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Abstract Large language models (LLMs) have shown remarkable abilities recently, including passing advanced professional exams and demanding benchmark tests. This performance has led many to suggest that they are close to achieving humanlike or “true” understanding of language, and even artificial general intelligence (AGI). Here, we provide a new open-source benchmark, the Two Word Test (TWT), that can assess semantic abilities of LLMs using two-word phrases in a task that can be performed relatively easily by humans without advanced training. Combining multiple words into a single concept is a fundamental linguistic and conceptual operation routinely performed by people. The test requires meaningfulness judgments of 1768 noun-noun combinations that have been rated as meaningful (e.g., baby boy) or as having low meaningfulness (e.g., goat sky) by human raters. This novel test differs from existing benchmarks that rely on logical reasoning, inference, puzzle-solving, or domain expertise. We provide versions of the task that probe meaningfulness ratings on a 0–4 scale as well as binary judgments. With both versions, we conducted a series of experiments using the TWT on GPT-4, GPT-3.5, Claude-3-Optus, and Gemini-1-Pro-001. Results demonstrated that, compared to humans, all models performed relatively poorly at rating meaningfulness of these phrases. GPT-3.5-turbo, Gemini-1.0-Pro-001 and GPT-4-turbo were also unable to make binary discriminations between sensible and nonsense phrases, with these models consistently judging nonsensical phrases as making sense. Claude-3-Opus made a substantial improvement in binary discrimination of combinatorial phrases but was still significantly worse than human performance. The TWT can be used to understand and assess the limitations of current LLMs, and potentially improve them. The test also reminds us that caution is warranted in attributing “true” or human-level understanding to LLMs based only on tests that are challenging for humans.

AIM: To investigate whether retinal nerve fiber layer defects (RNFLDs) is a potential risk factor for chronic kidney disease (CKD) in Chinese adults. METHODS: The Kailuan Eye Study was a population-based study that included 14 440 participants. All participants underwent detailed assessments, RNFLDs were diagnosed using color fundus photographs. RESULTS: Overall, 12 507 participants [8533 males (68.23%)] had complete systemic examination data and at least one evaluable fundus photograph. RNFLDs were found in 621 participants [5.0%; 95% confidence interval (CI): 4.6%-5.34%], and 70 cases of multiple RNFLDs were found (11.27%). After adjusting multiple factors, RNFLDs was significantly associated with CKD severity, the ORs of CKD stage 3, stage 4 and stage 5 were 1.698, 4.167, and 9.512, respectively. Multiple RNFLDs were also associated with CKD severity after adjusting multiple factors, the ORs of CKD stage 3 and stage 5 were 4.465 and 11.833 respectively. Furthermore, 2294 participants had CKD (18.34%, 95%CI: 17.68%-18.99%). After adjusting for other factors, CKD presence was significantly correlated with the presence of RNFLDs. CONCLUSION: The strongest risk factors for RNFLDs are CKD and hypertension. Conversely, RNFLDs can be an ocular feature in patients with CKD. Fundoscopy can help detect systemic diseases, and assessment for RNFLDs should be considered in CKD patients.

Measurement concepts are an essential foundation for more advanced mathematical concepts. To address the challenges of students with autism spectrum disorder (ASD) in learning measurement concepts, this study investigated the effects of using a combination of explicit instruction and virtual manipulatives (VMs) to teach measurement concepts to students with ASD in China. Using a single-case multiple-probe across skills design, researchers examined whether the intervention could support the acquisition and maintenance of measurement concepts in students with ASD. Based on visual analysis, a functional relation was found between the independent variable (i.e., explicit instruction with VMs) and student performance on solving measurement concepts problems. Implications for practice and research are discussed.

WHO classified Helicobacter pylori as a Group I carcinogen for gastric cancer as early as 1994. However, despite the high prevalence of H. pylori infection, only about 3 % of infected individuals eventually develop gastric cancer, with the highly virulent H. pylori strains expressing cytotoxin-associated protein (CagA) and vacuolating cytotoxin (VacA) being critical factors in gastric carcinogenesis. It is well known that H. pylori infection is divided into two types in terms of the presence and absence of CagA and VacA toxins in serum, that is, carcinogenic Type I infection (CagA+/VacA+, CagA+/VacA-, CagA-/VacA+) and non-carcinogenic Type II infection (CagA-/VacA-). Currently, detecting the two carcinogenic toxins in active modes is mainly done by diagnosing their serological antibodies. However, the method is restricted by expensive reagents and intricate procedures. Therefore, establishing a rapid, accurate, and cost-effective way for serological profiling of carcinogenic H. pylori infection holds significant implications for effectively guiding H. pylori eradication and gastric cancer prevention. In this study, we developed a novel method by combining surface-enhanced Raman spectroscopy with the deep learning algorithm convolutional neural network to create a model for distinguishing between serum samples with Type I and Type II H. pylori infections. This method holds the potential to facilitate rapid screening of H. pylori infections with high risks of carcinogenesis at the population level, which can have long-term benefits in reducing gastric cancer incidence when used for guiding the eradication of H. pylori infections.

