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Abstract Objective Our study successfully developed an assay kit for thrombin-antithrombin complex (TAT) and demonstrated the predictive value of plasma TAT concentration in the development of venous thromboembolism (VTE) in patients with cervical cancer. Method A retrospective analysis was conducted on 177 patients with cervical cancer who received treatment at the Affiliated Hospital of Jiangnan University in Wuxi City from July 1, 2023 to October 1, 2023. This study provides a comprehensive analysis of cervical cancer patients and their VTE risk factors. The patients were divided into two groups: 27 cases with VTE (Thrombosis group) and 150 cases without VTE (Non-thrombotic group). Additionally, the patients were classified into four stages based on tumor stage: 42 cases of stage I, 45 cases of stage II, 62 cases of stage III, and 28 cases of stage IV. The control group consisted of 80 healthy patients undergoing medical check-ups. Thrombin-antithrombin complex (TAT), fibrinolytic enzyme-α2-fibrinolytic inhibitor complex (PIC), thrombomodulin (TM), and tissue-type plasminogen activator inhibitor 1 complex (t-PAIC) were detected using quantitative chemiluminescence immunoassay. The study assessed the variations in thrombotic marker levels among cervical cancer patients of different stages through a receiver operating characteristic (ROC) curve. Result The TAT reagent demonstrated a detection limit of 0.048 ng/mL, with a linear R value of 0.9997, indicating high accuracy and precision. The reagent's accelerated stability was also excellent, with deviations of less than 10%. Furthermore, the correlation coefficient of this method with Hyson Mecon was R2 = 0.9683. Notably, in patients with cervical cancer, TAT and PIC levels were found to be elevated compared to those of the healthy population. Cervical cancer patients who developed thrombosis had significantly elevated levels of TAT and fibrinogen degradation products (FDP) compared to those who did not. Furthermore, patients with stage III-IV cervical cancer exhibited higher levels of the six markers than those with stage I-II during staging. Notably, the combination of four or six markers significantly improved the sensitivity and specificity of the diagnosis, as demonstrated by the ROC curves. Conclusion Our developed TAT test kit has excellent performance and low cost, making it a clinically valuable tool for widespread use. Elevated TAT levels have significant predictive value for thrombosis occurrence in cervical cancer patients. The combination of t-PAIC, TM, TAT, PIC, D-dimer(D-D), and FDP markers is superior to using a single marker for diagnosing VTE in patients with malignant tumors. Screening cervical cancer patients for the six markers is essential to aid in active prophylaxis, determine optimal treatment timing, and implement nursing interventions to improve prognosis, reduce venous thrombosis incidence and mortality, and prolong survival time.

Abstract This retrospective study used cone-beam computed tomography to investigated the crown-root morphology and alveolar bone structure in incisors region in subjects with closed deep overbite and comparison the difference between gender and age. The CBCT images for 40 subjects (group C) with Angle II division 2 were selected from patients of the HeFei Stomatological Hospital from November 2023 to March 2024.20 individual normal occlusion subjects (group A),20 patients with Angle II division 1(group B) were included. The crown-root ratio of the maxillary and mandibular anterior teeth, crown-root angle and alveolar bone structure were measured on the CBCT images, the data were statistically analyzed. In addition to mandibular lateral incisor, the crown-root ratio of maxillary and mandibular anterior teeth in the Class II division 2 group was higher than that in the individual normal occlusion group and the Class II division 1 (P

Abstract The threat of long‐term low wind output processes (LWOP) on the supply ability of the power system is escalating with the increasing integration of wind power. Accurate prediction of LWOP is crucial for maintaining the stable operation of the power system. However, the occurrence probability of LWOP is low and the available samples are lacking, limiting the high‐accuracy predictive modeling of LWOP. Therefore, a novel prediction method for LWOP under very few samples based on improved Wasserstein deep convolutional generative adversarial networks (W‐DCGAN) is proposed here. Firstly, a multi‐dimensional identification method is proposed to accurately identify historical LWOP. Then, an LWOP sample generation model based on improved W‐DCGAN is established. The model integrates a long short‐term memory layer into the deconvolutional layer of the generator to enhance the temporal characteristics of generated samples. Finally, three prediction algorithms are used to construct LWOP prediction models based on both generated and actual samples, respectively. The wind power operation data from a province in China is taken as an example to verify the effectiveness of the proposed method. The results show that the prediction accuracy of LWOP can be improved by 14.36%–55.85%.

Abstract Purpose Delirium has a significant impact on millions of people globally and is closely linked to an unfavorable prognosis for complications. Observational studies suggest that plasma metabolites may play significant roles as markers and effectors of delirium, but causal relationships have not yet been elucidated. Based on the most recent genome-wide association study (GWAS) data, our study aims to present novel insights into the genetic relationship between delirium and plasma metabolites. This investigation offers potential clues for utilizing plasma metabolites as predictors of delirium development. Methods We performed a thorough Mendelian randomization (MR) analysis to investigate the causal relationship between 1,091 individual metabolites and 309 metabolite ratios in plasma with respect to delirium. Inverse-variance weighting (IVW) was employed as the primary estimation method, while MR-Egger and weighed median methods were utilized to assess the robustness of the results. Sensitivity analyses encompassing the MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test, Cochran Q test, leave-one-out analysis and MR Egger intercept analysis were also undertaken. Additionally, the MR Steiger test was performed to explore any potential reverse causal effect of metabolites on delirium. Results A total of 63 types of plasma metabolites associated with delirium were detected using the IVW method (p < 0.05). Among the known metabolites, our analysis revealed that two specific metabolites (1-palmitoyl-2-palmitoleoyl-gpc (16:0/16:1) and homovanillate) and a metabolite ratio (phosphate to oleoyl-linoleoyl-glycerol (18:1 to 18:2)) demonstrated a consistent and significant causal relationship with delirium across all analysis methods. Finally, no evidence of pleiotropy was detected in our analysis. Conclusions Our study has revealed a causal association between blood metabolites and the risk of delirium. homovanillate is known to be associated with immunity and redox, 1-palmitoyl-2-palmitoleoyl-gpc (16:0/16:1) and metabolite ratio (phosphate to oleoyl-linoleoyl-glycerol (18:1 to 18:2)) may play a role in lipid regulation. These findings may provide fresh insights into the identification of suitable diagnostic markers and potential treatment strategies focused on specific plasma metabolites in patients with delirium. However, further experiments are required to gain a comprehensive understanding of the underlying biological mechanisms involved.

