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Abstract Preclinical studies demonstrating high cure rates with PD1/PD-L1 combinations have led to numerous clinical trials, but emerging results are disappointing. These combined immunotherapies are commonly employed for patients with refractory tumors following prior treatment with cytotoxic agents. Here, we uncovered that the post-chemotherapy tumor presents a unique mechanical microenvironment characterized by an altered extracellular matrix (ECM) elasticity and increased stiffness, which facilitate the development of aggressive tumor phenotypes and confer resistance to checkpoint blocking therapy. As thus, we rationally designed an in situ nanocomposite hydrogel system, LOS&FeOX@Gel, which enabled effective and specific delivery of the therapeutic payloads (losartan [LOS] and oxaliplatin [OX]) into tumor. We demonstrate that sustained release of LOS effectively remodels the tumor mechanical microenvironment (TMM) by reducing ECM deposition and its associated “solid stress”, thereby augmenting the efficacy of OX and its immunological effects. Importantly, this hydrogel system greatly sensitized post-chemotherapy tumor to checkpoint blocking therapy, showing synergistic therapeutic effects against cancer metastasis. Our study provides mechanistic insights and preclinical rationale for modulating TMM as a potential neoadjuvant regimen for tumor to optimize the benefits of chemo-immunotherapy, which lays the groundwork for leveraging “mechanical-immunoengineering” strategies to combat refractory tumors. Graphical Abstract

Abstract Cerebrovascular abnormalities are critical indicators of stroke and neurodegenerative diseases like Alzheimer’s disease (AD). Understanding the normal evolution of brain vessels is essential for detecting early deviations and enabling timely interventions. Here, for the first time, we proposed a pipeline exploring the joint evolution of cortical volumes (CVs) and arterial volumes (AVs) in a large cohort of 2841 individuals. Using advanced deep learning for vessel segmentation, we built normative models of CVs and AVs across spatially hierarchical brain regions. We found that while AVs generally decline with age, distinct trends appear in regions like the circle of Willis. Comparing healthy individuals with those affected by AD or stroke, we identified significant reductions in both CVs and AVs, wherein patients with AD showing the most severe impact. Our findings reveal gender-specific effects and provide critical insights into how these conditions alter brain structure, potentially guiding future clinical assessments and interventions.

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in China. Most HCC patients have the complication of chronic liver disease and need overall consideration and whole-course management, including diagnosis, treatment and follow-up. To develop a reasonable, long-term, and complete management plan, multiple factors need to be considered, including the patient's general condition, basic liver diseases, tumor stage, tumor biological characteristics, treatment requirements and economic cost. Summary: To better guide the whole-course management of HCC patients, the Chinese Association of Liver Cancer and the Chinese Medical Doctor Association has gathered multidisciplinary experts and scholars in relevant fields to formulate the “Chinese Expert Consensus on The Whole-Course Management of Hepatocellular Carcinoma (2023).” Key Messages: This expert consensus, based on the current clinical evidence and experience, proposes surgical and nonsurgical HCC management pathways and involves 18 recommendations, including perioperative treatment, systematic treatment combined with local treatment, conversion treatment, special population management, symptomatic support treatment, and follow-up management.

Abstract Bladder cancer (BCa), as the most common malignant tumor of the urinary system, has received significant attention in research on the clinical application of artificial intelligence algorithms. Nevertheless, it has been observed that certain investigations use data from various medical facilities to train models for BCa, which may pose a privacy risk. Given this concern, protecting patient privacy during machine learning algorithm training is a crucial aspect that requires substantial attention. One emerging machine learning paradigm that addresses this concern is federated learning (FL). FL enables multiple entities to collaboratively build machine learning models while preserving data privacy and security. In this study, we present a multicenter BCa magnetic resonance imaging (MRI) dataset. The dataset comprises 275 three-dimensional bladder T2-weighted MRI scans collected from four medical centers, and each scan includes diagnostic pathological labels for muscle invasion and pixel-level annotations of tumor contours. Four FL methods are used to assess the baseline of the dataset for both the task of diagnosing muscle-invasive bladder cancer and automatic bladder tumor lesion segmentation.

Abstract Background Exosomes (EXO) play crucial roles in intercellular communication and glioma microenvironment modulation. Tumor-associated macrophages are more likely to become M2-like type macrophages in the immunosuppressive microenvironment. Here, we aimed to investigate the effects and molecular mechanisms of hypoxic glioma-derived exosomes mediated M2-like macrophage polarization. Methods Highly expressed miRNAs in exosomes derived from glioma cells cultured under hypoxia condition compared to normoxic condition were identified through microRNA sequencing. The polarization status of macrophages was determined using qRT-PCR, Western blotting, flow cytometry, and immunohistochemistry. By using RNA-seq, we aimed to identify the downstream target genes regulated by miR-25-3p in macrophages and investigate the mechanistic pathways through which it exerts its effects. The proliferation and migration capabilities of glioma cells were assessed through EdU, Transwell assays, and in vivo experiments. Results We found that miR-25-3p was upregulated in the exosomes derived from hypoxic glioma cells and can be transferred to the macrophage. In macrophages, miR-25-3p downregulates the expression of PHLPP2, thereby activating the PI3K-AKT-mTOR signaling pathway, ultimately leading to macrophage M2 polarization. As part of a feedback loop, M2-polarized macrophages can, in turn, promote malignant glioma progression. Conclusion Our study reveals that miR-25-3p from hypoxic glioma cells is delivered to macrophages via exosomes as a mediator, promoting M2 polarization of macrophages through the miR-25-3p/PHLPP2/PI3K-AKT signaling pathway. This study suggests that targeted interventions to modulate miR-25-3p expression, transmission, or inhibition of PI3K-AKT pathway activation can disrupt the immune-suppressive microenvironment, providing a novel approach for immunotherapy in gliomas. Graphical Abstract

Abstract Abnormal subchondral bone remodeling plays a pivotal role in the progression of osteoarthritis (OA). Here, we analyzed subchondral bone samples from OA patients and observed a significant upregulation of ubiquitin carboxy-terminal hydrolase L1 (UCHL1) specifically in subchondral bone osteoclasts. Notably, we found a strong correlation between UCHL1 expression and osteoclast activity in the subchondral bone during OA progression in both human and murine models. Conditional UCHL1 deletion in osteoclast precursors exacerbated OA progression, while its overexpression, mediated by adeno-associated virus 9, alleviated this process in male mice. Mechanistically, RANKL stimulates UCHL1 expression in osteoclast precursors, subsequently stabilizing CD13, augmenting soluble CD13 (sCD13) release, and triggering an autocrine inhibitory effect on the MAPK pathway, thereby suppressing osteoclast formation. These findings unveil a previously unidentified negative feedback loop, RANKL-UCHL1-sCD13, that modulates osteoclast formation and presents a potential therapeutic target for OA.

Abstract Website Fingerprinting (WF) attacks enable a local eavesdropper to use metadata of packet flow, such as size, timing, and direction, to infer the websites a user is visiting. This can damage the user privacy provided by anonymity systems such as Tor. Tor has implemented the WF defense called Circuit Padding Framework, which provides an interface for developers to implement their own defenses. However, these defenses in the framework were overcome by the Deep Fingerprinting (DF) attack. In this paper, we propose a novel defense approach called break burst padding (Break-Pad), which injects a random number of padding packets into an incoming burst once the number of consecutive incoming packets exceeds a set number. We integrated Break-Pad into the existing Circuit Padding Framework. In addition, we have implemented two padding machines named August and October in the new framework and conducted experiments to evaluate these machines. In the open-world setting, our results show that August, with 29% bandwidth overhead, reduces Tik-Tok’s TPR by 14.48% and DF’s TPR by 22%. October outperforms the best padding machine, RBB. With 36% bandwidth overhead, it drops Tik-Tok’s TPR to 74.24% and DF’s TPR to 65.36%. In the one-page setting, October further reduces the bandwidth overhead by 11% while achieving similar performance to RBB. In the information leak analysis, for the burst sequence feature of the traffic, October leaks at 2.453 bits, while the best comparable padding machine Interspace leaks at 2.629 bits.

