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Mengjiao Wang,1 Liqing Chen,2 Wei Huang,2 Mingji Jin,2 Qiming Wang,2 Zhonggao Gao,2 Zhehu Jin1 1Klebs Research Center, Department of Dermatology, Yanbian University Hospital, Yanji 133000, China; 2State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China Background: Keloids represent benign fibroproliferative tumors which result from elevated expression of inflammation. Paclitaxel (PTX) was an effective chemotherapeutic agent and has been reported to have anti-fibrotic effects, but the strong hydrophobicity brings a challenge for its clinical application. Purpose: The objective of this study was to improve the water solubility of PTX and investigate its anti-keloid effects. Methods: We prepared a PTX-cholesterol-loaded liposomes (PTXL) by thin film evaporation fashion and characterized their physicochemical properties. We also investigated the effects of PTX on proliferation, invasion and fibrosis of keloid fibroblasts in vitro and in vivo. Results: The prepared PTXL have a spherical appearance, a particle size of 101.43 nm and a zeta potential of -41.63 mV. PTXL possessed a high drug entrapment efficiency of 95.63% and exhibited a good stability within 30 days. The drugs in PTXL were released in a slow and sustained mode. The PTXL could be effectively uptaken into human keloids fibroblast (HKFs) in a time-dependent manner. In vitro, PTXL showed better ability on inhibiting cell proliferation, migration and invasion, and effectively on promoting apoptosis and arresting cell cycle in G2/M phase compared to PTX. Meanwhile, in vivo studies indicated that the PTXL had better performance on inhibiting the keloids growth compared to the PTX in keloid-bearing BALB/c nude mice model. Finally, we found PTX treatment suppressed the production of tumor necrosis factor alpah (TNF-α), interleukin 6 (IL-6) and transforming growth factor beta (TGF-β) and inhibited the expression of alpha smooth muscle actin (β-SMA) and collagen I in HKFs. The activation of protein kinase B (AKT)/glycogen synthase kinase 3 beta (GSK3β) signaling pathway also blocked by PTX in cultured HKFs and keloid tissues. LY294002, a PI3K (phosphatidylinositol 3-kinase)/AKT inhibitor, also suppressed the expression of TNF-α, IL-6 and TGF-β, and simultaneously, reduced the production of α-SMA and collagen I in HKFs. The inhibition of AKT/GSK3β signaling pathway contribute to inhibit the generation of fibrogenic cytokines by PTXL on ameliorating fibrosis progress in keloids. Conclusion: Our results suggested that the developed PTXL would become a promising therapeutic agent in the field of anti-keloid therapy. Keywords: keloids, paclitaxel, liposomes, AKT, GSK3β, fibrosis

Zhouna Li, Zhehu Jin Department of Dermatology, Yanbian University Affiliated hospital, Yanji, Jilin, People’s Republic of China Background: Keloids and hypertrophic scars are the most common types of pathological scarring. Traditionally, keloids have been considered as a result of aberrant wound healing, involving excessive fibroblast participation that is characterized by hyalinized collagen bundles. However, the usefulness of this characterization has been questioned. In recent years, studies have reported the appropriate use of verapamil for keloids and hypertrophic scars.Methods: Searches were conducted on the databases Medline, Embase, Cochrane, PubMed, and China National Knowledge Infrastructure from 2006 to July 2016. State12.0 was used for literature review, data extraction, and meta-analysis. Treatment groups were divided into verapamil and nonverapamil group. Nonverapamil group includes steroids and intense pulsed light (IPL) therapy. Total effective rates include cure rate and effective rate. Cure: skin lesions were completely flattened, became soft and symptoms disappeared. Efficacy: skin lesions subsided, patient significantly reduced symptoms. Inefficient definition of skin was progression free or became worse. Random-effects model was used for the meta-analysis.Results: Six studies that included 331 patients with keloids and hypertrophic scars were analyzed. Analysis of the total effective rate of skin healing was performed. The total effective rates in the two groups were 54.07% (verapamil) and 53.18% (nonverapamil), respectively. The meta-analysis showed that there was no difference between the two groups. We also compared the adverse reactions between the verapamil treatment group and the steroids treatment group in two studies, and the result indicated that the verapamil group showed less adverse reactions.Conclusion: There were no differences between the application of verapamil and nonverapamil group in keloids and hypertrophic scars treatment. Verapamil could act as an effective alternative modality in the prevention and treatment of keloid and hypertrophic scars. A larger number of studies are required to confirm our conclusion. Keywords: keloids, hypertrophic scars, verapamil, steroids, IPL

Abstract Background Blotched snakehead (Channa maculata) displays significant sexual dimorphism, with males exhibiting faster growth rates and larger body sizes compared to females. The cultivation of the all-male population of snakeheads holds substantial economic and ecological value. Nonetheless, the intricate processes governing the development of bipotential gonads into either testis or ovary in C. maculata remain inadequately elucidated. Therefore, it is necessary to determine the critical time window of sex differentiation in C. maculata, providing a theoretical basis for sex control in production practices. Methods The body length and weight of male and female C. maculata were measured at different developmental stages to reveal when sexual dimorphism in growth initially appears. Histological observations and spatiotemporal comparative transcriptome analyses were performed on ovaries and testes across various developmental stages to determine the crucial time windows for sex differentiation in each sex and the sex-related genes. Additionally, qPCR and MG2C were utilized to validate and locate sex-related genes, and levels of E2 and T were quantified to understand sex steroid synthesis. Results Sexual dimorphism in growth became evident starting from 90 dpf. Histological observations revealed that morphological sex differentiation in females and males occurred between 20 and 25 dpf or earlier and 30–35 dpf or earlier, respectively, corresponding to the appearance of the ovarian cavity or efferent duct anlage. Transcriptome analyses revealed divergent gene expression patterns in testes and ovaries after 30 dpf. The periods of 40–60 dpf and 60–90 dpf marked the initiation of molecular sex differentiation in females and males, respectively. Male-biased genes (Sox11a, Dmrt1, Amh, Amhr2, Gsdf, Ar, Cyp17a2) likely play crucial roles in male sex differentiation and spermatogenesis, while female-biased genes (Foxl2, Cyp19a1a, Bmp15, Figla, Er) could be pivotal in ovarian differentiation and development. Numerous biological pathways linked to sex differentiation and gametogenesis were also identified. Additionally, E2 and T exhibited sexual dimorphism during sex differentiation and gonadal development. Based on these results, it is hypothesized that in C. maculata, the potential male sex differentiation pathway, Sox11a–Dmrt1–Sox9b, activates downstream sex-related genes (Amh, Amhr2, Gsdf, Ar, Cyp17a2) for testicular development, while the antagonistic pathway, Foxl2/Cyp19a1a, activates downstream sex-related genes (Bmp15, Figla, Er) for ovarian development. Conclusions This study provides a comprehensive overview of gonadal dynamic changes during sex differentiation and gametogenesis in C. maculata, establishing a scientific foundation for sex control in this species.

