 24.1 LMH, and outstanding mechanical strength that was more than 10-times higher than that of free-standing membranes. This study demonstrates a new pathway for engineering robust TFC-FO membranes with low structural parameters as well as excellent scalability of the membrane fabrication method.

IntroductionSelenium (Se) plays a vital role in various physiological processes in plants and is regarded as an essential micronutrient for human health as well.MethodsIn this study, sodium selenite solution at 10, 40, 70, and 100 mg·L-1 concentrations was foliar sprayed, and the strawberry plant growth, antioxidant system, and fruit quality with an emphasis on sugar and acid content were assessed.ResultsThe results showed that 10 mg·L-1 of sodium selenite treatment promoted plant growth, while all the treated concentrations could enhance photosynthesis, the antioxidant system in leaves, the content of Se, and ascorbic acid in fruits. More importantly, 40 mg·L-1 sodium selenite treatment significantly increased fruit weight, total soluble solid, total phenolic content, and anthocyanins, as well as improved the shape index. Furthermore, it decreased the total flavonoid and proanthocyanidin content. Particularly, sodium selenite treatment at 40 and 70 mg·L-1 largely increased the ratio of soluble sugars to titratable acid. The changes of predominant sugars and organic acids during fruit development were further investigated. The sucrose, fructose, and glucose content was upregulated by sodium selenite treatment through upregulating the activities of sucrose phosphate synthase (SPS) and acid invertase, as well as the FaSPS expression. In addition, sodium selenite treatment inhibited the activity of citrate synthase and phosphoenolpyruvate carboxylase, rather than modulating their transcript levels to reduce the citric acid content.ConclusionsThis work presented a potentially efficient approach to enhance plant growth and fruit quality and supplement Se in strawberry, providing insights into the mechanism of regulating sugar and acid metabolism by Se.

Pure large-cell neuroendocrine carcinomas of the ovary are extremely rare, so there is a lack of molecular information on this type of cancer. Herein, we presented a pure primary large-cell neuroendocrine carcinomas of the ovary in a 72-year-old female with a pathogenic somatic mutation at the c.5332+1g>a splice site of the BRCA1 gene and with no TP53 mutation. She was uneventful 32 months after the operation and chemotherapies. To the best of our knowledge, this is the first report of a BRCA1 somatic mutation in the ovary large-cell neuroendocrine carcinomas. Testing BRCA1/2 mutations in patients with large ovarian cell neuroendocrine carcinomas might provide an opportunity for their future target treatments. It would expand our understanding.

In the face of various risks and uncertainties including political instability, technological advancements, and natural disasters, businesses involved in cross-market activities are encountering a more competitive environment. This study investigates the relationship between competitive intensity, business intelligence, internal process efficiency, and the performance of small and medium-sized manufacturing enterprises in China. By incorporating the Technology-Organization-Environment (TOE) framework and Dynamic Capabilities Theory, a research model is developed to demonstrate that competitive intensity improves firms’ performance through the utilization of business intelligence capabilities and internal process efficiency. Through the use of a structural equation model, data collected from 15 industrial parks in Henan province, China, involving 429 participants, was analyzed. The findings show a positive correlation between competitive intensity and business intelligence sensing capability (both internal and external). The impact of business intelligence sensing capability on the performance of small and medium-sized manufacturing enterprises is shown to be mediated through internal process efficiency. Our study reveals the mediating roles of business intelligence capability and internal process efficiency in improving organizational performance among Chinese small and medium-sized manufacturing enterprises. This research not only fills gaps in business intelligence research from a management perspective but also contributes to the literature on the interactions among competitive intensity, business intelligence, internal processes, and organizational performance. It also sheds light on the relationship between competitive intensity and organizational performance, offering insights for companies involved in cross-market activities. By highlighting the importance of business intelligence capabilities in adapting to environmental influences, this study offers practical guidance for enterprise digital transformation efforts.