Abstract It is challenging to attain strong near-infrared (NIR) emissive gold nanoclusters. Here we show a rod-shaped cluster with the composition of [Au28(p-MBT)14(Hdppa)3](SO3CF3)2 (1 for short, Hdppa is N,N-bis(diphenylphosphino)amine, p-MBT is 4-methylbenzenethiolate) has been synthesized. Single crystal X-ray structural analysis reveals that it has a rod-like face-centered cubic (fcc) Au22 kernel built from two interpenetrating bicapped cuboctahedral Au15 units. 1 features NIR luminescence with an emission maximum at 920 nm, and the photoluminescence quantum yield (PLQY) is 12%, which is 30-fold of [Au21(m-MBT)12(Hdppa)2]SO3CF3 (2, m-MBT is 3-methylbenzenethiolate) with a similar composition and 60-fold of Au30S(S‑t‑Bu)18 with a similar structure. time-dependent DFT(TDDFT)calculations reveal that the luminescence of 1 is associated with the Au22 kernel. The small Stokes shift of 1 indicates that it has a very small excited state structural distortion, leading to high radiative decay rate (k r) probability. The emission of cluster 1 is a mixture of phosphorescence and thermally activated delayed fluorescence(TADF), and the enhancement of the NIR emission is mainly due to the promotion of k r rather than the inhibition of k nr. This work demonstrates that the metal kernel and the surface structure are both very important for cluster-based NIR luminescence materials.

A limited selection of natural dyes’ color impedes the development of textile dyeing with natural plant dyes. Inspiring by the conventional coloration of textiles with a combination of three synthetic dyes generally, the present work is to investigate the broadening color shade of dyed wool fiber with ternary natural dye combinations of madder red (MR), gardenia yellow (GY), and gardenia blue (GB) without mordants in a decamethylcyclopentasiloxane (D5) medium. The wool yarn was wetted in an aqueous solution of pH 3 to own a 300% pickup rate, followed by immersion in a D5 medium containing 2% of alcohol ethoxylate (AEO-3) and solid natural dyes at 90°C for 90 min for coloration. The colorfastness to washing was achieved at a 4–5 for fading and a 5 rating for staining for all colors. The XRD patterns and TGA analysis confirmed that the dyeing procedure did not affect the crystallinity nature and stable thermal tendency. SEM images and cross-sections showed that the dyeing procedure did not damage the morphological structure of the wool fiber surface, and the dyes were evenly distributed. Finally, many color shades of dyed fibers were prepared with various dyes’ ratios.

Abstract Background Venous thromboembolism (VTE), is a noteworthy complication in individuals with gastric cancer, but the current diagnosis and treatment methods lack accuracy. In this study, we developed a t-PAIC chemiluminescence kit and employed chemiluminescence to detect the tissue plasminogen activator inhibitor complex (t-PAIC), thrombin-antithrombin III complex (TAT), plasmin-α2-plasmin inhibitor complex (PIC) and thrombomodulin (TM), combined with D-dimer and fibrin degradation products (FDP), to investigate their diagnostic potential for venous thrombosis in gastric cancer patients. The study assessed variations in six indicators among gastric cancer patients at different stages. Results The t-PAIC reagent showed LOD is 1.2 ng/mL and a linear factor R greater than 0.99. The reagents demonstrated accurate results, with all accuracy deviations being within 5%. The intra-batch and inter-batch CVs for the t-PAIC reagent were both within 8%. The correlation coefficient R between this method and Sysmex was 0.979. Gastric cancer patients exhibited elevated levels of TAT, PIC, TM, D-D, FDP compared to the healthy population, while no significant difference was observed in t-PAIC. In the staging of gastric cancer, patients in III-IV stages exhibit higher levels of the six markers compared to those in I-II stages. The ROC curve indicates an enhancement in sensitivity and specificity of the combined diagnosis of four or six indicators. Conclusion Our chemiluminescence assay performs comparably to Sysmex’s method and at a reduced cost. The use of multiple markers, including t-PAIC, TM, TAT, PIC, D-D, and FDP, is superior to the use of single markers for diagnosing VTE in patients with malignant tumors. Gastric cancer patients should be screened for the six markers to facilitate proactive prophylaxis, determine the most appropriate treatment timing, ameliorate their prognosis, decrease the occurrence of venous thrombosis and mortality, and extend their survival.

Abstract Background Postoperative delirium (POD) is a common neurologic disorder among elderly patients after non-cardiac surgery, which leads to various negative outcomes. Sleep disorder is considered an important cause of POD. The objective of this study was to investigate whether the Chinese traditional five-element music intervention could reduce POD by improving sleep quality in elderly patients undergoing non-cardiac surgery. Methods A total of 132 patients aged 65 to 90 years who underwent non-cardiac surgery were randomized to two groups: the intervention (n = 60) and the control group (n = 63). Patients in the intervention group were subjected to the Chinese traditional five-element music intervention during the perioperative, while patients in the control group had no music intervention. POD was evaluated using the Confusion Assessment Method (CAM) in the first 5 days after surgery. The Richards‒Campbell Sleep Questionnaire (RCSQ) was used to assess subjective sleep quality. The levels of nocturnal melatonin and cortisol in saliva were measured on the preoperative and the first 2 postoperative days. Results The incidence of POD within 5 days was 27.0% in the control group and 11.7% in the intervention group. Preoperative PSQI and MMSE scores were associated with POD. The RCSQ scores on the first postoperative day were significantly decreased in the two groups compared to the preoperative day. Compared to the control group, the RCSQ scores showed a significant improvement in the intervention group on the first postoperative day. Compared to the control group, the level of saliva melatonin in the intervention group showed a significant increase on the first postoperative day. However, there was no statistical difference in cortisol levels between the two groups. Conclusions Chinese traditional five-element music intervention decreased the incidence of POD in elderly patients who underwent noncardiac surgery via improving sleep quality, which may be associated with increased levels of melatonin.