Abstract Protein kinases are key signaling nodes that regulate fundamental biological and disease processes. Illuminating kinase signaling from multiple angles can provide deeper insights into disease mechanisms and improve therapeutic targeting. While fluorescent biosensors are powerful tools for visualizing live-cell kinase activity dynamics in real time, new molecular tools are needed that enable recording of transient signaling activities for post hoc analysis and targeted manipulation. Here, we develop a light-gated kinase activity coupled transcriptional integrator (KINACT) that converts dynamic kinase signals into “permanent” fluorescent marks. KINACT enables robust monitoring of kinase activity across scales, accurately recording subcellular PKA activity, highlighting PKA activity distribution in 3D cultures, and identifying PKA activators and inhibitors in high-throughput screens. We further leverage the ability of KINACT to drive signaling effector expression to allow feedback manipulation of the balance of Gαs R201C-induced PKA and ERK activation and dissect the mechanisms of oncogenic G protein signaling.

Abstract High-harmonic generation (HHG) has emerged as a central technique in attosecond science and strong-field physics, providing a tool for investigating ultrafast dynamics. However, the microscopic mechanism of HHG in solids is still under debate, and it is unclear how it is modified in the ubiquitous presence of phonons. Here we theoretically investigate the role of collectively coherent vibrations in HHG in a wide range of solids (e.g., hBN, graphite, 2H-MoS2, and diamond). We predict that phonon-assisted high harmonic yields can be significantly enhanced, compared to the phonon-free case – up to a factor of ~20 for a transverse optical phonon in bulk hBN. We also show that the emitted harmonics strongly depend on the character of the pumped vibrational modes. Through state-of-the-art ab initio calculations, we elucidate the physical origin of the HHG yield enhancement – phonon-assisted photoinduced carrier doping, which plays a paramount role in both intraband and interband electron dynamics. Our research illuminates a clear pathway toward comprehending phonon-mediated nonlinear optical processes within materials, offering a powerful tool to deliberately engineer and govern solid-state high harmonics.

Objective At present, there are relatively few studies on the safety assessment of maintenance and construction of urban rail transit operation lines. In order to reduce the operation safety risk of urban rail transit lines, the safety level of urban rail transit line maintenance construction should be comprehensively evaluated to guide the operation production and management. Method Targeting the 19 maintenance work areas on 4 lines in Shanghai rail transit network, a 4 hierarchy-structured safety effectiveness evaluation index system for urban rail transit line maintenance and construction is established. Based on the actual situation of line maintenance construction indexes, the entropy weight method is improved and combined with the mutation progression theory, and a linear combination evaluation method based on improved entropy weight and mutation progression is proposed as the result. The safety effectiveness of maintenance construction in 19 mainten-ance work areas is evaluated and analyzed with this method. Result & Conclusion The linear combination evaluation method based on improved entropy weight-mutation level passes the consistency test, and the evaluation results are stable and reliable. This method effectively expands the applicability of entropy weight method and mutation level theory in the evaluation of urban rail transit maintenance construction, and realizes the dynamic comprehensive evaluation in the field of rail transit line maintenance construction.

Abstract Due to intermittent renewable energy and fluctuating load demand, distribution networks with renewable distributed generation (DG) installations are more likely to suffer voltage issues and significant power losses. The performance of conservation voltage regulation (CVR) schemes may be adversely affected by the undesirable voltage profile at specific nodes. This paper aims to reduce power losses in CVR‐implemented networks by optimally planning new renewable DGs without changing the existing ones. A scenario‐based optimal renewable DG planning model is proposed with a novel scenario formation method. The uncertainties of load demand and renewables are captured jointly and formed into a finite number of scenarios based on a multivariate Gaussian mixture model (MultiGMM). The locations and capacities of different types of new renewable DGs are optimally planned for CVR performance improvements on power loss saving by aggregating the operation status and probabilities of the scenarios using mixed‐integer non‐linear programming (MINLP). A time‐series simulation is formulated for accuracy verification. The results of case studies show that the proposed model can significantly reduce power losses, active load demand, and reactive load demand. The accuracy of the planning results can be guaranteed with fewer scenarios compared to a widely used classical scenario‐based planning method.

Background: Immunotherapy has emerged as a novel strategy for cancer treatment following surgery, radiotherapy, and chemotherapy. Immune checkpoint blockade and Chimeric antigen receptor (CAR)-T cell therapies have been successful in clinical trials. Cancer cells evade immune surveillance by hijacking inhibitory pathways via overexpression of checkpoint genes. The Cluster of Differentiation 47 (CD47) has emerged as a crucial checkpoint for cancer immunotherapy by working as a “don’t eat me” signal and suppressing innate immune signaling. Furthermore, CD47 is highly expressed in many cancer types to protect cancer cells from phagocytosis via binding to SIRPα on phagocytes. Targeting CD47 by either interrupting the CD47-SIRPα axis or combing with other therapies has been demonstrated as an encouraging therapeutic strategy in cancer immunotherapy. Antibodies and small molecules that target CD47 have been explored in pre- and clinical trials. However, formidable challenges such as the anemia and palate aggregation cannot be avoided because of the wide presentation of CD47 on erythrocytes. Aim of view: This review summarizes the current knowledge on the regulation and function of CD47, and provides a new perspective for immunotherapy targeting CD47. It also highlights the clinical progress of targeting CD47 and discusses challenges and potential strategies. Key scientific concepts of review: This review provides a comprehensive understanding of targeting CD47 in cancer immunotherapy, it also augments the concept of combination immunotherapy strategies by employing both innate and adaptive immune responses.

Spinal cord injury (SCI) often results in irreversible loss of sensory and motor functions, and most SCIs are incurable with current medical practice. One of the hardest challenges in treating SCI is the development of a dysfunctional pathological microenvironment, which mainly comprises excessive inflammation, deposition of inhibitory molecules, neurotrophic factor deprivation, glial scar formation, and imbalance of vascular function. To overcome this challenge, implantation of functional biomaterials at the injury site has been regarded as a potential treatment for modulating the dysfunctional microenvironment to support axon regeneration, remyelination at injury site, and functional recovery after SCI. This review summarizes characteristics of dysfunctional pathological microenvironment and recent advances in biomaterials as well as the technologies used to modulate inflammatory microenvironment, regulate inhibitory microenvironment, and reshape revascularization microenvironment. Moreover, technological limitations, challenges, and future prospects of functional biomaterials to promote efficient repair of SCI are also discussed. This review will aid further understanding and development of functional biomaterials to regulate pathological SCI microenvironment.

