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Abstract The rocket-based combined-cycle (RBCC) engine is regarded as one of the most viable propulsion systems for single-stage-to-orbit launch vehicles. Because of the relatively low total temperature of the incoming flow, it is difficult to maintain sustained and efficient subsonic combustion when the rocket engine is turned off. Mode transition and its control have also become critical techniques in the RBCC study. In the current work, it is proposed for the first time to improve the performance of RBCC engines in mode transition by using plasma combustion support. The numerical simulation and validation were conducted on the full path configuration of the RBCC engine, which is suitable for wide range operation. The impact of multi-channel gliding arc (MCGA) plasma-assisted combustion technology on the flow field was investigated during the transition phases from RBCC ejector/ramjet mode to ramjet/scramjet mode. The results show that: Adding arc plasma into the cavities at low Mach numbers promotes the heat release of the fuel, expanding the high-temperature flame range in the combustor. Although it weakens the ability of some air inlet to capture air, it overall increases engine thrust and diminishes aerodynamic drag during the transition process from ejector/ramjet mode. At high Mach numbers, the fast incoming flow speed results in the inability of the fuel to mix and burn with air in a timely manner, resulting in poor heat release and work performance. However, the addition of arc plasma for combustion support using the same mode transition method reduces the thrust fluctuation of the RBCC engine during the ramjet/scramjet mode transition process, greatly reducing the time required for mode transition, reducing engine resistance, and significantly improving engine thrust.

Panax ginseng, a venerable herb in traditional Chinese medicine, boasts a rich history of usage in the treatment of dementia, particularly in its various manifestations. However, despite its long-standing popularity and empirical evidence of effectiveness, the precise mechanisms underlying its therapeutic actions have remained elusive. Currently, research on pharmacodynamic components and mechanisms predominantly utilizes serum pharmacology and metabolomics research methods that are based on liquid chromatography-mass spectrometry technology. However, these methods are unable to capture the spatial distribution information of relevant substances, leading to a lack of comprehensive understanding of the pharmacodynamic components and their underlying mechanisms. To bridge this gap in knowledge, a method of spatial metabolomics and air flow assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI), was used to delve into the molecular mechanisms of Panax ginseng in treating Alzheimer’s disease (AD). The pharmacodynamic results demonstrated that Panax ginseng extract can significantly improve the state of brain pathological damage and spatial learning memory ability in AD model rats. This finding highlights the potential of ginseng as a therapeutic agent in AD management. Furthermore, the metabolomics analysis revealed that Panax ginseng modulates the levels of 19 biomarkers that are intricately linked to AD. These biomarkers span across 8 key metabolic pathways, including arginine and proline metabolism, purine metabolism, the tricarboxylic acid (TCA) cycle, and fatty acid metabolism. These pathways are essential for maintaining neuronal health and function, and their dysregulation is often associated with the pathogenesis of AD. Importantly, the study identified 7 active ginseng constituents that accumulate in brain tissue. These compounds work in a holistic manner to treat AD by modulating metabolites related to neuroinflammation, neuronal damage, energy deficits, and abnormal fatty acid metabolism. The comprehensive approach suggests that Panax ginseng may offer a multifaceted therapeutic strategy for AD. The unique capabilities of mass spectrometry imaging allow to analyze the spatial distribution of both endogenous and exogenous substances in parallel. This correspondence not only provides a deeper understanding of the specific effects of drug components, but also sheds light on how these components interact with the body’s endogenous metabolic networks to exert their therapeutic effects. In conclusion, the study provides new light on the mechanisms of action of Panax ginseng in treating AD and paves the way for future research and clinical applications of the ancient herb.

Abstract The fibrosis‐4 index (FIB‐4) is a noninvasive fibrosis test that is recommended for patients who are at risk of developing hepatic fibrosis. The aim of the study was to explore the correlation between FIB‐4 index and the decline of cognitive function among older patients with hypertension. The study used a cross‐sectional design to analyze data obtained from the NHANES 2011–2014. The significance of the FIB‐4 index correlation with cognitive function in individuals over the age of 60 was evaluated via multivariate regression models. The nonlinear link was described and fitted smoothed curves. There were a total of 2039 participants in the study, and those with a higher FIB‐4 index were more susceptible to developing cognitive decline. In the completely adjusted model, the association remained statistically significant between the FIB‐4 index and poor cognitive function as measured by CERAD: Total Score (OR = 0.72, 0.57−0.91), Animal Fluency Score (OR = 0.66, 0.48−0.91), and Digit Symbol Score (OR = 0.36, 0.17−0.77). A nonlinear association was found between the FIB‐4 and poor cognitive ability: Total Score, CERAD: Score Delayed Recall, Digit Symbol Score, and Animal Fluency Score. In elderly patients with hypertension, a high FIB‐4 index is correlated with an increased prevalence of cognitive decline. Hence, the FIB‐4 index could potentially serve as a valuable tool for determining individuals with hypertension who are susceptible to both liver‐related complications and cognitive impairment.

Abstract Background Viral infectious diseases of poverty (vIDPs) remain a significant global health challenge. Despite their profound impact, the burden of these diseases is not comprehensively quantified. This study aims to analyze the global burden of six major vIDPs, including coronavirus disease 2019 (COVID-19), HIV/AIDS, acute hepatitis, dengue, rabies, and Ebola virus disease (EVD), using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 (GBD 2021). Methods Following the GBD 2021 framework, we analyzed the incidence, mortality, and disability-adjusted life years (DALYs) of the six vIDPs across 204 countries and territories from 1990 to 2021. We examined the association between the Socio-Demographic Index (SDI) and the burden of vIDPs. All estimates were reported as numbers and rates per 100,000 population, calculated using the Bayesian statistical model employed by GBD 2021, with 95% uncertainty intervals (UI). Results In 2021, vIDPs caused approximately 8.7 million deaths and 259.2 million DALYs, accounting for 12.8% and 9.0% of the global all-cause totals, respectively. Globally, the burden of vIDPs varied significantly: COVID-19 caused around 7.9 million (95% UI: 7.5, 8.4) deaths and 212.0 million (95% UI 197.9, 234.7) DALYs in 2021. Acute hepatitis had the second-highest age-standardized incidence rate, with 3411.5 (95% UI: 3201.8, 3631.3) per 100,000 population, while HIV/AIDS had a high age-standardized prevalence rate, with 483.1 (95% UI: 459.0, 511.4) per 100,000 population. Dengue incidence cases rose from 26.5 million (95% UI: 3.9, 51.9) in 1990 to 59.0 million (95% UI: 15.5, 106.9) in 2021. Rabies, although reduced in prevalence, continued to pose a significant mortality risk. EVD had the lowest overall burden but significant outbreak impacts. Age-standardized DALY rates for vIDPs were significantly negatively correlated with SDI: acute hepatitis (r = −0.8, P

ABSTRACT: High-yield dairy cows typically undergo intense cellular metabolism, leading to oxidative stress in their mammary tissues. Our study found that compared with ordinary cows, these high-yield cows had significantly elevated levels of H2O2, lipoperoxidase, and total antioxidant capacity in their blood. This increased oxidative stress is associated with heightened expression of genes such as GCLC, GCLM, and SIRT1 and proteins such as SIRT1 in the mammary tissue of high-yield cows. We stimulated MAC-T cells with H2O2 at a concentration equal to the average H2O2 level in the serum of ethically high-yielding cows, as detected by an assay kit. Our observations revealed that short-term exposure (12 h) to H2O2 upregulated the expression of the SIRT1 gene and SIRT1 protein. It also increased gene expression for SOD2, CAT, GCLC, GCLM, PGC-1α, and NQO1, elevated the phosphorylation of AMPK, and enhanced protein expression of PGC-1α, NQO1, Nrf2, and HO-1, as well as reduced the phosphorylation of NF-κB. Additionally, short-term H2O2 stimulation resulted in increased total antioxidant capacity and levels of superoxide dismutase, glutathione, and catalase in the mammary epithelial cells of dairy cows. In contrast, prolonged exposure to H2O2 (24 h) yielded opposite results, indicating reduced antioxidant capacity. Further investigation showed that the SIRT1 inhibitor EX 527 could reverse the enhanced cellular antioxidant capacity triggered by short-term oxidative stress. However, it is crucial to note that although 12 h of H2O2 stimulation improved antioxidant capacity, reactive oxygen species (ROS) and malondialdehyde (MDA) levels inside the cell gradually increased over time, suggesting greater damage under long-term stimulation. Conversely, the SIRT1 activator SRT 2104 could reverse the reduced cellular antioxidant capacity caused by long-term oxidative stress and significantly inhibit the accumulation of ROS and MDA. Notably, SRT 2104 demonstrated similar effects in MAC-T cells during lactation. In summary, SIRT1 plays a crucial role in regulating the antioxidant capacity of mammary epithelial cells in dairy cows. This discovery provides valuable insights into the antioxidant mechanisms of mammary cells, which can serve as a theoretical foundation for future mammary health strategies.