Background: Association of asthma with the risk of cardiovascular disease has not been fully elucidated. So, this study tried to explore the genetic effect of asthma on five cardiovascular diseases and 90 peripheral cardiovascular proteins to answer the above topic. Methods: Instrumental variables predicting asthma was extracted from its genome-wide association study data. Two-sample and multivariate MR approaches were used to assess the genetic association of exposure factor (i.e., asthma) with outcome factors (i.e., hypertension, atrial fibrillation, angina pectoris, myocardial infarction, heart failure, and 90 peripheral cardiovascular proteins). Results: First, asthma nominally increased the risk of hypertension and atrial fibrillation (OR = 1.009, 95%CI = 1.003–1.016, P = 0.004; OR = 1.074, 95%CI = 1.024–1.127, P = 0.003). Second, of the 90 cardiovascular proteins, asthma was associated with the increased levels of tumor necrosis factor ligand superfamily member 14 and CC motif chemokine 4 (β = 0.145, 95%CI = 0.077–0.212, P = 2.936e-05; β = 0.128, 95%CI = 0.063–0.193, P = 1.036e-04). Third, CC motif chemokine 4 increased the risk of hypertension (P = 0.043); and after adjusting for this protein, asthma still increased the risk of hypertension, but the strength of its P-value changed from 0.004 to 0.011. Conclusion: Asthma was a risk factor for hypertension and atrial fibrillation at the genetic level, and CC motif chemokine 4 might play a mediating role in the mechanism by which asthma promoted hypertension. Thus, effective control of asthma may help reduce the risk of some cardiovascular diseases in older adults.

Tartaric acid is one of the characteristic acids in wine, playing a crucial role in wine characteristics. However, superabundant tartaric acid will form insoluble salts and precipitate in the form of crystals, affecting consumers' purchasing appetite. Therefore, tartaric stability is also one of the important indices for controlling the wine quality. At present, the main processing methods for tartaric stability include cold stabilization, ion exchange treatment, electrodialysis and the addition of exogenous components (gum arabic, metatartaric acid, carboxymethyl cellulose, mannoprotein and potassium polyaspartate). This review summarizes and analyzes the origin of tartaric acid in wine, factors influencing the tartaric stability, detection methods, treatments for tartaric stabilization, and the effects of these methods on the sensory quality of wine. Comparing the effects of these methods on wine quality can provide a basis for the further study of tartaric stabilization methods in order to select an appropriate tartaric stabilization method.

Fluorescent brightening agent OB-1 (OB-1) is often used in plastic goods because of its non-toxic nature, chemical stability, remarkable heat resistance, and light stability. Raw OB-1 is challenging to use in textiles using the exhaustion method. This study used a novel method using raw OB-1 powder to whiten polyester fabric in water and decamethylcyclopentasiloxane (D5). The Taguchi approach investigated the interaction between whitening process parameters such as temperature, OB-1 mass, water: D5 ratio, and treatment time with four levels. The study shows that the temperature and water: D5 ratio during the whitening process significantly affect the whiteness of polyester fabric (P

Abstract Accurate identification and localization of multiple abnormalities are crucial steps in the interpretation of chest X-rays (CXRs); however, the lack of a large CXR dataset with bounding boxes severely constrains accurate localization research based on deep learning. We created a large CXR dataset named CXR-AL14, containing 165,988 CXRs and 253,844 bounding boxes. On the basis of this dataset, a deep-learning-based framework was developed to identify and localize 14 common abnormalities and calculate the cardiothoracic ratio (CTR) simultaneously. The mean average precision values obtained by the model for 14 abnormalities reached 0.572-0.631 with an intersection-over-union threshold of 0.5, and the intraclass correlation coefficient of the CTR algorithm exceeded 0.95 on the held-out, multicentre and prospective test datasets. This framework shows an excellent performance, good generalization ability and strong clinical applicability, which is superior to senior radiologists and suitable for routine clinical settings.

Abstract Background Remote ischemic preconditioning (RIPC) is proven to have neuroprotective protective effects. Nevertheless, the impact of RIPC on postoperative cognitive dysfunction (POCD) in patients undergoing general anesthesia is controversial. This meta-analysis of randomized controlled trials (RCTs) aimed to assess the effect of RIPC on POCD in adults after general anesthesia. Methods Relevant literature was obtained by searching Embase, PubMed, Web of Science, Cochrane Library, Wanfang, and China National Knowledge Infrastructure (CNKI) databases in July 2022. RCTs were included to assess the influences of RIPC on POCD in adults following general anesthesia. Two investigators independently performed literature screening, data extraction, and quality assessment based on the inclusion and exclusion criteria. The incidence of POCD, operation time, and hospital stay were analyzed by Review manager5.4 software. Results Thirteen RCTs with 1122 participants were selected for this meta-analysis. Compared to the control group, RIPC decreased the incidence of POCD (OR = 0.50, 95% CI 0.31–0.82), as well as reduced the duration of hospitalization (MD = − 0.98, 95% CI − 1.69 to − 0.27), but did not prolong operative time (MD = − 2.65, 95% CI − 7.68 to 2.37). Conclusion RIPC reduced the incidence of POCD in adult patients after general anesthesia and accelerated their discharge.