Abstract Objectives To develop a deep learning model combining CT scans and clinical information to predict overall survival in advanced hepatocellular carcinoma (HCC). Methods This retrospective study included immunotherapy-treated advanced HCC patients from 52 multi-national in-house centers between 2018 and 2022. A multi-modal prognostic model using baseline and the first follow-up CT images and 7 clinical variables was proposed. A convolutional-recurrent neural network (CRNN) was developed to extract spatial-temporal information from automatically selected representative 2D CT slices to provide a radiological score, then fused with a Cox-based clinical score to provide the survival risk. The model’s effectiveness was assessed using a time-dependent area under the receiver operating curve (AUC), and risk group stratification using the log-rank test. Prognostic performances of multi-modal inputs were compared to models of missing modality, and the size-based RECIST criteria. Results Two-hundred seven patients (mean age, 61 years ± 12 [SD], 180 men) were included. The multi-modal CRNN model reached the AUC of 0.777 and 0.704 of 1-year overall survival predictions in the validation and test sets. The model achieved significant risk stratification in validation (hazard ratio [HR] = 3.330, p = 0.008), and test sets (HR = 2.024, p = 0.047) based on the median risk score of the training set. Models with missing modalities (the single-modal imaging-based model and the model incorporating only baseline scans) can still achieve favorable risk stratification performance (all p

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.

Energy decarbonization is essential for achieving carbon neutrality. To facilitate the low-carbon transition of the energy system, extensive utilization of low-carbon energy technologies is crucial across various sectors, including primary energy supply, energy processing and conversion, and end-use consumption. This study provides a comprehensive overview of the current status and future trends of key energy utilization technologies from the perspective of low-carbon energy system analysis and optimization. We analyze the application prospects and layout challenges of energy utilization technologies in China’s path toward carbon neutrality from multiple dimensions. Our study highlights the following points: Wind and solar energy, as the fastest-growing renewable energy sources, will continue to play a crucial role in energy supply. The utilization of biomass resources requires systematic evaluation of different conversion technologies, optimizing the allocation of biomass resources across industries. Utilization technologies of secondary energies such as hydrogen and energy storage face challenges related to materials, performance, and lifespan. Overcoming these technical bottlenecks is necessary to achieve low-cost and scalable system applications. Future end-use energy utilization technologies will focus on electrification, which depends on the secure and stable transformation and expansion of electricity distribution systems. Achieving low-carbon transformation in the energy system requires balancing the coordinated development of different energy technologies while addressing non-technical factors such as market dynamics, institutional frameworks, and societal acceptance, ultimately accelerating the decarbonization process.

Abstract Background Patients with airway stenosis (AS) are associated with considerable morbidity and mortality after lung transplantation (LTx). This study aims to develop and validate machine learning (ML) models to predict AS requiring clinical intervention in patients after LTx. Methods Patients who underwent LTx between January 2017 and December 2019 were reviewed. The conventional logistic regression (LR) model was fitted by the independent risk factors which were determined by multivariate LR. The optimal ML model was determined based on 7 feature selection methods and 8 ML algorithms. Model performance was assessed by the area under the curve (AUC) and brier score, which were internally validated by the bootstrap method. Results A total of 381 LTx patients were included, and 40 (10.5%) patients developed AS. Multivariate analysis indicated that male, pulmonary arterial hypertension, and postoperative 6-min walking test were significantly associated with AS (all P

Abstract The Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway serves as a paradigm for signal transduction from the extracellular environment to the nucleus. It plays a pivotal role in physiological functions, such as hematopoiesis, immune balance, tissue homeostasis, and surveillance against tumors. Dysregulation of this pathway may lead to various disease conditions such as immune deficiencies, autoimmune diseases, hematologic disorders, and cancer. Due to its critical role in maintaining human health and involvement in disease, extensive studies have been conducted on this pathway, ranging from basic research to medical applications. Advances in the structural biology of this pathway have enabled us to gain insights into how the signaling cascade operates at the molecular level, laying the groundwork for therapeutic development targeting this pathway. Various strategies have been developed to restore its normal function, with promising therapeutic potential. Enhanced comprehension of these molecular mechanisms, combined with advances in protein engineering methodologies, has allowed us to engineer cytokines with tailored properties for targeted therapeutic applications, thereby enhancing their efficiency and safety. In this review, we outline the structural basis that governs key nodes in this pathway, offering a comprehensive overview of the signal transduction process. Furthermore, we explore recent advances in cytokine engineering for therapeutic development in this pathway.

The depth-dependent dynamics of dissolved organic matter (DOM) structure and humification in an artificial lake limits the understanding of lake eutrophication and carbon cycling. Using fluorescence regional integration (FRI) and parallel factor analysis (PARAFAC) models to analyze the 3D fluorescence spectroscopy dataset, we revealed the depth-dependent structure and vertical distribution of DOM in the estuarine and center regions of Lake Hongfeng. The percentage fluorescence response (Pi,n) showed humic acid is an important part of DOM in Lake Hongfeng. Fluorescence results show that the fulvic-like and protein-like materials in HF1-DOM located at the estuarine position showed greater variation in the middle stage, probably due to human influence and sediment suspension. Fluorescence index (PI+II+IV,n/PIII+V,n and FIC4/FIC3) can be used to indicate the degree of humification of DOM in artificial lakes. Results of each index show that the estuary is more affected by human activities, and the humification degree is significantly lower than that of the center of the lake. The evaluation index system of the humification degree of artificial lake established in this study can effectively predict the eutrophication state of the typical area of artificial lake and deeply understand the possible important influence of human activities on the carbon cycle of lake. HIGHLIGHTS Complex factors in the estuary of the lake lead to significant changes in DOM structure.; Depth-dependent change sensitivity was for humic > fulvic> protein-like components.; Higher DOM humification in the middle of the lake is attributed to microbial action.; Spectral indices were confirmed to evaluate the DOM humification degree.;

Abstract National and global food security depend on both supply and demand, yet the vast majority of studies on the impact of climate change on food security have focused somewhat myopically on the supply side. Here, we assess planetary implications of the changing climate for food supply, concurrently considering implications of shifts in dietary preferences on food security. From 1990 to 2018, climate change detrimentally impacted on the food production of 92% of nations assessed. During this time, demand decreased at a greater rate than food supply in 28% of countries; food security for 35% of the global population was unperturbed by climate change. On the other hand, 2% of the global population did not benefit from positive impacts of climate change on food production, due to dietary changes faster increasing food demand. If consumers shift dietary preferences en masse towards healthier diets, detrimental impacts of the climate crisis on food security may be abated, although en mass and/or abrupt transitions in dietary preferences are unlikely.

Abstract Toll-like receptor (TLR) 4 contributes to be the induction of neuroinflammation by recognizing pathology-associated ligands and activating microglia. In addition, numerous physiological signaling factors act as agonists or antagonists of TLR4 expressed by non-immune cells. Recently, TLR4 was found to be highly expressed in cerebellar Purkinje neurons (PNs) and involved in the maintenance of motor coordination through non-immune pathways, but the precise mechanisms remain unclear. Here we report that mice with PN specific TLR4 deletion (TLR4PKO mice) exhibited motor impairments consistent with cerebellar ataxia, reduced PN dendritic arborization and spine density, fewer parallel fiber (PF) – PN and climbing fiber (CF) – PN synapses, reduced BK channel expression, and impaired BK-mediated after-hyperpolarization, collectively leading to abnormal PN firing. Moreover, the impaired PN firing in TLR4PKO mice could be rescued with BK channel opener. The PNs of TLR4PKO mice also exhibited abnormal mitochondrial structure, disrupted mitochondrial endoplasmic reticulum tethering, and reduced cytosolic calcium, changes that may underly abnormal PN firing and ultimately drive ataxia. These results identify a previously unknown role for TLR4 in regulating PN firing and maintaining cerebellar function.