Abstract Zingiber striolatum Diels is a unique medicine food homology plant native to China. In recent years, due to severe habitat destruction, studying the impact of climate change on the distribution of wild resources is of great significance for the ecological conservation and artificial cultivation of Z. striolatum. This study collected 141 valid species distribution records, and 37 environmental variables, and projected two future climate scenarios (SSP126 and SSP585) for two periods (2050s and 2090s). By employing Pearson analysis, Maximum Entropy Model (MaxEnt), and Geographic Information System (ArcGIS), we predicted the potential suitable habitats for Z. striolatum under present and future climates, as well as identified the dominant environmental variables influencing its distribution. The results indicated that the MaxEnt model performed well (AUC > 0.9) with high accuracy and reliability. The dominant environmental factors included Precipitation of driest quarter (39.0 ~ 473.8 mm), Precipitation of wettest quarter (593.2 ~ 1269.4 mm), Temperature annual range (9.8 ~ 28.6℃), and Mean diurnal range (6.5 ~ 9.6℃). The highly suitable areas for Z. striolatum were mainly distributed in western and southern Yunnan, northern and western Guangxi, Guangdong, Fujian, and central Hainan. Under future climate change, the centroid of the total suitable area for Z. striolatum is projected to shift towards the southwest (Yungui Plateau) at higher elevations.

Abstract Osteoarthritis (OA) is the most common form of arthritic disease, and phenotypic modification of chondrocytes is an important mechanism that contributes to the loss of cartilage homeostasis. This study identified that Fascin actin-bundling protein 1 (FSCN1) plays a pivotal role in regulating chondrocytes phenotype and maintaining cartilage homeostasis. Proteome-wide screening revealed markedly upregulated FSCN1 protein expression in human OA cartilage. FSCN1 accumulation was confirmed in the superficial layer of OA cartilage from humans and mice, primarily in dedifferentiated-like chondrocytes, associated with enhanced actin stress fiber formation and upregulated type I and III collagens. FSCN1-inducible knockout mice exhibited delayed cartilage degeneration following experimental OA surgery. Mechanistically, FSCN1 promoted actin polymerization and disrupted the inhibition of Decorin on TGF-β1, leading to excessive TGF-β1 production and ALK1/Smad1/5 signaling activation, thus, accelerated chondrocyte dedifferentiation. Intra-articular injection of FSCN1-overexpressing adeno-associated virus exacerbated OA progression in mice, which was mitigated by an ALK1 inhibitor. Moreover, FSCN1 inhibitor NP-G2-044 effectively reduced extracellular matrix degradation in OA mice, cultured human OA chondrocytes, and cartilage explants by suppressing ALK1/Smad1/5 signaling. These findings suggest that targeting FSCN1 represents a promising therapeutic approach for OA.

Abstract Background Data on long-term cancer survivors treated with apatinib are lacking. This study aimed to describe the characteristics of long-term cancer survivors after apatinib-based therapy, and to know about their satisfaction degree with apatinib and severity of depression and insomnia. Methods Patients with solid tumors who had received apatinib-based therapy for at least 5 years were invited to complete an online questionnaire. Characteristics of patients and treatment, knowledge of apatinib, satisfaction degree, and severity of depression and insomnia assessed by Patient Health Questionnaire-9 and Insomnia Severity Index were collected. Results Between December 8, 2023 and March 1, 2024, a total of 436 patients completed the online questionnaire. Most patients were satisfied with the efficacy (96.6%) and safety (93.1%) of apatinib, were willing to continue apatinib treatment (99.5%), and would recommend apatinib to other patients (93.3%). Continuous apatinib treatment resulted in significant negative impact on daily life, work, or study in only two (0.5%) patients. Almost all patients currently had no or mild depression (97.0%) and insomnia (97.9%) problems. The most common patient-reported adverse events were hand-foot syndrome (21.3%) and hypertension (18.3%). Conclusions Our survey showed a high satisfaction degree with apatinib in long-term cancer survivors. Long-term apatinib treatment resulted in almost no negative impact on patient’s quality of life.

Abstract Large oil and gas storage tanks serve as crucial industrial energy infrastructures, which are usually thin-walled steel structures with large volumes and light weights, and they are sensitive to wind loads. Under the influence of strong winds or typhoons, large oil and gas storage tanks may suffer wind-induced damage, resulting in the leakage of gas or liquid inside the tanks, posing hazards to the ecological environment and public safety. Therefore, it is of great theoretical and engineering significance to research the wind resistance of large oil and gas storage tanks. This paper provides a comprehensive review of key issues in wind resistance for large oil and gas storage tanks, including characteristics of flow around circular cylinders, wind effects on structures with circular cross-sections, near-surface wind field characteristics, wind effects on large oil and gas storage tanks, wind-induced interference effects, structural dynamic characteristics, wind loads and wind-induced response calculations, multiple load effects, and wind-induced vibration control. The deficiencies of current research are summarized. The prospects for research on the design theory and safety assurance of large oil and gas storage tanks are presented through various methods, including field measurements of near-surface wind fields and wind effects, wind tunnel tests utilizing aeroelastic models, numerical simulations involving fluid–solid coupling, theoretical analysis, and machine learning.

Abstract The beveling process is an important process in the manufacturing of resonators, which has a significant impact on the frequency stability of resonators. Without understanding the frequency characteristics of the resonator after beveling, it is impossible to accurately design the beveled resonators. Thus, in order to investigate the vibration characteristics of AT-cut beveled resonators, we investigated the high-frequency vibration in this work by using the subregional geometric fitting method (SGFM) based on Mindlin’s plate theory. Quartz crystal plates with nonuniform thicknesses are partitioned into three regions and each region is fitted by using the polynomial functions based on the measured geometric morphology data. The governing equations are obtained based on Mindlin’s two-dimensional theory and the coupled vibrations are further solved using the partial differential equation module of COMSOL. In the numerical calculation, we compare the results obtained by the SGFM with those obtained by the global fitting method and the measured data. The accuracy and effectiveness of the SGFM are also verified. It is found that the frequencies obtained by the SGFM are slightly higher than the frequencies obtained by the global fitting method, and the results of SGFM are closer to the measured results. Meanwhile, as the beveling time increases, the frequency increases and the energy trapping effect becomes more significant. The proposed method can significantly improve the computational efficiency of thickness-shear vibration while ensuring accuracy. It is expected to provide a new geometric fitting method for the analysis of beveled crystal resonators.

Abstract Colorectal cancer (CRC) is notable for its high mortality and high metastatic characteristics. The shear force generated by bloodstream provides mechanical signals regulating multiple responses of cells, including metastatic cancer cells, dispersing in blood vessels. We, therefore, studied the effect of shear flow on circulating CRC cells in the present study. The CRC cell line SW620 was subjected to shear flow of 12.5 dynes/cm2 for 1 and 2 h separately. Resulting elevated caspase‐9 and ‐3 indicated that shear flow initiated the apoptosis of SW620. Enlarged cell size associated with a higher level of cyclin D1 was coincident with the flow cytometric results indicating that the cell cycle was arrested at the G1 phase. An elevated phosphor‐eNOSS1177 increased the production of nitric oxide and led to reactive oxygen species‐mediated oxidative stress. Shear flow also regulated epithelial–mesenchymal transition (EMT) by increasing E‐cadherin and ZO‐1 while decreasing Snail and Twist1. The migration and invasion of sheared SW620 were also substantially decreased. Further investigations showed that mitochondrial membrane potential was significantly decreased, whereas mitochondrial mass and ATP production were not changed. In addition to the shear flow of 12.5 dynes/cm2, the expressions of EMT were compared at lower (6.25 dynes/cm2) and at higher (25 dynes/cm2) shear flow. The results showed that lower shear flow increased mesenchymal characteristics and higher shear flow increased epithelial characteristics. Shear flow reduces the malignancy of CRC in their metastatic dispersal that opens up new ways to improve cancer therapies by applying a mechanical shear flow device.