Abstract Background Pulmonary complications after thoracic surgery are common and associated with significant morbidity and high cost of care. Goal-directed fluid therapy (GDFT) could reduce the incidence of postoperative pulmonary complications (PPCs) and facilitate recovery in patients undergoing major abdominal surgery. However, whether GDFT could reduce the incidence of PPCs in patients undergoing thoracic surgery was unclear. The present meta-analysis was designed to assess the impact of Goal-directed Fluid Therapy on PPCs in patients undergoing thoracic surgery. Methods Randomized controlled trials (RCTs) comparing GDFT with other conventional fluid management strategies in adult patients undergoing thoracic surgery were identified. Databases searched included PubMed, Web of Science, Embase, and Cochrane Library databases. Review Manager 5.4 (The Cochrane Collaboration, Oxford, UK) software was used for statistical analysis. Heterogeneity was analyzed using I2 statistics, and a standardized mean difference with 95% CI and P value was used to calculate the treatment effect for outcome variables. The primary study outcomes were the incidence of PPCs. Secondary outcomes were the total volume infused, the length of hospitalization, the incidence of cardiac complications, and the incidence of renal dysfunction. Subgroup analysis was planned to verify the definite role of GDFT. Results A total of 6 RCTs consisting of 680 patients were included in this meta-analysis, which revealed that GDFT did not reduce the incidence of PPCs in patients undergoing thoracic surgery (RR, 0.57; 95% CI 0.29–1.14). However, GDFT decreased the total intra-operative fluid input (MD, − 244.40 ml; 95% CI − 397.06 to − 91.74). There was no statistical difference in the duration of hospitalization (MD; − 1.31, 95% CI − 3.00 to 0.38), incidence of renal dysfunction (RR, 0.62; 95% CI 0.29–1.35), and incidence of cardiac complications (RR, 0.62; 95% CI 0.27–1.40). Conclusions The results of this meta-analysis indicate that GDFT did not reduce the postoperative incidence of pulmonary complications in individuals undergoing thoracic surgery. However, considering the small number of contributing studies, these results should be interpreted with caution.

Background: Bloodstream infections (BSIs) pose a great challenge to treating patients, especially those with underlying diseases, such as immunodeficiency diseases. Early diagnosis helps to direct precise empirical antibiotic administration and proper clinical management. This study carried out a serum metabolomic analysis using blood specimens sampled from patients with a suspected infection whose routine culture results were later demonstrated to be positive. Methods: A liquid chromatograph-mass spectrometry-based metabolomic analysis was carried out to profile the BSI serum samples. The serum metabolomics data could be used to successfully differentiate BSIs from non-BSIs. Results: The major classes of the isolated pathogens (e.g., Gram-positive and Gram-negative bacteria) could be differentiated using our optimized statistical algorithms. In addition, by using different machine-learning algorithms, the isolated pathogens could also be classified at the species levels (e.g., Escherichia coli and Klebsiella pneumoniae) or according to their specific antibiotic-resistant phenotypes (e.g., extended-spectrum β-lactamase-producing and non-producing phenotypes) if needed. Conclusions: This study provides an early diagnosis method that could be an alternative to the traditional time-consuming culture process to identify BSIs. Moreover, this metabolomics strategy was less affected by several risk factors (e.g., antibiotics administration) that could produce false culture results.

Mitochondrial dysfunction is a hallmark of Alzheimer’s disease. We previously showed that neural stem cell-derived extracellular vesicles improved mitochondrial function in the cortex of APP/PS1 mice. Because Alzheimer’s disease affects the entire brain, further research is needed to elucidate alterations in mitochondrial metabolism in the brain as a whole. Here, we investigated the expression of several important mitochondrial biogenesis-related cytokines in multiple brain regions after treatment with neural stem cell-derived exosomes and used a combination of whole brain clearing, immunostaining, and lightsheet imaging to clarify their spatial distribution. Additionally, to clarify whether the sirtuin 1 (SIRT1)-related pathway plays a regulatory role in neural stem cell-derived exosomes interfering with mitochondrial functional changes, we generated a novel nervous system-SIRT1 conditional knockout APP/PS1 mouse model. Our findings demonstrate that neural stem cell-derived exosomes significantly increase SIRT1 levels, enhance the production of mitochondrial biogenesis-related factors, and inhibit astrocyte activation, but do not suppress amyloid-β production. Thus, neural stem cell-derived exosomes may be a useful therapeutic strategy for Alzheimer’s disease that activates the SIRT1-PGC1α signaling pathway and increases NRF1 and COXIV synthesis to improve mitochondrial biogenesis. In addition, we showed that the spatial distribution of mitochondrial biogenesis-related factors is disrupted in Alzheimer’s disease, and that neural stem cell-derived exosome treatment can reverse this effect, indicating that neural stem cell-derived exosomes promote mitochondrial biogenesis.

Traditional assessment indexes could not fully describe offshore wind resources, for the meteorological properties of offshore are more complex than onshore. As a result, the uncertainty of offshore wind power projects would be increased and final economic benefits would be affected. Therefore, a study on offshore wind resource assessment is carried out, including three processes of “studying data sources, conducting multi-dimensional indexes system and proposing an offshore wind resource assessment method based on analytic hierarchy process (AHP)”. First, measured wind data and two kinds of reanalysis data are used to analyze the characteristics and reliability of data sources. Second, indexes such as effective wind speed occurrence, affluent level occurrence, coefficient of variation, neutral state occurrence have been proposed to depict availability, richness, and stability of offshore wind resources, respectively. Combined with existing parameters (wind power density, dominant wind direction occurrence, water depth, distance to coast), a multi-dimensional indexes system has been built and on this basis, an offshore wind energy potential assessment method has been proposed. Furthermore, the proposed method is verified by the annual energy production of five offshore wind turbines and practical operating data of four offshore wind farms in China. This study also compares the ranking results of the AHP model to two multi-criteria decision making (MCDM) models including weighted aggregated sum product assessment (WASPAS) and multi-attribute ideal real comparative analysis (MAIRCA). Results show the proposed method gains well in practical engineering applications, where the economic score values have been considered based on the offshore reasonable utilization hours of the whole life cycle in China.