Abstract The Phosphatidylinositol-3-kinase (PI3K) family is well-known to comprise three classes of intracellular enzymes. Class I PI3Ks primarily function in signaling by responding to cell surface receptor stimulation, while class II and III are more involved in membrane transport. Under normal physiological conditions, the PI3K signaling network orchestrates cell growth, division, migration and survival. Aberrant activation of the PI3K signaling pathway disrupts cellular activity and metabolism, often marking the onset of cancer. Currently, the Food and Drug Administration (FDA) has approved the clinical use of five class I PI3K inhibitors. These small-molecule inhibitors, which exhibit varying selectivity for different class I PI3K family members, are primarily used in the treatment of breast cancer and hematologic malignancies. Therefore, the development of novel class I PI3K inhibitors has been a prominent research focus in the field of oncology, aiming to enhance potential therapeutic selectivity and effectiveness. In this review, we summarize the specific structures of PI3Ks and their functional roles in cancer progression. Additionally, we critically evaluate small molecule inhibitors that target class I PI3K, with a particular focus on their clinical applications in cancer treatment. Moreover, we aim to analyze therapeutic approaches for different types of cancers marked by aberrant PI3K activation and to identify potential molecular targets amenable to intervention with small-molecule inhibitors. Ultimately, we propose future directions for the development of therapeutic strategies that optimize cancer treatment outcomes by modulating the PI3K family.

Abstract Backgrounds Currently, family with sequence similarity 65 member A (FAM65A) is reported as a pivotal regulator in various cancers. However, the effect of FAM65A in lung squamous cell carcinoma (LSCC) is still unclear, the prime objective of this research is to explore the role of FAM65A in LSCC. Methods Gene expression data and correlated clinical information were downloaded from the public database and the expression of FAM65A was detected. The expression of FAM65A was also detected in our collected clinical samples and LSCC cell lines. Survival package of R language was used to determine the survival significance of FAM65A. Proteins expression level was determined via western blot assay. Cell function experiments and in vivo experiments were performed to explore the effect of FAM65A on LSCC cell biological behaviors. Results FAM65A expression was significantly increased in LSCC clinical samples and cell lines. High FAM65A expression predicted poor prognosis in LSCC patients. After silencing FAM65A, the ability of LSCC cell proliferation, invasion and migration was decreased, and LSCC cell cycle was blocked. Moreover, in vivo experiments revealed that silencing FAM65A could inhibit LSCC cell proliferation. Conclusions High FAM65A expression could enhance proliferative, invasive and migratory abilities of LSCC. FAM65A might be a novel biomarker of LSCC.

Abstract This retrospective study analyzed a large population of gastric cancer (GC) patients treated between 2010 and 2015 to investigate the clinical features and predictive risk factors for developing secondary primary malignancies (SPMs). The cumulative incidence of SPM was assessed using Kaplan–Meier analysis. Competing risk analyses adjusted for mortality were conducted using stratified Cox proportional hazard regression models and multivariate analyses to identify independent predictors of SPM. A total of 3289 out of 167,747 GC patients were included in the analytic cohort, with 155 patients diagnosed with SPM. Patients whose histologic type other than adenocarcinomas (AC) and signet ring cell carcinoma (SRCC) emerged as an independent risk factor for developing SPM (hazard ratio [HR] 2.262, 95% confidence interval [CI] 1.146–4.465, P = 0.019) in multivariate Cox regression analysis. The surgical method, including biopsy/local excision (HR 2.3, [CI] 1.291–4.095, P = 0.005) and subtotal/total resection ([HR] 1.947, [CI] 1.028–3.687, P = 0.041), chemotherapy ([HR] 1.527, [CI] 1.006–2.316, P = 0.047), and histologic type ([HR] 2.318, [CI] 1.193–4.504, P = 0.013)), were identified as independent risk factors in the competitive risk model. Subgroup analyses, stratified by chemotherapy, revealed an increased risk of SPM among older patients. Furthermore, a nomogram was developed and internally validated to predict the cumulative incidence of SPM in GC patients (C-index = 0.73 for 72 months). These findings suggested that in specific histologic types of GC, the lymph node infiltration region missed after local surgical resection, and concomitant chemotherapy would have an increased risk of SPM for cancer survivors.

Abstract Background Ischemic stroke elicits a complex and sustained immune response in the brain. Immunomodulatory treatments have long held promise for improving stroke outcomes, yet none have succeeded in the clinical setting. This lack of success is largely due to our incomplete understanding of how immune cells respond to stroke. The objective of the current study was to dissect the effect of permanent stroke on microglia, the resident immune cells within the brain parenchyma. Methods A permanent middle cerebral artery occlusion (pMCAO) model was used to induce ischemic stroke in young male and female mice. Microglia were sorted from fluorescence reporter mice after pMCAO or sham surgery and then subjected to single-cell RNA sequencing analysis. Various methods, including flow cytometry, RNA in situ hybridization, immunohistochemistry, whole-brain imaging, and bone marrow transplantation, were also employed to dissect the microglial response to stroke. Stroke outcomes were evaluated by infarct size and behavioral tests. Results First, we showed the morphologic and spatial changes in microglia after stroke. We then performed single-cell RNA sequencing analysis on microglia isolated from sham and stroke mice of both sexes. The data indicate no major sexual dimorphism in the microglial response to permanent stroke. Notably, we identified seven potential stroke-associated microglial clusters, including four major clusters characterized by a disease-associated microglia-like signature, a highly proliferative state, a macrophage-like profile, and an interferon (IFN) response signature, respectively. Importantly, we provided evidence that the macrophage-like cluster may represent the long-sought stroke-induced microglia subpopulation with increased CD45 expression. Lastly, given that the IFN-responsive subset constitutes the most prominent microglial population in the stroke brain, we used fludarabine to pharmacologically target STAT1 signaling and found that fludarabine treatment improved long-term stroke outcome. Conclusions Our findings shed new light on microglia heterogeneity in stroke pathology and underscore the potential of targeting specific microglial populations for effective stroke therapies.

Abstract Background This study introduced an Augmented Reality (AR) navigation system to address limitations in conventional high tibial osteotomy (HTO). The objective was to enhance precision and efficiency in HTO procedures, overcoming challenges such as inconsistent postoperative alignment and potential neurovascular damage. Methods The AR-MR (Mixed Reality) navigation system, comprising HoloLens, Unity Engine, and Vuforia software, was employed for pre-clinical trials using tibial sawbone models. CT images generated 3D anatomical models, projected via HoloLens, allowing surgeons to interact through intuitive hand gestures. The critical procedure of target tracking, essential for aligning virtual and real objects, was facilitated by Vuforia’s feature detection algorithm. Results In trials, the AR-MR system demonstrated significant reductions in both preoperative planning and intraoperative times compared to conventional navigation and metal 3D-printed surgical guides. The AR system, while exhibiting lower accuracy, exhibited efficiency, making it a promising option for HTO procedures. The preoperative planning time for the AR system was notably shorter (4 min) compared to conventional navigation (30.5 min) and metal guides (75.5 min). Intraoperative time for AR lasted 8.5 min, considerably faster than that of conventional navigation (31.5 min) and metal guides (10.5 min). Conclusions The AR navigation system presents a transformative approach to HTO, offering a trade-off between accuracy and efficiency. Ongoing improvements, such as the incorporation of two-stage registration and pointing devices, could further enhance precision. While the system may be less accurate, its efficiency renders it a potential breakthrough in orthopedic surgery, particularly for reducing unnecessary harm and streamlining surgical procedures.