[Objective] As China transitions from mid-stage to late-stage urbanization, the polycentric structure of cities is accelerating. This study explored its impact on carbon emission intensity and the underlying mechanisms. From a spatial planning perspective, it aimed to provide new insights for low-carbon city construction. [Methods] The study examined 279 prefecture-level and above cities in China from 2006 to 2020. Using a two-way fixed effects model, instrumental variables, and propensity score matching, it empirically tested the carbon emission reduction effects of the urban polycentric structure and its underlying mechanisms. [Results] (1) From 2006 to 2020, urban carbon emission intensity showed a declining trend. Spatially, it exhibited a core-periphery structure and provincial boundary phenomena, with minor changes in the east-west gap and an increase in the north-south gap. The urban polycentric structure showed an upward trend with stable geographic clustering characteristics. (2) The polycentric structure significantly reduced carbon emission intensity, but there is regional heterogeneity. It was higher in eastern and western cities compared to central cities and higher in southern cities compared to northern cities. Additionally, it was only present in economically advanced cities and cities with a large population. (3) The mechanism analyses indicated that the urban polycentric structure reduced carbon emission intensity through three pathways: promoting faster development of the service industry, optimizing land use structure, and attracting high-productivity enterprises. However, whether enterprise location choices result in sectoral-specific or mixed clustering varied between cities. [Conclusion] In the new stage of urbanization, supporting the development of polycentric cities is necessary. However, it is crucial to understand the preconditions for the effective carbon emission reduction effects of the urban polycentric structure and to create smooth transmission channels.

Thermal management of nanoscale quantum dots (QDs) in light-emitting devices is a long-lasting challenge. The existing heat transfer reinforcement solutions for QDs-polymer composite mainly rely on thermal-conductive fillers. However, this strategy failed to deliver the QDs’ heat generation across a long distance, and the accumulated heat still causes considerable temperature rise of QDs-polymer composite, which eventually menaces the performance and reliability of light-emitting devices. Inspired by the radially aligned fruit fibers in oranges, we proposed to eliminate this heat dissipation challenge by establishing long-range ordered heat transfer pathways within the QDs-polymer composite. Ultrahigh molecular weight polyethylene fibers (UPEF) were radially aligned throughout the polymer matrix, thus facilitating massive efficient heat dissipation of the QDs. Under a UPEF filling fraction of 24.46 vol%, the in-plane thermal conductivity of QDs-radially aligned UPEF composite (QDs-RAPE) could reach 10.45 W m−1 K−1, which is the highest value of QDs-polymer composite reported so far. As a proof of concept, the QDs’ working temperature can be reduced by 342.5 °C when illuminated by a highly concentrated laser diode (LD) under driving current of 1000 mA, thus improving their optical performance. This work may pave a new way for next generation high-power QDs lighting applications.

Abstract The educational environment plays a vital role in the development of students who participate in athletic pursuits both in terms of their physical health and their ability to detect fatigue. As a result of recent advancements in deep learning and biosensors benefitting from edge computing resources, we are now able to monitor the physiological fatigue of students participating in sports in real time. These devices can then be used to analyze the data using contemporary technology. In this paper, we present an innovative deep learning framework for forecasting fatigue in athletic students following physical exercise. It addresses the issue of lack of precision computational models and extensive data analysis in current approaches to monitoring students’ physical activity. In our study, we classified fatigue and non-fatigue based on photoplethysmography (PPG) signals. Several deep learning models are compared in the study. Using limited training data, determining the optimal parameters for PPG presents a significant challenge. For datasets containing many data points, several models were trained using PPG signals: a deep residual network convolutional neural network (ResNetCNN) ResNetCNN, an Xception architecture, a bidirectional long short-term memory (BILSTM), and a combination of these models. Training and testing datasets were assigned using a fivefold cross validation approach. Based on the testing dataset, the model demonstrated a proper classification accuracy of 91.8%.

Food taste-modulating peptides mainly interact with salt taste receptor ENaC, TRPV1 or TMC4, umami receptor T1R1/T1R3, sweet receptor T1R2/T1R3, bitter receptor T2R and kokumi receptor CaSR to induce PLCβ2/IP3 or cAMP/PKA pathway to achieve taste transduction. Computer aided analysis techniques such as molecular docking, dynamic simulation, virtual screening and deep learning can efficiently, accurately and widely identify and develop novel taste-modulating peptides, which can effectively promote the high-quality development of nutrition and health food industry. This paper aims to present the latest research progress in the field of taste-modulating peptides, including the human taste perception mechanism, the taste mechanism of food taste-modulating peptides, as well as computer aided analysis techniques. This provides ideas for cost reduction, efficiency enhancement, and subsequent in-depth research in the era of Big Compute and development of new taste-modulating peptide products in the field of food taste-modulating peptides development.

