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Abstract Early prediction of acute kidney injury (AKI) may provide a crucial opportunity for AKI prevention. To date, no prediction model targeting AKI among general hospitalized patients in developing countries has been published. Here we show a simple, real-time, interpretable AKI prediction model for general hospitalized patients developed from a large tertiary hospital in China, which has been validated across five independent, geographically distinct, different tiered hospitals. The model containing 20 readily available variables demonstrates consistent, high levels of predictive discrimination in validation cohort, with AUCs for serum creatinine-based AKI and severe AKI within 48 h ranging from 0.74–0.85 and 0.83–0.90 for transported models and from 0.81–0.90 and 0.88–0.95 for refitted models, respectively. With optimal probability cutoffs, the refitted model could predict AKI at a median of 72 (24–198) hours in advance in internal validation, and 54–90 h in advance in external validation. Broad application of the model in the future may provide an effective, convenient and cost-effective approach for AKI prevention.

Abstract Latexin (LXN) is abundant in macrophages and plays critical roles in inflammation. Much is known about macrophages in atherosclerosis, the role of macrophage LXN in atherosclerosis has remained elusive. Here, the expression of LXN in human and mouse atherosclerotic lesions was examined by immunofluorescence and immunohistochemistry. LXN knockout and LXN/ApoE double-knockout mice were generated to evaluate the functions of LXN in atherosclerosis. Bone marrow transplantation (BMT) experimentation was carried out to determine whether macrophage LXN regulates atherosclerosis. We found that LXN is enriched in human and murine atherosclerotic lesions, mainly localized to macrophages. LXN deletion ameliorated atherosclerosis in ApoE -/- mice. BMT demonstrate that deletion of LXN in bone marrow protects ApoE -/- mice against atherosclerosis. Mechanistically, we found that LXN targets and inhibits JAK1 in macrophages. LXN deficiency stimulates the JAK1/STAT3/ABC transporter pathway, thereby enhancing the anti-inflammatory and anti-oxidant phenotype, cholesterol efflux, subsequently minimizing foam cell formation and atherosclerosis. Gene therapy by treatment of atherosclerotic mice with adeno-associated virus harbouring LXN-depleting shRNA attenuated the disease phenotype. In summary, our study provides new clues for the role of LXN in the pathological regulation of atherosclerosis, and determines that LXN is a target for preventing atherosclerosis, which may be a potential new anti-atherosclerosis therapeutic target.

Abstract Background The purpose of this network meta-analysis was to assess the impact of different protective ventilatory strategies on postoperative pulmonary complications (PPCs). Methods Several databases were searched for randomized controlled trials (RCTs) that were published before October 2023 in a network meta-analysis. We assessed the effect of different lung-protective ventilation strategies on the incidence of PPCs using Bayesian network meta-analysis. Results We included 58 studies (11610 patients) in this meta-analysis. The network meta-analysis showed that low tidal volumes (LTVs) combined with iPEEP and recruitment manoeuvres (RM) was associated with significantly lower incidence of PPCs [HTVs: OR = 0.38, 95%CrI (0.19, 0.75), LTVs: OR = 0.33, 95%CrI (0.12, 0.82)], postoperative atelectasis[HTVs: OR = 0.2, 95%CrI (0.08, 0.48), LTVs: OR = 0.47, 95%CrI (0.11, 0.93)], and pneumonia[HTVs: OR = 0.22, 95%CrI (0.09, 0.48), LTVs: OR = 0.27, 95%CrI (0.08,0.89)] than was High tidal volumes (HTVs) or LTVs. LTVs combined with medium-to-high PEEP and RM were associated with significantly lower incidence of postoperative atelectasis, and pneumonia. Conclusion LTVs combined with iPEEP and RM decreased the incidence of PPCs, postoperative atelectasis, and pneumonia in noncardiac surgery patients. Individual PEEP-guided ventilation was the optimal lung protection ventilation strategy. The quality of evidence is moderate. Trial registration PROSPERO identifier CRD42023399485.

Abstract Antibacterial lysozyme hydrogels show attractive advantages in wound dressings due to their intrinsic antibacterial activity and excellent biochemical and mechanical properties. Unfortunately, the development of such hydrogels is still greatly limited due to the lack of universal gelation strategies. Herein, a universal gelation strategy between lysozyme‐nanofiber (LZF) and inorganic salts is proposed for the first time to construct functional nanofibrous lysozyme‐based hydrogels. In particular, divalent anions are found to universally drive LZF for the aggregation and transformation into three‐dimensional nanofibrous network hydrogels via electrostatic interaction, and the key role of divalent anions in the gelation is further proved by molecular dynamics simulation. In addition, near‐infrared light‐mediated photothermal characteristics are endowed with LZF to enhance its inhibitory activity of multidrug‐resistant bacteria by the skeleton modification with genipin to produce genipin‐conjuagted LZF (GLZF). As a distinct application paradigm, the brilliant immunomemory MnSO4‐crosslinked GLZF hydrogel is constructed to sensitize the cGAS‐STING pathway and skillfully establish an antibacterial immune microenvironment. It can excellently realize the anti‐recurrence of diabetic wound infection via photo‐enhanced bacterial killing and the cGAS‐STING pathway. Thereby, it paves the way to employ the universal divalent anion‐mediated gelation strategy for the future development of functional inorganic salt hybrid lysozyme hydrogels.

Combined lung and liver transplantation (CLLT) is a rare intervention for end-stage lung and liver diseases. It poses a challenge for patients with increased bleeding risk due to Hemophilia A and liver coagulopathy. We present the first documented case of CLLT in an elderly male with Hemophilia A, HCV-associated cirrhosis, and Idiopathic Pulmonary Fibrosis (IPF). Despite the patient exhibiting stable liver function and hemophilia, his lung condition rapidly deteriorated, prompting the listing for transplant. The patient underwent a successful CLLT with perioperative management coordinated by the multidisciplinary team to address the unique challenges of Hemophilia A, resulting in intra-operative correction of coagulopathy. The patient exhibited a favorable recovery, with no requirement for Factor FVIII replacement therapy postoperatively. This case demonstrates that CLLT can address three diseases with distinct pathophysiologies: end-stage lung and liver disease, and correct the hemophilia A phenotype. Our report contributes to the limited literature on the suitability of CLLT in patients with hemophilia A.

Stem cell factor receptor (C-KIT) or platelet-derived growth factor receptor α (PDGFRα) gene mutations have been identified as oncogenic drivers for most gastrointestinal stromal tumors (GISTs). Thus, small-molecule inhibitors of C-KIT or PDGFRα have emerged as effective treatments for GISTs. Although the currently approved first- to fourth-line drugs are initially effective against GISTs, the inevitable development of drug resistance remains an unmet challenge. To address secondary mutations leading to drug resistance, several novel selective C-KIT/PDGFRα small-molecule inhibitors have been developed and clinically studied. This review summarizes the pathogenesis, treatment, and drug resistance mechanisms of GISTs and briefly describes current challenges and future efforts for GIST treatment using small-molecule kinase inhibitors.

