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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.

Metabolizing ellagic acid (EA) to urolithin A with numerous bioactivities significantly improve the nutritional value of food rich in EA. In the present study, Streptococcus thermophilus FUA329 was applied to prepare pomegranate juice yogurt. The best process formula was investigated through single-factor experiments and response surface methodology. With S. thermophilus CGMCC1.8748 as control, the viability of strain, rheological properties and antioxidant activity of pomegranate juice yogurt fermented with strain FUA329 were evaluated. The content of urolithin A in pomegranate juice yogurt fermented with strain FUA329 were analyzed by high-performance liquid chromatography. The results showed that the optimal fermentation conditions for preparing pomegranate juice yogurt by S. thermophilus FUA329 were 15.79% pomegranate juice content, 7.08% sucrose content and 3.04% starter inoculum size, fermentation at 37 ℃ for 7 h and comprehensive sensory score was 79.4 points. Under the optimal conditions, the results of basic indicators showed that yogurt acidity was (82.5±1.3)°T, whey precipitation was 9.6%±0.97%, color difference was 68.17±2.75, bacterial activity was 2.01±0.31 (OD600). In terms of antioxidant activity, DPPH radical, ABTS+ radical and superoxide anion radical scavenging rates of fermented pomegranate juice yogurt by strain FUA329 were 82.87%±1.48%, 88.20%±2.10% and 76.92%±1.02%, respectively, which was significantly better than plain yogurt fermented by strain FUA329 and pomegranate juice yogurt fermented by S. thermophilus CGMCC1.8748. In addition, urolithin A content was 3.31 μmol/L in fermented pomegranate juice yogurt by strain FUA329 after 7 h. The results of this study would provide a theoretical basis for fermenting a functional pomegranate juice yogurt, and lay a foundation for the development and utilization of S. thermophilus FUA329.

In order to evaluate the effect of Streptococcus thermophilus fermentation on green tea extract and its storage characteristics, this study used Streptococcus thermophilus FUA329 and S. thermophilus ST1.8748 (control group) to conduct experiments on green tea extracts. After fermentation and storage at 4 ℃ for 0, 30, 60, 120 and 180 d, pH, viable bacterial count, tea polyphenol content, ellagic acid content, and urolithin A content were used as the main evaluation indicators, combined with anti-oxidation activity to evaluate the storage quality of fermented green tea extract. The results showed that compared with the S. thermophilus ST1.8748 control group, the pH of S. thermophilus FUA329 fermented green tea extract during the storage period was between 5.39 and 5.71. The highest number of viable bacteria at 48 h was 9.97×108 CFU/mL. The content of tea polyphenols gradually decreased and the ellagic acid content tended to be stable. Urolithin A was produced at 48 h, and its concentration was 0.664 μmol/L. The antioxidant activity was always maintained at a high level. In summary, S. thermophilus FUA329 fermented green tea extract can significantly delay the quality decline and nutrient loss of green tea extract during storage.

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.

To determine the promoting effects of enzyme hydrolysis products of Larimichthys polyactis on the proliferation of Streptococcus thermophilus FUA329. The in vitro antioxidant activity of the enzymatic hydrolysis with different molecular weights were determined. Papain was selected for the enzymatic hydrolysis of its by-products on the basis of selecting different enzymes to hydrolyze the processing by-products of Larimichthys polyactis. Taking the proliferative effect of enzymatic degradation products on Streptococcus thermophilus as an indicator of evaluation. The enzymatic hydrolysis conditions were optimized through single factor and response surface methodology. The in vitro antioxidant activity of the hydrolysis products of the by-products of Larimichthys polyactis (HPBL) were determined. The results showed that the best enzymatic hydrolysis conditions included the hydrolysis time, material-liquid ratio and enzyme loading were 5 h, 1:5.1 (w/v) and 2.8% (w/v), respectively. The HPBL prepared under the optimized conditions was separated by ultrafiltration into four fragments, according to the molecular weight: >10000 Da, 5000~10000 Da, 3000~5000 Da,

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.

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.

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.

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 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.

