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Abstract The purpose of this study is to examine how economic development and stability are affected by carbon trading pilot programs. Using panel data from 31 Chinese provinces and autonomous regions between 2005 and 2021, two hypotheses were tested using the DID model. The findings indicate that (1) the carbon trading market pilot program has an immediate effect on economic stability. (2) High-quality economic development is positively and significantly impacted by the carbon trading market pilot program. Regional heterogeneity exists in the effects of carbon trading pilot programs on high-quality development and economic stability. The relationship between carbon trading pilot programs and economic development is not conclusive, despite the growing number of these policies. Given this, additional investigation into this connection is required. Understanding the results of carbon trading pilot programs can be used to gauge how successful these initiatives are. This research adds to the body of knowledge regarding the impact of the carbon trading pilot programs. It then makes policy recommendations that may serve as a guide for future “double carbon” research.

Abstract Background The prevalence of chronic kidney disease (CKD) is on the rise, posing a significant public health challenge. Although gut microbiome dysbiosis has been implicated in the impairment of kidney functions, the existence of pathological subtypes-linked differences remains largely unknown. We aimed to characterize the intestinal microbiota in patients with membranous nephropathy (MN), IgA nephropathy (IgAN), minimal change disease (MCD), and ischemic renal injury (IRI) in order to investigate the intricate relationship between intestinal microbiota and CKD across different subtypes. Methods We conducted a cross-sectional study involving 94 patients with various pathological patterns of CKD and 54 healthy controls (HCs). The clinical parameters were collected, and stool samples were obtained from each participant. Gut microbial features were analyzed using 16S rRNA sequencing and taxon annotation to compare the HC, CKD, MN, IgAN, MCD, and IRI groups. Results The CKD subjects exhibited significantly reduced alpha diversity, modified community structures, and disrupted microbial composition and potential functions compared to the control group. The opportunistic pathogen Klebsiella exhibited a significant enrichment in patients with CKD, whereas Akkermansia showed higher abundance in HCs. The study further revealed the presence of heterogeneity in intestinal microbial signatures across diverse CKD pathological types, including MN, IgAN, MCD, and IRI. The depression of the family Lachnospiraceae and the genus Bilophila was prominently observed exclusively in patients with MN, while suppressed Streptococcus was detected only in individuals with MCD, and a remarkable expansion of the genus Escherichia was uniquely found in cases of IRI. The study also encompassed the development of classifiers employing gut microbial diagnostic markers to accurately discriminate between distinct subtypes of CKD. Conclusions The dysregulation of gut microbiome was strongly correlated with CKD, exhibiting further specificity towards distinct pathological patterns. Our study emphasizes the significance of considering disease subtypes when assessing the impact of intestinal microbiota on the development, diagnosis, and treatment of CKD.

Abstract Background Academic resilience is a crucial concept for nursing students to cope with academic challenges. Currently, there is significant variation in the description of the concept attributes of academic resilience among nursing students, which impedes the advancement of academic research. Therefore, it is essential to establish a clear definition of the concept of academic resilience for nursing students. Purpose The purpose of this paper is to report the results of concept analysis of academic resilience of nursing students. Methods The Rodgers evolutionary concept analysis was employed to test the attributes, antecedents, consequences and related concepts of academic resilience of nursing students. Walker and Avant’s method was utilized to construct a model case and provide empirical referents. Results The findings indicate that the attributes of nursing students’ academic resilience include self-efficacy, self-regulation and recovery, and the antecedents include internal factors and external environmental factors. The consequences include adaptability, career maturity, adversity quotient level, probability of academic success, a sense of belonging to school and low levels of psychological distress. Conclusion The systematic understanding of academic resilience among nursing students provides a pathway for nursing educators and students to enhance academic resilience, promote academic success, and establish a foundation for the training of more qualified nurses.

Abstract Dielectric capacitors offer great potential for advanced electronics due to their high power densities, but their energy density still needs to be further improved. High-entropy strategy has emerged as an effective method for improving energy storage performance, however, discovering new high-entropy systems within a high-dimensional composition space is a daunting challenge for traditional trial-and-error experiments. Here, based on phase-field simulations and limited experimental data, we propose a generative learning approach to accelerate the discovery of high-entropy dielectrics in a practically infinite exploration space of over 1011 combinations. By encoding-decoding latent space regularities to facilitate data sampling and forward inference, we employ inverse design to screen out the most promising combinations via a ranking strategy. Through only 5 sets of targeted experiments, we successfully obtain a Bi(Mg0.5Ti0.5)O3-based high-entropy dielectric film with a significantly improved energy density of 156 J cm−3 at an electric field of 5104 kV cm−1, surpassing the pristine film by more than eight-fold. This work introduces an effective and innovative avenue for designing high-entropy dielectrics with drastically reduced experimental cycles, which could be also extended to expedite the design of other multicomponent material systems with desired properties.

Abstract Objective This cross‐sectional study aimed to determine the epidemiology of olfactory and gustatory dysfunctions related to COVID‐19 in China. Methods This study was conducted by 45 tertiary Grade‐A hospitals in China. Online and offline questionnaire data were obtained from patients infected with COVID‐19 between December 28, 2022, and February 21, 2023. The collected information included basic demographics, medical history, smoking and drinking history, vaccination history, changes in olfactory and gustatory functions before and after infection, and other postinfection symptoms, as well as the duration and improvement status of olfactory and gustatory disorders. Results Complete questionnaires were obtained from 35,566 subjects. The overall incidence of olfactory and taste dysfunction was 67.75%. Being female or being a cigarette smoker increased the likelihood of developing olfactory and taste dysfunction. Having received four doses of the vaccine or having good oral health or being a alcohol drinker decreased the risk of such dysfunction. Before infection, the average olfactory and taste VAS scores were 8.41 and 8.51, respectively; after infection, they decreased to 3.69 and 4.29 and recovered to 5.83 and 6.55 by the time of the survey. The median duration of dysosmia and dysgeusia was 15 and 12 days, respectively, with 0.5% of patients having symptoms lasting for more than 28 days. The overall self‐reported improvement rate was 59.16%. Recovery was higher in males, never smokers, those who received two or three vaccine doses, and those that had never experienced dental health issues, or chronic accompanying symptoms. Conclusions The incidence of dysosmia and dysgeusia following infection with the SARS‐CoV‐2 virus is high in China. Incidence and prognosis are influenced by several factors, including sex, SARS‐CoV‐2 vaccination, history of head‐facial trauma, nasal and oral health status, smoking and drinking history, and the persistence of accompanying symptoms.

Background: Annual influenza vaccination is crucially recommended for the elderly to maintain humoral immunity. Insufficient coverage requires us to understand the determinants of their influenza behaviors and how these patterns impact vaccination choices. Methods: Data from 540 Beijing residents aged over 65 were collected through interviews, capturing vaccination history and sociodemographic details. Individual influenza vaccination records from 2016 to 2020 were obtained from China’s Immunization Information Systems. A latent class model identified three vaccination patterns. Multinomial logistic regression assessed relative risk ratios (RRRs) for vaccination based on sociodemographic factors. Vaccination patterns were used to predict future vaccination likelihood. Results: The analysis revealed three groups: sporadically vaccinated (63.33%), occasionally vaccinated (18.71%), and frequently vaccinated (17.96%). Factors associated with frequent vaccination included age over 70 (RRR = 2.81), lower income (RRR = 0.39), higher vaccine hesitancy (RRR = 3.10), multiple chronic conditions (RRR = 2.72), and rural residence (RRR = 2.48). The frequently vaccinated group was more likely to sustain regular vaccination habits in subsequent years compared to the occasionally vaccinated group. Conclusions: Only 17.96% of Beijing’s older population exhibited a consistent influenza vaccination pattern. Older age, rural residency, and chronic diseases correlated with repeated influenza vaccination. Segmenting the population based on past vaccination behavior can aid in designing targeted interventions to improve vaccination rates.