Purposes In actual processing of factories, the varying health status of each machine can cause machine failures and subsequently affect the processing and construction time. This article focuses on the problem of flexible job shops with machine disturbances. In order to reduce the impact of machine failures on production planning, a rescheduling model for machine disturbances and breakpoint finding is proposed. A mathematical model is constructed with the optimization objectives of the minimum processing time and the minimum total delay time. Methods The improved grey wolf optimization algorithm (GWO-GA) is proposed as a global optimization search algorithm for solution. In order to improve the convergence rate of its gray wolf algorithm, the work piece coding iteration is introduced with an adaptive operator be added, and the POX crossover of genetic algorithm is used to iterate the machine coding. Findings The validation is conducted on the solid wood workshop data of piano manufacturing enterprises, and the results show that compared with genetic algorithm, NSGA, and PSO-GA, the improved grey wolf algorithm has advantages of high efficiency, good accuracy, and good practical value in solving this scheduling problem.

Abstract The inner Helmholtz plane and thus derived solid-electrolyte interphase (SEI) are crucial interfacial structure to determine the electrochemical stability of Zn-ion battery (ZIB). In this work, we demonstrate that introducing β-cyclodextrins (CD) as anion-receptors into Zn(OTf)2 aqueous electrolyte could significantly optimize the Zn anode SEI structure for achieving stable ZIB. Specifically, β-CD with macrocyclic structure holds appropriate cavity size and charge distribution to encase OTf- anions at the Zn metal surface to form β-CD@OTf- dominated inner Helmholtz structure. Meanwhile, the electrochemically triggered β-CD@OTf- decomposition could in situ convert to the organic-inorganic hybrid SEI (ZnF2/ZnCO3/ZnS‒(C-O-C/*CF/*CF3)), which could efficiently hinder the Zn dendrite growth with maintain the proper SEI mechanical strength stability to guarantee the long-term stability. The thus-derived Zn | |Zn pouch cell (21 cm2 size) with β-CD-containing electrolyte exhibits a cumulative capacity of 6450 mAh−2 cm−2 at conditions of 10 mAh cm−2 high areal capacity. This work gives insights for reaching stable ZIB via electrolyte additive triggered SEI structure regulation.

Abstract Mounting evidence showed that HER2-Low breast cancer patients could benefit from the novel anti-HER2 antibody–drug conjugates (ADCs) treatment, which pointed the way towards better therapy for HER2-Low patients. The purpose of this study was to describe the clinicopathological features, along with chemotherapeutic effects and survival outcomes of HER2-Low and HER2-Zero in TNBC who received neoadjuvant chemotherapy (NACT). We retrospectively evaluated 638 triple-negative breast cancer patients who were treated with neoadjuvant chemotherapy between August 2014 and August 2022. Pathologic complete response (pCR) and survival outcomes were analyzed in HER2-Low cohort, HER2-Zero cohort and the overall patients, respectively. In the entire cohort, 342 (53.6%) patients were HER2-Low and 296 (46.4%) patients were HER2-Zero. No significant difference was found between HER2-Low and HER2-Zero patients based on all the clinical–pathological characteristics. 143 cases (22.4%) achieved pCR after NACT in the overall TNBC patients. The pCR rate of the HER2-Low patients and the HER2-Zero patients was 21.3% and 23.6%, respectively, exhibiting no statistical difference (p = 0.487). The survival of pCR group after NACT significantly improved compared to non-pCR group either in HER2-Low patients or in HER2-Zero patients. Although we found that patients with HER2-Low had longer DFS than patients with HER2-Zero, there was no considerable difference (p = 0.068). However, HER2-Low patients had a dramatically longer OS than HER2-Zero patients (p = 0.012). The data from present study confirmed the clinical importance of HER2-Low expression in TNBC. Further effort is needed to determine whether HER2-Low could be a more favorable prognostic marker for individual treatment.

Abstract Integrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I–III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p

Abstract Understanding the origin of superconductivity in correlated two-dimensional materials is a key step in leveraging material engineering techniques for next-generation nanoscale devices. While it is widely accepted that phonons fluctuations only mediate conventional (s-wave) superconductivity, the common phenomenology of superconductivity in Bernal bilayer and rhombohedral trilayer graphene, as well as in a large family of graphene-based moiré systems, suggests a common superconducting mechanism across these platforms. In particular, in all these platforms some superconducting regions violate the Pauli limit, indicating unconventional superconductivity, naively ruling out conventional phonon-mediated pairing as the underlying mechanism. Here we combine first principles simulations with effective low-energy theories to investigate the superconducting mechanism and pairing symmetry in rhombohedral stacked graphene multilayers. We find that phonon-mediated superconductivity explains the main experimental findings, namely the displacement field and doping level dependence of the critical temperature, and the presence of two superconducting regions with different pairing symmetries that depend on the parent normal state. In particular, we find that intra-valley phonon scattering favors a triplet f-wave pairing when combined with electronic correlations stabilizing a spin- and valley-polarized normal state. We also propose a so far unexplored superconducting region at higher hole doping densities n h ≈ 4 × 1012 cm−2, and demonstrate how this highly hole-doped regime can be reached in heterostructures consisting of monolayer α-RuCl3 and rhombohedral trilayer graphene. Our findings promote phonon-mediated pairing as a strong contender to explain superconductivity across a wide range of graphene platforms, and demonstrate that phonons can, in fact, stabilize unconventional superconducting orders.