Abstract Background Multidrug-resistant organisms (MDRO) pose a significant threat to public health. Intensive Care Units (ICU), characterized by the extensive use of antimicrobial agents and a high prevalence of bacterial resistance, are hotspots for MDRO proliferation. Timely identification of patients at high risk for MDRO can aid in curbing transmission, enhancing patient outcomes, and maintaining the cleanliness of the ICU environment. This study focused on developing a machine learning (ML) model to identify patients at risk of MDRO during the initial phase of their ICU stay. Methods Utilizing patient data from the First Medical Center of the People’s Liberation Army General Hospital (PLAGH-ICU) and the Medical Information Mart for Intensive Care (MIMIC-IV), the study analyzed variables within 24 h of ICU admission. Machine learning algorithms were applied to these datasets, emphasizing the early detection of MDRO colonization or infection. Model efficacy was evaluated by the area under the receiver operating characteristics curve (AUROC), alongside internal and external validation sets. Results The study evaluated 3,536 patients in PLAGH-ICU and 34,923 in MIMIC-IV, revealing MDRO prevalence of 11.96% and 8.81%, respectively. Significant differences in ICU and hospital stays, along with mortality rates, were observed between MDRO positive and negative patients. In the temporal validation, the PLAGH-ICU model achieved an AUROC of 0.786 [0.748, 0.825], while the MIMIC-IV model reached 0.744 [0.723, 0.766]. External validation demonstrated reduced model performance across different datasets. Key predictors included biochemical markers and the duration of pre-ICU hospital stay. Conclusions The ML models developed in this study demonstrated their capability in early identification of MDRO risks in ICU patients. Continuous refinement and validation in varied clinical contexts remain essential for future applications.

Abstract Background To compare the application of conventional MRI analysis and MRI-based radiomics to identify the circumferential resection margin (CRM) status of rectal cancer (RC). Methods A cohort of 301 RC patients with 66 CRM invloved status and 235 CRM non-involved status were enrolled in this retrospective study between September 2017 and August 2022. Conventional MRI characteristics included gender, age, diameter, distance to anus, MRI-based T/N phase, CEA, and CA 19 − 9, then the relevant logistic model (Logistic-cMRI) was built. MRI-based radiomics of rectal cancer and mesorectal fascia were calculated after volume of interest segmentation, and the logistic model of rectal cancer radiomics (Logistic-rcRadio) and mesorectal fascia radiomics (Logistic-mfRadio) were constructed. And the combined nomogram (nomo-cMRI/rcRadio/mfRadio) containing conventional MRI characteristics, radiomics of rectal cancer and mesorectal fascia was developed. The receiver operator characteristic curve (ROC) was delineated and the area under curve (AUC) was calculated the efficiency of models. Results The AUC of Logistic-cMRI was 0.864 (95%CI, 0.820 to 0.901). The AUC of Logistic-rcRadio was 0.883 (95%CI, 0.832 to 0.928) in the training set and 0.725 (95%CI, 0.616 to 0.826) in the testing set. The AUCs of Logistic-mfRadio was 0.891 (95%CI, 0.838 to 0.936) in the training set and 0.820 (95%CI, 0.725 to 0.905) in the testing set. The AUCs of nomo-cMRI/rcRadio/mfRadio were the highest in both the training set of 0.942 (95%CI, 0.901 to 0.969) and the testing set of 0.909 (95%CI, 0.830 to 0.959). Conclusion MRI-based radiomics of rectal cancer and mesorectal fascia showed similar efficacy in predicting the CRM status of RC. The combined nomogram performed better in assessment.

Abstract Atopic dermatitis (AD) is a chronic inflammatory skin disease affecting approximately 20% of children globally. While studies have been conducted elsewhere, air pollution and weather variability is not well studied in the tropics. This time-series study examines the association between air pollution and meteorological factors with the incidence of outpatient visits for AD obtained from the National Skin Centre (NSC) in Singapore. The total number of 1,440,844 consultation visits from the NSC from 2009 to 2019 was analysed. Using the distributed lag non-linear model and assuming a negative binomial distribution, the short-term temporal association between outpatient visits for AD and air quality and meteorological variability on a weekly time-scale were examined, while adjusting for long-term trends, seasonality and autocorrelation. The analysis was also stratified by gender and age to assess potential effect modification. The risk of AD consultation visits was 14% lower (RR10th percentile: 0.86, 95% CI 0.78–0.96) at the 10th percentile (11.9 µg/m3) of PM2.5 and 10% higher (RR90th percentile: 1.10, 95% CI 1.01–1.19) at the 90th percentile (24.4 µg/m3) compared to the median value (16.1 µg/m3). Similar results were observed for PM10 with lower risk at the 10th percentile and higher risk at the 90th percentile (RR10th percentile: 0.86, 95% CI 0.78–0.95, RR90th percentile: 1.10, 95% CI 1.01–1.19). For rainfall for values above the median, the risk of consultation visits was higher up to 7.4 mm in the PM2.5 model (RR74th percentile: 1.07, 95% CI 1.00–1.14) and up to 9 mm in the PM10 model (RR80th percentile: 1.12, 95% CI 1.00–1.25). This study found a close association between outpatient visits for AD with ambient particulate matter concentrations and rainfall. Seasonal variations in particulate matter and rainfall may be used to alert healthcare providers on the anticipated rise in AD cases and to time preventive measures to reduce the associated health burden.

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

Previous studies have delved into slope break zones in faulted basins, yet foreland basins, with their gentle slopes toward the forebulge, underdeveloped large-scale structures, and small terrain undulations, have received limited research on slope-fault belts. During the deposition periods of the 4th and 5th members of the Late Triassic Xujiahe Formation, a foreland basin developed in the Sichuan Basin. Scholars have noted the control exerted by the gentle slope break zone on the sedimentary lithofacies in the central and western Sichuan, particularly in the west of the Luzhou-Kaijiang Paleo-uplift, but related studies remain limited. By interpreting the tectonic slope break zones in seismic reflection profiles of the Sichuan Basin and incorporating existing regional geological data, this study employed particle flow numerical simulation to clarify the types of slope break zones in the central and western Sichuan regions, as well as their relationship with gravity sliding structures. It also analyzed the characte-ristics of new types of oil and gas traps associated with gravity-sliding structures. The findings are as follows: (1) The study area developed a fault slope break zone, with each side bounded by a "front squeezing and rear extension" tectonic combinations formed by gravity sliding. The tectonic deformation is weaker than those of gravity-sliding structures at passive continental margins. (2) The edge fault of the tectonic slope break zone controls the sedimentary facies and sand body types. (3) In the gentle slope zone, the stretching area of gravity-sliding structures lead to the uplift of the footwalls of normal faults, forming syndepositional anticlines with developed sandstones. These sandstones, juxtaposed with organic-rich mudstones within the contemporaneous fault depression, form "side-generated and lateral storage" hydrocarbon reservoirs. (4) In the steep slope zone, gravity sliding forms syndepositional anticlines in the 5th member of the Xujiahe Formation, which are bounded by flank mudstones and post-sliding deposited mudstones, forming in-source sand body reservoirs. (5) Syndepositional anticline hydrocarbon reservoirs related to gravity-sliding structures represent a new type of in-source hydrocarbon accumulation. The 5th member of the Xujiahe Formation in the study area likely contains such reservoirs, distributed in a NE-trending pattern parallel to the slope break zone.