Abstract Background Emerging evidence suggests that alterations in BCAA metabolism may contribute to the pathogenesis of sarcopenia. However, the relationship between branched-chain amino acids (BCAAs) and sarcopenia is incompletely understood, and existing literature presents conflicting results. In this study, we conducted a community-based study involving > 100,000 United Kingdom adults to comprehensively explore the association between BCAAs and sarcopenia, and assess the potential role of muscle mass in mediating the relationship between BCAAs and muscle strength. Methods Multivariable linear regression analysis examined the relationship between circulating BCAAs and muscle mass/strength. Logistic regression analysis assessed the impact of circulating BCAAs and quartiles of BCAAs on sarcopenia risk. Subgroup analyses explored the variations in associations across age, and gender. Mediation analysis investigated the potential mediating effect of muscle mass on the BCAA-muscle strength relationship. Results Among 108,017 participants (mean age: 56.40 ± 8.09 years; 46.23% men), positive associations were observed between total BCAA, isoleucine, leucine, valine, and muscle mass (beta, 0.56–2.53; p

Abstract Previous observational investigations suggest that structural and diffusion imaging-derived phenotypes (IDPs) are associated with major neurodegenerative diseases; however, whether these associations are causal remains largely uncertain. Herein we conducted bidirectional two-sample Mendelian randomization analyses to infer the causal relationships between structural and diffusion IDPs and major neurodegenerative diseases using common genetic variants-single nucleotide polymorphism (SNPs) as instrumental variables. Summary statistics of genome-wide association study (GWAS) for structural and diffusion IDPs were obtained from 33,224 individuals in the UK Biobank cohort. Summary statistics of GWAS for seven major neurodegenerative diseases were obtained from the largest GWAS for each disease to date. The forward MR analyses identified significant or suggestively statistical causal effects of genetically predicted three structural IDPs on Alzheimer’s disease (AD), frontotemporal dementia (FTD), and multiple sclerosis. For example, the reduction in the surface area of the left superior temporal gyrus was associated with a higher risk of AD. The reverse MR analyses identified significantly or suggestively statistical causal effects of genetically predicted AD, Lewy body dementia (LBD), and FTD on nine structural and diffusion IDPs. For example, LBD was associated with increased mean diffusivity in the right superior longitudinal fasciculus and AD was associated with decreased gray matter volume in the right ventral striatum. Our findings might contribute to shedding light on the prediction and therapeutic intervention for the major neurodegenerative diseases at the neuroimaging level.

Abstract Water body (WB) extraction is the basic work of water resources management. Tibetan Plateau is one of the largest alpine lake systems in the world. However, research on the characteristics of water bodies (WBs) is mainly focused on large and medium WBs due to spatial resolution. This research presents a dataset containing a 2-m resolution map of WBs in 2020 based on Gaofen-1 data, and morphometric and landscape indices of WBs across the Tibetan Plateau. The Swin-UNet model is well performed with overall accuracy at 98%. The total area of WBs is 56354.6 km2 across Tibetan Plateau in 2020. The abundance compared with that from size-abundance relationship indicate WBs in the Tibetan Plateau conformed to the classic power scaling law. We evaluate the influence of spatial-resolution in WB extraction, which shows the dataset could be valuable to fill the gap of existing WBs map, especially for small waters. The dataset is valuable for revealing the spatial patterns of WBs, and understanding the impacts of climate change on water resources in Plateau.

To investigate the differences in serum tryptophan, lysine, and phenylalanine levels in breast cancer patients, the correlation between the three amino acids with the chemotherapy regimen, and their significance in the clinical diagnosis and treatment of breast cancer. Clinical data were collected from the Department of Breast Surgery at Yunnan Cancer Hospital, encompassing 216 cases from July to December 2020, including 91 healthy individuals, 38 with benign tumors, and 87 with cancer. Amino acid levels were measured using liquid chromatography-tandem mass spectrometry. Statistical analyses, such as the Kruskal-Wallis H-test and Wilcoxon test, were conducted to compare the levels of these amino acids across the healthy group, benign tumor group, and breast cancer group. The χ2 test and Fisher's exact probability method were employed to assess the relationship between amino acid levels and breast cancer stage, grade, and chemotherapy regimen. The results indicated that there were significant differences in serum lysine (H = 36.13, P .05) and phenylalanine (F = 1.466, P > .05) levels across different conventional chemotherapy regimens among the breast cancer cases studied. Serum lysine and phenylalanine levels might serve as potential biomarkers for breast cancer, and the choice of chemotherapy regimen is unlikely to impact significant changes in these amino acid levels.

Summary: Background: Early detection of nasopharyngeal carcinoma (NPC) poses a significant challenge. The absence of highly sensitive and specific diagnostic biomarkers for nasopharyngeal carcinoma contributes to the unfavourable prognosis of NPC patients. Here, we aimed to establish a non-invasive approach for detecting NPC using circulating cell-free DNA (cfDNA). Methods: We investigated the potential of next-generation sequencing (NGS) of peripheral blood cells as a diagnostic tool for NPC. We collected data on genome-wide nucleosome footprint (NF), 5′-end motifs, fragmentation patterns, CNV information, and EBV content from 553 Chinese subjects, including 234 NPC patients and 319 healthy individuals. Through case–control analysis, we developed a diagnostic model for NPC, and validated its detection capability. Findings: Our findings revealed that the frequencies of NF, fragmentation, and motifs were significantly higher in NPC patients compared to healthy controls. We developed an NPC score based on these parameters that accurately distinguished NPC from non-NPC cases according to the American Joint Committee on Cancer staging system from non-NPC (validation set: area under curve (AUC) = 99.9% (95% CI: 99.8%–100%), se: 98.15%, sp: 100%). This model showed superior performance over plasma EBV DNA. Additionally, the NPC score effectively differentiated between NPC patients and healthy controls, even after clinical treatment. Furthermore, the NPC score was found to be independent of potential confounders such as age, sex, or TNM stage. Interpretation: We have developed and verified a non-invasive approach with substantial potential for clinical application in detecting NPC. Funding: A full list of funding bodies that contributed to this study can be found in Funding section.