The article proposes an optimization algorithm using a hierarchical environment selection strategyto solve the deficiencies of current multimodal multi-objective optimization algorithms in obtaining the completeness and convergence of Pareto optimal Sets (PSs). Firstly, the algorithm in this article is framed by a differential evolutionary algorithm (DE) and uses a special crowding distance to design a neighborhood-based individual variation strategy, which also ensures the diversity, and then special crowding distance is used to help populations with non-dominated sorting. In the stage of environmental selection, a strategy of hierarchical selection of individuals was designed, which selects sorted non-dominant ranked individual layer by layer according to the ratio, which allows potential individuals tobe explored. Finally, in the stage of evolution of individuals, the convergence and diversity of populations were investigated, anddifferent mutation strategies were selectedaccording to the characteristics of individuals. DE reproduction strategies are used for iteration, preventing individuals from avoiding premature convergence and ensuring the algorithm’s searchability. These strategies help the algorithm to obtain more diverse and uniformly distributed PSs and Pareto Front (PF). The algorithm of this article compares with several other excellent algorithms on 13 test problems, and the test results show that all the algorithms of this article exhibit superior performance.

Reporta-se este trabalho a um dicionário manuscrito de português-chinês datável do século XVIII, um códice inédito da Biblioteca Nacional de Portugal cuja edição preparámos nos últimos anos, no qual foram incluídas numerosas entradas relativas a mandarins, bem como equivalentes chineses específicos para os mesmos. Este conjunto de verbetes é muito informativo quanto ao que se considerava ser o mandarim, aos seus vários tipos, procedimentos, carreiras, utensílios, privilégios, família, etc., em muitos casos merecendo palavra própria, exclusiva do mandarim, ou de classes iguais ou mais elevadas. A comparação com as obras lexicográficas e gramaticais de Joaquim Afonso Gonçalves revela um curioso desaparecimento deste tipo de informação logo no século seguinte, podendo o próprio termo mandarim ser ignorado em benefício de outros tão opacos e gerais como empregado, ou sinónimos menos precisos que parecem ter servido para evitar o uso daquele lexema, como ministro e magistrado.

Abstract Wearable sensors hold immense potential for real‐time and non‐destructive sensing of volatile organic compounds (VOCs), requiring both efficient sensing performance and robust mechanical properties. However, conventional colorimetric sensor arrays, acting as artificial olfactory systems for highly selective VOC profiling, often fail to meet these requirements simultaneously. Here, a high‐performance wearable sensor array for VOC visual detection is proposed by extrusion printing of hybrid inks containing surface‐functionalized sensing materials. Surface‐modified hydrophobic polydimethylsiloxane (PDMS) improves the humidity resistance and VOC sensitivity of PDMS‐coated dye/metal‐organic frameworks (MOFs) composites. It also enhances their dispersion within liquid PDMS matrix, thereby promoting the hybrid liquid as high‐quality extrusion‐printing inks. The inks enable direct and precise printing on diverse substrates, forming a uniform and high particle‐loading (70 wt%) film. The printed film on a flexible PDMS substrate demonstrates satisfactory flexibility and stretchability while retaining excellent sensing performance from dye/MOFs@PDMS particles. Further, the printed sensor array exhibits enhanced sensitivity to sub‐ppm VOC levels, remarkable resistance to high relative humidity (RH) of 90%, and the differentiation ability for eight distinct VOCs. Finally, the wearable sensor proves practical by in situ monitoring of wheat scab‐related VOC biomarkers. This study presents a versatile strategy for designing effective wearable gas sensors with widespread applications.

In the present paper, we further study the asymptotical behavior of the following higher order nonlinear difference equation \begin{equation*} x(n+1)= ax(n)+ bf( x(n)) + cf(x(n-k)), \qquad n=0, 1, \dots \end{equation*} where $a, b $ and $c$ are constants with $00$ for $x>0$, and $k$ is a positive integer, which has been recently studied in: On global attractivity of a higher order difference equation and its applications [Electron. J. Qual. Theory Diff. Equ. 2022, No. 2, 1–14]. We obtain some new sufficient conditions for the global attractivity of positive solutions of the equation, and show the applications of these results to some population models.