Abstract Background The study aimed to evaluate the diagnostic efficacy of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) parameters in distinguishing sinonasal lymphoma from sinonasal carcinoma. Methods Forty-two participants with histologically confirmed sinonasal lymphomas and fifty-two cases of sinonasal carcinoma underwent imaging with a 3.0T MRI scanner. DCE-MRI and DWI were conducted, and various parameters including type of time-intensity curve(TIC), time to peak, peak enhancement, peak contrast enhancement, washout rate, apparent diffusion coefficient (ADC), and relative ADC were measured. Binary logistic regression and receiver operating characteristic (ROC) curve analysis were employed to assess the diagnostic capability of individual and combined indices for differentiating nasal sinus lymphoma from nasal sinus carcinoma. Results Sinonasal lymphoma predominantly exhibited type II TIC(n = 20), whereas sinonasal carcinoma predominantly exhibited type III TIC(n = 23). Significant differences were observed in all parameters except washout ratio (p

Abstract As an innovative, low-power consuming, and low-stiffness suspension approach, the diamagnetic levitation technique has attracted considerable interest because of its potential applicability in miniaturized mechanical systems. The foundation of a diamagnetic levitation system is mathematical modeling, which is essential for operating performance optimization and stability prediction. However, few studies on systematic mathematical modeling have been reported. In this study, a systematic mathematical model for a disc-shaped diamagnetically levitated rotor on a permanent magnet array is proposed. Based on the proposed model, the magnetic field distribution characteristics, diamagnetic levitation force characteristics (i.e., levitation height and stiffness), and optimized theoretical conditions for realizing stable levitation are determined. Experiments are conducted to verify the feasibility of the proposed mathematical model. Theoretical predictions and experimental results indicate that increasing the levitation height enlarges the stable region. Moreover, with a further increase in the rotor radius, the stable regions of the rotor gradually diminish and even vanish. Thus, when the levitation height is fixed, a moderate rotor radius permits stable levitation. This study proposes a mathematical modeling method for a diamagnetic levitation system that has potential applications in miniaturized mechanical systems.

Abstract The problem of hydrate plug, low efficiency of hydrate dissociation and short production time in hydrate exploitation processes have significantly hindered the commercial viability of gas hydrate extraction. This study investigated the inhibitory effects of ethylene glycol (EG), EG + polyvinyl pyrrolidone (PVP), and EG + PVP + sodium chloride (NaCl) on methane hydrate formation through experiment. The hydrate inhibitory performance is evaluated by using differential of pressure curve, the amount of hydrate, and pressure drop values, and the effects of different temperatures, pressures, inhibitors, and injection time on hydrate dissociation are further studied. The experiment results indicate that the rank of inhibitors combination in terms of effectiveness is 5%EG + 0.5 wt%PVP + 3 wt%Nacl > 10%EG + 1 wt%PVP > 30% EG. At low-temperature conditions, 30% EG exhibits good inhibition of hydrate synthesis but poor dissociation efficiency. As temperature increases, the hydrates dissociation rate with 30% EG also increases. For the combination inhibitor system of EG, PVP, and NaCl, PVP will reduce the dissociation efficiency of hydrates, while EG and Nacl will improve the hydrate dissociation performance. For low production pressure, it is found that 10% EG + 10% NaCl have a good promotion effect on hydrate dissociation, whereas under high production pressure, 20% EG + 10% NaCl is more effective. Furthermore, injecting the inhibitors earlier enhances the dissociation of hydrates more effectively.

Abstract Background The high recurrence rate after liver resection emphasizes the urgent need for neoadjuvant therapy in hepatocellular carcinoma (HCC) to enhance the overall prognosis for patients. Immune checkpoint inhibitors, camrelizumab combined with an anti-angiogenic tyrosine kinase inhibitor (TKI) apatinib, have emerged as a first-line treatment option for patients with unresectable HCC, yet its neoadjuvant application in combination with transarterial chemoembolization (TACE) in HCC remains unexplored. Therefore, this study aims to investigate the efficacy and safety of sequential TACE, camrelizumab, and apatinib as a neoadjuvant therapy for single, huge HCC. Methods This multi-center, open-label randomized phase 3 trial will be conducted at 7 tertiary hospitals. Patients with single huge (≥ 10 cm in diameter), resectable HCC will be randomly assigned in a 1:1 ratio to arm of surgery alone or arm of neoadjuvant therapy followed by surgery. In the neoadjuvant therapy group, patients will receive TACE within 1 week after randomization, followed by camrelizumab (200 mg q2w, 4 cycles), along with apatinib (250 mg qd, 2 months). Patients will receive liver resection after neoadjuvant therapy unless the disease is assessed as progressive. The primary outcome is recurrence-free survival (RFS) at 1 year. The planned sample size of 60 patients will be calculated to permit the accumulation of sufficient RFS events in 1 year to achieve 80% power for the RFS primary endpoint. Discussion Synergistic effects provided by multimodality therapy of locoregional treatment, TKI, and anti-programmed cell death 1 inhibitor significantly improved overall survival for patients with unresectable HCC. Our trial will investigate the efficacy and safety of the triple combination of TACE, camrelizumab, and apatinib as a neoadjuvant strategy for huge, resectable HCC. Trial registration www.chitr.org.cn ChiCTR2300078086. Registered on November 28, 2023. Start recruitment: 1st January 2024. Expected completion of recruitment: 15th June 2025.

Abstract Background The acute and long-term benefits of exercise training on cardiovascular health have been well established. The systematic review and meta-analysis aimed to systematically assess the effectiveness of exercise training on arterial stiffness and blood pressure among postmenopausal women with elevated blood pressure. Methods A comprehensive search was conducted on PubMed, Embase, Web of Science, ProQuest, Cochrane Library, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov website from inception to September 30, 2023, to identify the randomized controlled trials (RCTs), which evaluated the effectiveness of exercise training on arterial stiffness and blood pressure in postmenopausal women. Standardized mean differences (SMD), weighted mean differences (WMD), and 95% confidence intervals (95% CIs) were calculated using random/fixed effects models. Quality assessment was performed using the modified Jadad scale and the Cochrane Risk of Bias Tool. Sensitivity analysis and subgroup analysis were conducted based on drug dosage, treatment duration, and age of administration to further explore potential heterogeneity. Funnel plots were performed to assess publication bias and Begg’s regression test was carried out for funnel plot asymmetry. Results Twenty-two RCTs involving 1978 participants were included in the quantitative analysis. The mean quality of eligible studies was 4.2 out of 7 based on the modified Jadad scale. The results indicated that exercise training had a significant effect on reducing brachial-ankle pulse wave velocity [MD = − 0.69, 95%CI (− 1.11, − 0.27), P = 0.001], decreasing augmentation index (AIx) [MD = − 6.00, 95%CI (− 6.39, − 5.61), P

Abstract Clear cell renal cell carcinoma (ccRCC) is a prevalent malignancy with complex heterogeneity within epithelial cells, which plays a crucial role in tumor progression and immune regulation. Yet, the clinical importance of the malignant epithelial cell-related genes (MECRGs) in ccRCC remains insufficiently understood. This research aims to undertake a comprehensive investigation into the functions and clinical relevance of malignant epithelial cell-related genes in ccRCC, providing valuable understanding of the molecular mechanisms and offering potential targets for treatment strategies. Using data from single-cell sequencing, we successfully identified 219 MECRGs and established a prognostic model MECRGS (MECRGs’ signature) by synergistically analyzing 101 machine-learning models using 10 different algorithms. Remarkably, the MECRGS demonstrated superior predictive performance compared to traditional clinical features and 92 previously published signatures across six cohorts, showcasing its independence and accuracy. Upon stratifying patients into high- and low-MECRGS subgroups using the specified cut-off threshold, we noted that patients with elevated MECRGS scores displayed characteristics of an immune suppressive tumor microenvironment (TME) and showed worse outcomes after immunotherapy. Additionally, we discovered a distinct ccRCC tumor cell subtype characterized by the high expressions of PLOD2 (procollagen-lysine,2-oxoglutarate 5-dioxygenase 2) and SAA1 (Serum Amyloid A1), which we further validated in the Renji tissue microarray (TMA) cohort. Lastly, ‘Cellchat’ revealed potential crosstalk patterns between these cells and other cell types, indicating their potential role in recruiting CD163 + macrophages and regulatory T cells (Tregs), thereby establishing an immunosuppressive TME. PLOD2 + SAA1 + cancer cells with intricate crosstalk patterns indeed show promise for potential therapeutic interventions.

