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Stent(s) insertion is a common form of surgery for patients with cardiovascular diseases, and is associated with a high rate of hospital readmission. This study aims to investigate the acute association between PM2.5 exposure and hospital readmission for patients with cardiovascular disease and a history of stent(s) insertion. The records of hospital admission were collected from the Beijing Municipal Commission of Health and Family Planning Information Center between 1st January 2013 and 31st December 2017. Subsequent hospital readmission records for patients with a history of stent(s) insertion or without any surgery were extracted. The conditional logistic regression model was applied to investigate the association between PM2.5 concentration and cardiovascular disease readmission in patients who had undergone stent(s) insertion or without any surgery. A total of 81,468 patients who had a history of stent(s) insertion were included in this study. Of these, 17,224 patients (21.1 % of the total number of patients) were readmitted 27,749 times due to cardiovascular disease. The median daily PM2.5 concentration was 62.8 μg/m3 with an interquartile range (IQR) of 71.5 μg/m3. The excess risk (ER) associated 10 μg/m3 increase in PM2.5 concentration for readmission due to cardiovascular disease was 0.48 % (95 % CI: 0.09 %, 0.87 %) in patients with a history of stent(s) insertion. Patients who had stent(s) insertion at the vessel bifurcation site showed the highest risk of readmission for cardiovascular disease when exposed to PM2.5; the ER was 4.12 % (95 % CI: 1.60 %, 6.70 %). PM2.5 was significantly associated with angina pectoris and readmission for chronic ischemic heart disease in patients with a history of stent(s) insertion. PM2.5 had a significant association with cardiovascular readmission among patients with a history of insertion of stent(s). Patients who had vessel bifurcation treated showed the highest risk of readmission.

IntroductionLow back pain (LBP) was commonly induced by intervertebral disc degeneration (IVDD), which is accompanied by the loss of disc height and osteophyte generation. Cell-based therapy is a promising treatment for preventing the degeneration of interverbral disc. In our study, allogeneic fibroblasts are shown to ameliorate intervertebral disc degeneration by reducing osteophytes in rabbits.MethodsWe established a rabbits-derived fibroblast (Rab-Fib) which could be expanded in vitro and constructed puncture-induced intervertebral disc degeneration rabbit model. Histologic and imaging examinations and analyses were performed after 2 weeks, 3 months, and 12 months.ResultsOur data indicate that stable and reliably-extracted allogeneic fibroblasts can effectively ameliorate intervertebral disc degeneration by reducing osteophytes.ConclusionOur study provides a basis for advancing the further translation of fibroblasts in intervertebral disc therapy.

Sialic acid-binding immunoglobulin-like lectin 15 (Siglec-15) is a well-conserved type I transmembrane protein of the Siglecs family, distributed in macrophages and dendritic cells in the human spleen and lymph nodes. As an immune receptor, Siglec-15 is expressed in almost all branches of the spinal cord. Siglec-15 participates in the metabolism of the skeleton by regulating osteoclast activity and differentiation and has an influential role in dynamic bone remodelling. The binding of DNAX activation protein of 12 kDa (DAP12), which contains the immunoreceptor tyrosine-based activation motif (ITAM) activation domain, to the Siglec-15 receptor provides a positive stimulatory signal for osteoclast growth, with the involvement of the receptor activator of nuclear factor-κB (RANK)/RANK ligand (RANKL) signalling. Recently, Siglec-15 antibodies have been shown to effectively prevent bone resorption in mouse models of osteoporosis and accelerate fracture healing to some extent. Therefore, exploring the molecular characteristics and functions of Siglec-15 may lead to new therapeutic strategies for common clinical skeletal diseases.

Whey protein is an important food ingredient, but it is also considered a major food allergen. The aim of this study was to investigate the effect of ultrasound pretreatment on the structure, IgE binding capacity, functional properties and biological activity of whey protein isolate (WPI) hydrolysates (WPH), including WPI hydrolyzed by a combination of enzymes from Bromelain and ProteAXH (BA-WPI) and WPI hydrolyzed by a combination of enzymes from Papain W-40 and ProteAXH (PA-WPI). The IgE binding capacity of BA-WPI and PA-WPI was reduced to 40.28% and 30.17%, respectively, due to disruption/exposure/shielding of conformational and linear epitopes. The IgE binding capacity of sonicated WPI was increased, but ultrasound pretreatment further reduced the IgE binding capacity of the hydrolysates to 32.89% and 28.04%. This is due to the fact that ultrasound pretreatment leads to conformational changes including increased α-helix and β-sheet structure, exposure of aromatic amino acids, surface hydrophobicity, and increased sulfhydryl content, which increases the accessibility of allergenic epitopes to WPI by the enzyme. Multispectral and LC-MS/MS results further indicated that ultrasound pretreatment altered the conformational and primary structural changes of the hydrolysates. The thermograms showed that ultrasound pretreatment mainly altered the epitope spectra of β-lactoglobulin hydrolysates, while it had less effect on the epitope spectra of α-lactalbumin hydrolysates. Additionally, ultrasound pretreatment significantly improved the foaming properties, antioxidant activity, and α-glucosidase inhibition of the hydrolysates without impairing the solubility and emulsification properties of the hydrolysates. Therefore, ultrasound pretreatment is a feasible method to reduce the allergenicity of WPH and to improve their functional properties and bioactivity. Notably, ultrasonic pretreatment improved the effectiveness and efficiency of WPI hydrolysis, which is a feasible method to produce high-quality protein feedstock in a green, efficient, and economical way.

Objective: The CABANA study shows that atrial fibrillation (AF) paitents younger than 65 years benefit more from the AF radiofrequency catheter ablation (RFCA) procedure. The aim of this study is to investigate the impact of inherent patent foramen ovale (PFO) with a Left-to-Right Shunt on the RFCA procedure in young AF patients. Methods: Based on the presence or absence of inherent PFO, the AF patients were divided into the PFO groups and the non-PFO group. Clinical follow-up was also investigated. Results: A total of 285 AF patients were enrolled. PFO was detected by TEE in 42 patients. The age of patients at initial AF onset was younger in the PFO group than in the non-PFO group (58.3 ± 8.9 vs. 62.3 ± 9.6 years, P = 0.012). There were more AF patients aged

Rice bran, a byproduct of rice processing, holds great nutritional value. However, its application in the food industry is greatly restricted due to its high susceptibility to rancidity and spoilage during storage. Currently, it is primarily used as animal feed with low added value. The presence of lipase and lipoxygenase is the major cause of rapid rancidity of rice bran, and other factors such as water activity, microorganisms and phenolic substances also affect the rancidity reaction. Stabilization treatment of rice bran is a key prerequisite to achieving high-value utilization of the product. This paper provides an overview of the rancidity mechanism of rice bran, the common methods for stabilizing rice bran and their impact on its quality and nutritional characteristics, with a view to providing guidance and reference for the research and development of rice bran as a food-grade raw material.

Objective To analyze the genome-wide profiles of H3K9 crotonylation (H3K9cr) in mouse embryonic stem cells (mESCs) in normal or deficient folic acid (FA) by chromatin immunoprecipitation sequencing (ChIP-seq) in order to observe the genome-wide changes in H3K9cr status and the regulated pathway genes under FA deficiency condition. Methods The mESCs were divided into normal FA group (4 mg/L, FA4) and FA deficient group (0 mg/L, FA0). Western blotting and immunohistochemical (IHC) assay were used to detect the protein level of H3K9cr in the FA deficient mESCs and the embryonic brain tissues of neural tube defects (NTDs) mice, respectively. ChIP-seq technology was carried out for sequence identification of the obtained specific binding DNA fragments. Differentially expressed genes (DEGs) were analyzed and visualized by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathways, with the aim of analyzing the whole genome of mESCs with FA deficiency and validating the regulated genes. Results Overall H3K9cr level was significantly lower in the FA deficient mESCs and the embryonic brain tissues of NTDs mice than in the corresponding normal FA mESCs and mice (P < 0.05). Neurodevelopmental-related genes such as Bdnf, Pax6, and App were down-regulated in the FA deficient mESCs (P < 0.05). The KEGG pathway analysis indicated that the DEGs were concentrated in axon-guiding, neuroactive ligand-receptor interaction, glutaminergic synapses and other nervous system-related pathways. Conclusion FA deficiency in embryonic stem cells participates in the regulation of neurodevelopmental genes through modification of H3K9cr, suggesting that the modification of histone crotonylation may be involved in neurodevelopmental diseases induced by FA deficiency.