Rationale & Objectives: Diabetic kidney disease (DKD) is a significant complication of diabetes mellitus, often leading to kidney failure. The absence of well-defined factors prevents distinguishing DKD from non-diabetic kidney disease (non-DKD; alternative primary diagnosis identified on kidney biopsy). Study Design: Retrospective cohort study. Setting & Participants: This study assessed 1,242 patients with a history of diabetes from the Cleveland Clinic Kidney Biopsy Epidemiology Project between January 2015 and September 2021. Exposure: Proteinuria, retinopathy, A1c levels, and estimated glomerular filtration rate. Outcomes: Non-DKD, defined as an alternative primary diagnosis identified on kidney biopsy other than DKD. Analytical Approach: Multivariate logistic regression model with backward elimination method. Results: At the time of biopsy, the median (IQR) age was 63 (53-71 years) years, and 58.8% were men. The median hemoglobin A1c value was 6.7% (6.0%-8.1%), and the median serum creatinine level was 2.5 (1.6-3.9 mg/dL) mg/dL. Among 1,242 patients, 462 (37.2%) had DKD alone, and 780 (62.8%) had non-DKD. Among those with non-DKD, the most common diagnoses were focal segmental glomerulosclerosis (24%), global glomerulosclerosis otherwise not specified (13%), acute tubular necrosis (9%), IgA nephropathy (8%), antineutrophil cytoplasmic antibody vasculitis (7%), and membranous nephropathy (5%). Factors associated with having non-DKD on biopsy were having no retinopathy (vs retinopathy) (adjusted odds ratio [aOR], 3.98; 95% CI, 2.69-5.90), lower A1c levels (

Abstract Low‐level Jets (LLJs) play a critical role in triggering nocturnal rainfall in many areas on our planet. Nevertheless, little is known regarding the vertically resolved evolution of LLJs preceding rainfall. Here, the high‐resolution wind measurements from a radar wind profiler network in Beijing are used to monitor the continuous evolution of boundary‐layer jets (BLJs) and synoptic‐system‐related LLJs (SLLJs) before nocturnal rainfall under the southwesterlies synoptic pattern for the summers of 2020–2023. The results show that inertial oscillations precede LLJ‐induced nocturnal rainfall. The typical northward propagation of LLJ is driven primarily by horizontal advection. Starting 48 min before rainfall, the BLJ nose rapidly strengthens and moves downward from 0.8 km above ground level (AGL), while the SLLJ nose moves upward to 2.4 km AGL. This leads to enhanced moisture transport and convergence, which triggers nocturnal rainfall. The findings are of great significance for improving the forecast skill of nocturnal rainfall.

In the reform of medical laboratory courses, innovative teaching methods and the development of a teaching assessment system are crucial. However, in past practices, assessments have encountered some issues: a greater emphasis on recording outcomes, neglecting supervision of the process; a focus on summarizing writing, overlooking the importance of analysis and improvement. In the teaching process of Jilin University’s Oncological Rehabilitation Experimental Teaching Demonstration Center, the Peer-Assisted Learning (PAL) model is employed to enhance students’ learning approaches. The innovative incorporation of Direct Observation of Procedural Skills (DOPS) and Mini-Clinical Evaluation Exercise (Mini-CEX) facilitates effective assessment and feedback. The combination of these reform measures not only addresses issues in experimental teaching but also enhances the internalization of students’ knowledge and skills. In this study, we applied the evaluation systems of Direct Observation of Procedural Skills and Mini-Clinical Evaluation Exercise (Mini-CEX) to the comprehensive laboratory course in oncological rehabilitation. We utilized questionnaires to assess the impact of these reforms on students, aiming to evaluate the effectiveness of the course modifications. Statistical analysis of the data revealed a high level of student approval and a strong willingness to learn under the new evaluation system. Compared to traditional teaching methods, the introduction of DOPS and Mini-CEX significantly enhanced students’ overall competencies and improved the quality of the oncological rehabilitation course. Our approach represents an innovative reform, suggesting that incorporating DOPS and Mini-CEX into teaching could provide a widely applicable and promising new educational method. This paper explores and systematically elaborates on the reform and practice of the teaching model and formative assessment in the comprehensive laboratory course of oncological rehabilitation.

Atherosclerosis is a chronic inflammatory vascular disease characterized by lipid metabolism disorder and lipid accumulation. Equisetin (EQST) is a hemiterpene compound isolated from fungus of marine sponge origin, which has antibacterial, anti-inflammatory, lipid-lowering, and weight loss effects. Whether EQST has anti-atherosclerotic activity has not been reported. In this study, we revealed that EQST displayed anti- atherosclerosis effects through inhibiting macrophage inflammatory response, lipid uptake and foam cell formation in vitro, and finally ameliorated high-fat diet (HFD)-induced atherosclerosis in AopE-/- mice in vivo. Mechanistically, EQST directly bound to STAT3 with high-affinity by forming hydrophobic bonds at GLN247 and GLN326 residues, as well as hydrogen bonds at ARG325 and THR346 residues. EQST interacted with STAT3 physically, and functionally inhibited the transcription activity of STAT3, thereby regulating atherosclerosis. Therefore, these results supports EQST as a candidate for developing anti-atherosclerosis therapeutic agent.