Abstract To date, the types of fuels used in pottery kilns during the Western Zhou Dynasty have not been adequately addressed. Samples from updraft kilns and semi-downdraft kilns at the Fengjing site, the capital in the late Western Zhou period, were selected for analysis. Through phytolith and wood charcoal analysis, various grasses mainly Panicoideae, Pooideae, and Eragrostidoideae, as well as millet, rice, and wheat crops were identified. Additionally, wood primarily from trees of the Quercus, Ulmus, and Liquidambar taxa was found. These findings suggest that different pottery kilns used similar fuels, demonstrating a broad-spectrum rather than specialized fuel utilization during the Zhou period.

Abstract Background Maxillary expansion is an important treatment method for maxillary transverse hypoplasia. Different methods of maxillary expansion should be carried out depending on the midpalatal suture maturation levels, and the diagnosis was validated by palatal plane cone beam computed tomography (CBCT) images by orthodontists, while such a method suffered from low efficiency and strong subjectivity. This study develops and evaluates an enhanced vision transformer (ViT) to automatically classify CBCT images of midpalatal sutures with different maturation stages. Methods In recent years, the use of convolutional neural network (CNN) to classify images of midpalatal suture with different maturation stages has brought positive significance to the decision of the clinical maxillary expansion method. However, CNN cannot adequately learn the long-distance dependencies between images and features, which are also required for global recognition of midpalatal suture CBCT images. The Self-Attention of ViT has the function of capturing the relationship between long-distance pixels of the image. However, it lacks the inductive bias of CNN and needs more data training. To solve this problem, a CNN-enhanced ViT model based on transfer learning is proposed to classify midpalatal suture CBCT images. In this study, 2518 CBCT images of the palate plane are collected, and the images are divided into 1259 images as the training set, 506 images as the verification set, and 753 images as the test set. After the training set image preprocessing, the CNN-enhanced ViT model is trained and adjusted, and the generalization ability of the model is tested on the test set. Results The classification accuracy of our proposed ViT model is 95.75%, and its Macro-averaging Area under the receiver operating characteristic Curve (AUC) and Micro-averaging AUC are 97.89% and 98.36% respectively on our data test set. The classification accuracy of the best performing CNN model EfficientnetV2_S was 93.76% on our data test set. The classification accuracy of the clinician is 89.10% on our data test set. Conclusions The experimental results show that this method can effectively complete CBCT images classification of midpalatal suture maturation stages, and the performance is better than a clinician. Therefore, the model can provide a valuable reference for orthodontists and assist them in making correct a diagnosis.

Abstract Several (inter)national longitudinal dementia observational datasets encompassing demographic information, neuroimaging, biomarkers, neuropsychological evaluations, and muti-omics data, have ushered in a new era of potential for integrating machine learning (ML) into dementia research and clinical practice. ML, with its proficiency in handling multi-modal and high-dimensional data, has emerged as an innovative technique to facilitate early diagnosis, differential diagnosis, and to predict onset and progression of mild cognitive impairment and dementia. In this review, we evaluate current and potential applications of ML, including its history in dementia research, how it compares to traditional statistics, the types of datasets it uses and the general workflow. Moreover, we identify the technical barriers and challenges of ML implementations in clinical practice. Overall, this review provides a comprehensive understanding of ML with non-technical explanations for broader accessibility to biomedical scientists and clinicians.

Abstract Background To provide reference for clinical development of ADCs in the industry, we analyzed the landscape and characteristics of clinical trials about antibody-drug conjugates (ADCs). Method Clinical trials to study ADCs used for the pharmacotherapy of cancers initiated by the sponsor were searched in the Cite line Pharma Intelligence (Trialtrove database), and the landscape and characteristics of these clinical trials were analyzed from multiple perspectives, such as the number, phases, status, indications, and targets of the clinical trials. Result As of December 31, 2022, a total of 431 clinical trials have been initiated to study ADCs used for the pharmacotherapy of cancers, and the number of the last 10 years was 5.5 times as large as the first 11 years. These clinical trials involved 47 indications, including breast cancer, lymphoma (lymphoma, non-Hodgkin’s and lymphoma, Hodgkin’s), unspecified solid tumor, bladder cancer and lung cancer (lung, non-small cell cancer and lung, small cell cancer). As for each of these five indications, 50 + clinical trials have been carried out, accounting for as high as 48.50% (454/936). ADCs involve 38 targets, which are relatively concentrated. Among them, ERBB2 (HER2) and TNFRSF8 (CD30) involve in 100 + registered clinical trials, and TNFRSF17 (BCMA), NECTIN4 and CD19 in 10 + trials. The clinical trials for these five targets account for 79.02% (354/448) of the total number. Up to 93.97% (405/431) of these clinical trials explored the correlation between biomarkers and efficacy. Up to 45.91% (292/636) of Lots (lines of treatment) applied in the clinical trials were the second line. Until December 31, 2022, 54.52% (235/431) of the clinical trials have been completed or terminated. Conclusion ADCs are a hotspot of research and development in oncology clinical trials, but the indications, targets, phases, and Lot that have been registered are seemingly relatively concentrated at present. This study provides a comprehensive analysis which can assist researchers/developer quickly grasp relevant knowledge to assess a product and also providing new clues and ideas for future research.

When vibrations generated by marine machinery propagate through a ship’s hull into the ocean, they produce low-frequency radiated noise with distinct “acoustic fingerprint” characteristics. This noise, characterized by stable and concentrated energy, long transmission distances, and difficulty in elimination, becomes the primary target for enemy sonar detection. Active vibration isolation serves as a critical method for reducing low-frequency vibrations in ships and enhancing their acoustic stealth performance. However, control challenges persist, including multi-frequency excitation, frequency fluctuation, multi-channel coupling, and slow convergence speed. To address these issues, this paper introduced an innovative multi-channel decentralized decoupling filtered-x least mean square (DMFxLMS) algorithm. Firstly, a recursive least squares identification algorithm with a forgetting factor was proposed, taking into account the characteristics of single-input, multi-output and multi-input, and multi-output control systems, effectively enhancing the algorithm’s convergence speed and control accuracy. Secondly, based on the decentralized decoupling control concept, the multi-channel control system was simplified into parallel single-channel control loops. The control weight coefficient updates were only related to adjacent error signals, significantly reducing the algorithm’s computational complexity. Thirdly, an anti-impact link was designed to improve the algorithm’s robustness, considering the interference caused by other mechanical equipment during the control process. The influence of abnormal error signals in the control weight coefficient correction term was suppressed, and a percentage function was introduced to limit the output signal. Finally, the feasibility and effectiveness of the DMFxLMS algorithm were verified through simulations and experiments. The results demonstrated that the DMFxLMS algorithm achieved significant control effects for both constant frequency line spectrum excitation and frequency fluctuating line spectrum excitation, fulfilling the objective of reducing base vibration. The DMFxLMS algorithm exhibited fast convergence and excellent robustness, making it suitable for practical engineering applications.