Abstract Background This study is to propose a clinically applicable 2-echelon (2e) diagnostic criteria for the analysis of thyroid nodules such that low-risk nodules are screened off while only suspicious or indeterminate ones are further examined by histopathology, and to explore whether artificial intelligence (AI) can provide precise assistance for clinical decision-making in the real-world prospective scenario. Methods In this prospective study, we enrolled 1036 patients with a total of 2296 thyroid nodules from three medical centers. The diagnostic performance of the AI system, radiologists with different levels of experience, and AI-assisted radiologists with different levels of experience in diagnosing thyroid nodules were evaluated against our proposed 2e diagnostic criteria, with the first being an arbitration committee consisting of 3 senior specialists and the second being cyto- or histopathology. Results According to the 2e diagnostic criteria, 1543 nodules were classified by the arbitration committee, and the benign and malignant nature of 753 nodules was determined by pathological examinations. Taking pathological results as the evaluation standard, the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) of the AI systems were 0.826, 0.815, 0.821, and 0.821. For those cases where diagnosis by the Arbitration Committee were taken as the evaluation standard, the sensitivity, specificity, accuracy, and AUC of the AI system were 0.946, 0.966, 0.964, and 0.956. Taking the global 2e diagnostic criteria as the gold standard, the sensitivity, specificity, accuracy, and AUC of the AI system were 0.868, 0.934, 0.917, and 0.901, respectively. Under different criteria, AI was comparable to the diagnostic performance of senior radiologists and outperformed junior radiologists (all P 0.05). Conclusions The proposed 2e diagnostic criteria are consistent with real-world clinical evaluations and affirm the applicability of the AI system. Under the 2e criteria, the diagnostic performance of the AI system is comparable to that of senior radiologists and significantly improves the diagnostic capabilities of junior radiologists. This has the potential to reduce unnecessary invasive diagnostic procedures in real-world clinical practice.

Abstract Research on the association between dietary adherence and cancer risk is limited, particularly concerning overall cancer risk and its underlying mechanisms. Using the UK Biobank data, we prospectively investigate the associations between adherence to a Mediterranean diet (MedDiet) or a Mediterranean-Dietary Approaches to Stop Hypertension Diet Intervention for Neurodegenerative Delay diet (MINDDiet) and the risk of overall and 22 specific cancers, as well as the mediating effects of metabolites. Here we show significant negative associations of MedDiet and MINDDiet adherence with overall cancer risk. These associations remain robust across 14 and 13 specific cancers, respectively. Then, a sequential analysis, incorporating Cox regression, elastic net and gradient boost models, identify 10 metabolites associated with overall cancer risk. Mediation results indicate that these metabolites play a crucial role in the association between adherence to a MedDiet or a MINDDiet and cancer risk, independently and cumulatively. These findings deepen our understanding of the intricate connections between diet, metabolites, and cancer development.

Abstract The construction of a large-scale quantum internet requires quantum repeaters containing multiple entangled photon sources with identical wavelengths. Semiconductor quantum dots can generate entangled photon pairs deterministically with high fidelity. However, realizing wavelength-matched quantum-dot entangled photon sources faces two difficulties: the non-uniformity of emission wavelength and exciton fine-structure splitting induced fidelity reduction. Typically, these two factors are not independently tunable, making it challenging to achieve simultaneous improvement. In this work, we demonstrate wavelength-tunable entangled photon sources based on droplet-etched GaAs quantum dots through the combined use of AC and quantum-confined Stark effects. The emission wavelength can be tuned by ~1 meV while preserving an entanglement fidelity f exceeding 0.955(1) in the entire tuning range. Based on this hybrid tuning scheme, we finally demonstrate multiple wavelength-matched entangled photon sources with f > 0.919(3), paving the way towards robust and scalable on-demand entangled photon sources for quantum internet and integrated quantum optical circuits.

Abstract Lung cancer is a leading cause of cancer-related mortality globally, with a dismal 5-year survival rate, particularly for Lung Adenocarcinoma (LUAD). Mechanical changes within the tumor microenvironment, such as extracellular matrix (ECM) remodeling and fibroblast activity, play pivotal roles in cancer progression and metastasis. However, the specific impact of the basement membrane (BM) on the mechanical characteristics of LUAD remains unclear. This study aims to identify BM genes influencing internal mechanical stress in tumors, elucidating their effects on LUAD metastasis and therapy resistance, and exploring strategies to counteract these effects. Using Matrigel overlay and Transwell assays, we found that mechanical stress, mimicked by matrix application, augmented LUAD cell migration and invasion, correlating with ECM alterations and activation of the epithelial-mesenchymal transition (EMT) pathway. Employing machine learning, we developed the SVM_Score model based on relevant BM genes, which accurately predicted LUAD patient prognosis and EMT propensity across multiple datasets. Lower SVM_Scores were associated with worse survival outcomes, elevated cancer-related pathways, increased Tumor Mutation Burden, and higher internal mechanical stress in LUAD tissues. Notably, the SVM_Score was closely linked to COL5A1 expression in myofibroblasts, a key marker of mechanical stress. High COL5A1 expression from myofibroblasts promoted tumor invasiveness and EMT pathway activation in LUAD cells. Additionally, treatment with Sorafenib, which targets COL5A1 secretion, attenuated the tumor-promoting effects of myofibroblast-derived COL5A1, inhibiting LUAD cell proliferation, migration, and enhancing chemosensitivity. In conclusion, this study elucidates the complex interplay between mechanical stress, ECM alterations, and LUAD progression. The SVM_Score emerges as a robust prognostic tool reflecting tumor mechanical characteristics, while Sorafenib intervention targeting COL5A1 secretion presents a promising therapeutic strategy to mitigate LUAD aggressiveness. These findings deepen our understanding of the biomechanical aspects of LUAD and offer insights for future research and clinical applications.

Abstract Objective The mainstream view in trait aggression research has regarded the structure as representing the latent cause of the cognitions, emotions, and behaviors that supposedly reflect its nature. Under network perspective, trait aggression is not a latent cause of its features but a dynamic system of interacting elements. The current study uses network theory to explain the structure of relationships between trait aggression features in juvenile offenders and their peers. Methods Network analysis was applied to investigate the dynamic system of trait aggression operationalized by the Buss-Perry Aggression Questionnaire in a sample of community youths (Mage = 17.46, N = 715) and juvenile offenders (Mage = 18.36, N = 834). Results The facet level networks showed that anger is a particularly effective mechanism for activating all other traits. In addition, anger was more strongly associated with physical aggression and the overall network strength was greater in juvenile delinquency networks than in their peers. The item level networks revealed that A4 and A6 exhibited the highest predictability and strength centrality in both samples. Also, the Bayesian network indicated that these two items were positioned at the highest level in the model. There are similarities and differences between juvenile delinquents and community adolescents in trait aggression. Conclusion Trait aggression was primarily activated by difficulty controlling one’s temper and feeling like a powder keg.