A reaction model for γ+p→J/ψ+p photoproduction, which exposes the cc¯ content of the photon in making the transition γ→cc¯+P→J/ψ and couples the intermediate cc¯ system to the proton's valence quarks via Pomeron (P) exchange, is used to deliver a description of available data, viz. both differential and total cross sections from near threshold, where data has newly been acquired, to invariant mass W≈300GeV. The study suggests that it is premature to link existing γ+p→J/ψ+p data with, for instance, in-proton gluon distributions, the quantum chromodynamics trace anomaly, or pentaquark production. Further developments in reaction theory and higher precision data are necessary before the validity of any such connections can be assessed.

IntroductionThis study aims to investigate the effects of Polygonatum fermented liquor (PFL) on improving lipid metabolism and oxidative stress in mice by regulating the gut microbiota.MethodsForty SPF-grade male Kunming mice were randomly divided into four groups: normal control group (NC), general liquor group (GC), fresh Polygonatum fermented liquor group (FPC), and nine-steam-nine-bask Polygonatum fermented liquor group (NPC). Each group was administered with sterile water, general liquor, fresh Polygonatum fermented liquor, and nine-steam-nine-bask Polygonatum fermented liquor, respectively, by gavage. The mice's liver, brain tissue, serum, and intestinal contents were collected. The indicators of oxidative stress in the liver, four blood lipid indicators, gamma-aminobutyric acid (GABA), and brain-derived neurotrophic factor (BDNF) levels in the brain tissue were measured, liver hematoxylin and eosin (HE) staining was performed, and the gut microbiota in the small intestine were analyzed using 16S rRNA second-generation sequencing technology.ResultsCompared with the NC group, the NPC group showed significantly increased liver glutathione peroxidase (GSH-Px) content in mice (p < 0.05), reduced number of lipid droplets in the liver cells, and increased GABA and BDNF content in the brain tissues. The NPC group regulated lipid metabolism by lowering low-density lipoprotein cholesterol (LDL-C) and increasing high-density lipoprotein cholesterol (HDL-C) content in the mouse serum. Gut microbiota analysis showed significant changes in the gut microbiota of mice in the FPC and NPC groups, with increased richness and species diversity. These two groups increased the abundance of beneficial bacteria such as Lactobacillus, unclassified Muribaculaceae, unclassified Bacilli, and uncultured Bacteroidales bacterium while reducing the abundance of harmful bacteria such as Candidatus Arthromitus, and Staphylococcus, with a particularly significant reduction in Staphylococcus (p < 0.05). It is speculated that the two types of PFL may exert lipid-lowering and antioxidant effects by modulating the abundance of these dominant bacteria. Further studies showed that various environmental factors are closely related to the dominant gut bacteria. Malondialdehyde (MDA) was significantly negatively correlated with Lactobacillus and unclassified Bacilli, superoxide dismutase (SOD) was significantly negatively correlated with Staphylococcus (p < 0.01) and significantly negatively correlated with Candidatus Arthromitus (p < 0.05), and HDL-C was significantly negatively correlated with Staphylococcus and Facklamia (p < 0.05).DiscussionThe two types of PFL chosen in this study may exert lipid-lowering and antioxidant effects by modulating the composition and function of the gut microbiota, providing guidance for the industrial application of Polygonatum.

Abstract Spontaneous reversion from mild cognitive impairment (MCI) to normal cognition (NC) is little known. Based on the data of the Genetics of Personality Consortium and MCI participants from Alzheimer's Disease Neuroimaging Initiative, the authors investigate the effect of polygenic scores (PGS) for personality traits on the reversion of MCI to NC and its underlying neurobiology. PGS analysis reveals that PGS for conscientiousness (PGS‐C) is a protective factor that supports the reversion from MCI to NC. Gene ontology enrichment analysis and tissue‐specific enrichment analysis indicate that the protective effect of PGS‐C may be attributed to affecting the glutamatergic synapses of subcortical structures, such as hippocampus, amygdala, nucleus accumbens, and caudate nucleus. The structural covariance network (SCN) analysis suggests that the left whole hippocampus and its subfields, and the left whole amygdala and its subnuclei show significantly stronger covariance with several high‐cognition relevant brain regions in the MCI reverters compared to the stable MCI participants, which may help illustrate the underlying neural mechanism of the protective effect of PGS‐C.

Abstract Citri Reticulatae Pericarpium is a traditional Chinese medicine with extremely high health benefits as well as clinical value. In vivo and in vitro tests have proved that its main active secondary metabolites are flavonoids. However, they have not been comprehensively analyzed up to now mainly due to lack of suitable analysis method. To solve this problem, a novel strategy based on precursor ions locked and targeted MS/MS analysis was proposed. Firstly, the database of the flavonoids previously isolated from Citri Reticulatae Pericarpium was established to obtain the characteristics of their precursor ions. Secondly, after performing the full MS scan of the extract, all compounds in the total ion chromatogram were extracted by Compound Discoverer software. Thirdly, the precursor ions of the flavonoids were locked from the extracted compounds according to their characteristics, forming a precursor ions list. Finally, the precursor ions in the constructed list were performed targeted MS/MS analysis for structures characterization. As a result, total 187 flavonoids were successfully identified, and except for flavones, flavonols as well as dihydroflavones, some chalcones were also characterized from Citri Reticulatae Pericarpium for the first time.