Objective In the treatment of lumbar degenerative spondylolisthesis (LDS) with Posterior lumbar interbody fusion (PLIF) surgery, interbody fusion implants play a key role in supporting the vertebral body and facilitating fusion. The objective of this study was to assess the impact of implantation depth on sagittal parameters and functional outcomes in patients undergoing PLIF surgery. Methods This study reviewed 128 patients with L4‐L5 LDS between January 2016 and August 2019. All patients underwent an open PLIF surgery that included intravertebral decompression, implantation of pedicle screws and cage. We grouped according to the position of the center of the cage relative to the L5 vertebral endplate. Patients with the center of the cage located at the anterior 1/2 of the upper end plate of the L5 vertebral body were divided into Anterior group, and located at the posterior 1/2 of the upper end plate of the L5 vertebral body were divided into Posterior group. The lumbar lordosis (LL), segmental lordosis (SL), sacral slope (SS), pelvic incidence (PI), pelvic tilt (PT) and slope degree (SD) was measured for radiographic outcomes. We used the visual analog scale (VAS) and the oswestry disability index (ODI) score to assess functional outcomes. Paired t‐test was used to compare imaging and bedside data before and after surgery between the two groups, and independent sample t‐test, χ2 test and Fisher exact test were used to compare the data between the two groups. Result The mean follow‐up of Anterior group was 44.13 ± 9.23 months, and Posterior group was 45.62 ± 10.29 months (P > 0.05). The LL, SL, PT, SS, SD and PI‐LL after operation showed great improvements, relative to the corresponding preoperative values in both groups (P

[Introduction] Fusion energy has the characteristics of large energy released through reactions, safe and reliable operation, abundant fuel sources, and low environmental pollution. Therefore, it is expected to become a commercial energy source that can be supplied in the market on a large scale, providing stable energy output and power supply in the future. To popularize the development path of magnetic confined fusion energy in China, the article reviews the discovery and realization path of fusion energy. [Method] The article provided an overview of the early research and development process of magnetic confined fusion energy in China by the method of literature review. The paper took the development of magnetic confined fusion energy as an example to provide a preliminary overview of the construction of typical research devices in China, such as tokamak, stellarator, spherical tokamak, reversed field pinch, magnetic mirror field, linear plasma, and dipole magnetic field devices. [Result] Based on the construction and researches of these devices, China has cultivated a group of scientific and technological talents in the field of magnetic confined fusion research, achieving significant progress. In addition, the article provides an overview of international cooperation in fusion energy research, as well as the International Thermonuclear Experimental Reactor (ITER) project that China is participating in construction. [Conclusion] Although the current research on fusion energy still needs to overcome significant challenges from various aspects, such as fusion plasma physics, fusion reactor materials, and tritium self-sustaining technology, it is believed that the magnetic confined fusion energy in China will turn from a blueprint into a reality in the future thanks to the urgent need for energy structure transformation and the strong support for fusion researches in China.

Abstract Low efficiency and spectral instability caused by the surface defects have been considerable issues for the mixed‐halogen blue emitting perovskite quantum dots light‐emitting diodes (PeQLEDs). Here, an in situ surface passivation to perovskite quantum dots (PeQDs) is realized by introducing the metal cations competitive lattice occupancy assisted with acid‐etching, in which the long‐chain, insulating and weakly bond surface ligands are removed by addition of octanoic acid (OTAC). Meanwhile, the dissolved A‐site cations (Na+) compete with the protonated oleyl amine and are subsequently anchored to the surface vacancies. The preadded lead bromide, acting as inorganic ligands, demonstrates strong bonding to the uncoordinated surface ions. The as‐synthesized PeQDs show the boosted photoluminescence quantum yield (PLQY) and superior stability with longer lifetime. As a result, the PeQLEDs (470 nm) based on the OTAC‐Na PeQDs exhibit an external quantum efficiency of 8.42% in the mixed halogen PeQDs (CsPb(BrxCl1−x)3). Moreover, the device exhibits superior spectra stability with negligible shift. Our competition mechanism in combination with in situ passivation strategy paves a new way for improving the performance of blue PeQLEDs.

Background: Osteoporosis is one of the most common bone diseases in middle-aged and elderly populations worldwide. The development of new drugs to treat the disease is a key focus of research. Current treatments for osteoporosis are mainly directed at promoting osteoblasts and inhibiting osteoclasts. However, there is currently no ideal approach for osteoporosis treatment. l-arginine is a semi-essential amino acid involved in a number of cellular processes, including nitric production, protein biosynthesis, and immune responses. We previously reported that l-arginine-derived compounds can play a regulatory role in bone homeostasis. Purpose: To investigate the specific effect of l-arginine on bone homeostasis. Methods: Mildly aged and ovariectomized mouse models were used to study the effects of l-arginine on osteogenesis and angiogenesis, assessed by micro-computed tomography and immunostaining of bone tissue. The effect of l-arginine on osteogenesis, angiogenesis, and adipogenesis was further studied in vitro using osteoblasts obtained from cranial cap bone, endothelial cells, and an adipogenic cell line. Specific methods to assess these processes included lipid staining, cell migration, tube-forming, and wound-healing assays. Protein and mRNA expression was determined for select biomarkers. Results: We found that l-arginine attenuated bone loss and promoted osteogenesis and angiogenesis. l-arginine increased the activity of vascular endothelial cells, whereas it inhibited adipogenesis in vitro. In addition, we found that l-arginine altered the expression of PINK1/Parkin and Bnip3 in the mitochondria of osteoblast-lineage and endothelial cells, thereby promoting mitophagy and protecting cells from ROS. Similarly, l-arginine treatment effectively ameliorated osteoporosis in an ovariectomized mouse model. Conclusion: l-arginine promotes angio-osteogenesis, and inhibits adipogenesis, effects mediated by the PINK1/Parkin- and Bnip3-mediated mitophagy. The Translational Potential of this Article: L-arginine supplementation may be an effective adjunct therapy in the treatment of osteoporosis.

Abstract Ferroelectric materials have important applications in transduction, data storage, and nonlinear optics. Inorganic ferroelectrics such as lead zirconate titanate possess large polarization, though they are rigid and brittle. Ferroelectric polymers are light weight and flexible, yet their polarization is low, bottlenecked at 10 μC cm−2. Here we show poly(vinylidene fluoride) nanocomposite with only 0.94% of self-nucleated CH3NH3PbBr3 nanocrystals exhibits anomalously large polarization (~19.6 μC cm−2) while retaining superior stretchability and photoluminance, resulting in unprecedented electromechanical figures of merit among ferroelectrics. Comprehensive analysis suggests the enhancement is accomplished via delicate defect engineering, with field-induced Frenkel pairs in halide perovskite stabilized by the poled ferroelectric polymer through interfacial coupling. The strategy is general, working in poly(vinylidene fluoride-co-hexafluoropropylene) as well, and the nanocomposite is stable. The study thus presents a solution for overcoming the electromechanical dilemma of ferroelectrics while enabling additional optic-activity, ideal for multifunctional flexible electronics applications.