This paper introduces a comprehensive approach for predicting chemical concentrations (C) of sulfur compound in a two-dimensional space (x, y) by numerical solution of mass transfer equation and integration of machine learning. Data of training/validation are obtained from mass transfer modeling on adsorption separation utilizing porous adsorbent for petroleum desulfurization. Mass transfer modeling data were utilized for machine learning models which included three different regression models, namely Support Vector Machine (SVM), Decision Tree Regression (DT), and Multilayer Perceptron (MLP). The hyper-parameters of these base models were optimized using the Grey Wolf Optimization (GWO) algorithm. The ensemble models, denoted as ADA-DT, ADA-MLP, and ADA-SVM were assessed based on key performance metrics, including R2, MAE, RMSE, and MAPE. Results demonstrated the efficacy of the ensemble models in capturing complex relationships within the dataset. ADA-DT obtained an exceptional R2 score of 0.99031, highlighting its outstanding predictive accuracy. Similarly, ADA-MLP and ADA-SVM showed great accuracy, achieving R2 of 0.88272 and 0.96842, respectively. In this study, we uncover valuable insights into the application of ensemble methods and hybridized optimization methods for accurate and robust regression modeling in chemical concentration prediction scenarios applicable for petroleum engineering.

Introduction Pisa syndrome (PS) is a postural abnormality that frequently manifests in various neurological disorders. In recent years, the dangers associated with Parkinson’s disease (PD) and PS have been increasingly acknowledged, leading to heightened research efforts directed toward the treatment of PS. Nevertheless, the underlying causes of PS remain complex, and no clinically effective treatments have been established. While several studies have demonstrated the significant effects of Qigong in treating PD, there is currently no evidence to support the efficacy of Qigong in the treatment of PS.Objective To assess the immediate and long-term effects of Zhan Zhuang Qigong on PS in participants with PD using a rigorous randomised, parallel-control design with assignment concealment and evaluator-blinding methodologies.Methods 60 PD participants meeting the inclusion criteria will be recruited and randomly assigned to one of two groups: conventional treatment (n=30) or Zhan Zhuang Qigong (n=30). The conventional treatment group will receive standard medications and physical therapy. The Zhan Zhuang Qigong group will receive conventional medicine plus 30 min of Zhan Zhuang Qigong practiced five times per week. The long-term effects of Qigong on PS will be evaluated after 6 months and 1 year of follow-up. Assessment tools will include the NeuroPostureApp, the B-PHY(A model of a balance testing system) balance check training system, the Unified Parkinson’s Disease Rating Scale and the Parkinson’s Disease Quality of Life Questionnaire, which will measure total camptocormia, upper hump degree, Pisa angles, plantar pressure distribution, motor function and quality of life in participants with PD.Ethics and dissemination The local ethics committee approved this study (approval number: 2023-K068). The committee will oversee the study throughout its duration and will be notified of any protocol modifications. The results of the study will be disseminated through publication in an international journal or presentation at a conference.Trial registration number ChiCTR2400079696.

Despite availability of multiple FDA approved therapies, many children with juvenile idiopathic arthritis (JIA) suffer pain and disability due to uncontrolled disease. The term JIA includes a heterogeneous set of conditions unified by chronic inflammatory arthritis, collectively affecting 1:1,000 children. When reviewing treatment options with families the rheumatologist currently refers to the experience of the average patient in relatively small controlled clinical trials, to consensus-based treatment plans, or increasingly the choice is dictated by the formulary restrictions of insurance payers. The current paradigm for treatment selection does not incorporate real-world evidence of treatment effectiveness centered to the individual patients with whom decisions are to be made. Treatment decisions based on the evidence of the average patient are not optimized to reflect the unique clinical characteristics of an individual with JIA and their disease course, nor does it account for heterogeneous treatment effects. To guide treatment choices centered around each patient, we describe a novel concept of utilizing digital health technology to bring patient-centered information into shared decision-making discussions based on comparative effectiveness analysis of electronic health record or observational clinical registry data of patients with similar characteristics. The envisioned digital tool will organize and present data relevant to the individual patient and enable evidence-based individualized treatment decision making when used in a collaborative manner with the patient family and rheumatologist. Capabilities in digital health technology, data capturing, and analytical methodologies are ripe for this endeavor. This brings the concept of a learning health system directly to the point of care.

IntroductionLong-term use of chemical fertilizers (CFs) can cause soil compaction and acidification. In recent years, bio-organic fertilizers (BOFs) have begun to replace CFs in some vegetables and cash crops, but the application of CFs or BOFs has resulted in crop quality and disease occurrence.MethodsThis study aimed to analyze the microbial mechanism of differences between CFs and BOFs in root disease, quality, and yield of tuber Chinese herbal medicine. We studied the effects of CFs, organic fertilizers, commercial BOFs, biocontrol bacteria BOFs, and biocontrol fungi BOFs on rhizosphere microbial community structure and function, root rot, quality, and yield of Codonopsis pilosula at different periods after application and analyzed the correlation.Results and discussionCompared to CFs, the emergence rate and yield in BOF treatments were increased by 21.12 and 33.65%, respectively, and the ash content, water content, and disease index in the BOF treatments were decreased by 17.87, 8.19, and 76.60%, respectively. The structural equation model showed that CFs promoted the quality and yield of C. pilosula by influencing soil environmental factors, while BOFs directly drove soil bacterial community to reduce disease index and improve the quality and yield of C. pilosula. There was a stronger interaction and stability of soil microbial networks after BOF treatments. Microlunatus, Rubrobacter, Luteitalea, Nakamurella, and Pedomicrobium were identified as effector bacteria, which were related to disease prevention and yield and quality increase of C. pilosula. Microbial functional analysis indicated that the signal transduction and amino acid metabolism of soil bacteria might play a major role in improving the quality and yield of C. pilosula in the early and middle growth stages. In conclusion, compared to CFs, BOFs obtained a lower disease index of root rot and a higher quality and yield of C. pilosula by changing the structure and function of the rhizosphere bacterial community.

IntroductionThis study reports a patient who developed a secondary renal artery aneurysm (RAA) after occlusion of the main renal artery.MethodsA 25-year-old woman was hospitalized due to an enlarged renal artery aneurysm (RAA). Computed tomography angiography revealed a 2.2 mm left renal aneurysm and the absence of the left renal artery trunk, with collateral blood supply from the branch arteries of the aorta. The left kidney function remained normal, allowing successful aneurysm embolization. Three years after embolization, the patient's hypertension improved and became more manageable.ConclusionCompensation through other abdominal aorta branches after renal artery trunk occlusion is rare, and these branches may also lead to the development of aneurysms. Regular monitoring of these patients is essential.

ObjectiveTo evaluate the effect of malnutrition assessed by the Geriatric Nutritional Risk Index (GNRI) on major adverse cardiac and cerebrovascular events (MACCE) in the elderly patients after endovascular aortic aneurysm repair (EVAR).Materials and methodsThis was a retrospective cohort study of elderly patients who underwent EVAR in a tertiary hospital. Malnutrition status was assessed by the GNRI. The primary outcome was MACCE. The predictive ability of the GNRI was compared with both the Revised Cardiac Risk Index (RCRI) and the modified Frailty Index (mFI) using Receiver operating characteristic (ROC) curve.ResultA total of 453 patients underwent EVAR November 2015 and January 2020 was retrospectively analyzed, equally divided into three (low/medium/high) groups according to GNRI values which ranked from low to high. Five (1.10%) patients were lost in follow-up after surgery, and the median length of follow-up was 28.00 (15.00–47.00) months. The high GNRI values reduced length of hospital stay following EVAR in comparison to patients in low GNRI values group (β 9.67, 95% CI 4.01–23.32, p = 0.0113; adjusted β −1.96, 95% CI −3.88, −0.05, p = 0.0454). GNRI status was associated with a significantly increased risk of long-term mortality after EVAR (Medium GNRI, unadjusted HR 0.40, 95%CI 0.23–0.70, p = 0.0014; adjusted HR 0.47, 95%CI 0.26–0.84, p = 0.0107; high GNRI, 0.27 95%CI 0.14–0.55; p = 0.0003; adjusted HR 0.32 95%CI 0.15–0.68, p = 0.0029). Both medium and high GNRI values were linked to significantly reduced risks of MACCE compared to low GNRI score patients (Medium GNRI, unadjusted HR 0.34, 95%CI 0.13–0.88, p = 0.00265; adjusted HR 0.37, 95%CI 0.14–0.96, p = 0.0408; High GNRI, 0.26 95%CI 0.09–0.78; p = 0.0168; adjusted HR 0.21 95%CI 0.06–0.73, p = 0.0029). Compared with the RCRI and mFI, the GNRI had better discrimination in predicting long-term MACCE. An area under the curve (AUC) for GNRI mFI, and RCRI is 0.707, 0.614 and 0.588, respectively. (Z statistic, GNRI vs. mFI, p = 0.0475; GNRI vs. RCRI, p = 0.0017).ConclusionMalnutrition assessed by the GNRI may serve as a useful predictor of long-term MACCE in elderly patients after EVAR, with preferable discrimination abilities compared with both RCRI and mFI.