Abstract Bietti crystalline corneoretinal dystrophy is an inherited retinal disease caused by mutations in CYP4V2, which results in blindness in the working-age population, and there is currently no available treatment. Here, we report the results of the first-in-human clinical trial (NCT04722107) of gene therapy for Bietti crystalline corneoretinal dystrophy, including 12 participants who were followed up for 180–365 days. This open-label, single-arm exploratory trial aimed to assess the safety and efficacy of a recombinant adeno-associated-virus-serotype-2/8 vector encoding the human CYP4V2 protein (rAAV2/8-hCYP4V2). Participants received a single unilateral subretinal injection of 7.5 × 1010 vector genomes of rAAV2/8-hCYP4V2. Overall, 73 treatment-emergent adverse events were reported, with the majority (98.6%) being of mild or moderate intensity and considered to be procedure- or corticosteroid-related; no treatment-related serious adverse events or local/systemic immune toxicities were observed. Compared with that measured at baseline, 77.8% of the treated eyes showed improvement in best-corrected visual acuity (BCVA) on day 180, with a mean ± standard deviation increase of 9.0 ± 10.8 letters in the 9 eyes analyzed (p = 0.021). By day 365, 80% of the treated eyes showed an increase in BCVA, with a mean increase of 11.0 ± 10.6 letters in the 5 eyes assessed (p = 0.125). Importantly, the patients’ improvement observed using multifocal electroretinogram, microperimetry, and Visual Function Questionnaire-25 further supported the beneficial effects of the treatment. We conclude that the favorable safety profile and visual improvements identified in this trial encourage the continued development of rAAV2/8-hCYP4V2 (named ZVS101e).

Abstract Hepatitis B virus is a globally distributed pathogen and the history of HBV infection in humans predates 10000 years. However, long-term evolutionary history of HBV in Eastern Eurasia remains elusive. We present 34 ancient HBV genomes dating between approximately 5000 to 400 years ago sourced from 17 sites across Eastern Eurasia. Ten sequences have full coverage, and only two sequences have less than 50% coverage. Our results suggest a potential origin of genotypes B and D in Eastern Asia. We observed a higher level of HBV diversity within Eastern Eurasia compared to Western Eurasia between 5000 and 3000 years ago, characterized by the presence of five different genotypes (A, B, C, D, WENBA), underscoring the significance of human migrations and interactions in the spread of HBV. Our results suggest the possibility of a transition from non-recombinant subgenotypes (B1, B5) to recombinant subgenotypes (B2 - B4). This suggests a shift in epidemiological dynamics within Eastern Eurasia over time. Here, our study elucidates the regional origins of prevalent genotypes and shifts in viral subgenotypes over centuries.

Background Type 2 diabetes mellitus (T2DM) has become a public health burden facing the whole world, with the rapid development of Internet and digital technology, intelligent service model plays an important role in the management of patients with T2DM. Objective To explore the effectiveness of wearable devices combined with health coaching in patients with T2DM. Methods A total of 315 patients with T2DM who were hospitalized in the Second Affiliated Hospital of Nanchang University from June 2020 to June 2021 were selected as the study subjects, and divided into the control group, the intervention A group and the intervention B group based on the method of randomized numerical table, the control group implemented the routine management measures based on capillary blood glucose monitoring, the intervention A group adopted the wearable devices for routine management, the intervention B group was managed by wearable devices combined with health coaching. The differences in glycemic and lipid control status and self-management behaviors among the three groups before and 3, 6, 9 and 12 months after intervention were compared. Results A total of 15 lost visits were made during the implementation of the study, and 300 study subjects were finally included in the analysis, with 100 in each of the three groups. There was an interaction between intervention method and time in the three groups on 2-hour postprandial blood glucose (2 hPG) , glycated hemoglobin (HbA1c) , number of hypoglycemic episodes, low-density lipoprotein cholesterol (LDL-C) , self-management behaviors of diabetes mellitus (2-DSCS) , and self-management behaviors of diabetic patients (SDSCA) scores (P

Background Successful aging can help to alleviate the aging process, but may be affected by household income. Objective To explore the impact of household income on successful aging and provide fundamental data for improving health equity for the elderly in China. Methods Data from the 2018 China Health and Retirement Longitudinal Study (CHARLS) were used to select participants aged 60 and above. The older adults were categorized into the high-income (≤33.33%) , middle-income (33.34%-66.66%) , and low-income (≥66.67%) groups based on the annual household income levels within each province. Successful aging was measured based on the Rowe and Kahn models and the multivariate Logistic regression was conducted to identify the effects of different levels of household income on successful aging. Results A total of 7 741 subjects were finally included with 2 192 (28.32%) , 2 680 (34.62%) and 2 869 (37.06%) in the low-income group, middle-income group and high-income group, respectively. The proportion of successful aging was 15.55% (1 204/7 741) among Chinese older adults in 2018, with 21.02% (603/2 869) for high-income group, 13.62% (365/2 680) for middle-income group, and 10.77% (236/2 192) for low-income group (P0.05) . The results of multivariate Logistic regression analysis showed that after controlling for demographic characteristics (age, gender, ethnicity, education level, and region of residence) , the proportion of successful aging in the middle-income and high-income groups was 1.226 times (OR=1.226, 95%CI=1.028-1.463) and 1.721 times (OR=1.721, 95%CI=1.450-2.044) as high as those in the low-income group; after controlling for health status and behavioral factors (night sleep duration, accidental falls, hospitalization in the past year, hearing, and masticatory function) , the proportion of successful aging in the high-income group was 1.559 times higher than that in the low-income group (OR=1.559, 95%CI=1.300-1.882) ; after controlling for home living environment (bathing facilities, home hygiene) , the proportion of successful aging in the high-income group was 1.461 times higher than that in the low-income group (OR=1.461, 95%CI=1.207-1.770) (P