Stress corrosion cracking (SCC) of welded joints is a significant issue that affects the widespread application of multimetal welded structures in aerospace, transportation, and other fields. This paper investigates the effect of laser shock peening (LSP) on the SCC of TC4/2A14 friction stir welded (FSW) joints with dissimilar metals. The microstructural evolution, mechanical properties, and corrosion behavior with and without LSP treatment were investigated using optical microscopy, transmission electron microscopy, X-ray analysis, electrochemical testing, and slow strain rate tensile testing (SSRT). The results showed that the LSP significantly refined the grains and induced work-hardening on the near-surface of the material. After LSP, the compressive residual stresses on the surface of the titanium and aluminium sides were −817.6 MPa and −153.6 MPa for the joint, respectively. Corrosion resistance was also improved, with the self-corrosion current density on the Al side of the joints reduced by 77% and the SCC susceptibility index (Issrt) reduced from 0.140 to 0.121. The enhanced SCC resistance of the LSP-treated TC4/2A14 dissimilar metal FSW joints is primarily due to grain refinement, work-hardening effect, and high-level compressive residual stress. These factors not only enhance the material strength and improve the pitting resistance of the joints but also prevent the initiation and propagation of SCC.

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.

Low temperature causes rice yield losses of up to 30%–40%, therefore increasing its cold tolerance is a breeding target. Few genes in rice are reported to confer cold tolerance at both the vegetative and reproductive stages. This study revealed a rice-specific 24-nt miRNA, miR1868, whose accumulation was suppressed by cold stress. Knockdown of MIR1868 increased seedling survival, pollen fertility, seed setting, and grain yield under cold stress, whereas its overexpression conferred the opposite phenotype. Knockdown of MIR1868 increased reactive oxygen species (ROS) scavenging and soluble sugar content under cold stress by increasing the expression of peroxidase genes and sugar metabolism genes, and its overexpression produced the opposite effect. Thus, MIR1868 negatively regulated rice cold tolerance via ROS scavenging and sugar accumulation.

Existing studies have focused on the behavior of the retaining wall equipped with expanded polystyrene (EPS) geofoam inclusions under semi-infinite surcharge loading rather than limited surcharge loading. In this paper, the failure mode and the earth pressure acting on the rigid retaining wall with EPS geofoam inclusions and granular backfills (henceforth referred to as EPS-wall), under limited surcharge loading are investigated through two- and three-dimensional model tests. The testing results show that different from the sliding of almost all the backfill in the EPS-wall under semi-infinite surcharge loading, only an approximately triangular backfill slides in the wall under limited surcharge loading. The distribution of the lateral earth pressure on the EPS-wall under limited surcharge loading is non-linear, and the distribution changes from the increase of the wall depth to the decrease with the increase of the limited surcharge loading. An approach based on the force equilibrium of a differential element is developed to predict the lateral earth pressure behind the EPS-wall subjected to limited surcharge loading, and its performance was fully validated by the three-dimensional model tests.

PurposeTo explore molecular mechanisms affecting nutritional risk and neurodevelopment in children with congenital heart disease (CHD) by combining transcriptome and metabolome analysis.MethodsA total of 26 blood and serum samples from 3 groups of children with CHD low nutritional risk combined with normal neurodevelopment (group A), low nutritional risk combined with neurodevelopmental disorders (group B) and high nutritional risk combined with normal neurodevelopment (group C) were analyzed by transcriptome and metabolomics to search for differentially expressed genes (DEGs) and metabolites (DEMs). Functional analysis was conducted for DEGs and DEMs. Further, the joint pathway analysis and correlation analysis of DEGs and DEMs were performed.ResultsA total of 362 and 1,351 DEGs were detected in group B and C compared to A, respectively. A total of 6 and 7 DEMs were detected in group B and C compared to A in positive mode, respectively. There were 39 and 31 DEMs in group B and C compared to A in negative mode. Transcriptomic analysis indicated that neurodevelopment may be regulated by some genes such as NSUN7, SLC6A8, CXCL1 and LCN8, nutritional risk may be regulated by SLC1A3 and LCN8. Metabolome analysis and joint pathway analysis showed that tryptophan metabolism, linoleic and metabolism and glycerophospholipid metabolism may be related to neurodevelopment, and glycerophospholipid metabolism pathway may be related to nutritional risk.ConclusionBy integrating transcriptome and metabolome analyses, this study revealed key genes and metabolites associated with nutritional risk and neurodevelopment in children with CHD, as well as significantly altered pathways. It has important clinical translational significance.

Lithium argyrodite solid electrolytes have attracted ever‐increasing attention for all‐solid‐state batteries due to their high ionic conductivity and low cost. However, the relation between structure and ionic transport for the halogen‐rich lithium argyrodites under different synthesis routes is still elusive. Herein, the influence of synthesis procedures, such as annealing conditions and balling milling, on the structure, ionic conductivity, and activation energy of the lithium argyrodite (e.g., Li5.5PS4.5Cl1.5, Li5.3PS4.3Cl1.7), is systematically investigated. Compared with high‐energy ball milling followed by annealing, using fast dry mixing followed by annealing can obtain comparable ionic conductivity of the chlorine‐rich lithium argyrodites. Single‐crystal LiNi0.83Co0.11Mn0.06O2‐based solid‐state battery with these electrolytes shows stable cycling performance, demonstrating that chlorine‐rich lithium argyrodite is a promising candidate for all‐solid‐state batteries.

IntroductionBacteriophages have been shown to penetrate biofilms and replicate if they find suitable host cells. Therefore, these viruses appear to be a good option to tackle the biofilm problem and complement or even substitute more conventional antimicrobials. However, in order to successfully remove biofilms, in particular mature biofilms, phages may need to be administered along with other compounds. Phage-derived proteins, such as endolysins or depolymerases, offer a safer alternative to other compounds in the era of antibiotic resistance.MethodsThis study examined the interactions between phage Kayvirus rodi with a polysaccharide depolymerase (Dpo7) from another phage (Rockefellervirus IPLA7) against biofilms formed by different Staphylococcus aureus strains, as determined by crystal violet staining, viable cell counts and microscopy analysis.Results and discussionOur results demonstrated that there was synergy between the two antimicrobials, with a more significant decreased in biomass and viable cell number with the combination treatment compared to the phage and enzyme alone. This observation was confirmed by microscopy analysis, which also showed that polysaccharide depolymerase treatment reduced, but did not eliminate extracellular matrix polysaccharides. Activity assays on mutant strains did not identify teichoic acids or PNAG/PIA as the exclusive target of Dpo7, suggesting that may be both are degraded by this enzyme. Phage adsorption to S. aureus cells was not significantly altered by incubation with Dpo7, indicating that the mechanism of the observed synergistic interaction is likely through loosening of the biofilm structure. This would allow easier access of the phage particles to their host cells and facilitate infection progression within the bacterial population.