In biological systems, nanobubbles (NBs) effectively enhance hydrogen molecule retention and scavenging reactive oxygen species (ROS), but the underlying mechanisms remain elusive. To investigate this, we prepared hydrogen NB water samples with consistent dissolved hydrogen levels but varying NB densities to explore their physicochemical properties and effects on green algae (Chlorella vulgaris) under oxidative stress induced by copper ions (Cu2+) and cadmium ions (Cd2+). The results indicated a strong correlation between the hydrogen NB number density and the 25 % inhibitory concentration of Cu2+ over 24 h, with ROS removal efficiency increased with the NB number density. Gas chromatography showed that the hydrogen NBs in the solution had a high gas density that enhanced hydrogen transport into C. vulgaris. With regard to mitochondrial activity, hydrogen NBs were observed to enhance the function of mitochondrial complexes I and V and increase the mitochondrial membrane potential. Experiments with C. vulgaris mitochondrial electrodes showed that the electron transfer rates increased significantly in the presence of hydrogen NBs. We concluded that the high gas density of hydrogen NBs augments intracellular hydrogen delivery and strengthens mitochondrial functions.

Abstract Facing the global challenge of water scarcity, solar‐driven desalination is considered a sustainable technology for obtaining freshwater from seawater. However, issues such as uncontrolled salt crystallization and bacterial contamination limit its efficiency and practicality. This study proposes an innovative solar‐driven evaporator designed to address these challenges using optimized shape design and advanced photothermal materials. Based on finite element analyses, cylindrical evaporators with a “Starburst Turbine” shape are designed and fabricated, achieving directional salt crystallization and a record‐breaking water collection rate of 3.56 kg m−2 h−1 and an evaporation rate of 4.57 kg m−2 h−1 under one sun illumination. During continuous 60‐h illumination tests, the evaporator maintained a stable evaporation rate, attributed to its excellent directional salt crystallization capability. Additionally, the evaporator demonstrates superior photodynamic antibacterial performance and photocatalytic degradation of organic pollutants. Under one sun illumination for 1 h, it achieves 100% sterilization of S. aureus and E. coli, and a 95.4% degradation of methylene blue (MB), demonstrating its potential to purify various wastewater types. These findings underscore the significant scientific and practical value of integrating antibacterial and photocatalytic functions into solar water purification materials, providing a sustainable solution to global water scarcity challenges and environmental protection.

Abstract A large‐scale apparent polar wander occurred during the Jurassic interval, which is interpreted as true polar wander (TPW). As the motion is nearly orthogonal to the TPW axis, the North China Block (NCB) experienced the largest latitudinal and environmental changes and provides unique constraints on Jurassic TPW. However, due to the lack and uneven quality of paleomagnetic data, TPW records in North China are controversial. Here, we report a new paleomagnetic pole (80.8°N, 13.0°E, A95 = 7.4°) from the late Jurassic sills and dykes that intrude the Nandaling and Xiahuayuan formations in the NCB. The new pole places the NCB at 36.8° ± 7.4°N at 155 ± 3.4 Ma, using Beijing as the reference site. Combined with the reliable Jurassic poles, our study reveals a large, steady southward shift of 37.3° ± 7.2° for the NCB during the Middle and Late Jurassic, and reflects a component of TPW. The position of ∼155 Ma pole also supports significant TPW prior to ∼160 Ma and agrees with proposals attributing the diachronous 165–155 Ma aridification across the Eastern Asian blocks.

IntroductionDue to the high mortality rate and increasing severity of antibiotic resistance, there is a growing interest in new treatments for Klebsiella pneumoniae (KP)-induced pneumonia. Research has shown that the single herbs of SiHuangQingXinWan (SHQXW) are effective in treating pneumonia caused by KP. The PI3K/AKT signaling pathway has garnered attention for its potential role in the management of bacterial infections. This study aimed to evaluate the anti-pneumonia effect of SHQXW and to investigate its mechanism of action.Materials and MethodsThe potential plant metabolites and molecular targets of SHQXW in the context of pneumonia were determined through ultra-high performance liquid chromatography-tandem mass-spectrometry (UHPLC-MS/MS) and bioinformatics analysis. The therapeutic effect of SHQXW was evaluated in a KP-induced pneumonia murine model with imipenem/cilastatin as a positive control. Transcriptomics and non-targeted metabolomics were carried out to unveil potential mechanisms and targets for anti-pneumonia effects. Additionally, an in-depth exploration on the PI3K/AKT signaling pathway was conducted in this study.ResultsA total of 24 potential plant metabolites and 285 SHQXW-pneumonia-related targets selected by Homo sapiens were identified in this study. The tested doses of SHQXW significantly reduced mortality, improved body weight, decreased the lung index, reduced the bacterial load, and alleviated lung pathological damage in the KP-induced pneumonia murine model (p < 0.05). Notably, 1.3 g/kg/day of SHQXW provided the most effective protective outcome. Furthermore, SHQXW demonstrated the ability to suppress the production of inflammatory factors such as IL-1α, IL-1β, IL-3, IL-6, IL-12p70, G-CSF, GM-CSF, MCP-1, KC, and TNF-α. Analysis of transcriptomic and metabolomic data revealed that SHQXW could modulate inflammation-related signaling pathways (TNF, HIF-1, NF-κB, and PI3K/AKT) and metabolites to regulate pulmonary inflammation. Additional experiments using RT-qPCR and western blotting indicated that SHQXW may exert anti-inflammatory effects by activating the PI3K/AKT pathway.DiscussionThe findings indicate that SHQXW effectively reduces inflammation in mice with KP-induced pneumonia by modulating inflammatory signaling pathways and metabolites, rather than by directly inhibiting the growth of KP. This study introduces a novel treatment approach for KP-induced pneumonia and presents a new outlook on drug development.

Abstract Chronic kidney disease (CKD) poses a significant global health dilemma, emerging from complex causes. Although our prior research has indicated that a deficiency in Reticulon-3 (RTN3) accelerates renal disease progression, a thorough examination of RTN3 on kidney function and pathology remains underexplored. To address this critical need, we generated Rtn3-null mice to study the consequences of RTN3 protein deficiency on CKD. Single-cell transcriptomic analyses were performed on 47,885 cells from the renal cortex of both healthy and Rtn3-null mice, enabling us to compare spatial architectures and expression profiles across 14 distinct cell types. Our analysis revealed that RTN3 deficiency leads to significant alterations in the spatial organization and gene expression profiles of renal cells, reflecting CKD pathology. Specifically, RTN3 deficiency was associated with Lars2 overexpression, which in turn caused mitochondrial dysfunction and increased reactive oxygen species levels. This shift induced a transition in renal epithelial cells from a functional state to a fibrogenic state, thus promoting renal fibrosis. Additionally, RTN3 deficiency was found to drive the endothelial-to-mesenchymal transition process and disrupt cell-cell communication, further exacerbating renal fibrosis. Immunohistochemistry and Western-Blot techniques were used to validate these observations, reinforcing the critical role of RTN3 in CKD pathogenesis. The deficiency of RTN3 protein in CKD leads to profound changes in cellular architecture and molecular profiles. Our work seeks to elevate the understanding of RTN3’s role in CKD’s narrative and position it as a promising therapeutic contender.