Abstract Soft-tissue sarcomas (STS) emerges as formidable challenges in clinics due to the complex genetic heterogeneity, high rates of local recurrence and metastasis. Exploring specific targets and biomarkers would benefit the prognosis and treatment of STS. Here, we identified RCC1, a guanine-nucleotide exchange factor for Ran, as an oncogene and a potential intervention target in STS. Bioinformatics analysis indicated that RCC1 is highly expressed and correlated with poor prognosis in STS. Functional studies showed that RCC1 knockdown significantly inhibited the cell cycle transition, proliferation and migration of STS cells in vitro, and the growth of STS xenografts in mice. Mechanistically, we identified Skp2 as a downstream target of RCC1 in STS. Loss of RCC1 substantially diminished Skp2 abundance by compromising its protein stability, resulting in the upregulation of p27Kip1 and G1/S transition arrest. Specifically, RCC1 might facilitate the nucleo-cytoplasmic trafficking of Skp2 via direct interaction. As a result, the cytoplasmic retention of Skp2 would further protect it from ubiquitination and degradation. Notably, recovery of Skp2 expression largely reversed the phenotypes induced by RCC1 knockdown in STS cells. Collectively, this study unveils a novel RCC1-Skp2-p27Kip1 axis in STS oncogenesis, which holds promise for improving prognosis and treatment of this formidable malignancy.

Abstract Background Integrating multi-omics data is emerging as a critical approach in enhancing our understanding of complex diseases. Innovative computational methods capable of managing high-dimensional and heterogeneous datasets are required to unlock the full potential of such rich and diverse data. Methods We propose a Multi-Omics integration framework with auxiliary Classifiers-enhanced AuToencoders (MOCAT) to utilize intra- and inter-omics information comprehensively. Additionally, attention mechanisms with confidence learning are incorporated for enhanced feature representation and trustworthy prediction. Results Extensive experiments were conducted on four benchmark datasets to evaluate the effectiveness of our proposed model, including BRCA, ROSMAP, LGG, and KIPAN. Our model significantly improved most evaluation measurements and consistently surpassed the state-of-the-art methods. Ablation studies showed that the auxiliary classifiers significantly boosted classification accuracy in the ROSMAP and LGG datasets. Moreover, the attention mechanisms and confidence evaluation block contributed to improvements in the predictive accuracy and generalizability of our model. Conclusions The proposed framework exhibits superior performance in disease classification and biomarker discovery, establishing itself as a robust and versatile tool for analyzing multi-layer biological data. This study highlights the significance of elaborated designed deep learning methodologies in dissecting complex disease phenotypes and improving the accuracy of disease predictions.

Abstract Excessive uric acid (UA) is associated with age-related cataract. A previous study showed that a high UA level in the aqueous humor stimulated the senescence of lens epithelial cells (LECs), leading to cataract progression. To better understand the underlying mechanisms, we investigated UA-driven senescence in human lens tissue samples obtained during surgery, rat lens organ cultures, and in vivo experiments, using senescence-associated β-galactosidase (SA-β-gal) staining, electronic microscopy, Western blotting, and histological analyses. Initially, we identified markedly higher expressions of NLRP3 and caspase-1 in the lens capsules of hyper-uricemic patients compared to normo-uricemic patients. This increase was accompanied by a significant rise in the SA-β-gal positive rate. We next built a cataract model in which rat lenses in an organ culture system were treated with an increasing dosage of UA. Notably, opacification was apparent in the lenses treated with 800 μM of UA starting on the fifth day. Mechanistically, UA treatment not only significantly induced the expression of NLRP3, caspase-1, and IL-1β, but also upregulated the levels of SA-β-gal and the senescence regulators p53 and p21. These effects were fully reversed, and lens opacification was ameliorated by the addition of MCC950, a selective NLRP3 antagonist. Moreover, an in vivo model showed that intravitreal UA injection rapidly induced cataract phenotypes within 21 days, an effect significantly mitigated by co-injection with MCC950. Together, our findings suggest that targeting the UA-induced NLRP3 inflammasome with MCC950 could be a promising strategy for preventing cataract formation associated with inflammageing.

With the rapid development, shared bicycles have gradually become an important part of slow urban traffic in China and have played an important role in satisfying the travel needs and facilitating the transfer of residents. Exploring the spatial and temporal characteristics of the impact of the built environment on shared bike travel is of practical importance to reshape the construction of low-carbon transportation and an urban-friendly cycling environment dominated by slow traffic and public transportation. We analyzed the spatio-temporal characteristics of shared bicycle travel through multi-source big data including Shenzhen's shared bicycle OD data, OSM road network data, Baidu Street View, and POIs and used a multi-scale geographical weighted regression model (MGWR) based on the "5D" index of the built environment to analyze the spatial difference characteristics of the impact of different built environment on shared bicycle flow. The findings of the research indicate that: (1) In terms of time, the shared bicycle flow in the morning and evening peaks of both working and rest days is more significant than that of other periods, and the peak period of the remaining days lags behind that of the working days. (2) In terms of space, the spatial distribution characteristics of the traffic flow of shared bicycles during each peak period exhibit a spatial pattern of "multiple aggregation cores and several extended belts." (3) Significant differences were observed in the impact of various built environmental factors on the flow of shared bicycle travel, among which, employment facility density, enclosure degree and population density had a positive effect in each period; their influences were globally significant; and the remaining factors demonstrated varied characteristics in each period. (4) Factors with significant influence showed different spatial scales in different periods. The spatial changes of employment facility density and enclosure in each period were generally flat; the spatial changes of proximity, density of shopping facilities, and the nearest distance to subway stations in some periods were generally flat; the spatial changes of building continuity and relative walking width were obvious in some periods. Moreover, population density and green vision rate had different spatial characteristics in different periods. This study restores the travel track of shared bicycles, analyzes the spatiotemporal characteristics of shared bicycle travel in multiple periods of working days and rest days and long-term series, and increases micro-built environment factors of subjective perception of people and experience dimension based on existing objective material space environment variables, to explore the spatiotemporal differences of the impact of different built environments on the travel flow of shared bicycles which compensate for the existing shared-bike travel time and space characteristics, build a shortage of environmental impact research, and provide references for the construction of an urban-friendly cycling environment and the creation of a slow walking space.

Microneedles (MNs) is an emerging technology that employs needles ranging from 10 to 1000 μm in height, as a minimally invasive technique for various procedures such as therapeutics, disease monitoring and diagnostics. The commonly used method of fabrication, micromolding, has the advantage of scalability, however, micromolding is unable to achieve rapid customizability in dimensions, geometries and architectures, which are the pivotal factors determining the functionality and efficacy of the MNs. 3D printing offers a promising alternative by enabling MN fabrication with high dimensional accuracy required for precise applications, leading to improved performance. Furthermore, enabled by its customizability and one-step process, there is propitious potential for growth for 3D-printed MNs especially in the field of personalized and on-demand medical devices. This review provides an overview of considerations for the key parameters in designing MNs, an introduction on the various 3D-printing techniques for fabricating this new generation of MNs, as well as highlighting the advancements in biomedical applications facilitated by 3D-printed MNs. Lastly, we offer some insights into the future prospects of 3D-printed MNs, specifically its progress towards translation and entry into market.