To achieve all-organic polymer with high dielectric performances, we have designed a novel side-chain liquid crystalline polymer (P7) with strong polar mesogen of (Z)-4-(2-cyano-2-phenylvinyl)benzonitrile (CSCN) attached to polycyclooctene backbone. The bis-cyano-substituted CSCN is board-shaped and exhibits a large dipole moment (8.54 D) which tilts ∼34.2° away from its molecular long axis. Consequently, CSCN shows unique dual molecular anisotropy: one from biaxial shape anisotropy and the other from polarization anisotropy. The complex phase behaviors of P7 were investigated employing mainly the techniques of differential scanning calorimetry and X-ray diffraction. Four liquid crystal (LC) phases are identified as K0, K1, K2 and K3, which are SmA, highly-ordered biaxial SmA, B5-like and B7-like, respectively, with the thermal stability increased in sequence. The experimental results indicate that the different LC phases are arisen from the competition and balance between π-π stacking and dipole-dipole interaction. While the face-to-face π-π stacking is dominant in K0 and K1, optimizing the dipole-dipole interaction causes the CSCN mesogens within the smectic layer to tilt and rotate, resulting in K2 and K3. We further investigated the dielectric properties of P7 films using polarization-electric field loops test. The dielectric constant (εr) of P7 is found to be LC structure dependent, which is increased when the LC phase is varied from K0 to K3. With an average εr of 9.7 achieved in K3 and the low dielectric loss (tan δ = 0.001), P7 film offers a promising material in advanced applications like energy storage and electronic devices.

Abstract Activation of receptor‐interacting protein kinase 1 (RIPK1), a broadly expressed serine/threonine protein kinase, by pro‐inflammatory cytokines and pathogens can result in apoptosis, necroptosis, or inflammation. RIPK1 inhibition has been shown to reduce inflammation and cell damage in preclinical studies and may have therapeutic potential for degenerative and inflammatory diseases. SIR2446 is a potent and selective novel small molecule RIPK1 kinase inhibitor. This phase I, randomized, double‐blind, placebo‐controlled study in Australia (ACTRN12621001621808) evaluated the safety (primary objective), pharmacokinetics, and pharmacodynamics of single (3–600 mg) and multiple (5–400 mg for 10 days) ascending oral doses of SIR2446M (SIR2446 magnesium salt form) in healthy adults from Nov 24, 2021, until May 01, 2023. All treatment‐emergent adverse events (TEAEs) were mild/moderate. The most reported TEAEs were vascular access site pain, headache, and rash morbilliform. SIR2446M plasma half‐lives ranged from 11 to 19 h and there were no major deviations from dose proportionality for maximum concentration and area under the curve across doses. Renal excretion of unchanged SIR2446 was minimal. No marked accumulation was observed (mean accumulation ratio, 1.2–1.6) after multiple daily doses. A high‐fat meal mildly reduced the exposure but was not considered clinically significant. SIR2446M had a rapid and sustained inhibitory effect on the activity of RIPK1, with an overall 90% target engagement at repeated doses ranging from 30 to 400 mg in peripheral blood mononuclear cells ex vivo stimulated to undergo necroptosis. The favorable safety, pharmacokinetic, and pharmacodynamic profile of SIR2446M in healthy participants supports its further clinical development in patients with degenerative and inflammatory diseases.

Background: Chronic pelvic pain (CPP) in women is a critical challenge. Due to the complex etiology and difficulties in diagnosis, it has a greatly negative impact on women's physical and mental health and the healthcare system. At present, there is still a lack of research on the related factors and predictive models of chronic pelvic pain in women. Our study aims to identify risk factors associated with chronic pelvic pain in women and develop a predictive nomogram specifically tailored to high-risk women with CPP. Materials and methods: From May to October 2022, trained interviewers conducted face-to-face questionnaire surveys and pelvic floor surface electromyography assessments on women from community hospitals in Nanjing. We constructed a multivariate logistic regression-based predictive model using CPP-related factors to assess the risk of chronic pelvic pain and create a predictive nomogram. Both internal and external validations were conducted, affirming the model's performance through assessments of discrimination, calibration, and practical applicability using area under the curve, calibration plots, and decision curve analysis. Results: 1108 women were recruited in total (survey response rate:1108/1200), with 169 (15.3 %) being diagnosed as chronic pelvic pain. Factors contributing to CPP included weight, dysmenorrhea, sexual dysfunction, urinary incontinence, a history of pelvic inflammatory disease, and the surface electromyography value of post-baseline rest. In both the training and validation sets, the nomogram exhibited strong discrimination abilities with areas under the curve of 0.85 (95 % CI: 0.81–0.88) and 0.85 (95 % CI: 0.79–0.92), respectively. The examination of the decision curve and calibration plot showed that this model fit well and would be useful in clinical settings. Conclusions: Weight, dysmenorrhea, sexual dysfunction, history of urinary incontinence and pelvic inflammatory disease, and surface electromyography value of post-baseline rest are independent predictors of chronic pelvic pain. The nomogram developed in this study serves as a valuable and straightforward tool for predicting chronic pelvic pain in women.

Abstract Background Global myopia prevalence poses a substantial public health burden with vision-threatening complications, necessitating effective prevention and control strategies. Precise prediction of spherical equivalent (SE), myopia, and high myopia onset is vital for proactive clinical interventions. Methods We reviewed electronic medical records of pediatric and adolescent patients who underwent cycloplegic refraction measurements at the Eye & Ear, Nose, and Throat Hospital of Fudan University between January 2005 and December 2019. Patients aged 3–18 years who met the inclusion criteria were enrolled in this study. To predict the SE and onset of myopia and high myopia in a specific year, two distinct models, random forest (RF) and the gradient boosted tree algorithm (XGBoost), were trained and validated based on variables such as age at baseline, and SE at various intervals. Outputs included SE, the onset of myopia, and high myopia up to 15 years post-initial examination. Age-stratified analyses and feature importance assessments were conducted to augment the clinical significance of the models. Results The study enrolled 88,250 individuals with 408,255 refraction records. The XGBoost-based SE prediction model consistently demonstrated robust and better performance than RF over 15 years, maintaining an R 2 exceeding 0.729, and a Mean Absolute Error ranging from 0.078 to 1.802 in the test set. Myopia onset prediction exhibited strong area under the curve (AUC) values between 0.845 and 0.953 over 15 years, and high myopia onset prediction showed robust AUC values (0.807–0.997 over 13 years, with the 14th year at 0.765), emphasizing the models' effectiveness across age groups and temporal dimensions on the test set. Additionally, our classification models exhibited excellent calibration, as evidenced by consistently low brier score values, all falling below 0.25. Moreover, our findings underscore the importance of commencing regular examinations at an early age to predict high myopia. Conclusions The XGBoost predictive models exhibited high accuracy in predicting SE, onset of myopia, and high myopia among children and adolescents aged 3–18 years. Our findings emphasize the importance of early and regular examinations at a young age for predicting high myopia, thereby providing valuable insights for clinical practice.