Abstract Background Bacterial wilt caused by Ralstonia solanacearum severely affects peanut (Arachis hypogaea L.) yields. The breeding of resistant cultivars is an efficient means of controlling plant diseases. Therefore, identification of resistance genes effective against bacterial wilt is a matter of urgency. The lack of a reference genome for a resistant genotype severely hinders the process of identification of resistance genes in peanut. In addition, limited information is available on disease resistance-related pathways in peanut. Results Full-length transcriptome data were used to generate wilt-resistant and -susceptible transcript pools. In total, 253,869 transcripts were retained to form a reference transcriptome for RNA-sequencing data analysis. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of differentially expressed genes revealed the plant-pathogen interaction pathway to be the main resistance-related pathway for peanut to prevent bacterial invasion and calcium plays an important role in this pathway. Glutathione metabolism was enriched in wilt-susceptible genotypes, which would promote glutathione synthesis in the early stages of pathogen invasion. Based on our previous quantitative trait locus (QTL) mapping results, the genes arahy.V6I7WA and arahy.MXY2PU, which encode nucleotide-binding site-leucine-rich repeat receptor proteins, were indicated to be associated with resistance to bacterial wilt. Conclusions This study identified several pathways associated with resistance to bacterial wilt and identified candidate genes for bacterial wilt resistance in a major QTL region. These findings lay a foundation for investigation of the mechanism of resistance to bacterial wilt in peanut.

Abstract Owing to the specific electronic-redistribution and spatial proximity, diatomic catalysts (DACs) have been identified as principal interest for efficient photoconversion of CO2 into C2H4. However, the predominant bottom-up strategy for DACs synthesis has critically constrained the development of highly ordered DACs due to the random distribution of heteronuclear atoms, which hinders the optimization of catalytic performance and the exploration of actual reaction mechanism. Here, an up-bottom ion-cutting architecture is proposed to fabricate the well-defined DACs, and the superior spatial proximity of CuAu diatomics (DAs) decorated TiO2 (CuAu-DAs-TiO2) is successfully constructed due to the compact heteroatomic spacing (2-3 Å). Owing to the profoundly low C-C coupling energy barrier of CuAu-DAs-TiO2, a considerable C2H4 production with superior sustainability is achieved. Our discovery inspires a novel up-bottom strategy for the fabrication of well-defined DACs to motivate optimization of catalytic performance and distinct deduction of heteroatom synergistically catalytic mechanism.

Abstract There have been reports of long coronavirus disease (long COVID) and breakthrough infections (BTIs); however, the mechanisms and pathological features of long COVID after Omicron BTIs remain unclear. Assessing long-term effects of COVID-19 and immune recovery after Omicron BTIs is crucial for understanding the disease and managing new-generation vaccines. Here, we followed up mild BA.2 BTI convalescents for six-month with routine blood tests, proteomic analysis and single-cell RNA sequencing (scRNA-seq). We found that major organs exhibited ephemeral dysfunction and recovered to normal in approximately six-month after BA.2 BTI. We also observed durable and potent levels of neutralizing antibodies against major circulating sub-variants, indicating that hybrid humoral immunity stays active. However, platelets may take longer to recover based on proteomic analyses, which also shows coagulation disorder and an imbalance between anti-pathogen immunity and metabolism six-month after BA.2 BTI. The immunity-metabolism imbalance was then confirmed with retrospective analysis of abnormal levels of hormones, low blood glucose level and coagulation profile. The long-term malfunctional coagulation and imbalance in the material metabolism and immunity may contribute to the development of long COVID and act as useful indicator for assessing recovery and the long-term impacts after Omicron sub-variant BTIs.