Abstract Physics-informed neural networks (PINNs) are employed to solve the classical compressible flow problem in a converging–diverging nozzle. This problem represents a typical example described by the Euler equations, a thorough understanding of which serves as a guide for solving more general compressible flows. Given a geometry of the channel, analytical solutions for the steady states do indeed exist, and they depend on the ratio between the back pressure of the outlet and the stagnation pressure of the inlet. Moreover, in the diverging region, the solution may branch into subsonic flow, supersonic flow, or a mixture of both with a discontinuous transition where a normal shock occurs. Classical numerical schemes with shock fitting and capturing methods have been developed to solve this type of problem effectively, whereas the original PINNs are unable to predict the flows correctly. We make a first attempt to exploit the power of PINNs to solve this problem directly by adjusting the weights of different components of the loss function to acquire physical solutions and in the meantime, avoid trivial solutions. With a universal setting yet no exogenous data, we are able to solve this problem accurately; that is, for different given pressure ratios, PINNs provide different branches of solutions at both steady and unsteady states, some of which are discontinuous in nature. For an inverse problem such as unknown specific-heat ratio, it works effectively as well.

Ribonucleic acid (RNA) therapeutics hold great potential for the advancement of dermatological treatments due to, among other reasons, the possibility of treating previously undruggable targets, high specificity with minimal side effects, and ability to include multiple RNA targets in a single product. Although there have been research relating to RNA therapeutics for decades, there have not been many products translated for clinical use until recently. This may be because of challenges to the application of RNA therapeutics, including the dearth of effective modes of delivery to the target, and rapid degradation of RNA in the human body and environment. This article aims to provide insight on (1) the wide-ranging possibilities of RNA therapeutics in the field of dermatology as well as (2) how key challenges can be addressed, so as to encourage the development of novel dermatological treatments. We also share our experience on how RNA therapeutics have been applied in the management of hypertrophic and keloid scars.

This study seeks to assess the impact of varying concentrations of lysophospholipids on the antioxidant capacity, digestive performance, and intestinal microbiota of L. vannamei. A total of 840 shrimp, with an average initial weight of 2.22 ± 0.11 g, were randomly distributed across 28 aquaculture tanks (30 shrimp per tank), organized into 7 distinct treatment groups, each comprising 4 replicates. The control group (DL2) was administered a basal diet formula supplemented with 2% soy lecithin, whereas the experimental groups received lysophospholipids at varying concentrations of 0% (RL0), 0.1% (RL0.1), 0.5% (RL0.5), 1% (RL1), 1.5% (RL1.5), and 2% (RL2). The results revealed that the total antioxidant capacity (T-AOC) level in the RL0.1 group was significantly elevated compared to the DL2 and RL2 groups (p < 0.05). Furthermore, glutathione peroxidase (GSH-Px) and catalase (CAT) activities were markedly higher in the RL1 and RL1.5 groups relative to other groups (p < 0.05). Superoxide dismutase (SOD) activity exhibited a significant increase across all lysophospholipid-supplemented groups when compared to the DL2 group (p < 0.05). Malondialdehyde (MDA) levels were notably elevated in the RL0.5, RL1.5, and RL2 groups relative to the other groups (p < 0.05). Regarding antioxidant-related genes in the hemocytes, the relative expression levels of Nrf1, Nrf2, GPx, SOD, CAT, and Hippo were significantly higher in the RL0.5 and RL1 groups compared to the DL2 group (p < 0.05). Additionally, the relative expression levels of GPx and SOD were significantly elevated in the RL2 group compared to the DL2 group (p < 0.05). In the intestinal tract, the activities of trypsin and α-amylase (AMS) were significantly elevated in the RL0.1, RL0.5, and RL1 groups compared to the DL2 group (p < 0.05). Additionally, the RL0.1 group demonstrated significantly higher lipase (LPS) activity than the other groups supplemented with lysophospholipids (p < 0.05). Furthermore, the relative expression levels of the trypsin and α-amylase genes were significantly increased in the RL1 and RL1.5 groups in comparison to the DL2 group (p < 0.05). Sequencing analysis of the intestinal microbiota indicated that the incorporation of lysophospholipids resulted in an enhancement of the composition and structure of the intestinal microbiota. The functional abundance of the intestinal microbiome was primarily enriched in metabolic pathways. Overall, the incorporation of lysophospholipids into the diet exerted a beneficial effect on the antioxidant capacity, digestive performance, and intestinal microbiota of L. vannamei, especially with the supplementation of 0.1% lysophospholipids.

The positive relationship between species richness and area is a fundamental principle in ecology. However, this pattern deviates on small islands, where species richness either changes independently of area or increases at a slower rate—a phenomenon known as the Small-Island Effect (SIE). While the SIE has been well documented in natural ecosystem, its presence in highly fragmented and disturbed urban ecosystem remains unexplored, posing challenges for urban vegetation conservation. Urban remnant vegetation, isolated by surrounding infrastructures, preserves intact zonal vegetation characteristics, serves as a benchmark for restoring near-natural habitats and offers ideal conditions to test the existence of the SIE in urban area landscapes. In this study, we surveyed 17 remnant vegetation patches in Qingdao City, China. A total of 331 plants attributed to 255 genera in 81 families have been recorded. Firstly, by using six species–area relationship regression models testing the SIE for remnant vegetation with different plant life forms, we found the SIE in only woody plants, with the land surface area threshold ranging from 6.38 ha (tree) to 11.91 ha (shrub). Our finding revealed that the drivers of the SIE in shrubs were landscape shape index, perimeter–area ratio, and the proportion of sealed surfaces within the patch. For trees, the SIE was influenced by the distance to the source of species, GDP, night light intensity, and perimeter–area ratio. This finding justifies that conservation in urban planning, construction, and development should focus not only on protecting large areas but also on maintaining and promoting diverse habitats within these areas. At the same time, reducing anthropogenic disturbance and enhancing the connectivity of green spaces are important for the persistence of metacommunities and can contribute to the local species pool, thus potentially improving the ecological resilience of urban environments.