Brain imaging genetics is an evolving neuroscience topic aiming to identify genetic variations related to neuroimaging measurements of interest. Traditional linear regression methods have shown success, but their reliance on individual-level imaging and genetic data limits their applicability. Herein, we proposed S-GsMTLR, a group sparse multi-task linear regression method designed to harness summary statistics from genome-wide association studies (GWAS) of neuroimaging quantitative traits. S-GsMTLR directly employs GWAS summary statistics, bypassing the requirement for raw imaging genetic data, and applies multivariate multi-task sparse learning to these univariate GWAS results. It amalgamates the strengths of conventional sparse learning methods, including sophisticated modeling techniques and efficient feature selection. Additionally, we implemented a rapid optimization strategy to alleviate computational burdens by identifying genetic variants associated with phenotypes of interest across the entire chromosome. We first evaluated S-GsMTLR using summary statistics derived from the Alzheimer's Disease Neuroimaging Initiative. The results were remarkably encouraging, demonstrating its comparability to conventional methods in modeling and identification of risk loci. Furthermore, our method was evaluated with two additional GWAS summary statistics datasets: One focused on white matter microstructures and the other on whole brain imaging phenotypes, where the original individual-level data was unavailable. The results not only highlighted S-GsMTLR's ability to pinpoint significant loci but also revealed intriguing structures within genetic variations and loci that went unnoticed by GWAS. These findings suggest that S-GsMTLR is a promising multivariate sparse learning method in brain imaging genetics. It eliminates the need for original individual-level imaging and genetic data while demonstrating commendable modeling and feature selection capabilities.

Taking amphibians as island models, we examined the effects of interspecific interaction on the diversity and stability of microbial ecological. As skin area increased, the diversity and stability of skin microbes decreased, but the strength of negative interactions increased significantly. In contrast, as gut area increased, the diversity and stability of gut microbes increased, but the strength of interactions remained constant. These results indicate that microbial interactions are affected by habitat properties. When living in fluctuating environments without strong filtering, microorganisms can enhance their negative interactions with other taxa by changing the pH of their surroundings. In contrast, the pH of the gut is relatively stable, and colonized microorganisms cannot alter the gut pH and inhibit other colonizers. This study demonstrates that in the field of microbiology, diversity and stability are predominantly influenced by the intensity of interspecies interactions. The findings in this study deepen our understanding of microbial diversity and stability and provide a mechanistic link between species interactions, biodiversity, and stability in microbial ecosystems.

Dielectric metasurfaces have made significant advancements in the past decade for enhancing light–matter interaction at the nanoscale. Particularly, bound states in the continuum (BICs) based on dielectric metasurfaces have been employed to enhance nonlinear harmonic generation. However, conventional nonlinear metasurfaces are typically fixed in their operating wavelength after fabrication. In this work, we numerically demonstrate tunable third harmonic generation (THG) by integrating a dielectric metasurface with the phase-change material Ge2Sb2Te5 (GST). The hybrid phase-change metasurface can support two BICs with different electromagnetic origins, which are transformed into two high-Q quasi-BICs through the introduction of structural asymmetry. The two quasi-BICs are selectively excited by controlling the polarization of incident light, and their wavelengths are tunable due to the phase transition of GST. Notably, the efficiency of THG is significantly enhanced at the fundamental wavelengths corresponding to the two quasi-BICs, and the operating wavelength for THG enhancement can be dynamically tuned through the GST phase transition. Furthermore, the wavelength of THG enhancement can be further tuned by manipulating the polarization of pump light. Additionally, a high-Q analog of electromagnetically induced transparency is numerically achieved through the interaction between a low-Q Mie resonance and a quasi-BIC mode, which also improves the THG efficiency. The high-Q polarization-controlled hybrid phase-change metasurface holds promise for applications in dynamically tunable nonlinear optical devices.

Abstract Background 3% chloroprocaine (CP) has been reported as the common local anesthetic used in pregnant women undergoing urgent cesarean delivery during labor analgesia period. However, 0.75% ropivacaine is considered a promising and effective alternative. Therefore, we conducted a randomized controlled trial to compare the effectiveness and safety of 0.75% ropivacaine with 3% chloroprocaine for extended epidural anesthesia in pregnant women. Methods We conducted a double-blind, randomized, controlled, single-center study from November 1, 2022, to April 30, 2023. We selected forty-five pregnant women undergoing urgent cesarean delivery during labor analgesia period and randomized them to receive either 0.75% ropivacaine or 3% chloroprocaine in a 1:1 ratio. The primary outcome was the time to loss of cold sensation at the T4 level. Results There was a significant difference between the two groups in the time to achieve loss of cold sensation (303, 95%CI 255 to 402 S vs. 372, 95%CI 297 to 630 S, p = 0.024). There was no significant difference the degree of motor block (p = 0.185) at the Th4 level. Fewer pregnant women required additional local anesthetics in the ropivacaine group compared to the chloroprocaine group (4.5% VS. 34.8%, p = 0.011). The ropivacaine group had lower intraoperative VAS scores (p = 0.023) and higher patient satisfaction scores (p = 0.040) than the chloroprocaine group. The incidence of intraoperative complications was similar between the two groups, and no serious complications were observed. Conclusions Our study found that 0.75% ropivacaine was associated with less intraoperative pain treatment, higher patient satisfaction and reduced the onset time compared to 3% chloroprocaine in pregnant women undergoing urgent cesarean delivery during labor analgesia period. Therefore, 0.75% ropivacaine may be a suitable drug in pregnant women undergoing urgent cesarean delivery during labor analgesia period. Clinical trial number and registry URL The registration number: ChiCTR2200065201; http://www.chictr.org.cn , Principal investigator: MEN, Date of registration: 31/10/2022.

Abstract The overall health condition of patients significantly affects the diagnosis, treatment, and prognosis of endodontic diseases. A systemic consideration of the patient’s overall health along with oral conditions holds the utmost importance in determining the necessity and feasibility of endodontic therapy, as well as selecting appropriate therapeutic approaches. This expert consensus is a collaborative effort by specialists from endodontics and clinical physicians across the nation based on the current clinical evidence, aiming to provide general guidance on clinical procedures, improve patient safety and enhance clinical outcomes of endodontic therapy in patients with compromised overall health.