The rapid acceleration of global warming has led to an increased burden of high temperature-related diseases (HTDs), highlighting the need for advanced evidence-based management strategies. We have developed a conceptual framework aimed at alleviating the global burden of HTDs, grounded in the One Health concept. This framework refines the impact pathway and establishes systematic data-driven models to inform the adoption of evidence-based decision-making, tailored to distinct contexts. We collected extensive national-level data from authoritative public databases for the years 2010–2019. The burdens of five categories of disease causes – cardiovascular diseases, infectious respiratory diseases, injuries, metabolic diseases, and non-infectious respiratory diseases – were designated as intermediate outcome variables. The cumulative burden of these five categories, referred to as the total HTD burden, was the final outcome variable. We evaluated the predictive performance of eight models and subsequently introduced twelve intervention measures, allowing us to explore optimal decision-making strategies and assess their corresponding contributions. Our model selection results demonstrated the superior performance of the Graph Neural Network (GNN) model across various metrics. Utilizing simulations driven by the GNN model, we identified a set of optimal intervention strategies for reducing disease burden, specifically tailored to the seven major regions: East Asia and Pacific, Europe and Central Asia, Latin America and the Caribbean, Middle East and North Africa, North America, South Asia, and Sub-Saharan Africa. Sectoral mitigation and adaptation measures, acting upon our categories of Infrastructure & Community, Ecosystem Resilience, and Health System Capacity, exhibited particularly strong performance for various regions and diseases. Seven out of twelve interventions were included in the optimal intervention package for each region, including raising low-carbon energy use, increasing energy intensity, improving livestock feed, expanding basic health care delivery coverage, enhancing health financing, addressing air pollution, and improving road infrastructure. The outcome of this study is a global decision-making tool, offering a systematic methodology for policymakers to develop targeted intervention strategies to address the increasingly severe challenge of HTDs in the context of global warming.

Abstract Cross-sectional studies have demonstrated strong associations between physical frailty and depression. However, the evidence from prospective studies is limited. Here, we analyze data of 352,277 participants from UK Biobank with 12.25-year follow-up. Compared with non-frail individuals, pre-frail and frail individuals have increased risk for incident depression independent of many putative confounds. Altogether, pre-frail and frail individuals account for 20.58% and 13.16% of depression cases by population attributable fraction analyses. Higher risks are observed in males and individuals younger than 65 years than their counterparts. Mendelian randomization analyses support a potential causal effect of frailty on depression. Associations are also observed between inflammatory markers, brain volumes, and incident depression. Moreover, these regional brain volumes and three inflammatory markers—C-reactive protein, neutrophils, and leukocytes—significantly mediate associations between frailty and depression. Given the scarcity of curative treatment for depression and the high disease burden, identifying potential modifiable risk factors of depression, such as frailty, is needed.

Abstract Previous studies suggested odor stimulation may influence feeding of premature neonates. Therefore, this systematic review and meta-analysis of randomized controlled trials was conducted to assess the effect of human milk odor stimulation on feeding of premature infants. All randomized controlled trials related to human milk odor stimulation on feeding in premature infants published in PubMed, Cochrane, Library, Medline, Embase, Web of science databases and Chinese biomedical literature databases, China National Knowledge Infrastructure, China Science and Technology Journal Database (VIP) and Wanfang Chinese databases were searched, and The Cochrane Handbook 5.1.0 was used to evaluate the quality and authenticity of the literature. Relevant information of the included studies was extracted and summarized, and the evaluation indexes were analyzed using ReviewManager5.3. The retrieval time was from the establishment of the database to July 28, 2022.12 articles were assessed for eligibility, and six randomized controlled studies were eventually included in the meta-analysis (PRISMA). A total of 6 randomized controlled studies with 763 patients were finally included in the study, and the quality evaluation of literatures were all grade B. Human milk odor stimulation reduced the transition time to oral feeding in premature infants [SMD = − 0.48, 95% CI (− 0.69, − 0.27), Z = 4.54, P

Abstract Dietary salt has been associated with cognitive impairment in mice, possibly related to damaged synapses and tau hyperphosphorylation. However, the mechanism underlying how dietary salt causes cognitive dysfunction remains unclear. In our study, either a high-salt (8%) or normal diet (0.5%) was used to feed C57BL/6 mice for three months, and N2a cells were cultured in normal medium, NaCl medium (80 mM), or NaCl (80 mM) + Liraglutide (200 nM) medium for 48 h. Cognitive function in mice was assessed using the Morris water maze and shuttle box test, while anxiety was evaluated by the open field test (OPT). Western blotting (WB), immunofluorescence, and immunohistochemistry were utilized to assess the level of Glucagon-like Peptide-1 receptor (GLP-1R) and mTOR/p70S6K pathway. Electron microscope and western blotting were used to evaluate synapse function and tau phosphorylation. Our findings revealed that a high salt diet (HSD) reduced the level of synaptophysin (SYP) and postsynaptic density 95 (PSD95), resulting in significant synaptic damage. Additionally, hyperphosphorylation of tau at different sites was detected. The C57BL/6 mice showed significant impairment in learning and memory function compared to the control group, but HSD did not cause anxiety in the mice. In addition, the level of GLP-1R and autophagy flux decreased in the HSD group, while the level of mTOR/p70S6K was upregulated. Furthermore, liraglutide reversed the autophagy inhibition of N2a treated with NaCl. In summary, our study demonstrates that dietary salt inhibits the GLP-1R/mTOR/p70S6K pathway to inhibit autophagy and induces synaptic dysfunction and tau hyperphosphorylation, eventually impairing cognitive dysfunction.

Wind power generation has become an indispensable part of the power supply side of the power grid. Due to the intermittent and uncertain characteristics of wind energy, short-term wind power prediction plays an important role in the stable operation of power system. By constructing the digital twin model, real-time and high-precision prediction of wind energy is realized. First, the genetic algorithm-support vector machine (GA-SVM) algorithm is used to build the model. Multidimensional sensors and meteorological stations of the virtual wind power generation system collected the meteorological data of the environment and updated the meteorological history database at the same time. Second, based on the collected meteorological data, the preliminary prediction results are obtained, and by searching in the historical database, the predicted value and the actual output value of wind turbines or wind farms under similar conditions are obtained. Finally, the prediction results of the GA-SVM are modified to obtain the predicted value of the digital twin model. The prediction method can greatly improve the accuracy of the short-term forecast of wind energy.

Abstract Background Chronic back pain affected 619 million people globally in 2020 which accounts for a heavy disease burden causing tremendous productivity losses. Current therapies including ibuprofen, duloxetine, and opioids might cause side effects and even severe drug use disorders. Therefore, a non‐pharmacologic therapy with better or equivalent efficacy and fewer side effects is needed. Methods We did a multi‐center, single‐blinded, randomized, positive drug controlled, clinical trial. Patients with chronic back pain in moderate severity were randomized into receiving hot stone massage or flurbiprofen plaster group. Both interventions were 2 weeks with a follow‐up of 4 weeks. The primary outcome was the change in the score of the Global Pain Scale (GPS) from baseline to week 2. Secondary outcomes included Numerical Rating Scale (NRS), Chronic Pain Acceptance Questionnaire (CPAQ), Pain Self‐Efficacy Questionnaire (PSEQ), Hospital Anxiety and Depression Scale (HADS), and Short Form‐36 (SF36) from baseline to week 2 and week 6. Exploratory outcome assessment included the muscle thickness measured by ultrasound. Any adverse event was monitored throughout the study period. Results A total of 120 patients were enrolled in this trial. At 2 weeks GPS decreased significantly in the hot stone massage group compared to the flurbiprofen group (difference between groups = ‐8.1 points, 95% confidence interval [CI] ‐15.8 to ‐0.3, p = 0.047). Moreover, hot stone massage also showed more improvement at 2 weeks compared to flurbiprofen, including NRS (‐0.5 points, 95% CI ‐1.0 to ‐0.1, p = 0.029), PSEQ (5.4 points, 95% CI 0.5 to 10.2, p = 0.030), and mental component of Short Form‐36 (SF‐36) (1.7 points, 95% CI 0.4 to 2.9, p = 0.010), but not in CPAQ (p = 0.131), HADS (p = 0.303 for depression, p = 0.399 for anxiety), or SF‐36 (p = 0.129 for physical component, p = 0.246 for social component, p = 0.076 for fatigue component). A total of two participants in the hot stone massage group reported mild pain on skin surface when receiving the procedure at the first intervention session.