Abstract BackgroundAfter strict COVID-19–related restrictions were lifted, health systems globally were overwhelmed. Much has been discussed about how health systems could better prepare for future pandemics; however, primary health care (PHC) has been largely ignored. ObjectiveWe aimed to investigate what combined policies PHC could apply to strengthen the health care system via a bottom-up approach, so as to better respond to a public health emergency. MethodsWe developed a system dynamics model to replicate Shanghai’s response when COVID-19–related restrictions were lifted. We then simulated an alternative PHC-based integrated health system and tested the following three interventions: first contact in PHC with telemedicine services, recommendation to secondary care, and return to PHC for recovery. ResultsThe simulation results showed that each selected intervention could alleviate hospital overwhelm. Increasing the rate of first contact in PHC with telemedicine increased hospital bed availability by 6% to 12% and reduced the cumulative number of deaths by 35%. More precise recommendations had a limited impact on hospital overwhelm (

Summary: Chemical warfare agents (CWAs), epitomized by the notoriously used mustard gas (HD), represent a class of exceptionally toxic chemicals whose airborne removal is paramount for battlefield safety. This study integrates high-throughput computational screening (HTCS) with advanced machine learning (ML) techniques to investigate the efficacy of metal-organic frameworks (MOFs) in adsorbing and capturing trace amounts of HD present in the air. Our approach commenced with a comprehensive univariate analysis, scrutinizing the impact of six distinct descriptors on the adsorption efficiency of MOFs. This analysis elucidated a pronounced correlation between MOF density and the Henry coefficient in the effective capture of HD. Then, four ML algorithms were employed to train and predict the performance of MOFs. The Random Forest (RF) algorithm demonstrates strong model learning and good generalization, achieving the best prediction result of 98.3%. In a novel exploratory stride, we incorporated a 166-bit MACCS molecular fingerprinting (MF) to identify critical functional groups within adsorbents. From the top 100 MOFs analyzed, 22 optimal functional groups were identified. Leveraging these insights, we designed three innovative substructures, grounded in these key functional groups, to enhance HD adsorption efficiency. In this work, the combination of MF and ML could provide a new direction for efficient screening of MOFs for the capture of HD in the air. The outcomes of this study offer substantial potential to revolutionize the domain of CWA capture. This represents a significant stride toward developing practical solutions that enhance both environmental protection and battlefield security.

Abstract Background Whether early dietary fiber intake in septic patients is associated with a better clinical prognosis remains unclear, especially the time and the amount. Therefore, we assessed the association between early dietary fiber intake and clinical outcomes in septic patients by examining an extensive database. Methods We conducted a retrospective cohort study using data from the MIMIC IV 2.1 database, focusing on consecutive septic patients requiring mechanical ventilation in medical or mixed medical-surgical ICUs. We collected patient demographics and nutritional data. Dietary fiber amounts were calculated according to enteral nutrition instructions from manufacturers within the first 72 h after admission. After adjusting for covariates, we employed restricted cubic spline (RCS) regression to investigate the relationship between fiber intake (FI) and 28-day mortality. Patients were categorized into three groups based on their fiber index (FI) within 72 h of admission: low fiber index (LFI) group when FI was

Abstract Background Malnutrition is a prevalent and major challenge among senior citizens, possibly due to the continual low-grade inflammatory state of the body. A novel inflammatory parameter, the systemic immune-inflammation index (SII), is highly valuable in evaluating and predicting the prognosis of a wide range of diseases. This study aims to explore the significance of the SII in assessing malnutrition in older inpatients. Methods This retrospective study included 500 senior hospitalized patients who met the inclusion and exclusion criteria from the Comprehensive Geriatric Assessment database of the First Hospital of Jilin University. The Mini-Nutritional Assessment (MNA) questionnaire was used to evaluate the nutritional status of patients. The SII was calculated using complete blood counts, and we performed natural logarithm transformation of the SII [ln(SII)]. Multivariable logistic regression analysis was used to identify the association between ln(SII) and malnutrition. To ensure the stability of the findings, a sensitivity analysis was conducted. Results The 500 patients had a mean age of 77.29 ± 9.85 years, and 68.6% were male. In accordance with the MNA, 30.4% of the patients were malnourished or at risk of malnutrition, and patients in this group had considerably greater levels of ln(SII) than patients with adequate nutrition (P

【Objective】This study aims to reveal the effects of interplanting soybean under kiwifruit forests on soil microbial community structure, and analyze the changes in soil microbial community structure under kiwifruit plantations with and without soybeans, so as to provide theoretical basis and technical support, for studying the soil microecological improvement and green planting of kiwifruit, as well as the improvement of economic benefits per unit area of land in remote mountainous areas.【Method】The abundance of microbial communities in different soil samples under kiwifruit forests was detected by using high-throughput sequencing. The differences in microbial abundance and structural composition in soil samples under kiwifruit forests and those interplanted with soybeans were analyzed. The impact of interplanting soybeans under kiwifruit forests on the structure and diversity of soil microbial communities were explored. Firstly, the soils planting with soybeans under kiwifruit forest and the soils non-planting with soybeans were collected for pretreatment, DNA extraction and PCR amplification, and then the products were detected, purified and quantified based on Illumina MiSeq high-throughput sequencing method, and database for sequencing was built. The community classification structure, microbial abundance and diversity, and the dominant flora species were determined by data analysis【Result】The quality control and statistical results of Tags abundance and OTU showed that the microbial abundance and diversity in soils planting soybean (EK) were higher than non-planting soybean (CK). The diversity analysis showed the composition of microbial communities exhibited significant differences between EK and CK. The analysis of microbial community structure showed that the average proportions of EK and CK at family, genus, and species levels are 27.06% and 28.11%, 32.66% and 29.33%, 0.46% and 0.37%, respectively, and the soil microbial community of EK was higher than that of CK at genus and species levels. A total of 651 883 valid sequences were obtained from 6 soil samples, and the 4 740 and 4 551 OTUs were obtained by clustering for EK and CK, respectively. The LEfSe analysis showed that there were 19 dominant microbial groups in CK, while 41 dominant microbial groups in EK. Among them, Proteobacteria was the dominant phylum and Ensifer adhaerens, a member of the Rhizobiaceae family, was the dominant bacterium of EK.【Conclusion】The structure of soil microbial community was changed when soybean were interplaned under kiwifruit forests, and the abundance and diversity of soil microbial community, as well as the number of dominant and beneficial microbial communities in soils were increased. In summary, intercropping soybeans under kiwifruit forests has an important effect on improving the soil effective components and increasing soil fertility.

Slow and deep breathing (SDB) is a relaxation technique that can increase vagal activity. Respiratory sinus arrhythmia (RSA) serves as an index of vagal function usually quantified by the high-frequency power of heart rate variability (HRV). However, the low breathing rate during SDB results in deviations when estimating RSA by HRV. Besides, the impact of the inspiration-expiration (I: E) ratio and guidelines ways (fixed breathing rate or intelligent guidance) on SDB is not yet clear. In our study, 30 healthy people (mean age = 26.5 years, 17 females) participated in three SDB modes, including 6 breaths per minute (bpm) with an I:E ratio of 1:1/ 1:2, and intelligent guidance mode (I:E ratio of 1:2 with guiding to gradually lower breathing rate to 6 bpm). Parameters derived from HRV, multimodal coupling analysis (MMCA), Poincaré plot, and detrended fluctuation analysis were introduced to examine the effects of SDB exercises. Besides, multiple machine learning methods were applied to classify breathing patterns (spontaneous breathing vs. SDB) after feature selection by max-relevance and min-redundancy. All vagal-activity markers, especially MMCA-derived RSA, statistically increased during SDB. Among all SDB modes, breathing at 6 bpm with a 1:1 I:E ratio activated the vagal function the most statistically, while the intelligent guidance mode had more indicators that still significantly increased after training, including SDRR and MMCA-derived RSA, etc. About the classification of breathing patterns, the Naive Bayes classifier has the highest accuracy (92.2%) with input features including LFn, CPercent, pNN50, $\alpha 2$ , SDRatio, $\alpha 1$ , and LF. Our study proposed a system that can be applied to medical devices for automatic SDB identification and real-time feedback on the training effect. We demonstrated that breathing at 6 bpm with an I:E ratio of 1:1 performed best during the training phase, while intelligent guidance mode had a more long-lasting effect.