Abstract Background Ovarian cancer (OC) is distinguished by its aggressive nature and the limited efficacy of current treatment strategies. Recent studies have emphasized the significant role of cancer-associated fibroblasts (CAFs) in OC development and progression. Methods Employing sophisticated machine learning techniques on bulk transcriptomic datasets, we identified fibroblast growth factor 7 (FGF7), derived from CAFs, as a potential oncogenic factor. We investigated the relationship between FGF7 expression and various clinical parameters. A series of in vitro experiments were undertaken to evaluate the effect of CAFs-derived FGF7 on OC cell activities, such as proliferation, migration, and invasion. Single-cell transcriptomic analysis was also conducted to elucidate the interaction between FGF7 and its receptor. Detailed mechanistic investigations sought to clarify the pathways through which FGF7 fosters OC progression. Results Our findings indicate that higher FGF7 levels correlate with advanced tumor stages, increased vascular invasion, and poorer prognosis. CAFs-derived FGF7 significantly enhanced OC cell proliferation, migration, and invasion. Single-cell analysis and in vitro studies revealed that CAFs-derived FGF7 inhibits the ubiquitination and degradation of hypoxia-inducible factor 1 alpha (HIF-1α) via FGFR2 interaction. Activation of the FGF7/HIF-1α pathway resulted in the upregulation of mesenchymal markers and downregulation of epithelial markers. Importantly, in vivo treatment with neutralizing antibodies targeting CAFs-derived FGF7 substantially reduced tumor growth. Conclusion Neutralizing FGF7 in the medium or inhibiting HIF-1α signaling reversed the effects of FGF7-mediated EMT, emphasizing the dependence of FGF7-mediated EMT on HIF-1α activation. These findings suggest that targeting the FGF7/HIF-1α/EMT axis may offer new therapeutic opportunities to intervene in OC progression.

Abstract Glioblastoma, IDH-Wild type (GBM, CNS WHO Grade 4) is a highly heterogeneous and aggressive primary malignant brain tumor with high morbidity, high mortality, and poor patient prognosis. The global burden of GBM is increasing notably due to limited treatment options, drug delivery problems, and the lack of characteristic molecular targets. OTU deubiquitinase 4 (OTUD4) is a potential predictive factor for several cancers such as breast cancer, liver cancer, and lung cancer. However, its function in GBM remains unknown. In this study, we found that high expression of OTUD4 is positively associated with poor prognosis in GBM patients. Moreover, we provided in vitro and in vivo evidence that OTUD4 promotes the proliferation and invasion of GBM cells. Mechanism studies showed that, on the one hand, OTUD4 directly interacts with cyclin-dependent kinase 1 (CDK1) and stabilizes CDK1 by removing its K11, K29, and K33-linked polyubiquitination. On the other hand, OTUD4 binds to fibroblast growth factor receptor 1 (FGFR1) and reduces FGFR1’s K6 and K27-linked polyubiquitination, thereby indirectly stabilizing CDK1, ultimately influencing the activation of the downstream MAPK signaling pathway. Collectively, our results revealed that OTUD4 promotes GBM progression via OTUD4-CDK1-MAPK axis, and may be a prospective therapeutic target for GBM treatment.

Abstract Bone and mineral metabolism homeostasis accounts for the maintenance of normal skeletal remodeling. However, with aging and changes in hormone levels, over-activated osteoclasts disrupt homeostasis, induce osteoporosis, and even cause osteoporotic fractures, leading to an enormous economic burden. Despite the rapid development of pharmacological therapy for osteoporosis, safer and more effective treatments remain to be explored. Here, we demonstrate that Mulberroside A (Mul-A), a natural component extracted from mulberry bark and branches, effectively suppresses osteoclastogenesis in vitro and counteracts bone loss caused by ovariectomy (OVX). The mechanism underlying this effect involves the repression of autophagic flux during osteoclastogenesis by Mul-A, which can be attributed to the restrained expression of microphthalmia-related transcription factor (Mitf) and its nuclear translocation. Importantly, Mitf overexpression partially reverses the inhibitory effects of Mul-A on autophagy and osteoclastogenesis. Moreover, applying two autophagy agonizts, rapamycin and Torin 1, attenuates the osteoclastogenic regulatory role of Mul-A. Collectively, our study demonstrates that Mul-A damages osteoclast differentiation and ameliorates osteoporosis caused by estrogen deficiency by modulation of Mitf-associated autophagy, indicating its therapeutic potential against osteoporosis.

Abstract Background Owing to an increase in life expectancy, it is common for the older adults to suffer from chronic diseases that can result in disability and a low quality of life. This study aimed to explore the influence of chronic diseases and multimorbidities on activities of daily living (ADLs) and instrumental ADLs (IADLs) in an older Chinese population. Methods Based on the Chinese Longitudinal Healthy Longevity Survey (2018), 9,155 older adults aged 65 years and above were included in the study. A self-administered questionnaire was used to collect information on demographic characteristics, chronic diseases, ADLs, and IADLs. The impact of factors affecting ADL and IADL impairment in older adults was analysed using binary logistic regression. Results In total, 66.3% participants had chronic diseases. Hypertension, heart disease, arthritis, diabetes and cerebrovascular disease were among the top chronic diseases. Of these, 33.7% participants had multimorbidities. The most common combination of the two chronic diseases was hypertension and heart disease (11.2%), whereas the most common combination of the three chronic diseases was hypertension, heart disease, and diabetes (3.18%). After categorising the older adults into four age groups, dementia, visual impairment, and hearing impairment were found to be more prevalent with increasing age. The prevalence of hypertension, heart disease, cerebrovascular disease, gastrointestinal ulcers, arthritis and chronic nephritis gradually increased with age until the age of 75 years, peaked in the 75–84 years age group, and then showed a decreasing trend with age. Multimorbidity prevalence followed a similar pattern. Regression analysis indicated that the increase in age group and the number of chronic diseases independently correlated with impairments in ADL as well as IADL. Additionally, gender, physical activity, educational background, obesity, depressive symptoms, and falls also had an impact on ADLs or IADLs. Conclusion Chronic diseases and multimorbidities are common in older adults, and it is important to note that aging, multimorbidity, obesity, and unhealthy lifestyle choices may interfere with ADLs or IADLs in older adults. Therefore, it is imperative that primary healthcare providers pay special attention to older adults and improve screening for multimorbidity and follow-up needs.

Few-shot fine-grained (FSFG) categorization aims to classify new, fine-grained concepts using limited annotated data for each class. It requires a model capable of learning subtle, distinguishable features from similar classes. An intuitive approach is to identify several discriminative parts based on the input image and represent it using these localized parts. It is interpretable since the parts obtained and combined can be seen as the way humans learn about new concepts. Therefore, we propose a straightforward and efficient module for the FSFG task by emphasizing the importance of information from discriminative parts. Specifically, we design a plug-and-play meta-detector based on object detection models, which identifies the positions of distinguishable parts in fine-grained images. With the positions of objects and semantic parts identified, we can extract richer features to enhance few-shot results. Extensive experiments on five fine-grained datasets demonstrate that our approach is applicable to various few-shot backbones and significantly improves accuracy without adding extra parameters. More importantly, compared to other variants on the same base few-shot network, the meta-detector module significantly outperforms them, further demonstrating its effectiveness.

Bidirectional interlinking converter (BIC) is the core equipment in a hybrid AC/DC microgrid connected between AC and DC sub-grids. However, the variety of control modes and flexible bidirectional power flow complicate the influence of AC faults on BIC itself and on DC sub-grid, which potentially threaten both converter safety and system reliability. This study first investigates AC fault influence on the BIC and DC bus voltage under different BIC control modes and different pre-fault operation states, by developing a mathematical model and equivalent sequence network. Second, based on the analysis results, a general accommodative current limiting strategy is proposed for BIC without limitations to specific mode or operation condition. Current amplitude is predicted and constrained according to the critical requirements to protect the BIC and relieving the AC fault influence on the DC bus voltage. Compared with conventional methods, potential current limit failure and distortions under asymmetric faults can also be avoided. Finally, experiments verify feasibility of the proposed method.