Abstract Given the prohibited operating zones, losses, and valve point effects in power systems, energy optimization analysis in such systems includes numerous non-convex and non-smooth parameters, such as economic dispatch problems. In addition, in this paper, to include all possible scenarios in economic dispatch problems, multi-fuel generators, and transmission losses are considered. However, these features make economic dispatch problems more complex from a non-convexity standpoint. In order to solve economic dispatch problems as an important consideration in power systems, this paper presents a modified robust, and effective optimization algorithm. Here, some modifications are carried out to tackle such a sophisticated problem and find the best solution, considering multiple fuels, valve point effect, large-scale systems, prohibited operating zones, and transmission losses. Moreover, a few complicated power systems including 6, 13, and 40 generators which are fed by one type of fuel, 10 generators with multiple fuels, and two large-scale cases comprised of 80 and 120 generators are analyzed by the proposed optimization algorithm. The effectiveness of the proposed method, in terms of accuracy, robustness, and convergence speed is evaluated, as well. Furthermore, this paper explores the integration of cloud storage and internet of things (IoT) to augment the adaptability of monitoring capabilities of the proposed method in handling non-convex energy resource management and allocation problems across various generator quantities and constraints. The results show the capability of the proposed algorithm for solving non-convex energy resource management and allocation problems irrespective of the number of generators and constraints. Based on the obtained results, the proposed method provides good results for both small and large systems. The proposed method, for example, always yields the best results for the system of 6 power plants with and without losses, which are $15,276.894 and $15,443.7967. Moreover, the improvements made in the proposed method have allowed the economic dispatch problem regarding multi-fuel power plants to be solved not only with optimal results ($623.83) but also in less than 35 iterations. Lastly, the difference between the best-obtained results ($121,412) and the worst-obtained results ($121,316.1992) for the system of 40 power plants is only about $4 which is quite acceptable.

Abstract Temozolomide (TMZ) resistance presents a significant challenge in the treatment of gliomas. Although lysine demethylase 4A (KDM4A) has been implicated in various cancer‐related processes, its role in TMZ resistance remains unclear. This study aims to elucidate the contribution of KDM4A to TMZ resistance in glioma cells and its potential implications for glioma prognosis. We assessed the expression of KDM4A in glioma cells (T98G and U251MG) using qRT‐PCR and Western blot assays. To explore the role of KDM4A in TMZ resistance, we transfected siRNA targeting KDM4A into drug‐resistant glioma cells. Cell viability was assessed using the CCK‐8 assay and the TMZ IC50 value was determined. ChIP assays were conducted to investigate KDM4A, H3K9me3, and H3K36me3 enrichment on the promoters of ROCK2 and HUWE1. Co‐immunoprecipitation confirmed the interaction between HUWE1 and ROCK2, and we examined the levels of ROCK2 ubiquitination following MG132 treatment. Notably, T98G cells exhibited greater resistance to TMZ than U251MG cells, and KDM4A displayed high expression in T98G cells. Inhibiting KDM4A resulted in decreased cell viability and a reduction in the TMZ IC50 value. Mechanistically, KDM4A promoted ROCK2 transcription by modulating H3K9me3 levels. Moreover, disruption of the interaction between HUWE1 and ROCK2 led to reduced ROCK2 ubiquitination. Inhibition of HUWE1 or overexpression of ROCK2 counteracted the sensitization effect of si‐KDM4A on TMZ responsiveness in T98G cells. Our findings highlight KDM4A's role in enhancing TMZ resistance in glioma cells by modulating ROCK2 and HUWE1 transcription and expression through H3K9me3 and H3K36me3 removal.

Dihydrotanshinone I (DHT), a lipophilic compound extracted from Salvia miltiorrhiza, has cardiovascular protective effects, but the underlying molecular mechanisms of action have rarely been reported. Based on this, whether DHT affects cholesterol metabolism by regulating LDLR is investigated in this work. The results revealed that DHT can increase LDLR expression and promote LDL uptake by HepG2 cells. Meanwhile, DHT stabilizes LDLR mRNA expression by activating the epidermal growth factor receptor/extracellular signal-regulated kinase 1/2 (EGFR/erk1/2) signaling pathway. In addition, DHT inhibits the expression of the proprotein convertase subtilisin/kexin type 9 (PCSK9) by down-regulating the liver nuclear transcription factor 1 A (HNF1A) and up-regulating the forkhead box O3 (FOXO3). All of these indicate that DHT increases LDLR expression at the post-transcriptional and post-translational levels thereby promoting LDL-C metabolism. The potential mechanism of DHT to improve lipid metabolism has been revealed as a promising drug against AS.