This paper studies the elevation angle-based formation tracking control of multi-agent systems. Unlike bearing-based formation control, which uses bearing vectors, formation control using elevation angles eliminates the need for a global coordinate frame. This is beneficial because the coordinate frames of individual agents are often not aligned. Previous studies on elevation angle-based formation control have predominantly focused on leaderless formations. By incorporating a leader-follower structure, follower agents can effectively track and move with leaders, allowing the formation to move together and maneuver through obstacles. We consider three types of agents: single-integrator, double-integrator, and nonholonomic robots. For agents with a single integrator model, we first propose a control law for stationary leaders case and then modify the proposed control law to address moving leaders. Finite-time convergence to the desired formation is guaranteed. We then consider agents with double-integrator dynamics and nonholonomic robots, showing asymptotic convergence to the desired formation. Simulation results are provided to validate the proposed control laws.

Consensus has been widely used in distributed control, where distributed individuals need to share their states with their neighbors through communication links to achieve a common goal. However, the objectives of existing consensus-based control strategies for energy systems seldom address battery degradation cost, which is an important performance indicator to assess the performance and sustainability of battery energy storage (BES) systems. In this paper, we propose a consensus-based optimal control strategy for multi-microgrid systems, aiming at multiple control objectives including minimizing battery degradation cost. Distributed consensus is used to synchronize the ratio of BES output power to BES state-of-charge (SoC) among all microgrids while each microgrid is trying to reach its individual optimality. In order to reduce the pressure of commu-nication links and prevent excessive exposure of local information, this ratio is the only state variable shared between microgrids. Since our complex nonlinear problem might be difficult to solve by traditional methods, we design a compressive sensing-based gradient descent (CSGD) method to solve the control problem. Numerical simulation results show that our control strategy results in a 74.24 % reduction in battery degradation cost on average compared to the control method without considering battery degradation. In addition, the compressive sensing method causes an 89.12 % reduction in computation time cost compared to the traditional Monte Carlo (MC) method in solving the control problem.

ObjectiveTo evaluate long-term impact of periconceptional folic acid supplementation on the intelligence quotient (IQ) of offspring, as well as potential modification effects of nuts consumption during pregnancy and breastfeeding duration on the association of maternal folic acid supplementation with offspring′s IQ.MethodsThe information on maternal folic acid supplementation and frequency of nuts consumption was collected through a structured questionnaire interview conducted at 12 – 16 gestational weeks among pregnant women being enrolled in the Shanghai-Minhang Birth Cohort Study (S-MBCS) during April – December, 2012. Information on duration of exclusive breastfeeding of the mothers was collected during postnatal follow-up visits. The mothers′ children were followed up and the children′s intellectual development at the age of 6 years was evaluated with Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV)-simplified Chinese Version at follow-ups by well-trained interviewers. Eventually, 530 mother-child pairs with complete information were included in this study. Multiple linear regression model was used to analyze the correlation between periconceptional folic acid supplementation and the children′s IQ at age of 6 years and to explore potential modification effects of frequency of maternal nuts consumption during pregnancy or duration of exclusive breastfeeding on the correlation. ResultsMultiple analysis showed that the children with maternal folic acid supplements regularly during periconceptional period had better IQ performance, with significantly increased scores of perceptual reasoning index (PRI) of 4.57 (95% confidence interval [95%CI]: 0.13 – 9.02) compared to the children without the maternal supplementation; such effect of maternal folic acid supplementation beginning before the pregnancy was similar to that of supplementation beginning after the pregnancy, with the increased PRI scores of 4.41 (95%CI : – 0.25 – 9.07) and 4.71 (95%CI: 0.11 – 9.31), respectively. In addition, the effect of maternal folic acid supplementation on the children′s PRI was stronger when combined by maternal nuts consumption of ≤ 2 days/week during pregnancy (increased PRI = 5.80, 95%CI: 0.52 – 11.08) or by exclusive breastfeeding of their children less than 6 months (increased PRI = 6.36, 95%CI: 0.89 – 11.83). ConclusionMaternal periconceptional folic acid supplementation is associated with the improvement of offspring’s PRI at 6 years, indicating a protective effect of the supplementation on long-term intelligence development of the children. The beneficial effect was more profound when the supplementation being combined by nuts consumption two days/ per week and less during pregnancy or by exclusive breastfeeding of their children less than 6 months.

In order to improve the detection accuracy of ship wake, this paper proposed a ship wake detection method based on a one-dimensional convolutional neural network (1DCNN). Firstly, the simulation data set was constructed by using the ship wake scattering echo model. Then the reliability of the scattering echo model was verified by the water tank simulation experiment, and the experimental data set was constructed. Finally, a 1DCNN was built by comprehensively considering the detection accuracy and parameter quantity of different structural models and compared with the traditional detection algorithm (based on a one-class support vector machine and back propagation neural network) on the data set. The simulation results show that compared with the traditional detection algorithm, the 1DCNN proposed in this paper improves the detection accuracy and detection efficiency of ship wake under different signal-to-noise ratios and has good engineering application value.

Abstract Background A comprehensive understanding of subgroups of community-dwelling older adults and their long-term care (LTC) utilization can help to promote equality in the long-term services and support system. Dependency and household characteristics were found to affect the LTC utilization of homebound older adults. However, few studies considered the typologies of dependency of older populations according to co-occurring limitations, and little is known about differences in LTC use among elderly of typologies of dependency under distinct household conditions. Methods We aimed to identify typologies of dependency of older adults living at home and explore the disparities in formal care and informal care use among typologies of dependency by income and living situation. In this cross-sectional study, we used the public long-term care insurance (LTCI) database of Yiwu, Zhejiang Province, China, and included 1675 individuals aged ≥ 60 years living at home. Cluster analysis was conducted to determine typologies of dependency among older adults. A two-step multilevel analysis was used to examine disparities in formal and informal care use related to household income and living status among typologies of dependency. Results Seven dependency clusters were identified. Pro-wealthy inequalities in both formal and informal care use were found in the least dependent cluster and the limited-locomotion cluster. Pro-poor inequalities in formal care use were found in the fully dependent cluster without impaired vision and the cluster with intact continence and vision. Living with family members was positively associated with receiving formal care for the fully dependent cluster. Older adults in most clusters were more likely to use informal care when living with family members, except for the least dependent cluster and the limited-locomotion cluster. Conclusions Our findings suggest that household inequalities in LTC use varied among typologies of dependency of older adults, which may provide insights for researchers and policymakers to develop tailored LTC and targeted LTCI programs for older adults living at home and their family caregivers, considering both typologies of dependency and household characteristics.