IntroductionPrevious validation studies demonstrated that BrainCheck Assess (BC-Assess), a computerized cognitive test battery, can reliably and sensitively distinguish individuals with different levels of cognitive impairment (i.e., normal cognition (NC), mild cognitive impairment (MCI), and dementia). Compared with other traditional paper-based cognitive screening instruments commonly used in clinical practice, the Montreal Cognitive Assessment (MoCA) is generally accepted to be among the most comprehensive and robust screening tools, with high sensitivity/specificity in distinguishing MCI from NC and dementia. In this study, we examined: (1) the linear relationship between BC-Assess and MoCA and their equivalent cut-off scores, and (2) the extent to which they agree on their impressions of an individual’s cognitive status.MethodsA subset of participants (N = 55; age range 54–94, mean/SD = 80/9.5) from two previous studies who took both the MoCA and BC-Assess were included in this analysis. Linear regression was used to calculate equivalent cut-off scores for BC-Assess based on those originally recommended for the MoCA to differentiate MCI from NC (cut-off = 26), and dementia from MCI (cut-off = 19). Impression agreement between the two instruments were measured through overall agreement (OA), positive percent agreement (PPA), and negative percent agreement (NPA).ResultsA high Pearson correlation coefficient of 0.77 (CI = 0.63–0.86) was observed between the two scores. According to this relationship, MoCA cutoffs of 26 and 19 correspond to BC-Assess scores of 89.6 and 68.5, respectively. These scores are highly consistent with the currently recommended BC-Assess cutoffs (i.e., 85 and 70). The two instruments also show a high degree of agreement in their impressions based on their recommended cut-offs: (i) OA = 70.9%, PPA = 70.4%, NPA = 71.4% for differentiating dementia from MCI/NC; (ii) OA = 83.6%, PPA = 84.1%, NPA = 81.8% for differentiating dementia/MCI from NC.DiscussionThis study provides further validation of BC-Assess in a sample of older adults by showing its high correlation and agreement in impression with the widely used MoCA.

ObjectiveTo investigate the relationship between post-traumatic growth, morbidity stigma and readiness for discharge in post-operative thyroid cancer patients.Methods422 post-operative thyroid cancer patients from three tertiary care hospitals in Hunan and Tianjin were surveyed using the General Information Questionnaire, the Post-traumatic Growth Scale, the Readiness for Discharge Scale, and the Social Influence Scale.ResultsDischarge readiness positively predicted the level of post-traumatic growth in thyroid cancer patients (P < 0.01), and morbidity stigma negatively predicted post-traumatic growth (P < 0.01), with morbidity stigma playing a mediated role between discharge readiness and post-traumatic growth.ConclusionsReadiness for discharge can positively predict post-traumatic growth, and morbidity stigma plays a mediating role between readiness for discharge and post-traumatic growth. It is suggested that clinical and nursing staff should strengthen patients’ discharge readiness guidance and education, help patients and their families establish an effective feedback mechanism for disease condition and psychological cognitive condition, focus on reducing patients’ sense of shame, and improve patients’ physical and mental health.

Abstract Herein, we disclose a highly efficient cobalt-catalyzed cross-electrophile alkynylation of a broad range of unactivated chlorosilanes with alkynyl sulfides as a stable and practical alkynyl electrophiles. Strategically, employing easily synthesized alkynyl sulfides as alkynyl precursors allows access to various alkynylsilanes in good to excellent yields. Notably, this method avoids the utilization of strong bases, noble metal catalysts, high temperature and forcing reaction conditions, thus presenting apparent advantages, such as broad substrate scope (72 examples, up to 97% yield), high Csp-S chemo-selectivity and excellent functional group compatibility (Ar-X, X = Cl, Br, I, OTf, OTs). Moreover, the utilities of this method are also illustrated by downstream transformations and late-stage modification of structurally complex natural products and pharmaceuticals. Mechanistic studies elucidated that the cobalt catalyst initially reacted with alkynyl sulfides, and the activation of chlorosilanes occurred via an S N 2 process instead of a radical pathway.

Abstract Background Disulfidptosis is a novel form of programmed cell death induced by high SLC7A11 expression under glucose starvation conditions, unlike other known forms of cell death. However, the roles of disulfidptosis in cancers have yet to be comprehensively well-studied, particularly in ccRCC. Methods The expression profiles and somatic mutation of DGs from the TCGA database were investigated. Two DGs clusters were identified by unsupervised consensus clustering analysis, and a disulfidptosis-related prognostic signature (DR score) was constructed. Furthermore, the predictive capacity of the DR score in prognosis was validated by several clinical cohorts. We also developed a nomogram based on the DR score and clinical features. Then, we investigated the differences in the clinicopathological information, TMB, tumor immune landscapes, and biological characteristics between the high- and low-risk groups. We evaluated whether the DR score is a robust tool for predicting immunotherapy response by the TIDE algorithm, immune checkpoint genes, submap analysis, and CheckMate immunotherapy cohort. Results We identified two DGs clusters with significant differences in prognosis, tumor immune landscapes, and clinical features. The DR score has been demonstrated as an independent risk factor by several clinical cohorts. The high-risk group patients had a more complicated tumor immune microenvironment and suffered from more tumor immune evasion in immunotherapy. Moreover, patients in the low-risk group had better prognosis and response to immunotherapy, particularly in anti-PD1 and anti-CTLA-4 inhibitors, which were verified in the CheckMate immunotherapy cohort. Conclusion The DR score can accurately predict the prognosis and immunotherapy response and assist clinicians in providing a personalized treatment regime for ccRCC patients.

[Introduction] The "carbon peak and neutrality" strategy has put forward a new path for China's energy development, which restricts the use of traditional fossil energy, and promotes the Chinese government to increase its support for the development of the new energy industry. Photovoltaic, as a new energy which is the most accessible and has the widest coverage, has become the first choice to solve the current energy and environmental problems. However, if we want to increase its market scale and realize the vigorous development of photovoltaic industry, it is necessary to find out and solve the pain points and difficulties of the current stage. [Method] China's policy on the whole photovoltaic industry chain was combed and analyzed to explore the shortcomings of the photovoltaic industry incentive policy. Based on the data from 33 sample enterprises in the A-share market from 2000 to 2021, the DEA model was built and the integrated innovation benefits and scale benefits of China's PV industry under the guidance of policy were explored. And using the panel regression analysis method, the different impacts of different regional policies on the innovation capacity of the upstream, middle and downstream enterprises of the PV industry. were explored. [Result] The research shows that the policy subsidies have a more significant impact on the innovation benefits of upstream photovoltaic enterprises, which is positively correlated with the development of enterprises in the eastern region. While in the western region, the opposite is the case, and there are certain regional differences. [Conclusion] It is necessary to improve the preferential policy strength in the photovoltaic technology innovation level, and carry out a reasonable industry chain planning and layout in combination with the regional advantages.