Background: Male breast cancer (MBC) is a rare disease. Although several large-scale studies have investigated MBC patients in other countries, the features of MBC patients in China have not been fully explored. This study aims to explore the features of Chinese MBC patients comprehensively. Methods: We retrospectively collected data of MBC patients from 36 centers in China. Overall survival (OS) was evaluated by the Kaplan-Meier method, log-rank test, and Cox regression analyses. Multivariate Cox analyses were used to identify independent prognostic factors of the patients. Results: In total, 1119 patients were included. The mean age at diagnosis was 60.9 years, and a significant extension over time was observed (P

Abstract Current global climate models (GCMs), limited to grid‐scale land‐atmosphere coupling, cannot represent subgrid urban‐rural precipitation contrasts. This study develops an innovative two‐way subgrid land‐atmosphere coupling framework in the National Center for Atmospheric Research (NCAR) Community Earth System Model version 2 (CESM2) to explicitly resolve land‐atmosphere interaction over subgrid individual land units. Results show that urban heat island (UHI) leads to the urban rainfall effect (URE), which in turn alleviates overestimated UHI over China in CESM2. The URE manifests as a shift toward more heavy precipitation and less light precipitation in world urban areas than in surrounding rural counterparts. This feature is consistent with available observations. In heavy precipitation situations, the UHI promotes atmospheric instability and enhances atmospheric water vapor holding capacity, resulting in more heavy precipitation in urban areas. Conversely, in light precipitation situations, the UHI and decreased evaporation from urban impermeable surfaces diminish atmospheric relative humidity, suppressing light precipitation.

Increasing the utilisation rate of waste glass in asphalt mixtures, especially that with a wide range of particle sizes, is of great importance to resource recycling, while it may bring drawbacks to the engineering performance of asphalt mixtures. Incorporating polyurethane (PU) as a modifier can enhance asphalt mixture's performance, but there is limited research considering the usage of waste glass as aggregates. In this study, PU modified asphalt mixtures were prepared, incorporating waste glass particles ranging in size from 2.36 mm to 9.5 mm as a portion of the aggregates. Optimal preparation methods and mix designs for the PU-modified asphalt binder were determined through a series of tests designed based on Orthogonal method. The performances of the PU-modified asphalt binders were then evaluated to guide the selection of the optimal preparation method and mix design. PU-modified waste glass asphalt mixtures were then prepared and their engineering performances were assessed at various glass-to-aggregate ratios. The results show that scheme PU-1 with a shearing temperature of 140°C, a shearing time of 10 min, a PU content of 10% and a compatibiliser content of 2% is suggested for preparing the PU-modified asphalt binder, which shows the best performances due to superior chemical modification and compatibility. Higher glass content decreases the high/low-temperature performance, but it can be improved by adding silane coupling agent or hydrated lime, with the latter showing better results. The incorporation of glass particles has little impact on anti-sliding performance, and asphalt mixtures maintain excellent anti-sliding properties up to a 20% replacement rate. Overall, the performance of the asphalt with waste glass up to 15% can meet the specification requirements. This novel approach offers a potential solution to enhance the incorporation of waste materials in asphalt construction, contributing to sustainable and environmentally-friendly road construction.

Abstract Background Understanding the clinical implications of autoimmune manifestations associated with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is essential to reduce its consequences. This study was aimed at determining the activities of new‐onset primary Sjögren syndrome (pSS) since the emergence of SARS‐CoV‐2. Methods This retrospective cohort study included data from 471 participants with dry mouths and eyes who had been attending Nanjing Drum Tower Hospital since December 2019. By April 2023, patients diagnosed with pSS were sequentially assigned to vaccinated group (n = 24) or vaccinated and infected group based on exposure (n = 20). Patients diagnosed with pSS within 3 months of vaccination against SARS‐CoV‐2 were assigned to a vaccinated group, and those who had been vaccinated and then developed pSS within 3 months of follow up after direct exposure to SARS‐CoV‐2 were assigned to a vaccinated and infected group. The controls comprised age‐ and sex‐matched patients who had not been exposed to SARS‐CoV‐2 before December 2019 (n = 21). We then compared data among the three groups. Results The vaccinated and infected patients had more fever, malaise, splenomegaly, and weight loss before diagnosis and a higher European Alliance of Associations for Rheumatology Sjögren's syndrome disease activity index at the time of onset than the other two groups. Vaccinated patients had a higher frequency of anti‐nuclear antibody (ANA) titers > 1:320 (n = 12; 50%) and anti‐phospholipid antibodies (aPL) (n = 7; 29%) than the controls. The frequency of anti‐Ro/SSA antibodies (13, 65%), ANA titers > 1:320 (n = 16; 80%), and aPLs (n = 7; 29%) (n = 5; 25%) were all significantly higher in vaccinated patients with infection than those in the controls. Higher doses of glucocorticoids, cyclosporin A, and tacrolimus were administered to the vaccinated and infected than the vaccinated and control groups (p

Abstract P. ginseng is a precious traditional Chinese functional food, which is used for both medicinal and food purposes, and has various effects such as immunomodulation, anti-tumor and anti-oxidation. The growth year of P. ginseng has an important impact on its medicinal and economic values. Fast and nondestructive identification of the growth year of P. ginseng is crucial for its quality evaluation. In this paper, we propose a FC-CNN network that incorporates spectral and spatial features of hyperspectral images to characterize P. ginseng from different growth years. The importance ranking of the spectra was obtained using the random forest method for optimal band selection. Based on the hyperspectral reflectance data of P. ginseng after radiometric calibration and the images of the best five VNIR bands and five SWIR bands selected, the year-by-year identification of P. ginseng age and its identification experiments for food and medicinal purposes were conducted, and the FC-CNN network and its FCNN and CNN branch networks were tested and compared in terms of their effectiveness in the identification of P. ginseng growth years. It has been experimentally verified that the best year-by-year recognition was achieved by utilizing images from five visible and near-infrared important bands and all spectral curves, and the recognition accuracy of food and medicinal use reached 100%. The FC-CNN network is significantly better than its branching model in the effect of edible and medicinal identification. The results show that for P. ginseng growth year identification, VNIR images have much more useful information than SWIR images. Meanwhile, the FC-CNN network utilizing the spectral and spatial features of hyperspectral images is an effective method for the identification of P. ginseng growth year.

Abstract While many studies have sought to explore the degree to which sarcopenia-related traits are associated with cognitive performance, these studies have yielded contradictory results without any clear indication of the causality of such relationships. In efforts to better understand associations between sarcopenia-related traits and cognitive ability, a series of multivariate linear regression assessments were carried out upon datasets derived through the National Health and Nutrition Examination Survey (NHANES). Of these, cognitive performance was assessed by the Digit Symbol Substitution Test (DDST), the Consortium to Establish a Registry for Alzheimer’s Disease Immediate Recall Test (CERAD-IR), Delayed Recall Test (CERAD-DR) and Animal Fluency Test (AFT). Causal relationships between the two were further inferred via a two-sample Mendelian randomization (MR) analysis approach. Sarcopenia-related traits considered in these assessments included walking speed, appendicular skeletal muscle mass (ASM), and hand grip strength (HGS). Walking speed, ASM, and HGS were all significantly independently related to cognitive scores following adjustment for covariates. MR assessments also identified that each 1-SD higher walking speed and appendicular lean mass were causally and respectively associated with a 0.34 [standard error (SE) = 0.09; p

Abstract Background Modifying diet is crucial for diabetes and complication management. Numerous studies have shown that adjusting eating habits to align with the circadian rhythm may positively affect metabolic health. However, eating midpoint, eating duration, and their associations with diabetic kidney disease (DKD) are poorly understood. Methods The National Health and Nutrition Examination Survey (2013–2020) was examined for information on diabetes and dietary habits. From the beginning and ending times of each meal, we calculated the eating midpoint and eating duration. Urinary albumin-to-creatinine ratio (UACR) ≥ 30 mg/g and/or estimated glomerular filtration rate (eGFR)

Abstract Aim This study aimed to assess the performance of OpenAI’s ChatGPT in generating diagnosis based on chief complaint and cone beam computed tomography (CBCT) radiologic findings. Materials and methods 102 CBCT reports (48 with dental diseases (DD) and 54 with neoplastic/cystic diseases (N/CD)) were collected. ChatGPT was provided with chief complaint and CBCT radiologic findings. Diagnostic outputs from ChatGPT were scored based on five-point Likert scale. For diagnosis accuracy, the scoring was based on the accuracy of chief complaint related diagnosis and chief complaint unrelated diagnoses (1–5 points); for diagnosis completeness, the scoring was based on how many accurate diagnoses included in ChatGPT’s output for one case (1–5 points); for text quality, the scoring was based on how many text errors included in ChatGPT’s output for one case (1–5 points). For 54 N/CD cases, the consistence of the diagnosis generated by ChatGPT with pathological diagnosis was also calculated. The constitution of text errors in ChatGPT’s outputs was evaluated. Results After subjective ratings by expert reviewers on a five-point Likert scale, the final score of diagnosis accuracy, diagnosis completeness and text quality of ChatGPT was 3.7, 4.5 and 4.6 for the 102 cases. For diagnostic accuracy, it performed significantly better on N/CD (3.8/5) compared to DD (3.6/5). For 54 N/CD cases, 21(38.9%) cases have first diagnosis completely consistent with pathological diagnosis. No text errors were observed in 88.7% of all the 390 text items. Conclusion ChatGPT showed potential in generating radiographic diagnosis based on chief complaint and radiologic findings. However, the performance of ChatGPT varied with task complexity, necessitating professional oversight due to a certain error rate.