Abstract Background China was the last country in the world to relax COVID-19 restrictions. A successful public health policy requires public support. This analysis examined the factors associated with Chinese support for zero-COVID and relaxing COVID-19 restrictions in China. Method Two online surveys were conducted among Chinese participants in mainland China on June 10–13 (N = 460) and December 2, 2022 (N = 450). These two samples were similar based on the participants’ demographics. Results The results revealed that the perceived health consequences of a COVID-19 policy, perceived norms of approving a COVID-19 policy, and hope positively predicted the participants’ support for the COVID-19 policy. The results further showed that collectivism and fatalism positively predicted support for zero-COVID and negatively predicted support for relaxing restrictions. COVID fatigue was negatively associated with support for zero-COVID and positively associated with support for relaxing restrictions. Liberty positively predicted support for relaxing restrictions in June and negatively predicted zero-COVID in December 2023. It did not positively or negatively predict support for the policy adopted by the government. Conclusion Collectivism, liberty, COVID fatigue, and fatalistic beliefs are important considerations connected to public support for a COVID-19 policy. The role of liberty was more nuanced and depended on the survey’s time and whether the government adopted the policy.

Abstract In this study, we aimed to understand the potential role of the gut microbiome in the development of Alzheimer's disease (AD). We took a multi-faceted approach to investigate this relationship. Urine metabolomics were examined in individuals with AD and controls, revealing decreased formate and fumarate concentrations in AD. Additionally, we utilised whole-genome sequencing (WGS) data obtained from a separate group of individuals with AD and controls. This information allowed us to create and investigate host-microbiome personalised whole-body metabolic models. We predicted microbial formate as well as other microbial metabolites, which could alter urine formate production in the host-microbiome personalised models. Additionally, we identified specific reactions responsible for the production of formate in the host, and interestingly, these reactions were linked to genes that have correlations with AD. This study suggests formate as a possible early AD marker and highlights genetic and microbiome contributions to its production. The reduced formate secretion and its genetic associations point to a complex connection between gut microbiota and AD. This holistic understanding might pave the way for novel diagnostic and therapeutic avenues in AD management.

Abstract Dynamic luminescence behavior by external stimuli, such as light, thermal field, electricity, mechanical force, etc., endows the materials with great promise in optoelectronic applications. Upon thermal stimulus, the emission is inevitably quenched due to intensive non-radiative transition, especially for phosphorescence at high temperature. Herein, we report an abnormal thermally-stimulated phosphorescence behavior in a series of organic phosphors. As temperature changes from 198 to 343 K, the phosphorescence at around 479 nm gradually enhances for the model phosphor, of which the phosphorescent colors are tuned from yellow to cyan-blue. Furthermore, we demonstrate the potential applications of such dynamic emission for smart dyes and colorful afterglow displays. Our results would initiate the exploration of dynamic high-temperature phosphorescence for applications in smart optoelectronics. This finding not only contributes to an in-depth understanding of the thermally-stimulated phosphorescence, but also paves the way toward the development of smart materials for applications in optoelectronics.

Abstract Background Whether perceived stress is associated with loneliness and depressive symptoms in general adults, and to what extent sleep quality mediates the associations, remains unknown. The aim of this study was to estimate the associations of perceived stress with loneliness and depressive symptoms, and the mediating role of sleep quality in these associations. Methods Cross-sectional data on 734 participants (aged 18–87 years) were analyzed. Perceived stress was assessed using the 10-item Perceived Stress Scale (PSS-10; range 0–40). Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI; range 0–21). Loneliness was assessed using the three-item short form of the Revised University of California, Los Angeles (UCLA) loneliness scale (range 3–9). Depressive symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression (CESD-10) Scale (range 0–30). General linear regression models, multivariable logistic regression models, and formal mediation analysis were performed. Results After adjustment for age and sex, we found that with each 1-point increment in the perceived stress score, both the loneliness score (β = 0.07; 95% confidence interval [CI]: 0.06, 0.08) and depression score (β = 0.45; 95% CI: 0.40, 0.49) increased significantly. Robust results were observed when adjusting for more confounders. Furthermore, sleep quality mediated 5.3% (95% CI: 1.3%, 10.0%; P = 0.014) and 9.7% (95% CI: 6.2%, 14.0%; P