Carbon neutrality has become the global consensus, and wind power is one of the key technologies to achieve carbon neutrality in the power system. However, the randomness and fluctuation of wind energy pose a great challenge to the safe and stable operation of the power system. Accurate wind power prediction results can effectively reduce the adverse effects of wind power uncertainty on power system operation. The high proportion of wind power connected to the grid requires higher prediction accuracy. However, the existing wind power prediction methods exist the problems of inaccurate classification of numerical weather prediction (NWP) and insufficient consideration of actual characteristics. Therefore, a short-term wind power prediction method based on deep clustering-improved Temporal Convolutional Network (TCN) is proposed in this paper. First, 22 typical features of NWP are extracted (including maximum and minimum wind speed, maximum and minimum temperature, etc.). Then, a deep clustering model based on Categorical Generative Adversarial Network is constructed to classify the extracted NWP features accurately. Finally, to address the problem of partial feature loss in the training process of traditional TCN, a gating mechanism is introduced to improve the activation function of its residual block, and an improved TCN prediction model for each class is established. The actual operation data of three wind farms are used to verify the effectiveness and robustness of the proposed wind power prediction method. The results show that the proposed method can reduce the prediction error (Root Mean Squared Error) from 7.18% to 12.87% in three wind farms, compared with other traditional prediction methods.

Abstract Background Ajania Poljakov, an Asteraceae family member, grows mostly in Asia’s arid and semi-desert areas and is a significant commercial and decorative plant. Nevertheless, the genus’ classification has been disputed, and the evolutionary connections within the genus have not been thoroughly defined. Hence, we sequenced and analyzed Ajania’s plastid genomes and combined them with ETS data to assess their phylogenetic relationships. Results We obtained a total of six new Ajania plastid genomes and nine ETS sequences. The whole plastome lengths of the six species sampled ranged from 151,002 bp to 151,115 bp, showing conserved structures. Combined with publicly available data from GenBank, we constructed six datasets to reconstruct the phylogenetic relationships, detecting nucleoplasmic clashes. Our results reveal the affinities of Artemisia, Chrysanthemum and Stilpnolepis to Ajania and validate the early taxonomy reclassification. Some of the plastid genes with low phylogenetic information and gene trees with topological differences may have contributed to the ambiguous phylogenetic results of Ajania. There is extensive evolutionary rate heterogeneity in plastid genes. The psbH and ycf2 genes, which are involved in photosynthesis and ATP transport, are under selective pressure. Plastomes from Ajania species diverged, and structural aspects of plastomes may indicate some of the real evolutionary connections. We suggest the ycf1 gene as a viable plastid DNA barcode because it has significant nucleotide diversity and better reflects evolutionary connections. Conclusion Our findings validate the early Ajania taxonomy reclassification and show evolutionary rate heterogeneity, genetic variety, and phylogenetic heterogeneity of plastid genes. This research might provide new insights into the taxonomy and evolution of Ajania, as well as provide useful information for germplasm innovation and genetic enhancement in horticultural species.

Abstract A chemiluminescent immunoassay for human serum Cystatin C (Cys C) was established using a direct-antibody sandwich model. The immunoassay kit uses magnetic separation technology, using magnetic particles as the reaction solid phase, alkaline phosphatase as the marker enzyme, and a new chemiluminescent substrate APLS as the substrate. It has the characteristics of high sensitivity and short reaction time. This product uses high-affinity antibodies, resulting in a high specificity. The established method showed good accuracy, uniformity, and stability. The limit of detection was 2.39 ng/mL. The intra-assay coefficient of variation (CV) was 3.36%–6.00%, the interassay CV was 4.12%–5.35%, and the recovery rate was 99.07%. The correlation coefficient (r) of Cys-C kit was 0.999388 ≥ 0.9900. The accuracy of the developed method was tested by automatic chemiluminescence instrument (P > 0.05). The lowest titer was 0.92500, and the highest was 1.10000. The developed method showed a good correlation with the product from Roche by comparing these two kits in 240 clinical samples from China. In total, 1392 clinical patient from China samples were measured using the reagent kit developed in this study.

Abstract Surface phase diagrams (SPDs) are essential for understanding the dependence of surface chemistry on reaction condition. For multi-component systems such as metal alloys, the derivation of such diagrams often relies on separate first-principles global optimization tasks under different reaction conditions. Here we show that this can be significantly accelerated by leveraging the fact that all tasks essentially share a unified configurational search space, and only a single expensive electronic structure calculation is required to evaluate the stabilities of a surface structure under all considered reaction conditions. As a general solution, we propose a Bayesian evolutionary multitasking (BEM) framework combining Bayesian statistics with evolutionary multitasking, which allows efficient mapping of SPDs even for very complex surface systems. As proofs of concept, we showcase the performance of our methods in deriving the alloy SPDs for two heterogeneous catalytic systems: the electrochemical oxygen reduction reaction (ORR) and the gas phase steam methane reforming (SMR) reaction.

Abstract Skeletal muscle and thermogenic adipose tissue are both critical for the maintenance of body temperature in mammals. However, whether these two tissues are interconnected to modulate thermogenesis and metabolic homeostasis in response to thermal stress remains inconclusive. Here, we report that human and mouse obesity is associated with elevated Musclin levels in both muscle and circulation. Intriguingly, muscle expression of Musclin is markedly increased or decreased when the male mice are housed in thermoneutral or chronic cool conditions, respectively. Beige fat is then identified as the primary site of Musclin action. Muscle-transgenic or AAV-mediated overexpression of Musclin attenuates beige fat thermogenesis, thereby exacerbating diet-induced obesity and metabolic disorders in male mice. Conversely, Musclin inactivation by muscle-specific ablation or neutralizing antibody treatment promotes beige fat thermogenesis and improves metabolic homeostasis in male mice. Mechanistically, Musclin binds to transferrin receptor 1 (Tfr1) and antagonizes Tfr1-mediated cAMP/PKA-dependent thermogenic induction in beige adipocytes. This work defines the temperature-sensitive myokine Musclin as a negative regulator of adipose thermogenesis that exacerbates the deterioration of metabolic health in obese male mice and thus provides a framework for the therapeutic targeting of this endocrine pathway.