Protection, dispersion and delivery of the functional components can implement in the emulsion-encapsulating systems. Among the stabilizers of the emulsion, specific structure of the cellulose may improve the stability of the system, and supplying the utilization of the bioactive substances on encapsulation and release. Therefore, the recent advances on stabilizing mechanism, cellulosic materials, properties of bioactive substances and factors affecting on the release of cellulosic emulsion-encapsulating systems are summarized in this review. In addition, the paper focuses on the release process and regulated mechanism of cellulose, which shows high length-diameter ratio and mechanical strength in the emulsion-delivery system of bioactive substances, and providing reference for the development of the food-grade delivery system. Studies indicates that cellulose-stabilized emulsion can improve the dispersion and oxidation stability of the bioactive substances, while controlling the release and improving the bioavailability of the functional factors. However, there is still vast research space for its safety evaluation in the food system, and related toxicological experiments urgently need to be carried out.

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.

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.

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.

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.

In order to explore and analyze the genetic diversity of phenotypic traits and the relationship among different provenances of Rhodomyrtus tomentosa, samples from 20 different sources were taken as the research objects, and the phenotypic traits of vegetative organs and floral organs were observed under the condition of homogenous garden cultivation. At the same time, the methods of ANOVA, variance analysis, Shannon-Wiener diversity index analysis, and cluster analysis were used in order to discuss the diversity of various phenotypic traits among different provenances. The results were as follows: (1) The averages of phenotypic traits of R. tomentosa from different provenances were significantly different (P

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.

Abstract Background Children diagnosed with autism spectrum disorder (ASD) frequently suffer from persistent gastrointestinal symptoms, such as constipation and diarrhea. Various studies have highlighted differences in gut microbiota composition between individuals with ASD and healthy controls of similar ages. However, it’s essential to recognize that these disparities may be influenced by cultural practices, dietary habits, and environmental factors. Methods In this study, we collected fecal samples from both children diagnosed with ASD (n = 42) and healthy individuals (n = 41) residing in the southeastern coastal region of China. Subsequently, 16 S rRNA gene sequencing and advanced bioinformatics analyses were conducted to investigate the distinctive features of gut microbial communities within each group. Results The ASD group consisted of 28 males and 14 females, with a median age of 5.8 years, while the control group included 25 males and 16 females, with a median age of 6.8 years. Among the 83 sequenced fecal samples, a total of 1031 operational taxonomic units (OTUs) were identified. These included 122 unique OTUs specific to the control group and 285 unique OTUs specific to the ASD group. Analyses of α-diversity and β-diversity unveiled significant differences in the abundance and composition of gut microbiota between the two groups. It was found that the dominant bacterial taxa in healthy individuals were UBA1819, Flavonifractor, and Bradyrhizobium. In contrast, the ASD group exhibited a prevalence of Streptococcus, Ruminococcus, and Ruminiclostridium. Further analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Clusters of Orthologous Groups (COG) showed significant differences in the metabolic functionalities of the gut microbiota between the two groups. Notably, the metabolic pathway related to alpha-linolenic acid (ALA) in the gut microbiota of the ASD group was notably diminished compared to the control group. Conversely, the ASD group demonstrated significantly elevated levels of metabolic pathways involving uncharacterized conserved proteins, aminoglycoside phosphotransferase, and inorganic pyrophosphatase compared to the control group. Conclusions Overall, these results confirm that there are significant differences in the gut microbiota structure between children with ASD and healthy controls in the southeast coastal region of China. This underscores the critical significance of delving into clinical interventions capable of mitigating the gastrointestinal and psychological symptoms encountered by children with ASD. A particularly encouraging path for such interventions lies in the realm of fecal microbiota transplantation, a prospect that merits deeper inquiry.

With the increasing penetration of electric vehicles (EV) and distributed generations (DG) in distribution networks, operation and control of distribution networks (DN) is faced with many new challenges. Considering the remarkable characteristics of distribution network layered by voltage level and the spatial and temporal distribution of EV charging load, a hierarchical and distributed optimization method for DN is proposed. Firstly, the spatial and temporal distribution prediction model of EV charging load is established, which is composed of three parts: the resident travel probability model, the vehicle mobility model and traffic network model. Secondly, these three parts runs jointly to simulate the charging demand generated by EV, and then the charging load is connected to the charging station in the low-voltage distribution station area. Thirdly, considering the operation characteristics of the new energy units, energy storage system (ESS), DG and EV charging station, a dynamic economic dispatching model is established. Fourthly, according to the hierarchical operation characteristics of the medium- and low-voltage distribution network (MLV), a distributed optimization algorithm of DN is proposed to realize the hierarchical and decoupled calculation, which transforms the traditional centralized serial computing mode into distributed parallel computing mode, and improves the computing efficiency of the system. At last, the effectiveness and superiority of the proposed strategy are verified by the simulation test.