Abstract Ground subsidence in Western coal mining areas is characterized by rapid deformation, extensive damage, and a wide range of impacts. The conventional observation methods are inappropriate for surface damage monitoring in high-intensity mining areas of Western China. Therefore, it is a crucial problem to quickly, accurately, and comprehensively monitor the ground subsidence and environmental damage caused by high-intensity and large-scale mining. In this study, we propose a monitoring method for the ground subsidence of high-intensity mining with Unmanned Aerial Vehicle Lidar (UAV-LiDAR) measurement technology. Taking a mine in Ordos of China as an example, the Digital Elevation Model (DEM) is obtained by Kriging Interpolation of the ground point cloud from UAV-LiDAR. Then, the multi-stage DEM differential processing is employed to get ground subsidence. Finally, the median and bilateral filters combine for denoise to obtain the high-precision ground subsidence. The results show that the accuracy of the ground DEM generated by UAV-LiDAR is 15 mm and the mean square error of the ground subsidence basin is 39 mm. UAV-LiDAR technology can quickly obtain abundant surface data and obtain high-precision ground subsidence. Therefore, the application of this technology and method in subsidence monitoring in mining areas is feasible. And it can provide support for ecological environment monitoring, land reclamation, and ecological restoration in mining areas. The research results can provide a useful basis for monitoring the surface damage of coal mining in Western China.

Improving mechanical properties of solder alloy can result in a decrease of its conductivity. The decrease in conductivity of the solder increases the generation of Joule heat and reduces the reliability of the joint. This problem can be solved by adjusting the solidification parameters of solders. In this paper, the effect of the growth rate (V) on the microstructure evolution, microhardness and electrical conductivity of directionally solidified (DS) Sn-0.7Cu-xCo (x = 0.5, 1.0, 1.5, 2.0, mass %) alloys was investigated. The Sn-0.7Cu-xCo alloys consists of a Sn-based solid solution (Sn-ss), Cu6Sn5 phase, and CoSn2 phase. The volume fraction of the CoSn2 phase increases with increasing Co content. In the DS specimen, the CoSn2 phases change from block-shaped to a long strip shape with a long axis direction close to the heat flow direction. With increasing V, the growth direction tends to become disordered due to the weakening of the heat flow effect. The microhardness of DS Sn-0.7Cu-xCo alloys increases with increasing V due to an increase of solution strengthening effect. The microhardness of DS Sn-0.7Cu-xCo alloys increases with increasing Co content under the same V. The conductivity of the DS Sn-0.7Cu-xCo alloys decreases with increasing V. The conductivity of the DS Sn-0.7Cu-xCo alloy is even better than that of the as-cast Sn-0.7Cu alloy when V ≤ 20 μm/s. The findings in the research provide a new way to improve the strength of solder without reducing its conductivity.

Abstract The limited differentiation ability of adipose-derived stem cells (ADSCs) limits their application in stem cell therapy and regenerative medicine. Here, we explore the molecular mechanism by which miR-204-5p regulates ADSCs differentiation into cells derived from the three germ layers (i.e., adipocytes, neurocytes, and hepatocytes). Although miR-204-5p overexpression inhibited ADSCs differentiation into adipocytes, neurocyte and hepatocyte differentiation were promoted. Mechanistically, miR-204-5p inhibited the expression of PPARG by regulating the AMPK signaling pathway, thereby inhibiting ADSCs differentiation into adipocytes. Further, miR-204-5p regulated JAG1/NOTCH3 axis for the inhibition of differentiation into adipocytes and promotion of differentiation into neurocytes. miR-204-5p might also promote ADSCs differentiation into hepatocytes by upregulating E2F8. The findings of this study provide novel insights into the regulatory mechanisms underlying early embryonic development and will help to facilitate the application of ADSCs in stem cell therapy and regenerative medicine.