Abstract Wind turbine gearbox condition monitoring (C&M) is a key technology to promote wind farm maintenance cost reduction and power generation improvement. Existing gearbox C&M methods usually adopt the component‐by‐component modelling approach. Firstly, this approach is inefficient in modelling; secondly, due to the thermal conduction effect, abnormalities in one gearbox component usually affect other components, making it difficult to identify the source of faults. To solve these problems, a normal behaviour model (NBM) combining data adaptive noise reduction and an improved variational auto‐encoder (VAE) is proposed, which can monitor the operational condition of multiple components of one gearbox simultaneously and takes into account the correlation between components when warning of the specific abnormal component. As verified by practical cases, the method balances the modelling accuracy and efficiency of the multi‐component NBM and achieves effective early warning and accurate localization of gearbox abnormalities. The proposed model has lower false alarm and missed alarm rates compared to other single‐component and multi‐component NBMs.

Comastoma polycladum is one of the original plant of Tibetan medicine “Zangyinchen”, which contains abundant medical components. To further know the transcriptome of C. polycladum and enrich its genetic information of gene annotation and metabolic pathway, the Pacbio sequencing platform was used to perform full-length transcriptome sequencing of C. polycladum leaves. The results were as follows: (1) A total of 17 Gb of sequencing data was collected, and 87 814 high-quality full-length transcripts were obtained by clustering and de-redundancy of 795 698 circular consistency sequences (CCSs) sequences. (2) Comparing with seven databases, 277 451 transcripts were annotated successfully, and in NR database with 39 214 transcripts annotated the most transcripts. A total of 26 396 transcripts were annotated to the KOG database, with 26 subcategories, and a total of 39 104 transcripts with six major pathways and 40 secondary pathways to the KEGG database. A total of 39 102 transcripts were annotated to the GO database, which were divided into three major categories: molecular function, biological process and cellular component. (3) SSR analysis yielded 22 861 SSRs, with single-base repeats being the most abundant. A total of 1 874 transcription factors and 15 166 long non-coding RNAs (LncRNAs) were identified, and the C3H transcription factor family had the most annotated transcripts. (4) A total of 55 transcripts involved in the synthesis of monoterpenes and flavonoids were screened out. These results enrich the transcriptome information of C. polycladum, and provide significant genetic resources for further screening of candidate genes related to the synthesis of medicinal components of C. polycladum.

ABSTRACTNitrogen gas (N2) fixation driven by diazotrophs is a crucial process for supplying nitrogen to paddy soil ecosystems. The genus Geomonas has been considered to be an important potential diazotroph in paddy soils, but direct experimental evidence of the nitrogen-fixing ability of Geomonas in pure culture is still lacking. Hence, we aimed to demonstrate this nitrogen-fixing capability and shed light on how this process was regulated in response to ammonium (NH4+) in Geomonas. In this study, we determined that a key nitrogenase gene (nifH) was present in 50 isolates from paddy soils. Members of Geomonas contained the minimum nitrogen fixation gene cluster (nifBHDKEN) based on genomic analysis, implying Geomonas species had the potential to fix nitrogen. Acetylene reduction assay (ARA), 15N2 isotope labeling, and total nitrogen accumulation assays validated that Geomonas was, indeed, able to fix nitrogen in pure culture. Under nitrogen-fixing conditions, the cell morphology of Geomonas changed from short rod-shaped (with NH4+) to long rod-shaped and flagella became longer and thicker. The expression of genes correlated to nitrogen fixation in the Geomonas transcriptome was quantified in response to NH4+. Expression of genes associated with nitrogenase, flavin-based electron bifurcation complexes (such as the FixAB system), NH4+ uptake, and transformation (e.g., glutamine and glutamate synthetases) were significantly upregulated under nitrogen-fixing conditions, suggesting these mechanisms might be involved in N2 fixation in Geomonas. These results were verified by RT-qPCR. Taken together, our results demonstrate that Geomonas species possess the ability to fix N2 and expand our understanding on the ecological significance and potential applications of Geomonas in paddy soil ecosystems.IMPORTANCEThe ability of Geomonas species to fix nitrogen gas (N2) is an important metabolic feature for its application as a plant growth-promoting rhizobacterium. This research is of great importance as it provides the first comprehensive direct experimental evidence of nitrogen fixation by the genus Geomonas in pure culture. We isolated a number of Geomonas strains from paddy soils and determined that nifH was present in these strains. This study demonstrated that these Geomonas species harbored genes encoding nitrogenase, as do Geobacter and Anaeromyxobacter in the same class of Deltaproteobacteria. We demonstrated N2-dependent growth of Geomonas and determined regulation of gene expression associated with nitrogen fixation. The research establishes and advances our understanding of nitrogen fixation in Geomonas.

ABSTRACTRefractories subject to loading and unloading repeatedly because of physical effects and thermal stress attack in the service process, which is an important issue shortening the service life of the thermal equipment. Therefore, researches of predicting the service life of refractories under cyclic loading have the guiding significance. The present work investigated the synthesis of ZnAl2O4 and discussed its effects on the alumina castables. The results show that the optimized generation temperature of ZnAl2O4 phase is 1400°C and the hysteresis loop in the curves of cyclic loading reveals a general trend of first sparse and then dense. The cycle times of the specimen with 3 wt.% ZnAl2O4 is 50 times, and the time from starting to loop to fracture is about 4300 s. The fatigue resistance of the specimen with 3 wt.% ZnAl2O4 is superior to ZA-0 and ZA-1.5. The new method of cyclic loading was innovatively adopted in refractories, which provide data and theoretical support for the thermal shock evaluation methods.