Abstract Prion-like spreading of protein misfolding is a characteristic of neurodegenerative diseases, but the exact mechanisms of intercellular protein aggregate dissemination remain unresolved. Evidence accumulates that endogenous retroviruses, remnants of viral germline infections that are normally epigenetically silenced, become upregulated in neurodegenerative diseases such as amyotrophic lateral sclerosis and tauopathies. Here we uncover that activation of endogenous retroviruses affects prion-like spreading of proteopathic seeds. We show that upregulation of endogenous retroviruses drastically increases the dissemination of protein aggregates between cells in culture, a process that can be inhibited by targeting the viral envelope protein or viral protein processing. Human endogenous retrovirus envelopes of four different clades also elevate intercellular spreading of proteopathic seeds, including pathological Tau. Our data support a role of endogenous retroviruses in protein misfolding diseases and suggest that antiviral drugs could represent promising candidates for inhibiting protein aggregate spreading.

Abstract Bioenergy with carbon capture and storage (BECCS) is considered to be a key technology for removing carbon dioxide from the atmosphere. However, large-scale bioenergy crop cultivation results in land cover changes and activates biophysical effects on climate, with earth’s water recycling altered and energy budget re-adjusted. Here, we use a coupled atmosphere-land model with explicit representations of high-transpiration woody (i.e., eucalypt) and low-transpiration herbaceous (i.e., switchgrass) bioenergy crops to investigate the range of impact of large-scale rainfed bioenergy crop cultivation on the global water cycle and atmospheric water recycling. We find that global land precipitation increases under BECCS scenarios, due to enhanced evapotranspiration and inland moisture advection. Despite enhanced evapotranspiration, soil moisture decreases only slightly, due to increased precipitation and reduced runoff. Our results indicate that, at the global scale, the water consumption by bioenergy crop growth would be partially compensated by atmospheric feedbacks. Thus, to support more effective climate mitigation policies, a more comprehensive assessment, including the biophysical effects of bioenergy cultivation, is highly recommended.

Background: Everolimus is an inhibitor of the mammalian target of rapamycin and is used to treat various tumors. The presented study aimed to evaluate the Everolimus-associated adverse events (AEs) through data mining of the US Food and Drug Administration Adverse Event Reporting System (FAERS).Methods: The AE records were selected by searching the FDA Adverse Event Reporting System database from the first quarter of 2009 to the first quarter of 2022. Potential adverse event signals were mined using the disproportionality analysis, including reporting odds ratio the proportional reporting ratio the Bayesian confidence propagation neural network and the empirical Bayes geometric mean and MedDRA was used to systematically classify the results.Results: A total of 24,575 AE reports of Everolimus were obtained using data from the FAERS database, and Everolimus-induced AEs occurrence targeted 24 system organ classes after conforming to the four algorithms simultaneously. The common significant SOCs were identified, included benign, malignant and unspecified neoplasms, reproductive system and breast disorders, etc. The significant AEs were then mapped to preferred terms such as stomatitis, pneumonitis and impaired insulin secretion, which have emerged in the study usually reported in patients with Everolimus. Of note, unexpected significant AEs, including biliary ischaemia, angiofibroma, and tuberous sclerosis complex were uncovered in the label.Conclusion: This study provided novel insights into the monitoring, surveillance, and management of adverse drug reaction associated with Everolimus. The outcome of serious adverse events and the corresponding detection signals, as well as the unexpected significant adverse events signals are worthy of attention in order to improving clinical medication safety during treatment of Everolimus.