Abstract Facing to a planar tracking problem, a multiple-interpretable improved Proximal Policy Optimization (PPO) algorithm with few-shot technique is proposed, namely F-GBQ-PPO. Compared with the normal PPO, the main improvements of F-GBQ-PPO are to increase the interpretability, and reduce the consumption for real interaction samples. Considering to increase incomprehensibility of a tracking policy, three levels of interpretabilities has been studied, including the perceptual, logical and mathematical interpretabilities. Detailly speaking, it is realized through introducing a guided policy based on Apollonius circle, a hybrid exploration policy based on biological motions, and the update of external parameters based on quantum genetic algorithm. Besides, to deal with the potential lack of real interaction samples in real applications, a few-shot technique is contained in the algorithm, which mainly generate fake samples through a multi-dimension Gaussian process. By mixing fake samples with real ones in a certain proportion, the demand for real samples can be reduced.

As the basic protective element, steel plate had attracted world-wide attention because of frequent threats of explosive loads. This paper reports the relationships between microscopic defects of Q345 steel plate under the explosive load and its macroscopic dynamics simulation. Firstly, the defect characteristics of the steel plate were investigated by stereoscopic microscope (SM) and scanning electron microscope (SEM). At the macroscopic level, the defect was the formation of cave which was concentrated in the range of 0–3.0 cm from the explosion center, while at the microscopic level, the cavity and void formation were the typical damage characteristics. It also explains that the difference in defect morphology at different positions was the combining results of high temperature and high pressure. Secondly, the variation rules of mechanical properties of steel plate under explosive load were studied. The Arbitrary Lagrange-Euler (ALE) algorithm and multi-material fluid-structure coupling method were used to simulate the explosion process of steel plate. The accuracy of the method was verified by comparing the deformation of the simulation results with the experimental results, the pressure and stress at different positions on the surface of the steel plate were obtained. The simulation results indicated that the critical pressure causing the plate defects may be approximately 2.01 GPa. On this basis, it was found that the variation rules of surface pressure and microscopic defect area of the Q345 steel plate were strikingly similar, and the corresponding mathematical relationship between them was established. Compared with Monomolecular growth fitting models (MGFM) and Logistic fitting models (LFM), the relationship can be better expressed by cubic polynomial fitting model (CPFM). This paper illustrated that the explosive defect characteristics of metal plate at the microscopic level can be explored by analyzing its macroscopic dynamic mechanical response.

Objective: Bentall procedure used to be standard operation for involved aortic root in acute type A aortic dissection (ATAAD). But aortic root repair for preserving valve is still controversial in ATAAD. This study aimed to evaluate the midterm outcomes of aortic root repair by comparing with Bentall approach. Methods: A retrospective analysis of 1075 ATAAD patients with aortic root involvement was conducted. The patients were divided into aortic root repair group (n = 447) and Bentall group (n = 628). The propensity score matching analysis (PSMA) was used to adjust the baseline. Results: The median follow-up was 44 months (interquartile range, 17–65 months; range, 1–130 months). The 30-day mortality in the repair and replacement groups was 15.0 % and 12.9 % (P = 0.327) respectively; the late overall mortality was 15.9 % and 14.0 % (P = 0.394) respectively. The Kaplan-Meier 10-year survival and free-from-reoperation was 86.0 % and 92.5 % respectively in the repair group. After PSMA, the cumulative survival rate [Hazard Ratio (HR) 0.685; 95 % Confidence Interval (CI) 0.457–1.027; P = 0.747]) and reoperation rate (HR 0.308; 95 % CI 0.070–1.355; P = 0.157) was not significantly higher in the repair group than in the Bentall group. Conclusion: The mid-term outcome of aortic root repair is probably not inferior to Bentall procedure. Therefore, root repair is an alternative approach in ATAAD with the advantage of preserving native valve.