Abstract Background KNOTTED1-like homeobox (KNOX) genes, plant-specific homologous box transcription factors (TFs), play a central role in regulating plant growth, development, organ formation, and response to biotic and abiotic stresses. However, a comprehensive genome-wide identification of the KNOX genes in Moso bamboo (Phyllostachys edulis), the fastest growing plant, has not yet been conducted, and the specific biological functions of this family remain unknown. Results The expression profiles of 24 KNOX genes, divided into two subfamilies, were determined by integrating Moso bamboo genome and its transcriptional data. The KNOX gene promoters were found to contain several light and stress-related cis-acting elements. Synteny analysis revealed stronger similarity with rice KNOX genes than with Arabidopsis KNOX genes. Additionally, several conserved structural domains and motifs were identified in the KNOX proteins. The expansion of the KNOX gene family was primarily regulated by tandem duplications. Furthermore, the KNOX genes were responsive to naphthaleneacetic acid (NAA) and gibberellin (GA) hormones, exhibiting distinct temporal expression patterns in four different organs of Moso bamboo. Short Time-series Expression Miner (STEM) analysis and quantitative real-time PCR (qRT-PCR) assays demonstrated that PeKNOX genes may play a role in promoting rapid shoot growth. Additionally, Gene Ontology (GO) and Protein–Protein Interaction (PPI) network enrichment analyses revealed several functional annotations for PeKNOXs. By regulating downstream target genes, PeKNOXs are involved in the synthesis of AUX /IAA, ultimately affecting cell division and elongation. Conclusions In the present study, we identified and characterized a total of 24 KNOX genes in Moso bamboo and investigated their physiological properties and conserved structural domains. To understand their functional roles, we conducted an analysis of gene expression profiles using STEM and RNA-seq data. This analysis successfully revealed regulatory networks of the KNOX genes, involving both upstream and downstream genes. Furthermore, the KNOX genes are involved in the AUX/IAA metabolic pathway, which accelerates shoot growth by influencing downstream target genes. These results provide a theoretical foundation for studying the molecular mechanisms underlying the rapid growth and establish the groundwork for future research into the functions and transcriptional regulatory networks of the KNOX gene family.

We introduce an alternated inertial subgradient extragradient algorithm of non-Lipschitz and pseudo-monotone operators to solve variational inequality and fixed point problems. We also demonstrated that, under certain conditions, the sequence produced by our algorithm exhibits weak convergence. Moreover, some numerical experiments have been proposed to compare our algorithm with previous algorithms in order to demonstrate the effectiveness of our algorithm.

Abstract Background Enterococcus casseliflavus is a rare pathogenic bacterium that is characterized by vancomycin resistance and can lead to multiple infections in the human body. This report describes a rare case of polycystic intrahepatic infection with E. casseliflavus which necessitated antibiotic treatment and surgical intervention involving cystic drainage. Case Presentation A 59-year-old woman, a long-term hemodialysis patient, was hospitalized due to a 5-day history of fever, abdominal pain, and diarrhea, which were possibly caused by the ingestion of contaminated food. Her blood culture yielded a positive result for E. casseliflavus, and she was initially treated with piperacillin/tazobactam and linezolid. Later, the antibiotic regimen was adjusted to include meropenem and linezolid. Despite treatment, her body temperature remained elevated. However, subsequent blood cultures were negative for E.casseliflavus.Conventional CT scans and ultrasound examinations did not identify the source of infection. However, a PET-CT examination indicated an intrahepatic cyst infection. Following MRI and ultrasound localization, percutaneous intrahepatic puncture and drainage were performed on the 20th day. Fluoroquinolones were administered for 48 days. On the 32nd day, MRI revealed a separation within the infected cyst, leading to a repeat percutaneous drainage at a different site. Subsequently, the patient’s temperature returned to normal. The infection was considered resolved, and she was discharged on the 62nd day. Follow-up results have been favorable thus far. Conclusions Based on the findings from this case, it is recommended to promptly conduct PET-CT examination to exclude the possibility of intracystic infection in cases of polycystic liver infection that are challenging to control. Furthermore, timely consideration should be given to puncture drainage in difficult cases.

Abstract Purpose This study aimed to evaluate the clinical feasibility of early 30-minute dynamic 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) positron emission tomography (PET) scanning protocol for patients with lung lesions in comparison to the standard 65-minute dynamic FDG-PET scanning as a reference. Methods Dynamic 18F-FDG PET images of 146 patients with 181 lung lesions (including 146 lesions confirmed by histology) were analyzed in this prospective study. Dynamic images were reconstructed into 28 frames with a specific temporal division protocol for the scan data acquired 65 min post-injection. Ki images and quantitative parameters Ki based on two different acquisition durations [the first 30 min (Ki-30 min) and 65 min (Ki-65 min)] were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. The two acquisition durations were compared for Ki image quality (including visual score analysis and number of lesions detected) and Ki value (including accuracy of Ki, the value of differential diagnosis of lung lesions and prediction of PD-L1 status) by Wilcoxon’s rank sum test, Spearman’s rank correlation analysis, receiver operating characteristic (ROC) curve, and the DeLong test. The significant testing level (alpha) was set to 0.05. Results The quality of the Ki-30 min images was not significantly different from the Ki-65 min images based on visual score analysis (P > 0.05). In terms of Ki value, among 181 lesions, Ki-65 min was statistically higher than Ki-30 min (0.027 ± 0.017 ml/g/min vs. 0.026 ± 0.018 ml/g/min, P 0.05), while the diagnostic accuracies of Ki-65 min and Ki-30 min were both significantly higher than that of SUVmax (P 0.05), according to the results of ROC analysis and Delong test. Conclusions This study indicates that an early 30-minute dynamic FDG-PET acquisition appears to be sufficient to provide quantitative images with good-quality and accurate Ki values for the assessment of lung lesions and prediction of PD-L1 expression. Protocols with a shortened early 30-minute acquisition time may be considered for patients who have difficulty with prolonged acquisitions to improve the efficiency of clinical acquisitions.

In order to study the mechanical behavior of Chinese traditional style architecture dual-lintel-column joint, a typical Chinese traditional style architecture dual-lintel-column joint was selected as the model structure. Two specimens with viscous damper and one specimen without viscous damper were designed and tested under fast harmonic load. On the basis of experimental study, the key indexes of mechanical properties are analyzed, such as the load–displacement hysteretic curve of specimens and viscous damper, skeleton curve, and load-bearing capacity. The results indicate that mechanical properties of antique buildings dual-lintel-column subassemblages with steel and composite structures and viscous damper can significantly increase the mechanical properties. The hysteretic curve of the damping joint is plump. The descending phase of skeleton curves is smoother. The carrying capacity is increased by 13.9%–14.1%, and displacement ductility is increased by 13.0%–18.6%. The viscous damper and the dual-lintel-column subassemblages work together. They significantly improve the deformation performance of structures at the failure stage and enhance the collapse resistance of the structure. The study of traditional architecture can also provide valuable insights into the development of structural engineering and construction technology. Also, people can learn the wisdom and experience of ancestors and apply it to modern engineering practices.

Failure typically occurs during sintering due to high thermal stress and poor strength of LiH ceramics. The short sintering time has shown to be beneficial in preventing excessive grain growth and improving ceramic performance. In this study, we built a genetic algorithm back propagation artificial neural network (GA-BP-ANN) model to predict the strength margins under different work conditions. Sensitivity analysis showed that the thickness and end control time were the most relevant parameters for strength margins, and the GA-BP-ANN model demonstrated the most efficient sintering work condition for a given thickness. Through statistical analysis of the strength margin predicted by the GA-BP-ANN model, we found that the bilinear temperature control method expanded the range of safe sintering conditions by 30% compared to the linear temperature control method. The research results of this study may serve as a reference for the safe and efficient sintering of LiH ceramics.

Objective We aimed to investigate the clinical findings of hospitalized paediatric COVID-19 patients by the end of 2022.Method All confirmed children with COVID-19 infection admitted into Chaozhou Central Hospital during the COVID-19 outbreak from 19 December 2022 to 1 February 2023 were included. Detailed clinical data of those children were evaluated retrospectively.Results A total of 286 children, ranging in age from 1 month to 13 years old, were diagnosed with SARS-CoV-2 infection. Among these cases, 138 (48.3%) were categorized as mild, 126 (44.0%) as moderate and 22 (7.7%) as severe/critical. Symptoms varied among the children and included fever, upper respiratory tract symptoms, convulsions, sore throat, poor appetite, dyspnoea and gastrointestinal symptoms. Notably, febrile convulsions were observed in 96 (33.6%) patients, while acute laryngitis was documented in 50 (17.5%) cases. Among the severe/critical patients, eight developed multisystem inflammatory syndrome in children (MIS-C), and tragically, one patient’s condition worsened and resulted in death. Furthermore, MRI scans revealed abnormal brain signals in six severe/critical patients. The severe/critical group also exhibited more pronounced laboratory abnormalities, including decreased haemoglobin and elevated ALT, AST, LDH and CK levels.Conclusions Febrile convulsions and acute laryngitis are frequently observed in children diagnosed with SARS-CoV-2 Omicron infection. Moreover, MIS-C and abnormal neuroimaging appear to be relatively common phenomena in severe/critical cases.