In the context of stroke and revascularization therapy, brain ischemia-reperfusion injury is a significant challenge that leads to oxidative stress and inflammation. Central to the cell's intrinsic immunity is the cGAS-STING pathway, which is typically activated by unusual DNA structures. The involvement of oxidized mitochondrial DNA (ox-mtDNA)—an oxidative stress byproduct—in this type of neurological damage has not been fully explored. This study is among the first to examine the effect of ox-mtDNA on the innate immunity of neurons following ischemia-reperfusion injury. Using a rat model of transient middle cerebral artery occlusion and a cellular model of oxygen-glucose deprivation/reoxygenation, we have discovered that ox-mtDNA activates the cGAS-STING pathway in neurons. Importantly, pharmacologically limiting the release of ox-mtDNA into the cytoplasm reduces inflammation and improves neurological functions. Our findings suggest that targeting ox-mtDNA release may be a valuable strategy to attenuate brain ischemia-reperfusion injury following revascularization therapy for acute ischemic stroke.

Coronaviruses (CoVs) are enveloped single-stranded RNA viruses that predominantly attack the human respiratory system. In recent decades, several deadly human CoVs, including SARS-CoV, SARS-CoV-2, and MERS-CoV, have brought great impact on public health and economics. However, their high infectivity and the demand for high biosafety level facilities restrict the pathogenesis research of CoV infection. Exacerbated inflammatory cell infiltration is associated with poor prognosis in CoV-associated diseases. In this study, we used human CoV 229E (HCoV-229E), a CoV associated with relatively fewer biohazards, to investigate the pathogenesis of CoV infection and the regulation of neutrophil functions by CoV-infected lung cells. Induced pluripotent stem cell (iPSC)-derived alveolar epithelial type II cells (iAECIIs) exhibiting specific biomarkers and phenotypes were employed as an experimental model for CoV infection. After infection, the detection of dsRNA, S, and N proteins validated the infection of iAECIIs with HCoV-229E. The culture medium conditioned by the infected iAECIIs promoted the migration of neutrophils as well as their adhesion to the infected iAECIIs. Cytokine array revealed the elevated secretion of cytokines associated with chemotaxis and adhesion into the conditioned media from the infected iAECIIs. The importance of IL-8 secretion and ICAM-1 expression for neutrophil migration and adhesion, respectively, was demonstrated by using neutralizing antibodies. Moreover, next-generation sequencing analysis of the transcriptome revealed the upregulation of genes associated with cytokine signaling. To summarize, we established an in vitro model of CoV infection that can be applied for the study of the immune system perturbations during severe coronaviral disease.

Objective This study aimed to compare the effects of patient-controlled intravenous analgesia (PCIA) with and without low-basal infusion on postoperative hypoxaemia.Design A randomised parallel-group non-inferiority trial.Setting The trial was conducted at a grade-A tertiary hospital from December 2021 to August 2022.Participants 160 adults undergoing gastrointestinal tumour surgery and receiving postoperative PCIA.Interventions Participants randomly received a low-basal (0.1 mg/hour of hydromorphone) or no-basal infusion PCIA for postoperative 48 hours.Primary and secondary outcome measures Primary outcome was area under curve (AUC) per hour for hypoxaemia, defined as pulse oxygen saturation (SpO2)

In recent years, the ever-rising penetration of distributed photovoltaics (PV) power has presented substantial challenges in power system dispatch due to its inherent randomness and unpredictability. To bridge this gap, this paper proposes a two-stage robust optimization method for power system security dispatch considering traditional generators as well as flexible resources, such as load demand response and energy storage systems. Specifically, a price-based demand response model is established to optimize the system’s load curve during a day. On this basis, a two-stage optimization problem for day-ahead and intra-day power system dispatch model is proposed. The dispatch objective is to minimize the overall cost in worst-case scenarios through properly scheduling unit commitment (UC) as well as flexible resources in each dispatch interval. Column and constraint generation (C&CG) algorithm is adopted for problem solving. The effectiveness of the proposed method is validated by case studies based on a modified 6-node system and a 24-node system. Simulation results indicate that through appropriately scheduling the energy storage system and load demand response, the proposed dispatch method can significantly reduce the total operation cost of a PV rich power system, which in turn facilitates the integration of PV power.

Abstract Highly crystalline organic semiconductors are ideal materials for photocatalytic hydrogen evolution in water splitting. However, the instability and complex synthesis processes of most reported organic molecule‐based photocatalysts restrict their applications. In this study, we introduce benzo [1,2‐b:4,5‐bʹ] bis [1] benzothiophene‐3,9‐dicarboxylic acid, 5,5,11,11‐tetraoxide (FSOCA), a highly crystalline, stable molecular crystal that is easy to synthesize and serves as an efficient photocatalyst for the hydrogen evolution reaction. FSOCA exhibits high efficiency in sacrificial hydrogen evolution reaction (760 µmol h−1, 76 mmol g−1 h−1 at 330 mW cm−2; 570 µmol h−1, 57 mmol g−1 h−1 at 250 mW cm−2), and FSOCA remains stable during photocatalysis for up to 400 h. Experiments and theoretical studies confirmed the presence of hydrogen bonds between the sulfone group and the sacrificial agent (ascorbic acid). This interaction significantly improved the oxidation reaction kinetics and boosted the photocatalytic performance. This study presents a scalable and convenient approach to synthesize highly crystalline, active, and stable organic photocatalysts with potential applications in large‐scale photocatalysis.