In this paper, a single-generator aggregated model (SGAM) of a renewable power station (RPS) is derived for the quick especially simulation-based evaluation of small-signal stability. The common scenario that the generators in the station are of the same type and from the same supplier is considered. However, the steady-state operating points (SSOPs) of the generators and the network topology can be arbitrary. Based on the derivation results, by changing the SSOP of the generator in the aggregated model or the reactance of the connection line, SGAM of the RPS under different SSOPs and network topologies can be built. Thus, the SGAM is simple in utilization. In the meanwhile, efficiency of the small-signal stability evaluation of an RPS can be much improved when considering various SSOPs by using the SGAM. Furthermore, the derivations reveal the parameter relationship between the SGAM and the original station. Based on this, conclusions drawn about the small-signal stability of a single grid-connected generator can be developed to an RPS. Finally, effectiveness of the SGAM proposed in the small-signal stability analysis is examined and validated based on three example RPSs, including a PV station, a DFIG wind farm and a PMSG wind farm.

In visual object tracking, attention mechanisms can flexibly and efficiently handle complex dependencies and global information, which improves tracking accuracy. However, when dealing with scenarios that contain a large amount of background information or other complex information, its global attention ability can dilute the weight of important information, allocate unnecessary attention to background information, and thus reduce tracking performance. To relieve this problem, this paper proposes a visual object tracking framework based on a sparse transformer. Our tracking framework is a simple encoder-decoder structure that realizes the prediction of the target in an autoregressive manner, eliminating the additional head network and simplifying the tracking architecture. Furthermore, we introduce a Sparse Attention Mechanism (SMA) in the cross-attention layer of the decoder. Unlike traditional attention mechanisms, SMA focuses only on the top K pixel values that are most relevant to the current pixel when calculating attention weights. This allows the model to focus more on key information and improve foreground and background discrimination, resulting in more accurate and robust tracking. We conduct tests on six tracking benchmarks, and the experimental results prove the effectiveness of our method.

Ocean internal waves not only enhance ocean mixing and impact sediment resuspension, but also threaten the safety of marine engineering facilities and underwater navigation bodies. Therefore, the accurate detection and identification of ocean internal waves are crucial to ensure the safety of marine activities and optimize the development of marine resources. To improve the accuracy and efficiency of ocean internal wave identification, this paper proposes an automatic identification technique based on YOLOv7, which can quickly and accurately extract the signatures of ocean internal waves from a large amounts of SAR (Synthetic Aperture Radar) images, and realize the efficient identification of ocean internal waves. First, in this paper, dynamic snake convolution (DSConv) is introduced into the efficient layer aggregation network (ELAN) module of the backbone network, so that the network can adaptively focus on the irregular strip-like morphology of the ocean internal waves. In addition, large separable kernel attention (LSKA) is introduced in Conv_BN_SiLU (CBS) of the two downsampling modules in the neck network to capture a wider range of contextual information and enhance the feature fusion process of ocean internal waves. The experimental results show that the F1, (mean average precision) mAP50, and mAP50:95 of the improved YOLOv7 network model are 91.3%, 94.3%, and 59.1%, respectively, which are 5.3%, 2.7%, and 2.8% higher compared to the baseline model.

Abstract Purpose To investigate underlying co-mechanisms of PCOS and periodontitis through transcriptomic approach. Methods PCOS and periodontitis gene expression data were downloaded from the GEO database to identify differentially expressed genes. GO and KEGG pathway enrichment analysis and random forest algorithm were used to screen hub genes. GSEA analyzed the functions of hub genes. Correlations between hub genes and immune infiltration in two diseases were examined, constructing a TF-ceRNA regulatory network. Clinical samples were gathered from PCOS and periodontitis patients and RT-qPCR was performed to verify the connection. Results There were 1661 DEGs in PCOS and 701 DEGs in periodontitis. 66 intersected genes were involved and were enriched in immune and inflammation-related biological pathways. 40 common genes were selected from the PPI network. RF algorithm demonstrated that ACSL5, NLRP12, CCRL2, and CEACAM3 were hub genes, and GSEA results revealed their close relationship with antigen processing and presentation, and chemokine signaling pathway. RT-qPCR results confirmed the upregulated gene expression in both PCOS and periodontitis. Conclusion The 4 hub genes ACSL5, NLRP12, CCRL2, and CEACAM3 may be diagnostic genes for PCOS and periodontitis. The created ceRNA network could provide a molecular basis for future studies on the association between PCOS and periodontitis.