Adeno-associated virus (AAV) vectors have been widely used in therapy to treat hereditary retinal diseases. But its transduction efficiency by intravitreal injection still needs to be improved. In this study, we investigated the transduction efficiency of AAV-DJ (K137R)-GFP in different retinal cells of normal mice, as well as the therapy effection of AAV-DJ (K137R)-Rs1 on retinal function and structure in Rs1-KO mice. The intravitreal injection of AAV-DJ (K137R)-GFP demonstrated that this vector transduced cells in all layers of the retina, including the inner nuclear layer and photoreceptor layer. The intravitreal injection of AAV-DJ (K137R)-Rs1 found that 3 months post-injection of this vector improved retinal function and structure in Rs1-KO mice. Our conclusion is that AAV-DJ (K137R) vector can efficiently and safely penetrate the inner limiting membrane and transduce different layers of retinal cells in the long term, as well as being able to continuously and efficiently express target therapeutic proteins, making it a candidate therapeutic vector for X-linked retinoschisis (XLRS).

Age-related cognitive impairment represents a significant health concern, with the understanding of its underlying mechanisms and potential interventions being of paramount importance. This study aimed to investigate the effects of hyperbaric oxygen therapy (HBOT) on cognitive function and neuronal integrity in aged (22-month-old) C57BL/6 mice. Male mice were exposed to HBOT for 2 weeks, and spatial learning and memory abilities were assessed using the Morris water maze. We employed transcriptome sequencing and Gene Ontology (GO) term enrichment analysis to examine the effects of HBOT on gene expression profiles, with particular attention given to synapse-related genes. Our data indicated a significant upregulation of postsynapse organization, synapse organization, and axonogenesis GO terms, likely contributing to improved cognitive performance. Moreover, the hyperphosphorylation of tau, a hallmark of many neurodegenerative diseases, was significantly reduced in the HBO-treated group, both in vivo and in vitro. Transmission electron microscopy revealed significant ultrastructural alterations in the hippocampus of the HBOT group, including an increase in the number of synapses and the size of the active zone, a reduction in demyelinated lesions, and a decreased number of “PANTHOS.” Furthermore, Western blot analyses confirmed the upregulation of PSD95, BDNF, and Syn proteins, suggesting enhanced synaptic plasticity and neurotrophic support. Moreover, HBOT increased autophagy, as evidenced by the elevated levels of Beclin-1 and LC3 proteins and the reduced level of p62 protein. Finally, we demonstrated that HBOT activated the AMPK-mTOR signaling pathway, a critical regulator of autophagy. Notably, our findings provide novel insights into the mechanisms by which HBOT ameliorates age-related cognitive impairment, suggesting the potential therapeutic value of this approach.

ObjectiveTo determine whether there is a causal relationship between thyroid dysfunction and the risk of age-related cataract (ARC) in the European population.DesignA two-sample Mendelian randomization (MR) study.MethodsHypothyroidism, hyperthyroidism, free thyroxine (fT4), and thyrotropin (TSH) were selected as exposures. The single nucleotide polymorphisms (SNP) of hypothyroidism and hyperthyroidism were obtained from the genome-wide association studies (GWAS) of the IEU database, including 337,159 subjects. Data for fT4 and TSH (72,167 subjects) were extracted from the ThyroidOmics Consortium. ARC was used as the outcome. The SNPs associated with ARC were selected from a GWAS of 216,362 individuals in the FinnGen database. The main method used was the inverse variance-weighted method, together with four complementary methods. Sensitivity analyses were performed using Cochran’s Q test, MR-PRESSO, MR-Egger regression and leave-one-out test. MR pleiotropy was used to test for pleiotropy. MR Steiger test was used to test for the directionality.ResultsTwo-sample MR analysis revealed a positive association between genetically predicted hypothyroidism and risk of ARC (OR = 2.501, 95% CI: 1.325-4.720; P = 0.004). Hyperthyroidism, circulating fT4 and TSH levels did not have a significant causal effect on ARC (P > 0.05). The results were robust and reliable, and no horizontal pleiotropy was found after sensitivity analyses. In the MR Steiger test, we found no reverse causal effects of hypothyroidism on the ARC (P