Abstract Parkinson’s disease (PD) is a progressive neurodegenerative disease characterized by mitochondrial dysfunction and accumulation of alpha-synuclein (α-Syn)-containing protein aggregates known as Lewy bodies (LB). Here, we investigated the entry of α-Syn into mitochondria to cause mitochondrial dysfunction and loss of cellular fitness in vivo. We show that α-Syn expressed in yeast and human cells is constitutively imported into mitochondria. In a transgenic mouse model, the level of endogenous α-Syn accumulation in mitochondria of dopaminergic neurons and microglia increases with age. The imported α-Syn is degraded by conserved mitochondrial proteases, most notably NLN and PITRM1 (Prd1 and Cym1 in yeast, respectively). α-Syn in the mitochondrial matrix that is not degraded interacts with respiratory chain complexes, leading to loss of mitochondrial DNA (mtDNA), mitochondrial membrane potential and cellular fitness decline. Importantly, enhancing mitochondrial proteolysis by increasing levels of specific proteases alleviated these defects in yeast, human cells, and a PD model of mouse primary neurons. Together, our results provide a direct link between α-synuclein-mediated cellular toxicity and its import into mitochondria and reveal potential therapeutic targets for the treatment of α-synucleinopathies.

Abstract Interfacial solar evaporation is a sustainable and effective method that uses solar energy to produce freshwater. As this technology continues to develop, the ability of interfacial solar evaporators to tolerate high salt concentrations and achieve stable evaporation has gradually improved. Some evaporators can even achieve complete separation of water and solutes, resulting in zero liquid discharge. Here, we discuss strategies for interfacial solar evaporators for treating high-salinity wastewater and achieving zero liquid discharge. We particularly focus on representative management strategies, including timely removal of salt crystals and prevention of salt deposition on photothermal materials. Additionally, we present three design ideas for evaporators, including the fundamental principles behind these strategies. Current challenges and future research opportunities are proposed.

Abstract Nowadays, sparse arrays have been a focus for direction‐of‐arrival (DOA). The existing arrays can achieve high degree of freedom (DOF) bigger than the number of sensors when using the spatial smoothing methods. However, the small inter‐element spacing degrades the DOA estimation accuracy when facing severe mutual coupling. In order to alleviate mutual coupling, a coprime linear array using three uniform linear arrays (CLA‐U3) is proposed. The expression of sensor locations is given, and the analysis of DOF is considered. The minimum subarray inter‐element spacing in CLA‐U3 is bigger than that of the existing arrays, which means that CLA‐U3 can be less sensitive to mutual coupling. Moreover, the difference co‐subarrays can fill each other's holes, so CLA‐U3 and other sparse arrays composed of three subarrays have close DOF. Simulation experiments prove the favourable performance of DOA estimation.

Abstract Background Cesarean section-induced postpartum hemorrhage (PPH) potentially causes anemia and hypovolemic shock in pregnant women. Hence, it is helpful for obstetricians and anesthesiologists to prepare pre-emptive prevention when predicting PPH occurrence in advance. However, current works on PPH prediction focus on whether PPH occurs rather than assessing PPH amount. To this end, this work studies quantitative PPH prediction with machine learning (ML). Methods The study cohort in this paper was selected from individuals with PPH who were hospitalized at Shijiazhuang Obstetrics and Gynecology Hospital from 2020 to 2022. In this study cohort, we built a dataset with 6,144 subjects covering clinical parameters, anesthesia operation records, laboratory examination results, and other information in the electronic medical record system. Based on our built dataset, we exploit six different ML models, including logistic regression, linear regression, gradient boosting, XGBoost, multilayer perceptron, and random forest, to automatically predict the amount of bleeding during cesarean section. Eighty percent of the dataset was used as model training, and 20 $$\%$$ % was used for verification. Those ML models are constantly verified and improved by root mean squared error(RMSE) and mean absolute error(MAE). Moreover, we also leverage the importance of permutation and partial dependence plot (PDP) to discuss their feasibility. Result The experiment results show that random forest obtains the highest accuracy for PPH amount prediction compared to other ML methods. Random forest reaches the mean absolute error of 21.7, less than 5.4 $$\%$$ % prediction error. It also gains the root mean squared error of 33.75, less than 9.3 $$\%$$ % prediction error. On the other hand, the experimental results also disclose indicators that contributed most to PPH prediction, including Ca, hemoglobin, white blood cells, platelets, Na, and K. Conclusion It effectively predicts the amount of PPH during a cesarean section by ML methods, especially random forest. With the above insight, ML predicting PPH amounts provides early warning for clinicians, thus reducing complications and improving cesarean sections’ safety. Furthermore, the importance of ML and permutation, complemented by incorporating PDP, promises to provide clinicians with a transparent indication of individual risk prediction.

Abstract Objectives To investigate whether reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with deep learning reconstruction (DLR) can improve the accuracy of evaluating muscle invasion using VI-RADS. Methods Eighty-six bladder cancer participants who were evaluated by conventional full field-of-view (fFOV) DWI, standard rFOV (rFOVSTA) DWI, and fast rFOV with DLR (rFOVDLR) DWI were included in this prospective study. Tumors were categorized according to the vesical imaging reporting and data system (VI-RADS). Qualitative image quality scoring, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC value were evaluated. Friedman test with post hoc test revealed the difference across the three DWIs. Receiver operating characteristic analysis was performed to calculate the areas under the curve (AUCs). Results The AUC of the rFOVSTA DWI and rFOVDLR DWI were higher than that of fFOV DWI. rFOVDLR DWI reduced the acquisition time from 5:02 min to 3:25 min, and showed higher scores in overall image quality with higher CNR and SNR, compared to rFOVSTA DWI (p 0.05). Conclusions rFOV DWI with DLR can improve the diagnostic accuracy of fFOV DWI for evaluating muscle invasion. Applying DLR to rFOV DWI reduced the acquisition time and improved overall image quality while maintaining ADC value and diagnostic accuracy. Critical relevance statement The diagnostic performance and image quality of full field-of-view DWI, reduced field-of-view (rFOV) DWI with and without DLR were compared. DLR would benefit the wide clinical application of rFOV DWI by reducing the acquisition time and improving the image quality. Key Points Deep learning reconstruction (DLR) can reduce scan time and improve image quality. Reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with DLR showed better diagnostic performances than full field-of-view DWI. There was no difference of diagnostic accuracy between rFOV DWI with DLR and standard rFOV DWI. Graphical Abstract

Abstract Complicated associations between multiplexed environmental factors and aging are poorly understood. We manipulated aging using multidimensional metrics such as phenotypic age, brain age, and brain volumes in the UK Biobank. Weighted quantile sum regression was used to examine the relative individual contributions of multiplexed environmental factors to aging, and self-organizing maps (SOMs) were used to examine joint effects. Air pollution presented a relatively large contribution in most cases. We also found fair heterogeneities in which the same environmental factor contributed inconsistently to different aging metrics. Particulate matter contributed the most to variance in aging, while noise and green space showed considerable contribution to brain volumes. SOM identified five subpopulations with distinct environmental exposure patterns and the air pollution subpopulation had the worst aging status. This study reveals the heterogeneous associations of multiplexed environmental factors with multidimensional aging metrics and serves as a proof of concept when analyzing multifactors and multiple outcomes.