Abstract Background Myasthenia gravis (MG) and the experimental autoimmune MG (EAMG) animal model are characterized by T-cell-induced and B-cell-dominated autoimmune diseases that affect the neuromuscular junction. Several subtypes of CD4+ T cells, including T helper (Th) 17 cells, follicular Th cells, and regulatory T cells (Tregs), contribute to the pathogenesis of MG. However, increasing evidence suggests that CD8+ T cells also play a critical role in the pathogenesis and treatment of MG. Main body Herein, we review the literature on CD8+ T cells in MG, focusing on their potential effector and regulatory roles, as well as on relevant evidence (peripheral, in situ, cerebrospinal fluid, and under different treatments), T-cell receptor usage, cytokine and chemokine expression, cell marker expression, and Treg, Tc17, CD3+CD8+CD20+ T, and CXCR5+ CD8+ T cells. Conclusions Further studies on CD8+ T cells in MG are necessary to determine, among others, the real pattern of the Vβ gene usage of autoantigen-specific CD8+ cells in patients with MG, real images of the physiology and function of autoantigen-specific CD8+ cells from MG/EAMG, and the subset of autoantigen-specific CD8+ cells (Tc1, Tc17, and IL-17+IFN-γ+CD8+ T cells). There are many reports of CD20-expressing T (or CD20 + T) and CXCR5+ CD8 T cells on autoimmune diseases, especially on multiple sclerosis and rheumatoid arthritis. Unfortunately, up to now, there has been no report on these T cells on MG, which might be a good direction for future studies.

Abstract Background Although several studies have reported that selective posterior thoracolumbar/lumbar (TL/L) fusion can yield satisfactory results in Lenke 5C adolescent idiopathic scoliosis (AIS), the proximal junctional kyphosis (PJK) is still a common complication that occurs after surgery. The purpose of this study is to analyse the risk factors for postoperative proximal junctional kyphosis in Lenke 5C patients who underwent selective posterior TL/L fusion and explore whether PJK can be predicted. Methods A total of 83 AIS patients with Lenke 5C curves who met the inclusion criteria were analysed. All patients were divided into two groups based on the occurrence of postoperative PJK. Univariate and multivariate analyses were used to identify independent factors significantly associated with PJK, and an PJK index was proposed and verified. Results PJK was observed in 27 of 83 (32.5%) patients in the study. Preoperative thoracic kyphosis (TK) and the immediate postoperative proximal junctional angle (PJA) were the primary factors identified by the binary logistic regression analysis. The PJK index was defined as 1.1× preoperative TK + 2.3× immediate postoperative PJA. The receiver operating characteristics curve indicated that the occurrence rate of PJK was 85% and non-occurrence rate was 82% when the PJK index was greater than 42. Conclusion Large preoperative TK and a large immediate postoperative PJA play important roles in the development of PJK in Lenke 5C patients treated with selective posterior thoracolumbar/lumbar fusion. The PJK index can be used to predict the occurrence of PJK with high accuracy. To prevent the occurrence of PJK, we should pay attention to the TLK, and preserving more posterior proximal intervertebral elements at the upper instrumented vertebral level would be an important part of corrective surgery; however, moderate correction of the lumbar curve is recommended.

Abstract The 2023 update of the Chinese Society of Clinical Oncology (CSCO) Clinical Guidelines for Gastric Cancer focuses on standardizing cancer diagnosis and treatment in China, reflecting the latest advancements in evidence‐based medicine, healthcare resource availability, and precision medicine. These updates address the differences in epidemiological characteristics, clinicopathological features, tumor biology, treatment patterns, and drug selections between Eastern and Western gastric cancer patients. Key revisions include a structured template for imaging diagnosis reports, updated standards for molecular marker testing in pathological diagnosis, and an elevated recommendation for neoadjuvant chemotherapy in stage III gastric cancer. For advanced metastatic gastric cancer, the guidelines introduce new recommendations for immunotherapy, anti‐angiogenic therapy and targeted drugs, along with updated management strategies for human epidermal growth factor receptor 2 (HER2)‐positive and deficient DNA mismatch repair (dMMR)/microsatellite instability‐high (MSI‐H) patients. Additionally, the guidelines offer detailed screening recommendations for hereditary gastric cancer and an appendix listing drug treatment regimens for various stages of gastric cancer. The 2023 CSCO Clinical Guidelines for Gastric Cancer updates are based on both Chinese and international clinical research and expert consensus to enhance their applicability and relevance in clinical practice, particularly in the heterogeneous healthcare landscape of China, while maintaining a commitment to scientific rigor, impartiality, and timely revisions.

Objective: To investigate the accuracy of implant height and width measurement in the mandibular and maxillary first molar region based on cone-beam CT (CBCT) data, and to establish an accurate method for bone measurement in the implant region. Materials and methods: CBCT images of 122 patients with implant in mandibular or maxillary first molar region were retrospectively collected. Two methods were used to measure sagittal height (SH), coronal height (CH), sagittal width (SW), and coronal width (CW) of implants. Method 1 (general method): the images were analyzed using the built-in software NNT 9.0 software. SHl, CHl, SWl, and CWl were measured on the reconstructed sagittal and coronal based on the radiologist’s own experience. Method 2 (triaxial rotation method): the raw data were demonstrated in Expert mode of NNT 9.0 software, in which the coronal axis and sagittal axis were rotated paralleling to the long axis of the implant for reconstruction, and then SH2, CH2, SW2, and CW2 were measured on the reconstructed sagittal and coronal images. The results of two methods were compared with the actual implant size (H0, W0). Paired T-test was performed for statistical analysis. Dahlberg formula was used to check the measurement error. Results: For method 1, there was no significant differences between SHl and H0 (P > 0.05), but significant differences between CHl and H0, SWl and W0, and CWl and W0 (P 0.05). The random error range measured using Dahlberg formula was 0.157–1.171 mm for general method and 0.017–0.05 mm for triaxial rotation method. Conclusion: The triaxial rotation method is accurate for implant height and width measurements on CBCT images and could be used in pre-operatively bone height and width measurement of potential implant sites.