In recent years, polymyxin has been used as a last-resort therapy for carbapenem-resistant bacterial infections. The emergence of heteroresistance (HR) to polymyxin hampers the efficacy of polymyxin treatment by amplifying resistant subpopulation. However, the mechanisms behind polymyxin HR remain unclear. Small noncoding RNAs (sRNAs) play an important role in regulating drug resistance. The purpose of this study was to investigate the effects and mechanisms of sRNA on polymyxin B (PB)-HR in carbapenem-resistant Klebsiella pneumoniae. In this study, a novel sRNA PhaS was identified by transcriptome sequencing. PhaS expression was elevated in the PB heteroresistant subpopulation. Overexpression and deletion of PhaS were constructed in three carbapenem-resistant K. pneumoniae strains. Population analysis profiling, growth curve, and time-killing curve analysis showed that PhaS enhanced PB-HR. In addition, we verified that PhaS directly targeted phoP through the green fluorescent protein reporter system. PhaS promoted the expression of phoP, thereby encouraging the expression of downstream genes pmrD and arnT. This upregulation of arnT promoted the 4-amino-4-deoxyL-arabinosaccharide (L-Ara4N) modification of lipid A in PhaS overexpressing strains, thus enhancing PB-HR. Further, within the promoter region of PhaS, specific PhoP recognition sites were identified. ONPG assays and RT-qPCR analysis confirmed that PhaS expression was positively modulated by PhoP and thus up-regulated by PB stimulation. To sum up, a novel sRNA enhancing PB-HR was identified and a positive feedback regulatory pathway of sRNA-PhoP/Q was demonstrated in the study. This helps to provide a more comprehensive and clear understanding of the underlying mechanisms behind polymyxin HR in carbapenem-resistant K. pneumoniae.

Background: Ovarian cancer (OC) patients have an increased risk for a mental health illness (MHI) after their cancer diagnosis, but limited research exists on whether this risk differs by race/ethnicity. Hence, we used SEER-Medicare data to evaluate racial/ethnic differences in MHI incidence among OC patients aged 65+. Methods: Non-Hispanic (NH) Black, NH White, and Hispanic women diagnosed with OC in 2008–2015 without a mental health history 12 months prior to their cancer diagnosis were identified from SEER-Medicare. Cox proportional hazards regression evaluated new MHI incidence in the first five years post diagnosis and the differences by race/ethnicity. Hazard ratios (HR) and 95% confidence intervals (CI) adjusted for demographic/clinical covariates and healthcare access (HCA) dimensions. Results: We identified 5441 OC patients, including 364 NH Black (6.7%), 4982 NH White (91.6%), and 95 Hispanic (1.7%) patients. About 41% of NH White, 33.3% of NH Black, and 37.2% of Hispanic OC patients were diagnosed with MHI during the follow-up period between 2008 and 2016. In the fully adjusted model, NH Black OC patients were less likely to be diagnosed with any MHI (aHR: 0.67, 95% CI: 0.54, 0.82), depression (aHR: 0.66, 95% CI: 0.51, 0.85), and anxiety disorder (aHR: 0.64, 95% CI: 0.49, 0.84), while Hispanic OC patients were less likely to be diagnosed with anxiety disorder (aHR: 0.56, 95% CI: 0.33, 0.95) compared to NH White OC patients. Discussion: NH Black OC patients are less likely to receive a clinical MHI diagnosis compared to NH White OC patients. Further studies on racial differences in MHI incidence after OC diagnosis in primary cohorts are needed to better estimate population-level prevalence less vulnerable to exposure misclassification and to account for patient-level factors impacting MHI.

Background: Surveillance systems revealed that the prevalence of vancomycin-resistant Enterococcus faecium (VREfm) has increased. We aim to investigate the epidemiological and genomic characteristics of VREfm in China. Methods: We collected 20,747 non-redundant E. faecium isolates from inpatients across 19 hospitals in six provinces between January 2018 and June 2023. VREfm was confirmed by antimicrobial susceptibility testing. The prevalence was analyzed using changepoint package in R. Genomic characteristics were explored by whole-genome sequencing. Results: 5.59% (1159/20,747) of E. faecium isolates were resistant to vancomycin. The prevalence of VREfm increased in Guangdong province from 5% before 2021 to 20−50% in 2023 (p

ABSTRACTThis study investigated resistance evolution mechanisms of conjugated plasmids and bacterial hosts under different concentrations of antibiotic pressure. Ancestral strain ECNX52 was constructed by introducing the blaNDM-5-carrying IncX3 plasmid into E. coli C600, and was subjected to laboratory evolution under different concentrations of meropenem pressure. Minimal inhibitory concentrations and conjugation frequency were determined. Fitness of these strains was assessed. Whole genome sequencing and transcriptional changes were performed. Ancestral host or plasmids were recombined with evolved hosts or plasmids to verify plasmid or host factors in resistance evolution. Role of the repA mutation on plasmid copy number was determined. Two out of the four clones (EM2N1 and EM2N3) exhibited four-fold increase in MIC when exposed to a continuous pressure of 2 μg/mL MEM (1/32 MIC), by down regulating expression of outer membrane protein ompF. Besides, all four clones displayed four-fold increase in MIC and higher conjugation frequency when subjected to a continuous pressure of 4 μg/mL MEM (1/16 MIC), attributing to increasing plasmid copy number generated by repA D140Y (GAT→TAT) mutation. Bacterial hosts and conjugative plasmids can undergo resistance evolution under certain concentrations of antimicrobial pressure by reducing the expression of outer membrane proteins or increasing plasmid copy numbers.

Abstract Background Our study aims to investigate the mechanisms through which Fc receptor‐like A (FCRLA) promotes renal cell carcinoma (RCC) and to examine its significance in relation to tumor immune infiltration. Materials and Methods The correlation between FCRLA and data clinically related to RCC was explored using The Cancer Genome Atlas (TCGA), then validated using Gene Expression Omnibus (GEO) gene chip data. Enrichment and protein–protein interaction (PPI) network analyses were performed for FCRLA and its co‐expressed genes. FCRLA was knocked down in RCC cell lines to evaluate its impact on biological behavior. Then the potential downstream regulators of FCRLA were determined by western blotting, and rescue experiments were performed for verification. The relevance between FCRLA and various immune cells was analyzed through GSEA, TIMER, and GEPIA tools. TIDE and ESTIMATE algorithms were used to predict the effect of FCRLA in immunotherapy. Results Fc receptor‐like A was associated with clinical and T stages and could predict the M stage (AUC = 0.692) and 1–3‐ and 5‐year survival rates (AUC = 0.823, 0.834, and 0.862) of RCC patients. Higher expression of FCLRA predicted an unfavorable overall survival (OS) in TCGA‐RCC and GSE167573 datasets (p = 0.03, p = 0.04). FCRLA promoted the malignant biological behavior of RCC cells through the pERK1/2/‐MMP2 pathway and was associated with tumor immune microenvironment in RCC. Conclusion Fc receptor‐like A is positively correlated with poor outcomes in RCC patients and plays an oncogenic role in RCC through the pERK1/2‐MMP2 pathway. Patients with RCC might benefit from immunotherapy targeting FCRLA.

Introduction Endovascular therapy has emerged as a prominent strategy for managing femoropopliteal peripheral artery disease, offering acceptable safety and efficacy compared with open surgical bypass. Both paclitaxel-eluting stents and heparin-bonded covered stents have exhibited enhanced clinical outcomes compared with bare metal stents. However, there is currently a lack of level I evidence comparing the safety and efficacy of paclitaxel-eluting stents and heparin-bonded covered stents. Therefore, the primary objective of this study is to systematically evaluate the efficacy and safety outcomes of these two types of stents.Methods and analysis The ELITE trial is a prospective, multicentre, parallel, randomised controlled trial. A total of 450 patients will be recruited. The primary endpoints of the study include primary patency at 1 year post-index procedure.Ethics and dissemination Ethical approval for this study was obtained from the Ethics Committee of West China Hospital of Sichuan University (approval number: 2023–1186). The results will be submitted to a major clinical journal for peer review and publication.Trial registration ELITE trial was registered on 27 September 2023 in the Chinese Clinical Trials Registry (ChiCTR2300076236).