Abstract Celiac Disease (CD) is a primary malabsorption syndrome resulting from the interplay of genetic, immune, and dietary factors. CD negatively impacts daily activities and may lead to conditions such as osteoporosis, malignancies in the small intestine, ulcerative jejunitis, and enteritis, ultimately causing severe malnutrition. Therefore, an effective and rapid differentiation between healthy individuals and those with celiac disease is crucial for early diagnosis and treatment. This study utilizes Raman spectroscopy combined with deep learning models to achieve a non-invasive, rapid, and accurate diagnostic method for celiac disease and healthy controls. A total of 59 plasma samples, comprising 29 celiac disease cases and 30 healthy controls, were collected for experimental purposes. Convolutional Neural Network (CNN), Multi-Scale Convolutional Neural Network (MCNN), Residual Network (ResNet), and Deep Residual Shrinkage Network (DRSN) classification models were employed. The accuracy rates for these models were found to be 86.67%, 90.76%, 86.67% and 95.00%, respectively. Comparative validation results revealed that the DRSN model exhibited the best performance, with an AUC value and accuracy of 97.60% and 95%, respectively. This confirms the superiority of Raman spectroscopy combined with deep learning in the diagnosis of celiac disease.

Abstract Background Addison’s disease and X-linked adrenoleukodystrophy (X-ALD) (Addison’s-only) are two diseases that need to be identified. Addison’s disease is easy to diagnose clinically when only skin and mucosal pigmentation symptoms are present. However, X-ALD (Addison’s-only) caused by ABCD1 gene variation is ignored, thus losing the opportunity for early treatment. This study described two patients with initial clinical diagnosis of Addison’s disease. However, they rapidly developed neurological symptoms triggered by infection. After further genetic testing, the two patients were diagnosed with X-ALD. Methods We retrospectively analyzed X-ALD patients admitted to our hospital. Clinical features, laboratory test results, and imaging data were collected. Whole-exome sequencing was used in molecular genetics. Results Two patients were included in this study. Both of them had significantly increased adrenocorticotropic hormone level and skin and mucosal pigmentation. They were initially clinically diagnosed with Addison’s disease and received hydrocortisone treatment. However, both patients developed progressive neurological symptoms following infectious disease. Further brain magnetic resonance imaging was completed, and the results suggested demyelinating lesions. Molecular genetics suggested variations in the ABCD1 gene, which were c.109_110insGCCA (p.C39Pfs*156), c.1394–2 A > C (NM_000033), respectively. Therefore, the two patients were finally diagnosed with X-ALD, whose classification had progressed from X-ALD (Addison’s-only) to childhood cerebral adrenoleukodystrophy (CCALD). Moreover, the infection exacerbates the demyelinating lesions and accelerates the onset of neurological symptoms. Neither the two variation sites in this study had been previously reported, which extends the ABCD1 variation spectrum. Conclusions Patients with only symptoms of adrenal insufficiency cannot be simply clinically diagnosed with Addison’s disease. Being alert to the possibility of ABCD1 variation is necessary, and complete genetic testing is needed as soon as possible to identify X-ALD (Addison’s-only) early to achieve regular monitoring of the disease and receive treatment early. In addition, infection, as a hit factor, may aggravate demyelinating lesions of CCALD. Thus, patients should be protected from external environmental factors to delay the progression of cerebral adrenoleukodystrophy.

ABSTRACT: The objective of this study was to examine the aroma profiles of 12 Gouda cheeses sold in China and to determine which aromas were preferred by young Chinese consumers (n = 110). The consumers selected 11 descriptors of the aromas of the Gouda cheeses in a check-all-that-apply questionnaire. These 11 descriptors were used by a panel of experts for sensory analysis to perform a quantitative descriptive analysis of the cheeses. A principal component analysis of the data from the quantitative descriptive analysis revealed that the characteristic aromas of young Gouda cheeses, medium-aged Gouda cheeses, and aged Gouda cheeses were “milky” and “whey”; “creamy” and “sour”; and “rancid” and “nutty,” respectively. The results of a penalty analysis combined with the check-all-that-apply results and the preference scores showed that the 3 groups of young Chinese consumers (those who often ate cheese, occasionally ate cheese, and never ate cheese) preferred the Gouda cheeses with “milky” or “creamy” aromas and did not enjoy those with “sour” or “rancid” aromas. Occasional cheese eaters comprised the majority of the young Chinese consumers, and they were more tolerant of the Gouda cheeses with “whey” and “sulfury” aromas than those who often or never ate cheese. In addition, we identified a positive correlation between the consumers' preferences for the aromas of the Gouda cheeses and their willingness to pay for them. Overall, the results of this study should help promote the development of Gouda cheeses and associated products that meet the preferences of young Chinese consumers.

Abstract Imbalanced class distributions are common in real-world scenarios, including datasets with multiple labels. One widely acknowledged approach to addressing imbalanced distributions is through oversampling, a technique that both balances the class distribution and improves the effectiveness of classification models. However, when generating synthetic data for multi-label datasets, complexities arise due to the presence of multiple-label sets, which require careful placement and labeling. We propose MLCSMOTE-FRST, an algorithm for synthetic data generation based on label-specific clustering and fuzzy rough set theory. Generation ratios and dependency samples are provided by clusters specific to each label, with a focus on the overall label distribution and the distribution within each cluster. The labels are supported by intra-cluster positive samples, determined using fuzzy rough set theory, which helps to capture the consensus label set. Experimental results on multi-label datasets using four classifiers demonstrate the effectiveness of the proposed method in terms of macro-F1 and micro-F1 scores.

Abstract Background Anisodus tanguticus (Maxim.) Pascher (A. tanguticus) is a valuable botanical for extracting tropane alkaloids, which are widely used in the pharmaceutical industry. Implementing appropriate cultivation methods can improve both the quality and yield of A. tanguticus. A two-year field experiment was conducted from 2021 to 2023 using a single-factor randomized complete block design replicated three times. The study examined the effects of different nutrient levels (nitrogen: 0, 75, 150, 225, 300, 375 kg/ha; phosphorus: 0, 600, 750, 900, 1050, 1200 kg/ha; potassium: 0, 75, 112.5, 150, 187.5, 225 kg/ha) on the growth, primary alkaloid contents, and alkaloid yield of A. tanguticus at different growth stages (S-Greening, S-Growing, S-Wilting; T-Greening, T-Growing, and T-Wilting) in both the roots and aboveground portions. Results Our results demonstrate that nutrient levels significantly affect the growth and alkaloid accumulation in A. tanguticus. High nitrogen levels (375 kg/ha) notably increased both root and aboveground biomass, while phosphorus had a minimal effect, especially on aboveground biomass. For alkaloid content (scopolamine, anisodamine, anisodine, atropine), a moderate nitrogen level (225 kg/ha) was most effective, followed by low potassium (75 kg/ha), with phosphorus showing a limited impact. Increased phosphorus levels led to a decrease in scopolamine content. During the T-Growing period, moderate nitrogen addition (225 kg/ha) yielded the highest alkaloid levels per unit area (205.79 kg/ha). In the T-Wilting period, low potassium (75 kg/ha) and low phosphorus (750 kg/ha) resulted in alkaloid levels of 146.91 kg/ha and 142.18 kg/ha, respectively. This indicates nitrogen has the most substantial effect on alkaloid accumulation, followed by potassium and phosphorus. The Douglas production function analysis suggests focusing on root biomass and the accumulation of scopolamine and atropine in roots to maximize alkaloid yield in A. tanguticus cultivation. Conclusions Our findings show that the optimum harvesting period for A. tanguticus is the T-Wilting period, and that the optimal nitrogen addition is 225 kg/ha, the optimal potassium addition is 75 kg/ha, and the optimal phosphorus addition is 600 kg/ha or less.