Introduction: Laparoendoscopic single-site inguinal lymphadenectomy (LESS-IL), a minimally invasive technique, has been reported in patients with vulvar or vaginal cancer regarding its safety and feasibility. However, the long-term outcomes, especially oncologic outcomes, are still lacking. We aimed to evaluate the long-term outcomes of LESS-IL to confirm its safety further. Patients and Methods: Data were prospectively collected from patients with vulvar or vaginal cancer who underwent LESS-IL at our institution between July 2018 and June 2021. The patients were followed up for at least 12 months. All procedures were performed according to treatment standards. Short- and long-term complications and oncologic outcomes were analysed. Results: A total of 16 patients undergoing 28 LESS-IL procedures were identified, amongst whom 4 underwent unilateral LESS-IL. The median numbers of excised groin lymph nodes were 9.0 (6.5–11.8) and 10.5 (8.3–12.0) in each left and right groin, respectively. Short-term complications occurred in 4 (25%) patients, including 18.7% lymphocele and 6.3% wound infection. Long-term complications regarding lower-limb lymphoedema appeared in 6 (37.5%) patients. Most short- and long-term complications were Clavien–Dindo 1 or 2, accounting for 90% of all post-operative issues. After a median follow-up of 27 (21.3–35.8) months, only 1 (6.3%) patient had isolated inguinal recurrence at 13 months postoperatively. No local or distant recurrence occurred. Conclusion: Our results suggest that LESS-IL is associated with little incidence of complications and promising oncologic outcomes, further demonstrating the safety and feasibility of the LESS-IL technique in patients requiring IL.

In dynamic environments, the traditional relative positioning methods based on the Kalman filter model suffer from low accuracy and stability due to the influence of noise and outliers. This paper proposes a variational Bayesian filtering algorithm based on the combination of four-frequency observations from BDS (BeiDou Navigation Satellite System) and models the observation noise using the T-distribution to enhance the stability of filtering. Firstly, a geometrically correlated ambiguity resolution model is constructed based on the characteristics of the combined observations, effectively improving the precision of float ambiguity resolution and fixing rate. Moreover, considering the characteristics of outliers that are likely to occur in dynamic conditions, a T-distribution-based variational Bayesian filtering approach is employed to estimate the time-varying observation noise and system states. Experimental results demonstrate that the proposed method exhibits robustness and stability in dynamic short baseline scenarios, leading to further improvements in positioning accuracy, float ambiguity resolution precision, and fixing rate.

Graph Pooling technology plays an important role in graph node classification tasks. Sorting pooling technologies maintain large-value units for pooling graphs of varying sizes. However, by analyzing the statistical characteristic of activated units after pooling, we found that a large number of units dropped by sorting pooling are negative-value units that contain representative information and can contribute considerably to the final decision. To maintain more representative information, we proposed a novel pooling technology, called Geometric Pooling (GP), containing the unique node features with negative values by measuring the similarity of all node features. We reveal the effectiveness of GP from the entropy reduction view. The experiments were conducted on TUdatasets to show the effectiveness of GP. The results showed that the proposed GP outperforms the SOTA graph pooling technologies by $1\%~\sim ~5\%$ with fewer parameters.

Point cloud generation and representation is important in industry areas. Generating and editing high quality 3D shapes is challenging work in deep learning. Inspired by StyleGAN, a style based generative adversarial networks is proposed to generate high quality 3D point cloud. An improved non-linear mapping network learn distribution of points and is used to generate well distributed point cloud point cloud. We also provide a coarse to fine representation for point cloud. According to the experimental results on the ShapeNet Part data set(including aircraft, chair single category and overall 16 categories), our method can generate more uniform point cloud than other GAN methods with less training epoches. The latent code for point cloud has better linear separation,and is more easy to edit.

Abstract Sustainable Development Goal 8 proposes the promotion of full and productive employment for all. Intelligent production factors, such as robots, the Internet of Things, and extensive data analysis, are reshaping the dynamics of labour supply and demand. In China, which is a developing country with a large population and labour force, analysing the impact of artificial intelligence technology on the labour market is of particular importance. Based on panel data from 30 provinces in China from 2006 to 2020, a two-way fixed-effect model and the two-stage least squares method are used to analyse the impact of AI on employment and to assess its heterogeneity. The introduction and installation of artificial intelligence technology as represented by industrial robots in Chinese enterprises has increased the number of jobs. The results of some mechanism studies show that the increase of labour productivity, the deepening of capital and the refinement of the division of labour that has been introduced into industrial enterprises through the introduction of robotics have successfully mitigated the damaging impact of the adoption of robot technology on employment. Rather than the traditional perceptions of robotics crowding out labour jobs, the overall impact on the labour market has exerted a promotional effect. The positive effect of artificial intelligence on employment exhibits an inevitable heterogeneity, and it serves to relatively improves the job share of women and workers in labour-intensive industries. Mechanism research has shown that virtual agglomeration, which evolved from traditional industrial agglomeration in the era of the digital economy, is an important channel for increasing employment. The findings of this study contribute to the understanding of the impact of modern digital technologies on the well-being of people in developing countries. To give full play to the positive role of artificial intelligence technology in employment, we should improve the social security system, accelerate the process of developing high-end domestic robots and deepen the reform of the education and training system.

Abstract Studies regarding the relationship between fiber intake and prostate cancer (PCa) have conflicting results. Therefore, this study examined the relationship between fiber intake and the risk of PCa by using data from Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. A total of 54,336 participants in the United States, consisting of 6,414 patients with PCa, were included in this study. Multivariate Cox regression models were applied to estimate adjusted hazard ratios (aHRs) and corresponding 95% confidence intervals (CIs). Compared with individuals in the lowest quartile, individuals in the highest quartile of insoluble fiber intake had a significantly lower risk of PCa (aHR, 0.87; 95% CI, 0.78–0.98). By contrast, no significant associations were detected between total fiber intake (aHR, 0.90; 95% CI, 0.80–1.01) or soluble fiber intake (aHR, 0.90; 95% CI, 0.80–1.02). Subgroup analyses showed that insoluble fiber was related to a decreased risk of PCa in subjects with the following characteristics: age > 65 years, nonsmoking or former smokers, education level ≤ high school, non-Hispanic white ethnicity, or without a family history of PCa. In addition, significant combined effects of insoluble fiber intake, age and family history of PCa on the risk of PCa were observed, but no combined effects of smoking status and insoluble fiber intake were observed. In addition, total fiber, insoluble fiber, and soluble fiber intake had no influence on the mortality of PCa patients. These results show that all 3 measures of fiber suggest a protective association, but insoluble fiber may have a stronger association with the risk of PCa. Future studies are warranted to further investigate these relationships.

Abstract Topology created by quasi-continuous spatial variations of a local polarization direction represents an exotic state of matter, but field-driven manipulation has been hitherto limited to creation and destruction. Here we report that relatively small electric or mechanical fields can drive the non-volatile rotation of polar spirals in discretized microregions of the relaxor ferroelectric polymer poly(vinylidene fluoride-ran-trifluoroethylene). These polar spirals arise from the asymmetric Coulomb interaction between vertically aligned helical polymer chains, and can be rotated in-plane through various angles with robust retention. Given also that our manipulation of topological order can be detected via infrared absorption, our work suggests a new direction for the application of complex materials.