Activated sludge models are increasingly being adopted to guide the operation of wastewater treatment plants. Chemical oxygen demand (COD) is an indispensable input for such models. To ensure that the activated sludge mathematical model can adapt to various water quality conditions and minimize prediction errors, it is essential to predict the parameters of the COD components in real-time based on the actual influent COD concentrations. However, conventional methods of determining the components' contributions are too intricate and time-consuming to be really useful. In this study, the chemical oxygen demand in the actual waste water treatment plant was disassembled and analyzed. The research involved determining the proportions of each COD component, assessing the reliability of the measurement parameters, and examining potential factors affecting measurement accuracy, including weather conditions, pipeline conditions, and residents' habits. Then, a backpropagation neural network was developed which can deliver real-time predictions for five important contributors to COD in real time. In addition, using the receiver operating characteristics curve and prediction accuracy to evaluate the performance of the prediction model. For all five components, which SS, XS, SI, XA, and XH, the prediction accuracy of model was more than 80 %. The maximum deviation values of these parameters fall within the range of the actual detected values, suggesting that the model's predictions align well with real-world observations, and demonstrated prediction performance adequate for practical application in wastewater treatment. This article can provide research basis for the engineering application of activated sludge model and help for the intelligent upgrading of waste water treatment plants.

BackgroundET, one of the most prevalent neurological disorders, presents a significant challenge in terms of disability. Despite the growing focus on ET in recent years, comprehensive bibliometric analysis has been lacking.MethodsThis study delves into essential tremor research covering the period from 2013 to 2023, utilizing the Web of Science (WOS) database. Employing CiteSpace for quantitative analysis, it examines an array of metrics including annual publication trends, contributions from countries and institutions, authorship patterns, key terminologies, and patterns of reference co-citation. The primary objective is to use CiteSpace for a detailed visual exploration of the literature over the last decade, pinpointing the evolving landscape and key areas of focus in essential tremor research, and thus providing a foundation for future investigative endeavors.ResultsThere were 2,224 literary works included in all. The amount of published works has been steadily rising in recent years. Of them, the majority originate from the United States, Louis, Elan D. is the publisher of the most publications (161 articles), and Movement Disorders is the journal that receives the most citations. The key words contribution and co-cited literatures suggest that the main research hotspots in recent years are the physiological and pathological mechanism of essential tremor, the determination of optimal targets for deep brain stimulation (DBS) and surgery transcranial magnetic resonance-guided focused ultrasound (MRgFUS) in the surgical management of essential tremor and the innovative research of botulinum toxin administration method.

Plasmid-mediated conjugation is a common mechanism for most bacteria to transfer antibiotic resistance genes (ARGs). The conjugative transfer of ARGs is emerging as a major threat to human beings. Although several transfer-related factors are known to regulate this process, small RNAs (sRNAs)-based regulatory roles remain to be clarified. Here, the Hfq-binding sRNA GadY in donor strain Escherichia coli (E. coli) SM10λπ was identified as a new regulator for bacterial conjugation. Two conjugation models established in our previous studies were used, which SM10λπ carrying a chromosomally integrated IncP-1α plasmid RP4 and a mobilizable plasmid pUCP24T served as donor cells, and P. aeruginosa PAO1 or E. coli EC600 as the recipients. GadY was found to promote SM10λπ-PAO1 conjugation by base-pairing with its target mRNA SdiA, an orphan LuxR-type receptor that responds to exogenous N-acylated homoserine lactones (AHLs). However, SM10λπ-EC600 conjugation was not affected due to EC600 lacking AHLs synthase. It indicates that the effects of GadY on conjugation depended on AHLs-SdiA signalling. Further study found GadY bound SdiA to negatively regulate the global RP4 repressors KorA and KorB. When under ciprofloxacin or levofloxacin treatment, GadY expression in donor strain was enhanced, and it positively regulated quinolone-induced SM10λπ-PAO1 conjugation. Thus, our study provides a novel role for sRNA GadY in regulating plasmid-mediated conjugation, which helps us better understand bacterial conjugation to counter antibiotic resistance.

The organic expanded vermiculite (OEVMT) is a good anti-aging agent for asphalt binder due to its excellent heat and oxygen barrier properties. However, the application form of OEVMT is usually limited to being as a modifier for asphalt binder while seldom research takes it as an alternative to filler in asphalt mixture. Using the OEVMT as an alternative to filler has the potential to further improve the aging resistance of asphalt mixture in comparison with using the OEVMT as an asphalt binder modifier, because the amount of OEVMT in asphalt mixture can be largely increased in this case. In present study, different proportions of fillers in asphalt mixture were replaced by OEVMT to produce asphalt mixtures with better aging resistance. The effects of using OEVMT as an alternative to fillers on road performance and aging resistance of asphalt mixture were investigated. The results indicate that replacing a large proportion of fillers in asphalt mixture can lead to a poor moisture resistance of asphalt mixture. In comprehensive consideration of moisture, cracking and rutting resistances, the optimal proportion of filler that should be replaced by OEVMT is 12.5 %. In comparison with the form of using OEVMT as a modifier for asphalt binder, using an appropriate amount of OEVMT to replace limestone fillers in asphalt mixture can further enhance the aging resistance of asphalt mixture by increasing the amount of OEVMT in asphalt mixture.

The burgeoning proliferation of integrated energy systems has fostered an unprecedented degree of coupling among various energy streams, thereby elevating the necessity for unified multi-energy forecasting (MEF). Prior approaches predominantly relied on independent predictions for heterogeneous load demands, overlooking the synergy embedded within the dataset. The two principal challenges in MEF are extracting the intricate coupling correlations among diverse loads and accurately capturing the inherent uncertainties associated with each type of load. This study proposes an attentive quantile regression temporal convolutional network (QTCN) as a probabilistic framework for MEF, featuring an end-to-end predictor for the probabilistic intervals of electrical, thermal, and cooling loads. This study leverages an attention layer to extract correlations between diverse loads. Subsequently, a QTCN is implemented to retain the temporal characteristics of load data and gauge the uncertainties and temporal correlations of each load type. The multi-task learning framework is deployed to facilitate simultaneous regression of various quantiles, thereby expediting the training progression of the forecasting model. The proposed model is validated using realistic load data and meteorological data from the Arizona State University metabolic system and National Oceanic and Atmospheric Administration respectively, and the results indicate superior performance and greater economic benefits compared to the baselines in existing literature.

In order to fully exploit the relationship between temporal features in photovoltaic power generation data and improve the prediction accuracy of photovoltaic power generation, a photovoltaic power generation forecasting method is proposed based on a hybrid model of the convolutional neural network (CNN) and extreme gradient boost (XGBoost). Taking the historical data of China’s photovoltaic power plants as a sample, the high-dimensional mapping relationship of photovoltaic power generation variables is extracted based on the convolutional layer and pooling layer of the CNN network to construct a high-dimensional time-series feature vector, which is an input for the XGBoost. A photovoltaic power generation prediction model is established based on CNN-XGBoost by training CNN and XGBoost parameters. Since it is difficult for a single model to achieve optimal prediction accuracy under different weather conditions, the k-means clustering algorithm is used to group the power datasets and train independent models to improve prediction accuracy. Through the actual data verification of photovoltaic power plants, the proposed photovoltaic power generation prediction model can accurately predict the power, which shows high prediction accuracy and generalization ability compared with other methods.

Industrial drawing recognition attains much attention for its significance in drawing image digitalization. However, traditional deep methods fail to achieve a satisfactory performance, due to their inferior feature representation ability. To address this issue, we introduce an industrial drawing recognition method based on a new neural architecture, dubbed as DrawingNet. Our network is designed based on layer-wise aggregation module and deformable convolution to extract more representational features for input drawing images. We provide an end-to-end and one-stage pipeline to train DrawingNet for an automatic drawing recognition in an anchor-free manner. A dataset with 10,000 drawings is collected to validate our method. We introduce a data enhancement method, by cutting out the tower and various components in the picture, and then randomly paste them on the blank drawing, each paste can produce different combinations. Experimental results show that our DrawingNet outperforms CenterNet in a large margin.