BackgroundIt remains unclear whether intensification of the chemotherapy backbone in tandem with an anti-EGFR can confer superior clinical outcomes in a cohort of RAS/BRAF wild-type colorectal cancer (CRC) patients with initially unresectable colorectal liver metastases (CRLM). To that end, we sought to comparatively evaluate the efficacy and safety of cetuximab plus FOLFOXIRI (triplet arm) versus cetuximab plus FOLFOX (doublet arm) as a conversion regimen (i.e., unresectable to resectable) in CRC patients with unresectable CRLM.Methods and findingsThis open-label, randomized clinical trial was conducted from April 2018 to December 2022 in 7 medical centers across China, enrolling 146 RAS/BRAF wild-type CRC patients with initially unresectable CRLM. A stratified blocked randomization method was utilized to assign patients (1:1) to either the cetuximab plus FOLFOXIRI (n = 72) or cetuximab plus FOLFOX (n = 74) treatment arms. Stratification factors were tumor location (left versus right) and resectability (technically unresectable versus ≥5 metastases). The primary outcome was the objective response rate (ORR). Secondary outcomes included the median depth of tumor response (DpR), early tumor shrinkage (ETS), R0 resection rate, progression-free survival (PFS), overall survival (not mature at the time of analysis), and safety profile. Radiological tumor evaluations were conducted by radiologists blinded to the group allocation. Primary efficacy analyses were conducted based on the intention-to-treat population, while safety analyses were performed on patients who received at least 1 line of chemotherapy. A total of 14 patients (9.6%) were lost to follow-up (9 in the doublet arm and 5 in the triplet arm). The ORR was comparable following adjustment for stratification factors, with 84.7% versus 79.7% in the triplet and doublet arms, respectively (odds ratio [OR] 0.70; 95% confidence intervals [CI] [0.30, 1.67], Chi-square p = 0.42). Moreover, the ETS rate showed no significant difference between the triplet and doublet arms (80.6% (58/72) versus 77.0% (57/74), OR 0.82, 95% CI [0.37, 1.83], Chi-square p = 0.63). Although median DpR was higher in the triplet therapy group (59.6%, interquartile range [IQR], [50.0, 69.7] versus 55.0%, IQR [42.8, 63.8], Mann-Whitney p = 0.039), the R0/R1 resection rate with or without radiofrequency ablation/stereotactic body radiation therapy was comparable with 54.2% (39/72) of patients in the triplet arm versus 52.7% (39/74) in the doublet arm. At a median follow-up of 26.2 months (IQR [12.8, 40.5]), the median PFS was 11.8 months in the triplet arm versus 13.4 months in the doublet arm (hazard ratio [HR] 0.74, 95% CI [0.50, 1.11], Log-rank p = 0.14). Grade ≥ 3 events were reported in 47.2% (35/74) of patients in the doublet arm and 55.9% (38/68) of patients in the triplet arm. The triplet arm was associated with a higher incidence of grade ≥ 3 neutropenia (44.1% versus 27.0%, p = 0.03) and diarrhea (5.9% versus 0%, p = 0.03). The primary limitations of the study encompass the inherent bias in subjective surgical decisions regarding resection feasibility, as well as the lack of a centralized assessment for ORR and resection.ConclusionsThe combination of cetuximab with FOLFOXIRI did not significantly improve ORR compared to cetuximab plus FOLFOX. Despite achieving an enhanced DpR, this improvement did not translate into improved R0 resection rates or PFS. Moreover, the triplet arm was associated with an increase in treatment-related toxicity.Trial registrationClinicalTrials.gov Identifier: NCT03493048.

Carbon monoxide (CO) is a gas that has no odor or color, making it difficult to detect until exposure leads to coma or death. CO poisoning is one of the most common and deadly poisonings around the world. CO poisoning is a common and often fatal form of poisoning worldwide. A toxic effect of CO is tissue hypoxia, which leads to systemic complications. Additionally, there may be severe neurological symptoms and delayed complications following CO poisoning. However, peripheral neuropathy is relatively rare after CO poisoning. Previously, only one case of unilateral plexopathy after CO poisoning, accompanied by rhabdomyolysis and cognitive dysfunction, has been reported. In this report, an isolated unilateral brachial plexopathy following CO intoxication is described. A key mechanism in this case may be CO-induced spinal cord ischemia. Immediate administration of hyperbaric oxygen therapy (HBOT) is crucial to prevent peripheral neuropathy after acute CO intoxication. Hyperbaric oxygen therapy (HBOT) should be administered immediately after acute CO intoxication to prevent peripheral neuropathy. Additionally, peripheral neuropathy following acute CO intoxication may benefit from consistent rehabilitation training.

Background: Current treatments for primary Sjögren's Syndrome (pSS) are with limited effect, partially due to the heterogeneity and uncleared mechanism. Methods: We got GSE40568 (Japan) and GSE40611 (USA), and analyzed them with WGCNA to find key Differentially expressed genes (DEGs) between pSS and healthy salivary glands (SG). Key pSS genes (KPGs) were further selected through 3 machine-learning methods. The expression of KPGs was validated via two other GEO datasets (GSE127952 and GSE154926). Infiltrated immune cells, ceRNA network, and potential compounds were explored. Results: Our study identified 376 DEGs from the pSS patients, with 186 genes located in the “plum2'' module, showing the strongest correlation with clinical characteristics. SAMD9 and IFIT3 emerged as KPGs with excellent diagnostic potential. SAMD9 demonstrated close association with immune cell infiltration. We constructed a lncRNA-miRNA-mRNA network comprising 2 KPGs, 12 miRNAs, 124 lncRNAs, and potential therapeutic targets. Conclusion: In the investigation of pSS public datasets, our study revealed two potential critical mediators in the pathological process of pSS salivary glands, namely SAMD9 and IFIT3. Furthermore, we put forth a hypothesis regarding the ceRNA network and made predictions regarding potential therapeutic drugs targeting these two genes.

A highly efficient diazotization of diazoacetates with para-quinone methides has been established via a tetrabutyl ammonium bromide (TBAB)-catalyzed 1,6-conjugated addition pathway. This methodology affords a convenient, safe, and rapid way to generating diverse polysubstituted α-diazocarbonyl compounds, displaying good functional group tolerance, high atom economy, and easy accessibility.

The microbiota, also referred to as the microbial community, is a crucial component of the human microenvironment. It is located predominantly in various organs, including the intestines, skin, oral cavity, respiratory tract, and reproductive tract. The microbiota maintains a symbiotic relationship with the human body, influencing physiological and pathological functions to a significant degree. There is increasing evidence linking the microbial flora to human cancers. In contrast to the traditional belief that the urethra and urine of normal individuals are sterile, recent advancements in high-throughput sequencing technology and bacterial cultivation methods have led to the discovery of specific microbial communities in the urethras of healthy individuals. Given the prevalence of bladder cancer (BCa) as a common malignancy of the urinary system, researchers have shifted their focus to exploring the connection between disease development and the unique microbial community within tumors. This shift has led to a deeper investigation into the role of microbiota in the onset, progression, metastasis, prognosis, and potential for early detection of BCa. This article reviews the existing research on the microbiota within BCa tumors and summarizes the findings regarding the roles of different microbes in various aspects of this disease.

Cold/hot forming wrought Al components with the apparent advantage of lightweight, outstanding formability and strength-ductility synergy are promising in structural materials field. Recrystallization is an indispensable process during deformation or heat treatment, whose driving force and microstructures have great relevance with the mechanical properties. In recent years, reinforcement and intermetallic particles have attracted great interests in precise intervening and controlling of recrystallization microstructures due to their immense potentials in regulating the driving and retarding force of recrystallization. Nevertheless, optimizing recrystallization microstructures of particle tailored wrought Al alloys is highly challenging due to the numerous affecting factors of particles (e.g., particle addition method, size, morphology, spatial distribution, coherency, and content, etc.) and the different driving force of static and dynamic recrystallization. To further impel the progress of recrystallization process of wrought Al alloy, this review gives an in-depth cognition of the roles of intermetallic and ceramic particles in recrystallization process of wrought Al alloys. The potential relevance between the particle characteristics, recrystallization driving force, and recrystallization microstructures in wrought Al alloys are summarized. The influences of regulated recrystallization microstructures on mechanical properties of wrought Al alloy are also overviewed. This review contributes to the comprehensive understanding of mechanisms of particle manipulated recrystallization evolution, and the future research orientations and development opportunities are prospected.