Abstract Background Postoperative delirium (POD) is an acute mental disorder that often occurs in the elderly after surgery. It can delay functional recovery, extend hospital stay, and increase 1-year mortality and financial costs. Studies have shown that inflammation and cerebral desaturation are the potential pathogenesis of postoperative delirium. Prone-position surgery increases peak airway pressure and decreases lung compliance, exacerbating ventilator-induced inflammation response, as well as the decrease of the patient's cerebral oxygen saturation. Recent studies demonstrated that lung-protective ventilation strategy could reduce inflammatory response and improve cerebral oxygen saturation (rSO2) to prevent POD. In this trial, we aim to investigate the effect of the individualized PEEP on postoperative delirium in elderly patients during prone position. Methods A prospective, randomized clinical trial will be performed in Hebei General Hospital. 106 patients undergoing elective surgery in prone position will be randomly divided into controlled group (group C) and individualized PEEP group (group I). Lung-protective ventilation with tidal volume of 6ml/kg predictive body weight (PBW) and positive end-expiratory pressure (PEEP) of 5 cm H2O will be applied to patients in group C. Patients in group I will receive the same tidal volume as described in group C plus individualized PEEP corresponding to the maximum dynamic compliance (Cdyn) in the titration method. Our primary endpoint is the prevalence of postoperative delirium based on the Confusion Assessment Method (CAM) until postoperative day 3. Secondary endpoints include the intraoperative rSO2, respiratory variables, arterial blood gases, lung ultrasound score (LUS), postoperative VAS score, and plasma concentrations of IL-6, IL-1β and neuron-specific enolase (NSE). Discussion The results of the current protocol might provide evidence for individualized PEEP to prevent POD among older surgical patients in prone position. Trial registration Chinese Clinical Trial Registry (ChiCTR2200056001). Registered 2022 January 30, http://www.chictr.org.cn/index.aspx .

Perivascular adipose tissue and the vessel wall are connected through intricate bidirectional paracrine and vascular secretory signaling pathways. The secretion of inflammatory factors and oxidative products by the vessel wall in the diseased segment has the ability to influence the phenotype of perivascular adipocytes. Additionally, the secretion of adipokines by perivascular adipose tissue exacerbates the inflammatory response in the diseased vessel wall. Therefore, quantitative and qualitative studies of perivascular adipose tissue are of great value in the context of vascular inflammation and may provide a reference for the assessment of cardiovascular ischemic disease.

IntroductionThe causal association between non-alcoholic fatty liver disease (NAFLD) and osteoporosis remains controversial in previous epidemiological studies. We employed a bidirectional two-sample Mendelian analysis to explore the causal relationship between NAFLD and osteoporosis.MethodThe NAFLD instrumental variables (IVs) were obtained from a large Genome-wide association study (GWAS) meta-analysis dataset of European descent. Two-sample Mendelian randomization (MR) analyses were used to estimate the causal effect of NAFLD on osteoporosis, fracture, and fall. Reverse Mendelian randomization analysis was conducted to estimate the causal effect of osteoporosis on NAFLD. The inverse-variance weighted (IVW) method was the primary analysis in this analysis. We used the MR-Egger method to determine horizontal pleiotropic. The heterogeneity effect of IVs was detected by MR-Egger and IVW analyses.ResultsFive SNPs (rs2980854, rs429358, rs1040196, rs738409, and rs5764430) were chosen as IVs for NAFLD. In forward MR analysis, the IVW-random effect indicated the causal effect of NAFLD on osteoporosis (OR= 1.0021, 95% CI: 1.0006-1.0037, P= 0.007) but not on fracture (OR= 1.0016, 95% CI: 0.998-1.0053, P= 0.389) and fall (OR= 0.9912, 95% CI: 0.9412-1.0440, P= 0.740). Furthermore, the reverse Mendelian randomization did not support a causal effect of osteoporosis on NAFLD (OR= 1.0002, 95% CI: 0.9997-1.0007, P= 0.231). No horizontal pleiotropic was detected in all MR analyses.ConclusionsThe results of this study indicate a causal association between NAFLD and osteoporosis. NAFLD patients have a higher risk of osteoporosis but not fracture and falling risk. In addition, our results do not support a causal effect of osteoporosis on NAFLD.

Abstract Cardiac fibrosis is associated with activation of cardiac fibroblasts (CFs), a pathological, phenotypic transition that is widely believed to be irreversible in the late stages of disease development. Sensing of a stiffened mechanical environment through regulation of integrin-based adhesion plaques and activation of the Piezo1 mechanosensitive ion channel is known to factor into this transition. Here, using integrated in vitro and in silico models, we discovered a mutually reinforcing, mechanical positive feedback loop between integrin β1 and Piezo1 activation that forms a bistable switch. The bistable switch is initiated by perturbations in matrix elastic modulus that amplify to trigger downstream signaling involving Ca2+ and YAP that, recursively, leads fibroblasts to further stiffen their environment. By simultaneously interfering with the newly identified mechanical positive feedback loop and modulating matrix elastic modulus, we reversed markers of phenotypical transition of CF, suggesting new therapeutic targets for fibrotic disease.

ObjectiveThe present study aimed to explore the combined associations of depression and cognitive impairment with functional disability and mortality, and whether the joint effects of depression and cognitive impairment on mortality were influenced by functional disability.MethodsA total of 2,345 participants aged 60 and above from the 2011–2014 cycle of the National Health and Nutrition Examination Survey (NHANES) were included in the analyses. Questionnaires were used to evaluated depression, global cognitive function and functional disability (including disability in activities of daily living (ADLs), instrumental activities of daily living (IADLs), leisure and social activities (LSA), lower extremity mobility (LEM), and general physical activity (GPA)). Mortality status was ascertained up to December 31, 2019. Multivariable logistic regression was performed to investigate the associations of depression and low global cognition with functional disability. Cox proportional hazards regression models were conducted to evaluate the effect of depression and low global cognition on mortality.ResultsInteractions between depression and low global cognition were observed when exploring associations of depression and low global cognition with IADLs disability, LEM disability, and cardiovascular mortality. Compared with normal participants, participants with both depression and low global cognition had the highest odds ratios of disability in ADLs, IADLs, LSA, LEM, and GPA. Besides, participants with both depression and low global cognition also had the highest hazard ratios of all-cause mortality and cardiovascular mortality, and these associations remained after adjusting for disability in ADLs, IADLs, LSA, LEM, and GPA.ConclusionOlder adults with both depression and low global cognition were more likely to have functional disability, and had the highest risk of all-cause mortality and cardiovascular mortality.