Abstract Background Peer victimization (PV) is one of the major causes of non-suicidal self-injury. Non-suicidal self-injury (NSSI), peer victimization, social anxiety, and mobile phone addiction are significantly related; however, the interaction mechanism and effect of sex differences remain to be determined. Objective Herein, we investigated the relationship between peer victimization and NSSI among Chinese high school students. We also explored the chain mediating roles of social anxiety and mobile phone addiction and the regulatory role of sex. The findings of this study provide insights for theoretical interventions based on internal mechanisms. Method A self-reported survey of 14,666 high school students from Sichuan County was conducted using a peer victimization scale, NSSI scale, social anxiety scale, and mobile phone addiction scale. A self-administered questionnaire was used to capture sociodemographic information. Results Peer victimization, social anxiety, and mobile phone addiction were positively correlated with NSSI. Peer victimization had significant direct predictive effects on NSSI (95% CI: 0.341, 0.385) and significant indirect predictive effects on NSSI through social anxiety (95% CI: 0.008, 0.019) or mobile phone addiction (95% CI: 0.036, 0.053). Peer victimization had significant indirect predictive effects on NSSI through social anxiety as well as mobile phone addiction (95% CI: 0.009, 0.014). The first stage (predicting the effect of peer victimization on NSSI) and the third stage (predicting the effect of mobile phone addiction on NSSI) were both moderated by sex. Conclusions Peer victimization could directly predict NSSI and indirectly predict NSSI through social anxiety and mobile phone addiction. Thus, social anxiety and mobile phone addiction exhibited chain mediating effects between peer victimization and NSSI in high school students; moreover, sex might be involved in the regulation of the mediation process.

In recent years, the application of deep learning in remote-sensing (RS) image change detection (CD) has been deepening, especially in the challenges faced in lightweight model design, that is, how to effectively balance model complexity and detection accuracy. Although some simplified models have achieved compression in existing research, there are shortcomings in maintaining detailed information and improving detection performance. On the other hand, large network architectures limit their actual deployment in resource-limited environments. This article innovatively proposes a lightweight CD network called Multilevel Feature Cross-Fusing Network (MFCF-Net) to address this issue. MFCF-Net uses a lightweight convolutional neural network for feature extraction and introduces the adjacent layer enhancement module in the feature extraction stage to significantly enhance the network's ability to extract high-dimensional features while only moderately increasing parameters. Furthermore, MFCF-Net integrates dense skip connections and cross-attention mechanisms in the decoder to efficiently propagate contextual information and accurately capture and fuse global spatial features, especially for detecting small changes. Experimental results show that on four public RS CD datasets, MFCF-Net achieves excellent detection performance and has a smaller model size (with parameters as low as 1.35M). Particularly on the WHU-CD dataset, compared with the current state-of-the-art method, MFCF-Net achieves significant improvements, with an F1-score increase in 1.4% and an intersection-over-union improvement of 2.45%.

Abstract Background Extensive local invasion of glioblastoma (GBM) cells within the central nervous system (CNS) is one factor that severely limits current treatments. The aim of this study was to uncover genes involved in the invasion process, which could also serve as therapeutic targets. For the isolation of invasive GBM cells from non-invasive cells, we used a three-dimensional organotypic co-culture system where glioma stem cell (GSC) spheres were confronted with brain organoids (BOs). Using ultra-low input RNA sequencing (ui-RNA Seq), an invasive gene signature was obtained that was exploited in a therapeutic context. Methods GFP-labeled tumor cells were sorted from invasive and non-invasive regions within co-cultures. Ui-RNA sequencing analysis was performed to find a gene cluster up-regulated in the invasive compartment. This gene cluster was further analyzed using the Connectivity MAP (CMap) database. This led to the identification of SKF83566, an antagonist of the D1 dopamine receptor (DRD1), as a candidate therapeutic molecule. Knockdown and overexpression experiments were performed to find molecular pathways responsible for the therapeutic effects of SKF83566. Finally, the effects of SKF83566 were validated in orthotopic xenograft models in vivo. Results Ui-RNA seq analysis of three GSC cell models (P3, BG5 and BG7) yielded a set of 27 differentially expressed genes between invasive and non-invasive cells. Using CMap analysis, SKF83566 was identified as a selective inhibitor targeting both DRD1 and DRD5. In vitro studies demonstrated that SKF83566 inhibited tumor cell proliferation, GSC sphere formation, and invasion. RNA sequencing analysis of SKF83566-treated P3, BG5, BG7, and control cell populations yielded a total of 32 differentially expressed genes, that were predicted to be regulated by c-Myc. Of these, the UHRF1 gene emerged as the most downregulated gene following treatment, and ChIP experiments revealed that c-Myc binds to its promoter region. Finally, SKF83566, or stable DRD1 knockdown, inhibited the growth of orthotopic GSC (BG5) derived xenografts in nude mice. Conclusions DRD1 contributes to GBM invasion and progression by regulating c-Myc entry into the nucleus that affects the transcription of the UHRF1 gene. SKF83566 inhibits the transmembrane protein DRD1, and as such represents a candidate small therapeutic molecule for GBMs.

Abstract Existing studies about wind pressure on agricultural greenhouse buildings concentrate on the mean wind pressure while ignoring the systematic research on fluctuating wind pressure characteristics and the influence of roof shape on the wind pressure characteristics, which are closely associated with the wind-induced damage mechanism. In this study, two typical agricultural greenhouse buildings on tropical islands are selected as prototypes to conduct pressure measurement experiments in the wind tunnel. Based on the wind pressure time series for the two greenhouses, the mean and fluctuating wind pressure distribution pattern and the localized high-pressure generation mechanism are analyzed. Then, the shape coefficient of the two greenhouses is compared in depth to the standards from four countries. Besides, wind pressure non-Gaussian determination criteria for agricultural greenhouse buildings considering the roof shape and wind directions are proposed. Lastly, the differences in wind pressure spectra on the roofs and walls of the two greenhouses are summarized. The results indicate the roof shape has a significant influence on the wind pressure characteristics. Compared with the pitched roof, the vaulted roof will increase the suction effect on the windward front zone and the middle area, mitigate the suction impact on the leeward roof, and weaken the wind pressure non-Gaussian characteristics. The experimental shape coefficient of the pitched-roof greenhouse is basically consistent with the standard from the U.S., while that of the vaulted-roof greenhouse has some deviation from the existing standards. The results provide a theoretical basis for the wind-resistant design of agricultural greenhouse buildings on tropical islands.

Abstract Artificial biomaterials with dynamic mechano-responsive behaviors similar to those of biological tissues have been drawing great attention. In this study, we report a TiO2-based nanowire (TiO2NWs) scaffolds, which exhibit dynamic mechano-responsive behaviors varying with the number and amplitude of nano-deformation cycles. It is found that the elastic and adhesive forces in the TiO2NWs scaffolds can increase significantly after multiple cycles of nano-deformation. Further nanofriction experiments show the triboelectric effect of increasing elastic and adhesive forces during the nano-deformation cycles of TiO2NWs scaffolds. These properties allow the TiO2NW scaffolds to be designed and applied as intelligent artificial biomaterials to simulate biological tissues in the future.

Abstract The monitoring of physiological parameters is a crucial topic in promoting human health and an indispensable approach for assessing physiological status and diagnosing diseases. Particularly, it holds significant value for patients who require long-term monitoring or with underlying cardiovascular disease. To this end, Visual Contactless Physiological Monitoring (VCPM) is capable of using videos recorded by a consumer camera to monitor blood volume pulse (BVP) signal, heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2) and blood pressure (BP). Recently, deep learning-based pipelines have attracted numerous scholars and achieved unprecedented development. Although VCPM is still an emerging digital medical technology and presents many challenges and opportunities, it has the potential to revolutionize clinical medicine, digital health, telemedicine as well as other areas. The VCPM technology presents a viable solution that can be integrated into these systems for measuring vital parameters during video consultation, owing to its merits of contactless measurement, cost-effectiveness, user-friendly passive monitoring and the sole requirement of an off-the-shelf camera. In fact, the studies of VCPM technologies have been rocketing recently, particularly AI-based approaches, but few are employed in clinical settings. Here we provide a comprehensive overview of the applications, challenges, and prospects of VCPM from the perspective of clinical settings and AI technologies for the first time. The thorough exploration and analysis of clinical scenarios will provide profound guidance for the research and development of VCPM technologies in clinical settings.