Background Idiopathic membranous nephropathy (IMN) with deposits of phospholipase A2 receptor (PLA2R) antigen in glomerular tissue (GAg+) but no circulating serum PLA2R antibody (SAb−) has been reported. However, little is known about the clinicopathological characteristics and prognosis of this subtype.Methods A total of 74 IMN patients with GAg + identified by kidney biopsy were enrolled in this study. We categorized patients into two groups based on the presence or absence of serum PLA2R antibody. Data on clinical features, pathological features, and outcomes were collected. Kaplan–Meier analysis of complete remission (CR) and partial remission (PR) comparing SAb−/GAg + and SAb+/GAg + patients. Cox proportional hazards models was used to examine factors associated with CR and PR.Results Among 74 IMN patients, 14 were SAb−/GAg+. Compared with SAb+/GAg + patients, SAb−/GAg + patients presented with higher levels of albumin, lower levels of cholesterol and low density lipoprotein cholesterol (all p

IntroductionAcute myeloid leukemia (AML) is an aggressive blood cancer with high heterogeneity and poor prognosis. Although the metabolic reprogramming of nicotinamide adenine dinucleotide (NAD) has been reported to play a pivotal role in the pathogenesis of acute myeloid leukemia (AML), the prognostic value of NAD metabolism and its correlation with the immune microenvironment in AML remains unclear.MethodsWe utilized our large-scale RNA-seq data on 655 patients with AML and the NAD metabolism-related genes to establish a prognostic NAD metabolism score based on the sparse regression analysis. The signature was validated across three independent datasets including a total of 1,215 AML patients. ssGSEA and ESTIMATE algorithms were employed to dissect the tumor immune microenvironment. Ex vivo drug screening and in vitro experimental validation were performed to identify potential therapeutic approaches for the high-risk patients. In vitro knockdown and functional experiments were employed to investigate the role of SLC25A51, a mitochondrial NAD+ transporter gene implicated in the signature.ResultsAn 8-gene NAD metabolism signature (NADM8) was generated and demonstrated a robust prognostic value in more than 1,800 patients with AML. High NADM8 score could efficiently discriminate AML patients with adverse clinical characteristics and genetic lesions and serve as an independent factor predicting a poor prognosis. Immune microenvironment analysis revealed significant enrichment of distinct tumor-infiltrating immune cells and activation of immune checkpoints in patients with high NADM8 scores, acting as a potential biomarker for immune response evaluation in AML. Furthermore, ex vivo drug screening and in vitro experimental validation in a panel of 9 AML cell lines demonstrated that the patients with high NADM8 scores were more sensitive to the PI3K inhibitor, GDC-0914. Finally, functional experiments also substantiated the critical pathogenic role of the SLC25A51 in AML, which could be a promising therapeutic target.ConclusionOur study demonstrated that NAD metabolism-related signature can facilitate risk stratification and prognosis prediction in AML and guide therapeutic decisions including both immunotherapy and targeted therapies.

Based on the configuration theory, this paper discusses the multiple concurrent causes and causal complex mechanisms affecting the performance differences among different new farmers. Using the fuzzy set qualitative comparative analysis method, taking 40 cases of CCTV’s “ZHI FU JING” column as samples, the paper analyzes the necessary conditions for new farmers to produce high performance by the anthefactory-variable configuration composed of human capital, social capital, psychological capital, entrepreneurial learning and entrepreneurial opportunity identification. The results show that: (1) high human capital is the necessary core condition for new farmers to produce high entrepreneurial performance, lack of high entrepreneurial learning and lack of high entrepreneurial opportunity identification is the core necessary condition for low entrepreneurial performance; (2) the driving mechanism of new farmers’ high entrepreneurial performance is divided into three paths, and the driving mechanism of new farmers’ low entrepreneurial performance is divided into two paths; and (3) the ways of inhibiting new farmers’ performance and promoting their performance are asymmetrical.

Background: Ultrafine particle (UFP) has been linked with higher risks of cardiovascular diseases; however, the biological mechanisms remain to be fully elucidated. Objectives: This study aims to investigate the cardiovascular responses to short-term UFP exposure and the biological pathways involved. Methods: A longitudinal panel study was conducted among 32 healthy, non-smoking young adults in Shanghai, China, who were engaged in five rounds of follow-ups between December 2020 and November 2021. Individual exposures were calculated based on the indoor and outdoor real-time measurements. Blood pressure, arterial stiffness, targeted biomarkers, and untargeted proteomics and metabolomics were examined during each follow-up. Linear mixed-effect models were applied to analyze the exposure and health data. The differential proteins and metabolites were used for pathway enrichment analyses. Results: Short-term UFP exposure was associated with significant increases in blood pressure and arterial stiffness. For example, systolic blood pressure increased by 2.10 % (95 % confidence interval: 0.63 %, 3.59 %) corresponding to each interquartile increase in UFP concentrations at lag 0–3 h, while pulse wave velocity increased by 2.26 % (95 % confidence interval: 0.52 %, 4.04 %) at lag 7–12 h. In addition, dozens of molecular biomarkers altered significantly. These effects were generally present within 24 h after UFP exposure, and were robust to the adjustment of co-pollutants. Molecular changes detected in proteomics and metabolomics analyses were mainly involved in systemic inflammation, oxidative stress, endothelial dysfunction, coagulation, and disturbance in lipid transport and metabolism. Discussion: This study provides novel and compelling evidence on the detrimental subclinical cardiovascular effects in response to short-term UFP exposure. The multi-omics profiling further offers holistic insights into the underlying biological pathways.

Warfarin is an anticoagulant that requires INR-based dosage adjustment. Ascorbic acid may impair warfarin effectiveness according to limited literature. We report a rare case of a 63-year-old woman with an aortic valve replacement history who developed warfarin resistance after taking ascorbic acid for anemia following breast cancer surgery. Despite increasing the warfarin dose from 6 mg to 10 mg daily, her INR remained below the therapeutic range. After ruling out other causes of warfarin resistance, we discontinued ascorbic acid and observed a rapid increase in INR to target values. The temporal relationship and the absence of other confounding factors confirmed the causality of ascorbic acid in this case. We recommend that patients concomitantly taking vitamin C and warfarin should monitor their INR values closely and discontinue ascorbic acid as soon as possible if they exhibit signs of warfarin resistance.

The ectonucleotidase CD39 has been regarded as a promising immune checkpoint in solid tumors. However, the expression of CD39 by tumor-infiltrating CD8+ T cells as well as their potential roles and clinical implications in human gastric cancer (GC) remain largely unknown. Here, we found that GC-infiltrating CD8+ T cells contained a fraction of CD39hi cells that constituted about 6.6% of total CD8+ T cells in tumors. These CD39hi cells enriched for GC-infiltrating CD8+ T cells with features of exhaustion in transcriptional, phenotypic, metabolic and functional profiles. Additionally, GC-infiltrating CD39hiCD8+ T cells were also identified for tumor-reactive T cells, as these cells expanded in vitro were able to recognize autologous tumor organoids and induced more tumor cell apoptosis than those of expanded their CD39int and CD39-CD8+ counterparts. Furthermore, CD39 enzymatic activity controlled GC-infiltrating CD39hiCD8+ T cell effector function, and blockade of CD39 efficiently enhanced their production of cytokines IFN-γ and TNF-α. Finally, high percentages of GC-infiltrating CD39hiCD8+ T cells correlated with tumor progression and independently predicted patients’ poor overall survival. These findings provide novel insights into the association of CD39 expression level on CD8+ T cells with their features and potential clinical implications in GC, and empowering those exhausted tumor-reactive CD39hiCD8+ T cells through CD39 inhibition to circumvent the suppressor program may be an attractive therapeutic strategy against GC.