Super wear-resistant absorbers are important for next-generation high-stability optical splitters. However, traditional absorbers cannot obtain ideal wear resistance because of the limitation of hardness. We show that solid solutions of transition metal carbides are new hard, low-refractive-index lossy materials (HLLM). Super wear-resistant absorbers were obtained by constructing HLLM-based optical cavities. As a proof-of-concept, the absorptance of our fabricated Ti0.93W0.07C-based optical cavity was 95.6% in 400–800 nm wavelength range. In addition, its wear resistance was 23.3 times greater than that of traditional absorbers. Through the experiments and theoretical calculations, we proposed the design principles of HLLM and presented the materials map.[Graphic: see text]

Abstract. Background:. High-dose dual therapy (HDDT) with proton pump inhibitors (PPIs) and amoxicillin has attracted widespread attention due to its favorable efficacy in eradicating Helicobacter pylori (H. pylori). This study aimed to compare the efficacy and safety of high-dose PPI–amoxicillin dual therapy and bismuth-containing quadruple therapy for H. pylori rescue treatment. Methods:. This was a prospective, randomized, multicenter, non-inferiority trial. Patients recruited from eight centers who had failed previous treatment were randomly (1:1) allocated to two eradication groups: HDDT (esomeprazole 40 mg and amoxicillin 1000 mg three times daily; the HDDT group) and bismuth-containing quadruple therapy (esomeprazole 40 mg, bismuth potassium citrate 220 mg, and furazolidone 100 mg twice daily, combined with tetracycline 500 mg three times daily; the tetracycline, furazolidone, esomeprazole, and bismuth [TFEB] group) for 14 days. The primary endpoint was the H. pylori eradication rate. The secondary endpoints were adverse effects, symptom improvement rates, and patient compliance. Results:. A total of 658 patients who met the criteria were enrolled in this study. The HDDT group achieved eradication rates of 75.4% (248/329), 81.0% (248/306), and 81.3% (248/305) asdetermined by the intention-to-treat (ITT), modified intention-to-treat (MITT), and per-protocol (PP) analyses, respectively. The eradication rates were similar to those in the TFEB group: 78.1% (257/329), 84.2% (257/305), and 85.1% (257/302). The lower 95% confidence interval boundary (−9.19% in the ITT analysis, − 9.21% in the MITT analysis, and −9.73% in the PP analysis) was greater than the predefined non-inferiority margin of −10%, establishing a non-inferiority of the HDDT group vs. the TFEB group. The incidence of adverse events in the HDDT group was significantly lower than that in the TFEB group (11.1% vs. 26.8%, P

CasRx, a recently discovered member of the type VI CRISPR system with minimum size, offers a new approach for RNA manipulation with high efficiency and specificity in prokaryotes and eukaryotes. However, in vivo studies of functional recovery using the CasRx system have not been well characterized. Here, we sought to establish an adeno-associated virus (AAV)-CasRx-guide RNA (gRNA) system for the specific knockdown of Htra2 transcript to protect mice from aminoglycosides-induced hearing loss. For the study, we verified an optimized gRNA in vitro, which was packaged into a single AAV with CasRx, and injected the packaged AAV into mice with hearing loss induced by neomycin and auditory functions investigated by auditory brainstem response tests. Upon using the AAV-CasRx-gRNA system, we found the knockdown of Htra2 transcript led to less cochlear hair cell loss and improved auditory function, with low off-target and adverse side effects. Additionally, the decrease in Htra2 significantly inhibits mRNA expression of Casp3 and Casp9. In conclusion, the AAV-CasRx-gRNA-mediated knockdown of Htra2 transcript in mice has been proved effective and safe for preventing hearing loss induced by aminoglycosides and, thus, represents a promising genetic approach for the future clinical applications for treating non-inherited hearing loss.

Abstract The structural stability of nanoalloys is a challenging research subject due to the complexity of size, shape, composition, and chemical ordering. The genetic algorithm is a popular global optimization method that can efficiently search for the ground-state nanoalloy structure. However, the algorithm suffers from three significant limitations: the efficiency and accuracy of the energy evaluator and the algorithm’s efficiency. Here we describe the construction of a neural network potential intended for rapid and accurate energy predictions of Pt-Ni nanoalloys of various sizes, shapes, and compositions. We further introduce a symmetry-constrained genetic algorithm that significantly improves the efficiency and viability of the algorithm for realistic size nanoalloys. The combination of the two allows us to explore the space of homotops and compositions of Pt-Ni nanoalloys consisting of up to 4033 atoms and quantitatively report the interplay of shape, size, and composition on the dominant chemical ordering patterns.

Al–Cu–Li bicrystals with different misorientation gradients were prepared to study the effect of misorientation and precipitates on the initial corrosion behavior of the Al–Cu–Li alloy by scanning electron microscopy (SEM), transmission electron microscopy (TEM), immersion testing, and electrochemical testing. The results show that the initial corrosions were generated on the matrix rather than on the grain boundary for the as-quenched alloy. The effect of grain boundary misorientation on the corrosion rates of the as-quenched alloy is very limited. On the other hand, for the aged alloy, the initial corrosions were generated on the grain boundaries, which suffer more severe corrosion than the matrix. Meanwhile, the corrosion of high angle grain boundary (HAGB) is more severe than that of low angle grain boundary (LAGB) for the aged alloy. These results are associated with the high number density of the continuously distributed precipitates on grain boundaries.

Wave energy has emerged as a focal point in marine renewable energy research. Accurate prediction of wave power plays a pivotal role in enhancing power supply reliability. This paper introduces an innovative wave power prediction method that combines seasonal–trend decomposition using LOESS (STL) with a dual-channel Seq2Seq model. The decomposition model addresses the issue of component redundancy in current input decomposition methods, thereby uncovering key components. The prediction model improves upon the limitations of current prediction models that directly concatenate multiple features, allowing for a more detailed consideration of both trend and periodic features. The proposed approach begins by decomposing the power sequence based on tidal periods and optimal correlation criteria, effectively extracting both trend and periodic features. Subsequently, a dual-channel Seq2Seq model is constructed. The first channel employs temporal pattern attention to capture the trend and stochastic fluctuation information, while the second channel utilizes multi-head self-attention to further enhance the extraction of periodic components. Model validation is performed using data from two ocean buoys, each with a five-year dataset. The proposed model achieves an average 2.45% reduction in RMSE compared to the state-of-the-art method. Both the decomposition and prediction components of the model contribute to this increase in accuracy.