There is an increasingly urgent need of lightweight components in aerospace industry, among which aluminum (Al) alloys have been the optimal materials of choice for aircraft structural parts since being used in the Junkers F.13 aircraft in the 1920s. Compared to other metal materials, Al alloys have a lower density, and the use of Al alloys reduces the total weight of the aircraft and improves fuel efficiency and load capacity. Meanwhile, the strength and hardness of Al alloys with alloying and heat treatment can be significantly enhanced for uses in high loads and vibration environments. Furthermore, in the harsh aerospace environment, aircraft may receive various climatic conditions and chemical corrosion. Due to good corrosion and fatigue resistance, Al alloys demonstrate excellent performance under these conditions, ensuring the long–term service life of aircraft. In addition, Al alloys have good recyclability, and they can be recycled to reduce resource consumption and environmental load, in line with the principle of sustainable development. In recent years, although composites have been widely used in aerospace, high–strength Al alloys are still in an indispensable position. Therefore, this article reviews the progress and applications of Al alloys commonly used in aerospace. The common strengthening methods and advanced manufacturing and processing technologies of Al alloy are also discussed, which can provide references for the development of advanced high–performance aviation Al alloys in the future.

Predictive maintenance of wind turbines plays a crucial part in directing power grid dispatching and maintaining power grid security. In this paper, a way of ultra-short term wind power prediction relied on digital twin technology is proposed, which realizes actual time and accurate wind power prediction by building a digital model. Firstly, BP neural network (back propagation neutral network) was used to predict the wind power, and the initial predicted value of wind power was obtained. Then the meteorological data was substituted into the historical meteorological database to find similar meteorological conditions data, and the BP neural network predicted value was weighted to get the final digital twin predicted value. The simulation results indicate that this method can effectively enhance prediction accuracy of wind power.

Night lighting is essential for urban life, and the occurrence of faults can significantly affect the presentation of lighting effects. Many reasons can cause lighting faults, including the damage of lamps and circuits, and the typical manifestation of the faults is that the lights do not light up. The current troubleshooting mainly relies on artificial visual inspection, making detecting faults difficult and time-consuming. Therefore, it is necessary to introduce technical means to detect lighting faults. However, current research on lighting fault detection mainly focuses on using non-visual methods such as sensor data analysis, which has the disadvantages of having a high cost and difficulty adapting to large-scale fault detection. Therefore, this study mainly focuses on solving the problem of the automatic detection of night lighting faults using machine vision methods, especially object detection methods. Based on the YOLOv5 model, two data fusion models have been developed based on the characteristics of lighting fault detection inverse problems: YOLOv5 Channel Concatenation and YOLOv5 Image Fusion. Based on the dataset obtained from the developed automatic image collection and annotation system, the training and evaluation of these three models, including the original YOLOv5, YOLOv5 Channel Concatenation, and YOLOv5 Image Fusion, have been completed. Research has found that applying complete lighting images is essential for the problem of lighting fault detection. The developed Image Fusion model can effectively fuse information and accurately detect the occurrence and area of faults, with a mAP value of 0.984. This study is expected to play an essential role in the intelligent development of urban night lighting.

In this study, a quantitative method based on fluorescein isothiocyanate (FITC)-labelled Hizikia fusiforme polyphenol–polysaccharide complex (HPC) and its purified fractions (PC1, PC4) was used, and its pharmacokinetics and tissue distribution were investigated in mice. The results showed that the FITC-labelled method had good linearity (R2 > 0.99), intra-day and inter-day precision (RSD, %) consistently lower than 15%, recovery (93.19–106.54%), and stability (RSD < 15%), which met the basic criteria for pharmacokinetic studies. The pharmacokinetic and tissue distribution results in mice after administration showed that all three sample groups could enter the blood circulation. and HPC-FITC had a longer half-life (T1/2: 26.92 ± 0.76 h) and mean retention time (MRT0–∞: 36.48 h) due to its larger molecular weight. The three groups of samples could be absorbed by the organism in a short time (0.5 h) mainly in the stomach and intestine; the samples could be detected in the urine after 2 h of administration indicating strong renal uptake, and faecal excretion reached its maximum at 12 h. The samples were also detected in the urine after 2 h of administration. This study provides some theoretical basis for the tissue distribution pattern of polyphenol–polysaccharide complex.

Although the adoption of green innovation has been explored in various contexts, there is still a lack of research on the determinants of green technology innovation adoption (GTIA) in the third-party logistics (3PL) industry of emerging economies and the resulting economic, environmental, operational, and intangible outcomes. This study aims to investigate the influence of different determinants of technological, organizational, and environmental factors in the TOE-DOI framework on the adoption of green technology innovation, as well as the outcomes of such adoption. The study utilizes sample data from 544 Chinese 3PL firms and employs two-stage structural equation modeling and artificial neural network analysis. Partial least squares structural equation modeling (PLS-SEM) explains 85.4% of the variance in green technology innovation adoption, 21% in environmental outcomes, 18.5% in economic outcomes, 20.8% in operational outcomes, and 22.3% in intangible outcomes. The artificial neural network (ANN) model ranks the standardized importance of each predictive variable. The results indicate that institutional pressure is the most significant determinant of GTIA. Additionally, 3PL firms should consider the positive impact of green supplier integration and relative advantage. Complexity does not have a positive impact on GTIA. The longer a company has been established, the more experience and resources it accumulates, and the more opportunities it has to adopt green technology innovation. This study contributes to the existing research on emerging economies and other regions. Furthermore, this is the first study to successfully validate the nonlinear relationship within the Technology-Organization-Environment (TOE) framework and diffusion of innovation (DOI) theory, namely the TOE-DOI framework. The research findings further enhance the current understanding of green technology innovation adoption and its impact. This study provides valuable insights for managers and policymakers in the 3PL industry to achieve various effects, such as environmental, economic, operational, and intangible outcomes.

Lipids have not traditionally been considered likely candidates for catalyzing reactions in biological systems. However, there is significant evidence that aggregates of amphiphilic compounds are capable of catalyzing reactions in synthetic organic chemistry. Here, we demonstrate the potential for the hydrophobic region of a lipid bilayer to provide an environment suitable for catalysis by means of a lipid aggregate capable of speeding up a chemical reaction. By bringing organic molecules into the nonpolar or hydrophobic region of a lipid bilayer, reactions can be catalyzed by individual or collections of small, nonpolar, or amphiphilic molecules. We demonstrate this concept by the ester hydrolysis of calcein-AM to produce a fluorescent product, which is a widely used assay for esterase activity in cells. The reaction was first carried out in a two-phase octanol–water system, with the organic phase containing the cationic amphiphiles cetyltrimethylammonium bromide (CTAB) or octadecylamine. The octanol phase was then replaced with phospholipid vesicles in water, where the reaction was also found to be carried out. The reaction was monitored using quantitative fluorescence, which revealed catalytic turnover numbers on a scale of 10−7 to 10−8 s−1 for each system, which is much slower than enzymatic catalysis. The reaction product was characterized by 1H-NMR measurements, which were consistent with ester hydrolysis. The implications of thinking about lipids and lipid aggregates as catalytic entities are discussed in the context of biochemistry, pharmacology, and synthetic biology.

This study utilized activated carbon fibers (ACFs) as adsorbents to investigate the removal efficiency of naphthalene and toluene at elevated temperatures and their competitive adsorption behavior. Three types of ACFs, inlet concentrations of naphthalene (343, 457, and 572 mg·Nm−3), and toluene (2055, 2877, and 4110 mg·Nm−3) were investigated to determine the adsorption capacities of naphthalene and toluene. To study the reaction mechanisms of naphthalene and toluene on the ACFs, the BET, SEM, FTIR, and TGA methods were used to examine the physical and chemical characteristics of ACFs. Results showed ACF-A’s superior adsorption capacity for naphthalene that was attributed to its mesoporous structure and hydrophobicity. Adsorption equilibrium studies indicated multilayer adsorption behavior. Competitive adsorption experiments demonstrated the displacement of toluene by naphthalene on ACF-A, highlighting its higher selectivity for naphthalene. Functional group analysis revealed changes in ACF surfaces after naphthalene adsorption, suggesting π-π dispersion and electron donor–acceptor interactions. Overall, this study underscores the importance of pore structure and surface properties in designing ACFs for the efficient adsorption of high-boiling-point organic pollutants.