Abstract Background Growing evidence indicated that to develop of atherosclerosis observed more often by people with Alzheimer’s disease (AD), but the underlying mechanism is not fully clarified. Considering that amyloid-β (Aβ) deposition in the brain is the key pathophysiology of AD and plasma Aβ is closely relate to Aβ deposition in the brain, in the present study, we investigated the relationships between atherosclerosis and plasma Aβ levels. Methods This was a population based cross-sectional study. Patients with high risk of atherosclerosis from Qubao Village, Xi’an were underwent carotid ultrasound for assessment of atherosclerosis. Venous blood was collected on empty stomach in the morning and plasma Aβ1−40 and Aβ1−42 levels were measured using ELISA. Multivariate logistic regression analysis was performed to investigate the relationships between carotid atherosclerosis (CAS) and plasma Aβ levels. Results Among 344 patients with high risk of atherosclerosis, 251(73.0%) had CAS. In the univariate analysis, the plasma Aβ levels had no significant differences between CAS group and non-CAS group (Aβ1−40: 53.07 ± 9.24 pg/ml vs. 51.67 ± 9.11pg/ml, p = 0.211; Aβ1−42: 40.10 ± 5.57 pg/ml vs. 40.70 pg/ml ± 6.37pg/ml, p = 0.285). Multivariate logistic analysis showed that plasma Aβ levels were not associated with CAS (Aβ1−40: OR = 1.019, 95%CI: 0.985–1.054, p = 0.270;Aβ1−42: OR = 1.028, 95%CI: 0.980–1.079, p = 0.256) in the total study population. After stratified by hypertension, CAS was associated with plasma Aβ1−40 positively (OR = 1.063, 95%CI: 1.007–1.122, p = 0.028) in the non-hypertension group, but not in hypertensive group. When the plasma Aβ concentrations were classified into four groups according to its quartile, the highest level of plasma Aβ1−40 group was associated with CAS significantly (OR = 4.465, 95%CI: 1.024–19.474, p = 0.046). Conclusion Among patients with high risk of atherosclerosis, CAS was associated with higher plasma Aβ1−40 level in non-hypertension group, but not in hypertension group. These indicated that atherosclerosis is associated with plasma Aβ level, but the relationship may be confounded by hypertension.

Abstract Background Apoptotic cell‐conditioned mesenchymal stem cells (AC‐MSCs) exhibit stronger T cell suppressive ability via cyclooxygenase 2 (COX2)/prostaglandin E2 (PGE2); however, whether AC‐MSCs exhibit enhanced therapeutic effects on systemic lupus erythematosus (SLE) remains unknown. Methods Splenocytes from MRL/MPJ‐Faslpr (MRL/lpr) mice were cocultured with AC‐MSCs, and the proportion of plasma cells was determined by flow cytometry. MSCs, AC‐MSCs, COX2 knockdown MSCs, and COX2 knockdown AC‐MSCs were infused into MRL/lpr mice (n = 10/group). Survival rates and lupus symptoms, including proteinuria, kidney injury, renal immune complex deposition, and autoantibody production, were assessed. Additionally, the number of plasma cells and serum levels of inflammatory cytokines were measured. Results The AC‐MSCs significantly inhibited plasma cells via PGE2 after 24 h coculture in vitro, whereas MSCs did not. In the MRL/lpr mice, AC‐MSC treatment led to a significantly higher survival rate than phosphate‐buffered saline (PBS) treatment (90% vs. 50%, p

Dracocephalum moldavica is widely used as an ornamental, medicine, and perfume in industry. Real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) is widely and accurately utilized for gene expression evaluations. Selecting optimal reference genes is essential for normalizing RT-qPCR results. However, the identification of suitable reference genes in D. moldavica has not been documented. A total of 12 reference genes in D. moldavica were identified by PEG6000 (15%) treatment under hypertonia conditions in different tissues (roots, stem, leaves, flower, seeds and sepal) and during three stages of flower development, then used to validate the expression stability. There were four algorithms (delta Ct, geNorm, NormFinder, and BestKeeper) used to analyze the stability. Finally, the RefFinder program was employed to evaluate the candidate reference genes’ stability. The results showed that ACTIN, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and EF1α (elongation factor-1α) were stable reference genes under the PEG6000 treatment. Heat shock protein 70 (HSP70) was the most stable gene across different flower development stages. ADP-ribosylation factor (ARF) was the most stable gene in different tissues and total samples. This study provides reliable gene expression studies for future research in D. moldavica.

Abstract We conducted spatial immune tumor microenvironment (iTME) profiling using formalin-fixed paraffin-embedded (FFPE) samples of 25 KRAS-mutated non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), including 12 responders and 13 non-responders. An eleven-marker panel (CD3, CD4, CD8, FOXP3, CD68, arginase-1, CD33, HLA-DR, pan-keratin (PanCK), PD-1, and PD-L1) was used to study the tumor and immune cell compositions. Spatial features at single cell level with cellular neighborhoods and fractal analysis were determined. Spatial features and different subgroups of CD68+ cells and FOXP3+ cells being associated with response or resistance to ICIs were also identified. In particular, CD68+ cells, CD33+ and FOXP3+ cells were found to be associated with resistance. Interestingly, there was also significant association between non-nuclear expression of FOXP3 being resistant to ICIs. We identified CD68dim cells in the lung cancer tissues being associated with improved responses, which should be insightful for future studies of tumor immunity.

Abstract Steering on the intrinsic active site of an electrode material is essential for efficient electrochemical biomass upgrading to valuable chemicals with high selectivity. Herein, we show that an in-situ surface reconstruction of a two-dimensional layered CdPS 3 nanosheet electrocatalyst, triggered by electrolyte, facilitates efficient 5-hydroxymethylfurfural (HMF) hydrogenation to 2,5-bis(hydroxymethyl)furan (BHMF) under ambient condition. The in-situ Raman spectroscopy and comprehensive post-mortem catalyst characterizations evidence the construction of a surface-bounded CdS layer on CdPS3 to form CdPS 3 /CdS heterostructure. This electrocatalyst demonstrates promising catalytic activity, achieving a Faradaic efficiency for BHMF reaching 91.3 ± 2.3 % and a yield of 4.96 ± 0.16 mg/h at − 0.7 V versus reversible hydrogen electrode. Density functional theory calculations reveal that the in-situ generated CdPS 3 /CdS interface plays a pivotal role in optimizing the adsorption of HMF* and H* intermediate, thus facilitating the HMF hydrogenation process. Furthermore, the reconstructed CdPS 3 /CdS heterostructure cathode, when coupled with MnCo 2 O 4.5 anode, enables simultaneous BHMF and formate synthesis from HMF and glycerol substrates with high efficiency.

Anticipating uncertainty in short-term traffic flow is crucial for effective traffic management within intelligent transportation systems. Various methods for predicting uncertainty have been proposed and implemented. However, conventional techniques struggle to provide accurate forecasts when confronted with sparse data. Hence, this study focuses on developing an uncertainty prediction model for short-term traffic flow under limited data conditions. A novel grey model that considers the volatility of the traffic data is proposed, which extends the grey model (GM) by integrating two techniques: smooth pre-processing and background value construction. The performance of the proposed novel grey model is mainly illustrated by comparing the novel grey model with the traditional GM model. Our results, in terms of uncertainty quantification, demonstrate that the proposed model outperforms the GM model regarding mean kick-off percentage (KP), width interval (WI) and width amplitude.