Large yellow croaker (Larimichthys crocea), the most developing fish of China, suffering from both biotic and abiotic stressors. A genome-wide study was performed for the first time to investigate the roles of Toll-like receptor genes in large yellow croaker (LcTLRs) working in hypoxia response and Aeromonas hydrophila infection. 12 TLR genes were identified and annotated, and phylogenetic tree, analysis of structure and motifs demonstrated that TLRs were highly conserved. To further investigate the LcTLRs under environmental stress, expression pattern analysis of hypoxic response and Aeromonas hydrophila infection revealed that there were nine and six members of LcTLRs showing significant differential expression, indicating that they were concerned in hypoxia stress and disease responses. Meanwhile, their expression levels were validated utilizing qPCR. Taken together, a greater appreciation and understanding of TLRs function in the reaction to biotic and abiotic stress would ultimately lead to more efficiently environmental adaptation in large yellow croaker.

Objective This study aimed to compare the effectiveness of instant versus text messaging intervention (TMI) on antiretroviral therapy (ART) adherence among men who have sex with men (MSM) living with HIV. Methods This study was conducted in an infectious disease hospital of Jinan, China from October 2020 to June 2021, using non-randomized concurrent controlled design to compare the effectiveness of instant messaging intervention (IMI) versus TMI. The intervention strategies (health messaging, medication reminder, and peer education) and contents were consistent between the two groups, and the difference was service delivery method and type of information. The primary outcome was the proportion of achieving optimal ART adherence, defined as never missing any doses and delayed any doses more than 1 hour. Results A total of 217 participants (including 72 in TMI group and 145 in IMI group) were included in the study. The proportion of achieving optimal adherence was higher in IMI group than TMI group at the first follow-up (90.2% versus 77.6%, p = 0.021) and second follow-up (86.5% versus 76.6%, p = 0.083). The effect of IMI versus TMI on improving ART adherence was found not to be statistically significant (risk ratio (RR) = 1.93, 95% confidence interval (CI): 0.95–3.94) in complete-case analysis. However, when excluding participants who did not adhere to the interventions, a significant improvement was observed (RR = 2.77, 95%CI: 1.21–6.38). More participants in IMI group expressed highly rated satisfaction to the intervention services than those in TMI group (67.3% versus 50.0%). Conclusions The IMI demonstrated superior efficacy over TMI in improving ART adherence and satisfaction with intervention services. It is suggested that future digital health interventions targeting ART adherence should prioritize instant messaging with multimedia information in areas with Internet access. Trial registration The study was registered at the Chinese Clinical Trial Register (ChiCTR), with number [ChiCTR2000041282].

The presence of organic matter in lakes profoundly impacts drinking water supplies, yet treatment processes involving coagulants and disinfectants can yield carcinogenic disinfection by-products. Traditional assessments of organic matter, such as chemical oxygen demand (CODMn) and biochemical oxygen demand (BOD5), are often time-consuming. Alternatively, optical measurements of dissolved organic matter (DOM) offer a rapid and reliable means of obtaining organic matter composition data. Here we employed DOM optical measurements in conjunction with parallel factor analysis to scrutinize CODMn and BOD5 variability. Validation was performed using an independent dataset encompassing six lakes on the Yungui Plateau from 2014 to 2016 (n = 256). Leveraging multiple linear regressions (MLRs) applied to DOM absorbance at 254 nm (a254) and fluorescence components C1–C5, we successfully traced CODMn and BOD5 variations across the entire plateau (68 lakes, n = 271, R2 > 0.8, P 0.9) in mesotrophic lakes compared to oligotrophic and eutrophic lakes. This study underscores the utility of MLR-based DOM indices for inferring CODMn and BOD5 variability in plateau lakes and highlights the potential of integrating in situ and remote sensing platforms for water pollution early warning.

Wind turbines are one of the important carriers of clean energy utilization. Accurately and rapidly detecting wind turbine objects in large-scale remote sensing images can effectively monitor the development activities and optimize energy utilization. Addressing the detection challenges posed by the complex distribution scenes and the slender, dispersed structural characteristics of wind turbines in remote sensing images, this article proposes a remote sensing image wind turbine detector, RSWDet, based on neural networks. RSWDet comprises two innovative key modules. The first is a dual-branch structured point set detection head, which, through training, adapts to the unique features of wind turbines, enabling accurate detection in large-scale complex backgrounds. The second is the Low-level Feature Enhancement module, which compensates for the loss of wind turbine feature information during sampling by leveraging rich low-level feature information. Experimental verification of RSWDet was conducted on datasets and real-world scenes. The results demonstrate that RSWDet exhibits significant advantages compared to other algorithms, achieving the highest average accuracy of 83.1%, Precision of 97.8%, and Recall of 99% on the validation set. In the actual multiscene GF2 remote sensing image test, with a threshold of 0.4, the Precision can reach 85.3%, and the Recall can reach 89.9%.