Cancer stem cells (CSCs) are a small subset of cells in cancers that are thought to initiate tumorous transformation and promote metastasis, recurrence, and resistance to treatment. Growing evidence has revealed the existence of CSCs in various types of cancers and suggested that CSCs differentiate into diverse lineage cells that contribute to tumor progression. We may be able to overcome the limitations of cancer treatment with a comprehensive understanding of the biological features and mechanisms underlying therapeutic resistance in CSCs. This review provides an overview of the properties, biomarkers, and mechanisms of resistance shown by CSCs. Recent findings on metabolic features, especially fatty acid metabolism and ferroptosis in CSCs, are highlighted, along with promising targeting strategies. Targeting CSCs is a potential treatment plan to conquer cancer and prevent resistance and relapse in cancer treatment.

ABSTRACTAccurate carbon (C) stock estimation is crucial for C sequestration research, environmental protection, and policy formulation related to C management. Although research on C stock in forests, oceans, soil, and desert has received increasing attention, relatively few studies have focused on urban C stock. Moreover, the current mainstream methods for C stock assessment, including field surveys and satellite mapping, are characterised by notable limitations, including being labour-intensive and having limited real-time data acquisition capabilities. Therefore, this paper aims to assess urban C stock and proposes a novel two-stage estimation model based on deep learning and unmanned aerial vehicle (UAV) remote sensing. The first stage is that tree areas recognition via YOLOv5 and achieved 0.792 precision, 0.814 recall, and 0.805 mAP scores, respectively. In the second stage, a grid generation strategy and a Convolutional Neural Network (CNN) regression model were developed to estimate C stock based on recognised tree areas (R2 = 0.711, RMSE = 26.08 kg). Three regions with a minimum of 300 trees in each area were selected as validation sets. The experimental results, in terms of R2 and RMSE in kg, were (0.717, 0.711, 0.686) and (27.263, 27.857, 28.945), respectively.

Abstract Matrix vesicles (MVs) have shown strong effects in diseases such as vascular ectopic calcification and pathological calcified osteoarthritis and in wound repair of the skeletal system due to their membranous vesicle characteristics and abundant calcium and phosphorus content. However, the role of MVs in the progression of osteoporosis is poorly understood. Here, we report that annexin A5, an important component of the matrix vesicle membrane, plays a vital role in bone matrix homeostasis in the deterioration of osteoporosis. We first identified annexin A5 from adherent MVs but not dissociative MVs of osteoblasts and found that it could be sharply decreased in the bone matrix during the occurrence of osteoporosis based on ovariectomized mice. We then confirmed its potential in mediating the mineralization of the precursor osteoblast lineage via its initial binding with collagen type I to achieve MV adhesion and the subsequent activation of cellular autophagy. Finally, we proved its protective role in resisting bone loss by applying it to osteoporotic mice. Taken together, these data revealed the importance of annexin A5, originating from adherent MVs of osteoblasts, in bone matrix remodeling of osteoporosis and provided a new strategy for the treatment and intervention of bone loss.

Abstract Background To investigate the prevalence and risk factors of refractive astigmatism (RA) and corneal astigmatism (CA) in preschool children and school-aged children in Shanghai, China. Methods In this school-based, cross-sectional study, 4–15 years old children across three learning stages of kindergarten, primary school, and junior high school underwent noncycloplegic autorefraction and completed comprehensive questionnaires involving time spent on daily homework and outdoor activities. Data from the right eyes were analysed. Results Overall, 7084 children (mean ± standard deviation (SD) of age: 8.08 ± 3.11 years) were included, and the prevalence rates of RA/CA ( ≤ − 1.0 D) in children were 15.8%/64% in kindergartens, 16.5%/65% in primary schools, and 32.8%/76.9% in junior high schools. The magnitude and prevalence of RA and CA all increased with age or with learning stage (all P

Taking the constituent elements other than the main buildings of local Confucian temples as a research object, including memorial archway, screen wall, Pan-chi (pond), worship altar, sacrificial hall, pavilion and tower, this paper combines textual narrative and historical measurement to sort out the production and development history of these constituent elements. It analyzes the spatial evolution trend of Confucian temples to present the dynamic processes of derivation of constituent elements and spatial evolution of local Confucian temples. On this basis, this paper surveys the causes of the growth of Confucian temples from a macro historical perspective by considering political, social and cultural factors. This dynamic development process, sacred and secular as it is, will grow and last forever under the multiple official implications and folk beliefs.

The advent of new digital technologies has catalyzed a disruptive technological revolution, fostering significant industrial changes and advancing the green transformation of the economy and society. This paper investigates the influence of digitization on the green transformation of agribusiness firms, focusing on agriculture-related companies listed on the Shanghai and Shenzhen A-share markets from 2013 to 2021. Employing fixed-effect and mediated-effect models, the study examines the mechanisms through which digitization impacts these enterprises. The findings indicate that the relationship between digitization and green transformation in agribusiness is non-linear; a certain threshold of digitization must be achieved before it positively affects green transformation. The effect of digitization on green transformation varies according to the nature of business ownership, company size, supply chain flexibility, and regional environmental regulations. The study reveals that digitization influences green transformation through several mechanisms that promote economies of scale, technological innovation, and structural adjustments. While economies of scale derived from digitization do not directly support green transformation, they facilitate technological innovation and structural adjustments that enhance green initiatives in agribusiness.

To meet the challenges of energy sustainability, the integrated energy system (IES) has become a key component in promoting the development of innovative energy systems. Accurate and reliable multivariate load prediction is a prerequisite for IES optimal scheduling and steady running, but the uncertainty of load fluctuation and many influencing factors increase the difficulty of forecasting. Therefore, this article puts forward a multi-energy load prediction approach of the IES, which combines the fennec fox optimization algorithm (FFA) and hybrid kernel extreme learning machine. Firstly, the comprehensive weight method is used to combine the entropy weight method and Pearson correlation coefficient, fully considering the information content and correlation, selecting the key factors affecting the prediction, and ensuring that the input features can effectively modify the prediction results. Secondly, the coupling relationship between the multi-energy load is learned and predicted using the hybrid kernel extreme learning machine. At the same time, the FFA is used for parameter optimization, which reduces the randomness of parameter setting. Finally, the approach is utilized for the measured data at Arizona State University to verify its effectiveness in multi-energy load forecasting. The results indicate that the mean absolute error (MAE) of the proposed method is 0.0959, 0.3103 and 0.0443, respectively. The root mean square error (RMSE) is 0.1378, 0.3848 and 0.0578, respectively. The weighted mean absolute percentage error (WMAPE) is only 1.915%. Compared to other models, this model has a higher accuracy, with the maximum reductions on MAE, RMSE and WMAPE of 0.3833, 0.491 and 2.8138%, respectively.