Abstract Artificial intelligence (AI) telephone is reliable for the follow‐up and management of hypertensives. It takes less time and is equivalent to manual follow‐up to a high degree. We conducted a reliability study to evaluate the efficiency of AI telephone follow‐up in the management of hypertension. During May 18 and June 30, 2020, 350 hypertensives managed by the Pengpu Community Health Service Center in Shanghai were recruited for follow‐up, once by AI and once by a human. The second follow‐up was conducted within 3–7 days (mean 5.5 days). The mean length time of two calls were compared by paired t‐test, and Cohen's Kappa coefficient was used to evaluate the reliability of the results between the two follow‐up visits. The mean length time of AI calls was shorter (4.15 min) than that of manual calls (5.24 min, P

Abstract Kidney renal clear cell carcinoma (KIRC) is the most common histological type of renal cancer, enhancer RNA plays a significant role in tumor growth, however, it has been less studied in renal cancer. The aim of this study was to investigate the role of eRNA AC003092.1 in KIRC. Clinical and RNA expression data were downloaded from a TCGA database, and performed bioinformatics analysis, including expression level analysis, survival analysis, clinical correlation analysis, immune correlation analysis. We further confirmed the expression level of AC003092.1 between normal and tumor cell, predicted the biological role of AC003092.1 in KIRC, and performed cell proliferation and wound healing assays, followed by GSEA enrichment analysis and western blot to detect the proteins of the enriched pathway. Bioinformatics results showed that AC003092.1 expression was elevated in tumor tissues, and knockdown of AC003092.1 expression inhibited cell proliferation and migration. GSEA and western blot results showed that knockdown AC003092.1 expression alleviated the extracellular matrix (ECM) process in KIRC cell lines. Our study provides evidence that AC003092.1 play an important role in KIRC, and AC003092.1 may promote tumor cell progression by affecting the ECM process during tumor development.

Abstract Background No reliable clinical tools exist to predict acute kidney injury (AKI) progression. We aim to explore a scoring system for predicting the composite outcome of progression to severe AKI or death within seven days among early AKI patients after cardiac surgery. Methods In this study, we used two independent cohorts, and patients who experienced mild/moderate AKI within 48 h after cardiac surgery were enrolled. Eventually, 3188 patients from the MIMIC-IV database were used as the derivation cohort, while 499 patients from the Zhongshan cohort were used as external validation. The primary outcome was defined by the composite outcome of progression to severe AKI or death within seven days after enrollment. The variables identified by LASSO regression analysis were entered into logistic regression models and were used to construct the risk score. Results The composite outcome accounted for 3.7% (n = 119) and 7.6% (n = 38) of the derivation and validation cohorts, respectively. Six predictors were assembled into a risk score (AKI-Pro score), including female, baseline eGFR, aortic surgery, modified furosemide responsiveness index (mFRI), SOFA, and AKI stage. And we stratified the risk score into four groups: low, moderate, high, and very high risk. The risk score displayed satisfied predictive discrimination and calibration in the derivation and validation cohort. The AKI-Pro score discriminated the composite outcome better than CRATE score, Cleveland score, AKICS score, Simplified renal index, and SRI risk score (all P

Abstract In order to cope with the grid fluctuation caused by large‐scale wind power connected to the grid, the wind thermal power generation system has been proposed and extensively studied. The wind thermal power generation system uses a wind turbine to drive a heat generation device to heat the heat storage medium, which is further exchanged to drive a turbine to generate electricity. A superconducting magnetic eddy current heater (SMH) is proposed for the characteristics of wind thermal power generation system, which uses non‐resistive, large current‐carrying superconducting coils for excitation, and has high output efficiency and power density. The working principle of magnetic eddy current heating is analysed, and the structure of SMH with no ferromagnetic material and two heating screens inside and outside is proposed according to the characteristics of SMH. An analytical model of the SMH is established, and the influence of the structure and materials of the SMH on the magnetic field distribution is analysed. Based on this, a 22‐pole SMH was designed and analysed for output power at 10–20 rpm. A three‐dimensional magnetism‐stress combined analysis model of SMH is established, and the strain and stress characteristics of SMH are simulated under the condition of maximum output power, which verifies the feasibility of the mechanical properties of existing superconducting materials for application in SMH.

Abstract The envelope (E) protein of the Japanese encephalitis virus (JEV) is a key protein for virus infection and adsorption of host cells, which determines the virulence of the virus and regulates the intensity of inflammatory response. The mutation of multiple aa residues in the E protein plays a critical role in the attenuated strain of JEV. This study demonstrated that the Asp to Gly, Ser, and His mutation of the E389 site, respectively, the replication ability of the viruses in cells was significantly reduced, and the viral neuroinvasiveness was attenuated to different degrees. Among them, the mutation at E389 site enhanced the E protein flexibility contributed to the attenuation of neuroinvasiveness. In contrast, less flexibility of E protein enhanced the neuroinvasiveness of the strain. Our results indicate that the mechanism of attenuation of E389 aa mutation attenuates neuroinvasiveness is related to increased flexibility of the E protein. In addition, the increased flexibility of E protein enhanced the viral sensitivity to heparin inhibition in vitro, which may lead to a decrease in the viral load entering brain. These results suggest that E389 residue is a potential site affecting JEV virulence, and the flexibility of the E protein of aa at this site plays an important role in the determination of neuroinvasiveness.

Abstract Background None of the early M-Health applications are designed for case management care services. This study aims to describe the process of developing a M-health component for the case management model in breast cancer transitional care and to highlight methods for solving the common obstacles faced during the application of M-health nursing service. Methods We followed a four-step process: (a) Forming a cross-functional interdisciplinary development team containing two sub-teams, one for content development and the other for software development. (b) Applying self-management theory as the theoretical framework to develop the M-health application, using contextual analysis to gain a comprehensive understanding of the case management needs of oncology nursing specialists and the supportive care needs of out-of-hospital breast cancer patients. We validated the preliminary concepts of the framework and functionality of the M-health application through multiple interdisciplinary team discussions. (c) Adopting a multi-stage optimization strategy consisting of three progressive stages: screening, refining, and confirmation to develop and continually improve the WeChat mini-programs. (d) Following the user-centered principle throughout the development process and involving oncology nursing specialists and breast cancer patients at every stage. Results Through a continuous, iterative development process and rigorous testing, we have developed patient-end and nurse-end program for breast cancer case management. The patient-end program contains four functional modules: “Information”, “Interaction”, “Management”, and “My”, while the nurse-end program includes three functional modules: “Consultation”, “Management”, and “My”. The patient-end program scored 78.75 on the System Usability Scale and showed a 100% task passing rate, indicating that the programs were easy to use. Conclusions Based on the contextual analysis, multi-stage optimization strategy, and interdisciplinary team work, a WeChat mini-program has been developed tailored to the requirements of the nurses and patients. This approach leverages the expertise of professionals from multiple disciplines to create effective and evidence-based solutions that can improve patient outcomes and quality of care.

Abstract Two-dimensional semiconductors with high thermal conductivity and charge carrier mobility are of great importance for next-generation electronic and optoelectronic devices. However, constrained by the long-held Slack’s criteria, the reported two-dimensional semiconductors such as monolayers of MoS2, WS2, MoSe2, WSe2 and black phosphorus suffer from much lower thermal conductivity than silicon (~142 W·m–1·K–1) because of the complex crystal structure, large average atomic mass and relatively weak chemical bonds. Despite the more complex crystal structure, the recently emerging monolayer MoSi2N4 semiconductor has been predicted to have high thermal conductivity and charge carrier mobility simultaneously. In this work, using a noncontact optothermal Raman technique, we experimentally measure a high thermal conductivity of ~173 W·m–1·K–1 at room temperature for suspended monolayer MoSi2N4 grown by chemical vapor deposition. First-principles calculations reveal that such unusually high thermal conductivity benefits from the high Debye temperature and small Grüneisen parameter of MoSi2N4, both of which are strongly dependent on the high Young’s modulus induced by the outmost Si-N bilayers. Our study not only establishes monolayer MoSi2N4 as a benchmark 2D semiconductor for next-generation electronic and optoelectronic devices, but also provides an insight into the design of 2D materials for efficient heat conduction.