Abstract Developing biomaterials with antimicrobial and wound‐healing activities for the treatment of wound infections remains challenging. Macrophages play non‐negligible roles in healing infection‐related wounds. In this study, a new sequential immunomodulatory approach is proposed to promote effective and rapid wound healing using a novel hybrid hydrogel dressing based on the immune characteristics of bacteria‐associated wounds. The hydrogel dressing substrate is derived from a porcine dermal extracellular matrix (PADM) and loaded with a new class of bioactive glass nanoparticles (BGns) doped with copper (Cu) and zinc (Zn) ions (Cu–Zn BGns). This hybrid hydrogel demonstrates a controlled release of Cu2+ and Zn2+ and sequentially regulates the phenotypic transition of macrophages from M1 to M2 by alternately activating nucleotide‐binding oligomerization domain (NOD) and inhibiting mitogen‐activated protein kinases (MAPK) signaling pathways. Additionally, its dual‐temporal bidirectional immunomodulatory function facilitates enhanced antibacterial activity and wound healing. Hence, this novel hydrogel is capable of safely and efficiently accelerating wound healing during infections. As such, the design strategy provides a new direction for exploring novel immunomodulatory biomaterials to address current clinical challenges related to the treatment of wound infections.

The shear strength of asphalt mixtures significantly influences the rut resistance of flexible pavements. Existing methods predominantly address macroscopic aspects, failing to unveil the underlying mechanisms. Moreover, experimental determination of shear strength parameters is time-consuming, but there is a lack of simple prediction methods. This study explores correlations between macroscopic parameters (friction angle and cohesion) and key mesoscopic shear-related factors in Porous Asphalt Mixtures (PAMs) using multiscale triaxial compressive tests, dynamic shear rheometer tests, and sessile drop tests. The research reveals that PAM is influenced not only by aggregate interlock but also by stiff mastic, resulting in a reduced friction angle at a lower temperature. Regression analyses establish a prediction formula for PAMs, incorporating the friction angle of the aggregate skeleton and the complex modulus of the mastic. A correlation function, inspired by Griffith's fracture theory, was also proposed to link PAM's cohesion with the complex modulus and the work of cohesion of mastic, and the friction angle of PAMs. Predictions for PAM's friction angle and cohesion align well with macro-level experimental results, with all the coefficients of determination of over 0.94. These findings enhance the understanding of asphalt mixture shear strength formation and enable shear-resistance optimisation from meso-level.

Polyetheretherketone (PEEK) is a frequently utilized orthopedic implant material in clinical settings. However, the adverse inflammatory and immunological reactions due to the PEEK surface after implantation often cause poor osseointegration and thereby hinder its clinical utility. To improve osseointegration and enhance the success rate of PEEK implants, the surface can be biofunctionalized to be immunomodulatory. Consequently, in this study, lithium-doped bioglass nanospheres (Li/BGs) was coated on the sulfonated PEEK surface. Furthermore, we assessed the anti-inflammatory potential of the biofunctionalized PEEK implants and their impact on osteogenesis. In our study, it was observed that the in vitro biofunctionalized PEEK surface exhibited enhanced osteogenesis and immunomodulatory osteogenesis properties, while also effectively suppressing the acute inflammatory response initiated by macrophages. Furthermore, our in vivo experiments demonstrated that the biofunctionalized PEEK surface contributed to improved osteogenesis properties and mitigated the formation of fibrous capsules. Therefore, the in vitro and in vivo results demonstrated that PEEK surface modification with Li/BGs not only changed the disadvantage of being bioinert on the surface but also endowed it with osteoimmunomodulatory regulation and bone-promoting properties. Thus, the biofunctionalized PEEK may be a promising candidate for use as an orthopedic implant in clinical settings.

The musculoskeletal network is a complex system of different types of nodes and edges interacting with each other. Although there is a wealth of knowledge about the anatomical components of the human body and the connections between them, the interdependence of these components as a system remains largely unexplored. This study aims to understand the structure of musculoskeletal networks by using hypergraphs as a model of the musculoskeletal system with many-to-many connections. We used both pairwise and hypergraph-based embedding methods to learn the connectivity of muscles. Experiments demonstrated the superiority of the proposed hypergraph-based method over pairwise methods in distinguishing the specific roles of the muscles connecting different body parts.