Abstract Engineering natural microbiomes for biotechnological applications remains challenging, as metabolic interactions within microbiomes are largely unknown, and practical principles and tools for microbiome engineering are still lacking. Here, we present a combinatory top-down and bottom-up framework to engineer natural microbiomes for the construction of function-enhanced synthetic microbiomes. We show that application of herbicide and herbicide-degrader inoculation drives a convergent succession of different natural microbiomes toward functional microbiomes (e.g., enhanced bioremediation of herbicide-contaminated soils). We develop a metabolic modeling pipeline, SuperCC, that can be used to document metabolic interactions within microbiomes and to simulate the performances of different microbiomes. Using SuperCC, we construct bioremediation-enhanced synthetic microbiomes based on 18 keystone species identified from natural microbiomes. Our results highlight the importance of metabolic interactions in shaping microbiome functions and provide practical guidance for engineering natural microbiomes.

In network service systems, the occurrence of anomaly events often leads to a large number of alarm events in the system, forming alarm storms. Operators need to spend a lot of time and effort searching for key information and identifying the root cause of anomaly events from these alarm data. In order to reduce the number of alarms that operators needed to handle, as well as automatically extracted the root alarms in the alarm storm, a method for generating an alarm causality graph based on the analysis of the propagation mode of network service alarms was proposed , and applied to extract key information of the alarm storm when anomaly events occurred. Real datasets of an operator's online network management system were used in experiments to verify the effect of building the alarm causal graph in extracting the alarm storm abstract. A real-world case was used to analyze the physical significance of this method. The results show that the recall rate of extracting alarm storm summary can reach 96% and the vast majority of key information is retained by using the method of alarm causality graph generation. In addition, the compression rate of alarms using this method can reach 66.5% for alarm codes that are difficult to compress.

BACKGROUND: It is reported that sudden sensorineural hearing loss (SSNHL) is closely related to diabetes, hypertension, and hyperlipidemia. While the metabolic syndrome (MetS) is a multifactorial disease that includes diabetes, hypertension, dyslipidemia, and obesity, which are known to be associated with SSNHL. Weather conditions have long been known to affect the SSNHL. This study aimed to make a clear connection between MetS, or weather conditions, and the severity and prognosis of SSNHL. METHODS: 127 SSNHL patients have been divided into the MetS group and the non-MetS group, and the demographic and clinical characteristics of the 2 groups have been analyzed retrospectively. RESULTS: There were 52 (40.9%) patients in the MetS group, while there were 75 (59.1%) patients in the non-MetS group. The rate of vertigo, hypertension, diabetes, lower high-density lipoprotein cholesterol (HDL-C) levels, high triglyceride (TG), and body mass index (BMI) ≥25 (kg/m2 ) were significantly higher in the MetS group than those in non-MetS group. Vertigo, hypertension, and Mets were linked to the severity of hearing loss. The rate of complete recovery and partial recovery in the MetS group was clearly lower than that in non-MetS group. According to the multivariate analysis, MetS was significantly associated with a poorer prognosis of SSNHL; a high ambient temperature difference at onset and hypertension were correlated with a poor prognosis. CONCLUSION: These results demonstrate that the severity and prognosis of SSNHL can be influenced by the MetS. High ambient temperature differences at onset and hypertension were indicators of a poor prognosis for SSNHL

Abstract Transcriptional regulation plays a crucial role in determining cell fate and disease, yet inferring the key regulators from gene expression data remains a significant challenge. Existing methods for estimating transcription factor (TF) activity often rely on static TF-gene interaction databases and cannot adapt to changes in regulatory mechanisms across different cell types and disease conditions. Here, we present a new algorithm - Transcriptional Inference using Gene Expression and Regulatory data (TIGER) - that overcomes these limitations by flexibly modeling activation and inhibition events, up-weighting essential edges, shrinking irrelevant edges towards zero through a sparse Bayesian prior, and simultaneously estimating both TF activity levels and changes in the underlying regulatory network. When applied to yeast and cancer TF knock-out datasets, TIGER outperforms comparable methods in terms of prediction accuracy. Moreover, our application of TIGER to tissue- and cell-type-specific RNA-seq data demonstrates its ability to uncover differences in regulatory mechanisms. Collectively, our findings highlight the utility of modeling context-specific regulation when inferring transcription factor activities.

Abstract The identification of effective therapeutic targets plays a pivotal role in advancing cancer treatment outcomes. We employed a comprehensive pan-cancer analysis, complemented by experimental validation, to explore the potential of Nicotinamide N-methyltransferase (NNMT) as a promising therapeutic strategy for human cancers. By analyzing large-scale transcriptomic datasets across various cancer types, we consistently observed upregulated expression of NNMT. Furthermore, elevated NNMT expression correlated with inferior overall survival in multiple cancer cohorts, underscoring its significance as a prognostic biomarker. Additionally, we investigated the relationship between NNMT expression and the tumor immune microenvironment, which plays a crucial role in regulating anti-tumor immune responses. To confirm the malignant functions of NNMT in tumor cells, we conducted a series of cell-based experiments, revealing that NNMT promotes cancer cell proliferation and invasion, indicative of its oncogenic properties. The integration of computational analysis and experimental validation in our study firmly establishes NNMT as a potential therapeutic target for human cancers. Specifically, targeting NNMT holds promise for the development of innovative and effective cancer treatments. Further investigations into NNMT's role in cancer pathogenesis could potentially pave the way for groundbreaking advancements in cancer treatment.

Abstract Abscisic acid (ABA) plays a crucial role in promoting plant stress resistance and seed dormancy. However, how ABA regulates rice quality remains unclear. This study identifies a key transcription factor SLR1-like2 (SLRL2), which mediates the ABA-regulated amylose content (AC) of rice. Mechanistically, SLRL2 interacts with NF-YB1 to co-regulate Wx, a determinant of AC and rice quality. In contrast to SLR1, SLRL2 is ABA inducible but insensitive to GA. In addition, SLRL2 exhibits DNA-binding activity and directly regulates the expression of Wx, bHLH144 and MFT2. SLRL2 competes with NF-YC12 for interaction with NF-YB1. NF-YB1 also directly represses SLRL2 transcription. Genetic validation supports that SLRL2 functions downstream of NF-YB1 and bHLH144 in regulating rice AC. Thus, an NF-YB1-SLRL2-bHLH144 regulatory module is successfully revealed. Furthermore, SLRL2 regulates rice dormancy by modulating the expression of MFT2. In conclusion, this study revealed an ABA-responsive regulatory cascade that functions in both rice quality and seed dormancy.

Abstract Background This study aims to implement a validated prediction model and application medium for postoperative pneumonia (POP) in elderly patients with hip fractures in order to facilitate individualized intervention by clinicians. Methods Employing clinical data from elderly patients with hip fractures, we derived and externally validated machine learning models for predicting POP. Model derivation utilized a registry from Nanjing First Hospital, and external validation was performed using data from patients at the Fourth Affiliated Hospital of Nanjing Medical University. The derivation cohort was divided into the training set and the testing set. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used for feature screening. We compared the performance of models to select the optimized model and introduced SHapley Additive exPlanations (SHAP) to interpret the model. Results The derivation and validation cohorts comprised 498 and 124 patients, with 14.3% and 10.5% POP rates, respectively. Among these models, Categorical boosting (Catboost) demonstrated superior discrimination ability. AUROC was 0.895 (95%CI: 0.841–0.949) and 0.835 (95%CI: 0.740–0.930) on the training and testing sets, respectively. At external validation, the AUROC amounted to 0.894 (95% CI: 0.821–0.966). The SHAP method showed that CRP, the modified five-item frailty index (mFI-5), and ASA body status were among the top three important predicators of POP. Conclusion Our model’s good early prediction ability, combined with the implementation of a network risk calculator based on the Catboost model, was anticipated to effectively distinguish high-risk POP groups, facilitating timely intervention.

Abstract In plants, the plant-specific RNA polymerase V (Pol V) transcripts non-coding RNAs and provides a docking platform for the association of accessory proteins in the RNA-directed DNA methylation (RdDM) pathway. Various components have been uncovered that are involved in the process of DNA methylation, but it is still not clear how the transcription of Pol V is regulated. Here, we report that the conserved RNA polymerase II (Pol II) elongator, SPT6L, binds to thousands of intergenic regions in a Pol II-independent manner. The intergenic enrichment of SPT6L, interestingly, co-occupies with the largest subunit of Pol V (NRPE1) and mutation of SPT6L leads to the reduction of DNA methylation but not Pol V enrichment. Furthermore, the association of SPT6L at Pol V loci is dependent on the Pol V associated factor, SPT5L, rather than the presence of Pol V, and the interaction between SPT6L and NRPE1 is compromised in spt5l. Finally, Pol V RIP-seq reveals that SPT6L is required to maintain the amount and length of Pol V transcripts. Our findings thus uncover the critical role of a Pol II conserved elongator in Pol V mediated DNA methylation and transcription, and shed light on the mutual regulation between Pol V and II in plants.

Abstract Background Postoperative cognitive dysfunction (POCD) is a common complication after anesthesia/surgery, especially among elderly patients, and poses a significant threat to their postoperative quality of life and overall well-being. While it is widely accepted that elderly patients may experience POCD following anesthesia/surgery, the exact mechanism behind this phenomenon remains unclear. Several studies have indicated that the interaction between silent mating type information regulation 2 homologue 1 (SIRT1) and brain-derived neurotrophic factor (BDNF) is crucial in controlling cognitive function and is strongly linked to neurodegenerative disorders. Hence, this research aims to explore how SIRT1/BDNF impacts cognitive decline caused by anesthesia/surgery in aged mice. Methods Open field test (OFT) was used to determine whether anesthesia/surgery affected the motor ability of mice, while the postoperative cognitive function of 18 months old mice was evaluated with Novel object recognition test (NORT), Object location test (OLT) and Fear condition test (FC). The expressions of SIRT1 and other molecules were analyzed by western blot and immunofluorescence staining. The hippocampal synaptic plasticity was detected by Golgi staining and Long-term potentiation (LTP). The effects of SIRT1 and BDNF overexpression as well as chemogenetic activation of glutamatergic neurons in hippocampal CA1 region of 18 months old vesicular glutamate transporter 1 (VGLUT1) mice on POCD were further investigated. Results The research results revealed that older mice exhibited cognitive impairment following intramedullary fixation of tibial fracture. Additionally, a notable decrease in the expression of SIRT1/BDNF and neuronal excitability in hippocampal CA1 glutamatergic neurons was observed. By increasing levels of SIRT1/BDNF or enhancing glutamatergic neuron excitability in the CA1 region, it was possible to effectively mitigate synaptic plasticity impairment and ameliorate postoperative cognitive dysfunction. Conclusions The decline in SIRT1/BDNF levels leading to changes in synaptic plasticity and neuronal excitability in older mice could be a significant factor contributing to cognitive impairment after anesthesia/surgery. Graphical Abstract

The fissure morphology has an important influence on rock mechanical properties and crack propagation behavior. A series of uniaxial compression tests were carried out on the intact granite samples and granite samples with different prefabricated fissure dip angles (0°, 15°, 30°, 45°, 60°, 75°, and 90°). Simultaneously, the rock failure process was monitored and recorded by acoustic emission (AE) and high-definition camera, respectively. As the fissure dip angle increases, the test results indicate that the crack initiation angle of rock decreases gradually; the peck strength, crack initiation stress, and peak strain of all the fractured rocks are increased gradually. The elastic modulus of rock increases firstly and then decreases with the increase of fracture dip angle. The initial compaction section and linear elastic section of the rock stress-strain relationship curve correspond to the quiet period of acoustic emission. The acoustic emission enters the development period after the load exceeds the crack initiation stress. When the load approaches the peak strength, the acoustic emission is in the peak period until the rock failure completely. The lager the fracture dip angle, the longer the peak duration period of acoustic emission and the more in quantity of the cumulative ringing count. A good linear relationship is presented between fracture rock peak strength and cumulative ringing count, and the influence of crack shape on rock strength damage is quantified. With the increase of fissure dip angle, the fracture mode of rock gradually transitions from shear fracture to tensile fracture. According to the relationship curves between rock axial stress and cumulative AE impact number, combined with the calculation method of rock initiation stress, It found that the calculated value is slightly larger than the camera observation value with the error range of 1.7% ~ 6.9%, indicating that the calculation method of rock crack initiation stress is reasonable. This study provides basic information for investigating the engineering properties and failure mode of fracture rock.

Abstract A novel framework for adaptive energy management, rooted in deep learning principles, is proposed to minimize fuel consumption in extended‐range electric vehicles amidst intricate driving scenarios. This innovative approach integrates a long short‐term memory (LSTM) network for pattern recognition across three driving patterns and an adaptive fuzzy controller. To mitigate the impact of poor hyperparameter selection on recognition accuracy, Gray Wolf Optimization is employed to optimize the hidden layer nodes, training times, and learning rate of the LSTM. Simultaneously, a genetic algorithm is utilized to optimize the vertex coordinates of the fuzzy control membership function, enabling the adaptive adjustment of parameters in the fuzzy energy management strategy. The condition recognition model accurately identifies the vehicle's driving status and seamlessly transitions to an energy management strategy tailored to the present conditions. This ensures optimal operation, enhancing overall fuel efficiency and performance. The simulation results robustly validate the efficacy of this approach: the GWO‐LSTM network achieves an impressive 97.7% accuracy in recognizing working conditions, surpassing the 88.9% accuracy of the traditional LSTM network. Furthermore, the fuel consumption reduction achieved by the adaptive fuzzy energy management strategy amounts to 11.9% compared with the conventional fuzzy energy management approach. This outcome underscores the tangible enhancement in vehicle fuel economy resulting from the seamless integration of deep learning techniques.

Abstract Objective To assess the influence of supply and demand factors on the contract behavior of occupational populations with general practitioner (GP) teams. Methods We employed a system dynamics approach to assess and predict the effect of the general practitioner service package (GPSP) and complementary incentive policies on the contract rate for 2015–2030. First, the GPSP is designed to address the unique needs of occupational populations, enhancing the attractiveness of GP contracting services, including three personalized service contents tailored to demand-side considerations: work-related disease prevention (WDP), health education & counseling (HEC), and health-care service (HCS). Second, the complementary incentive policies on the supply-side included income incentives (II), job title promotion (JTP), and education & training (ET). Considering the team collaboration, the income distribution ratio (IDR) was also incorporated into supply-side factors. Findings The contract rate is predicted to increase to 57.8% by 2030 after the GPSP intervention, representing a 15.4% increase on the non-intervention scenario. WDP and HEC have a slightly higher (by 2%) impact on the contract rate than that from HCS. Regarding the supply-side policies, II have a more significant impact on the contract rate than JTP and ET by 3–5%. The maximum predicted contract rate of 75.2% is expected by 2030 when the IDR is 0.5, i.e., the GP receives 50% of the contract income and other members share 50%. Conclusion The GP service package favorably increased the contract rate among occupational population, particularly after integrating the incentive policies. Specifically, for a given demand level, the targeted content of the package enhanced the attractiveness of contract services. On the supply side, the incentive policies boost GPs’ motivation, and the income distribution motivated other team members.

Abstract Glioblastoma multiforme (GBM) is a highly aggressive brain tumor characterized by invasive behavior and a compromised immune response, presenting treatment challenges. Surgical debulking of GBM fails to address its highly infiltrative nature, leaving neoplastic satellites in an environment characterized by impaired immune surveillance, ultimately paving the way for tumor recurrence. Tracking and eradicating residual GBM cells by boosting antitumor immunity is critical for preventing postoperative relapse, but effective immunotherapeutic strategies remain elusive. Here, we report a cavity-injectable bacterium-hydrogel superstructure that targets GBM satellites around the cavity, triggers GBM pyroptosis, and initiates innate and adaptive immune responses, which prevent postoperative GBM relapse in male mice. The immunostimulatory Salmonella delivery vehicles (SDVs) engineered from attenuated Salmonella typhimurium (VNP20009) seek and attack GBM cells. Salmonella lysis-inducing nanocapsules (SLINs), designed to trigger autolysis, are tethered to the SDVs, eliciting antitumor immune response through the intracellular release of bacterial components. Furthermore, SDVs and SLINs administration via intracavitary injection of the ATP-responsive hydrogel can recruit phagocytes and promote antigen presentation, initiating an adaptive immune response. Therefore, our work offers a local bacteriotherapy for stimulating anti-GBM immunity, with potential applicability for patients facing malignancies at a high risk of recurrence.

Abstract Background Prior observational research has investigated the association between dietary patterns and Alzheimer’s disease (AD) risk. Nevertheless, due to constraints in past observational studies, establishing a causal link between dietary habits and AD remains challenging. Methods Methodology involved the utilization of extensive cohorts sourced from publicly accessible genome-wide association study (GWAS) datasets of European descent for conducting Mendelian randomization (MR) analyses. The principal analytical technique utilized was the inverse-variance weighted (IVW) method. Results The MR analysis conducted in this study found no statistically significant causal association between 20 dietary habits and the risk of AD (All p > 0.05). These results were consistent across various MR methods employed, including MR-Egger, weighted median, simple mode, and weighted mode approaches. Moreover, there was no evidence of horizontal pleiotropy detected (All p > 0.05). Conclusion In this MR analysis, our finding did not provide evidence to support the causal genetic relationships between dietary habits and AD risk.

Abstract Distributed stochastic zeroth-order optimization (DSZO), in which the objective function is allocated over multiple agents and the derivative of cost functions is unavailable, arises frequently in large-scale machine learning and reinforcement learning. This paper introduces a distributed stochastic algorithm for DSZO in a projection-free and gradient-free manner via the Frank-Wolfe framework and the stochastic zeroth-order oracle (SZO). Such a scheme is particularly useful in large-scale constrained optimization problems where calculating gradients or projection operators is impractical, costly, or when the objective function is not differentiable everywhere. Specifically, the proposed algorithm, enhanced by recursive momentum and gradient tracking techniques, guarantees convergence with just a single batch per iteration. This significant improvement over existing algorithms substantially lowers the computational complexity. Under mild conditions, we prove that the complexity bounds on SZO of the proposed algorithm are O ( n / ϵ 2 ) $\mathcal{O}(n/\epsilon ^{2})$ and O ( n ( 2 1 ϵ ) ) $\mathcal{O}(n(2^{\frac{1}{\epsilon}}))$ for convex and nonconvex cases, respectively. The efficacy of the algorithm is verified on black-box binary classification problems against several competing alternatives.

Background: Refractive errors, particularly myopia, are the leading visual disorders worldwide, significantly affecting the quality of life (QOL) even after correction. This scoping review focuses on health-related quality of life (HRQOL) measurements for children and adolescents with refractive errors. Main text: We explored generic and disease-specific HRQOL tools, examining their content, psychometric properties, and the impact of various interventions on QOL. Two English databases—PubMed, Embase, and one Chinese database, CNKI, were searched for relevant studies published from January 2001 to October 2023. Inclusion criteria encompassed studies using standardized instruments to assess the QOL of children aged 0–18 with refractive errors. The review compares prevalent HRQOL measurements, analyzes children's refractive error assessments, and discusses intervention effects on patient QOL. Conclusions: The study underlines the necessity of developing disease-specific QOL instruments for very young children and serves as a practical guide for researchers in this field. The findings advocate for a targeted approach in HRQOL assessment among the pediatric population, identifying critical gaps in current methodologies.

The increasing penetration of renewable energy sources in power systems presents frequency stability challenges, as power electronic-connected sources like photovoltaics and batteries inherently provide limited inertia and damping for frequency regulation. To address this issue, this paper proposes a distributed cooperative control method for secondary frequency regulation. Additionally, it achieves economic dispatch among generators and proportional power sharing among renewable energy sources. The proposed control system enables photovoltaics and battery energy storage systems to actively manage frequency in conjunction with power generators. It operates using a sparse communication network that mirrors the topology of the power network. Moreover, the cooperative control method can tolerate communication time delays while maintaining a stable frequency response. The frequency stability of the proposed control system, both with and without time delays, is assured through Lyapunov methods and eigenvalue analysis. Validation is performed on a modified IEEE 14-bus system with integrated photovoltaics and batteries, demonstrating the efficacy of the proposed secondary frequency control.

This study employs two-sample Mendelian Randomization (MR) analysis to investigate the causal relationship between light DIY activities and prostate cancer. We used single nucleotide polymorphisms (SNPs) associated with light DIY activities obtained from published genome-wide association studies (GWASs) and summary-level genetic data related to prostate cancer from published GWAS. The primary analysis was conducted using the inverse-variance weighted (IVW) method for two-sample MR analysis. Cochran’s Q statistic was used to assess heterogeneity, MR-Egger was employed to detect horizontal pleiotropy, and “leave-one-out” analysis was performed for sensitivity analysis. Given the presence of heterogeneity, the random-effects IVW method was used for the primary analysis. The random-effects IVW results indicated a positive causal relationship between participation in light DIY activities and the risk of prostate cancer (odds ratio [OR] = 1.024, 95% confidence interval [CI]: 1.001–1.048; p = .039). The weighted median (WM) method results supported this finding (OR = 1.025, 95% CI: 1.003–1.048; p = .024). Participation in light DIY activities may slightly increase the risk of prostate cancer. This finding emphasizes the need to carefully consider the types and intensities of physical activities when making public health recommendations and personal lifestyle choices.

Abstract Heteroaromatic N‐oxides, renowned for their highly polar N─O bond and robust structure, exhibit significant bioactivities and have played a pivotal role in various drug development projects since the discovery of Minoxidil. Moreover, heteroaromatic N‐oxides, featuring axially chiral biaryl frameworks, are indispensable as Lewis base catalysts and ligands in organic synthesis. Despite their importance, synthesizing these chiral compounds is challenging, necessitating chiral starting materials or resolution processes. Catalytic strategies rely on the functionalization of heteroaromatic N‐oxide compounds, leading to products with a relatively limited skeletal diversity. This study introduces a Cu‐catalyzed atroposelective method for synthesizing biaryl N‐oxides via de novo heteroaromatic N‐oxide ring formation. This mild and efficient approach achieves excellent stereoselectivities (up to 99:1 er), enabling the production of a wide array of N‐oxides with novel heteroaromatic scaffolds. The axially chiral N‐oxide product 3f demonstrates high stereoselectivity and recyclability as a Lewis base catalyst. Additionally, product 3e exhibits promising therapeutic efficacy against triple‐negative breast cancer, with IC50 values of 4.8 and 5.2 µm in MDA‐MB‐231 and MDA‐MB‐468 cells, respectively. This research not only advances the synthesis of challenging chiral heteroaromatic N‐oxides but also encourages further exploration of N‐oxide entities in the discovery of bioactive small molecules.