The transition to electric vehicles (EVs) has introduced new challenges in lubrication, demanding innovative solutions to ensure consistent performance. One promising approach is the use of nanoparticle additives, which have the potential to improve lubrication performance significantly. However, achieving a stable suspension of these nanoparticles in lubricating oils remains a critical challenge, as suspension stability is essential for maintaining consistent performance and maximizing the benefits of these advanced additives. In this study, carbon nanoparticles (CNPs) were modified with dodecylamine (DDA) to achieve stable suspension in nonpolar fluids. The successful functionalization was confirmed by the FTIR results, which showed characteristic peaks of various bonding. The suspension stability tests demonstrated that DDA-CNPs remained suspended for over 60 days in the Polyalphaolefin (PAO) oil, whereas unmodified CNPs were sedimented within 3–7 days. The rheological behavior was measured under different shear rates and temperatures. Viscosity measurements indicated that DDA-CNPs maintained a lower value compared to base PAO. The lubricants’ friction coefficient (COF) was also determined under various speeds and loads. The addition of DDA-CNPs at a concentration of 0.05 wt.% resulted in a significant reduction in COF, with values decreasing by 26% compared to base PAO oil under a load of 1 N. Additionally, the COF for DDA-CNPs was consistently lower than that of PAO, with reductions ranging from 15% to 18% across all tested speeds. The Stribeck curve further highlighted the improved performance of DDA-CNPs across boundary, mixed, and hydrodynamic lubrication regimes. These findings suggest that DDA-CNPs significantly improve the lubrication performance of PAO oil, making them suitable for advanced lubrication applications in automotive and industrial systems.

It is an important way to study the ship wake by building simulation data through the acoustic wake echo signal model. At present, the scattering echo of a single bubble is ignored in the existing models. Therefore, a point scattering model for different regions was proposed in this paper. Firstly, the wake geometry model was determined according to the ship size, speed, and sea condition, and then the wake was divided into different scattering regions according to the bubble size distribution(BSD). The range of the wake homing system was determined according to the beam width, position, and launch angle of the transmitting and receiving platform. Finally, the range of the wake homing system was divided into finite scattering elements, and the scattering echo signal was calculated according to the point scattering model after considering the propagation loss. The results of simulation and water tank experiments show that the model can be used in ship wake simulation and provide support for further wake detection and identification.

The evaluation of geological suitability for urban underground space (UUS) development is an indispensable prerequisite for its optimal utilization. As the actual carrier of underground facilities, the evaluation of rock mass quality plays a crucial role in assessing geological suitability. However, it is notable that the evaluation of rock mass quality has regrettably remained somewhat marginalized within the broader framework of the geological suitability assessment in recent years. The selection of pertinent indicators for the evaluation of rock mass quality inherently presents an appreciable degree of subjectivity. Predominantly subjective evaluation methods continue to dominate the field, while the application of objective algorithms, such as unsupervised clustering, remains in its nascent stage. Furthermore, there is a lack of comprehensive investigations into distinct combinations of attributes. This limitation confines the broader applicability of the evaluation outcomes in the context of urban underground space. Within this study, we meticulously amassed rock core test data from over 40 boreholes of engineering geological significance within the urban planning ambit of Guang'An City. Utilizing the K-means unsupervised clustering algorithm and the Principal Component Analysis (PCA) algorithm. We successfully conducted an unsupervised clustering procedure with nine distinct physical and mechanical attributes. This yielded an aggregation into five discernible clusters. Building upon the derived clustering outcomes, a stratification of rock mass quality was effectuated into three distinct tiers: Level 1 (characterized by pure sandstone), Level 2 (primarily dominated by sandstone), and Level 3 (denoting fair conditions predominantly influenced by mudstone). This structured stratification facilitates a relatively objective and comprehensive evaluation of rock mass quality within the context of the red-bed hilly terrain. In the course of this analytical trajectory, we conducted a dissection of the clustering efficacy. For strongly correlated attributes, we propose a preliminary dimensionality reduction procedure prior to the clustering endeavor. Moreover, we recommend intervals of 10 m for the stratified evaluation in red bed hilly urban terrains.

Abstract Tumor metastasis remains a leading factor in the failure of cancer treatments and patient mortality. To address this, a silver‐induced absorption red‐shifted core‐shell nano‐particle is developed, and surface‐modified with triphenylphosphonium bromide (TPP) and hyaluronic acid (HA) to obtain a novel nanodiagnosis‐treatment agent (Ag@CuS‐TPP@HA). This diagnosis‐treatment agent can dual‐targets cancer cells and mitochondria, and exhibits maximal light absorption at 1064 nm, thereby enhancing nesr‐infrared II (NIR‐II) photoacoustic (PA) signal and photothermal effects under 1064 nm laser irradiation. Additionally, the silver in Ag@CuS‐TPP@HA can catalyze the Fenton‐like reactions with H2O2 in the tumor tissue, yielding reactive oxygen species (ROS). The ROS production, coupled with enhanced photothermal effects, instigates immunogenic cell death (ICD), leading to a substantial release of tumor‐associated antigens (TAAs) and damage‐associated molecular patterns, which have improved the tumor immune suppression microenvironment and boosting immune checkpoint blockade therapy, thus stimulating a systemic antitumor immune response. Hence, Ag@CuS‐TPP@HA, as a cancer diagnostic‐treatment agent, not only accomplishes targeted the NIR‐II PA imaging of tumor tissue and addresses the challenge of accurate diagnosis of deep cancer tissue in vivo, but it also leverages ROS/photothermal therapy to enhance immune checkpoint blockade, thereby eliminating primary tumors and effectively inhibiting distant tumor growth.

To decrease the consumption of energy and material resources caused by the traditional ''two-step'' process for separating propylene from the C3 crude components, including propane, propylene, methylacetylene and propadiene, this work utilizes the metal-organic frameworks (MOFs) involved ''one-step'' process to purify propylene. First, the relationship between the geometric/energy descriptors of MOFs and their performance metrics was established through univariate analysis, and results show that the top-performance MOFs can be screened by the differences of LCD, ρ, VSA and ϕ. Then, different combinations of descriptors and algorithms were used for machine learning. The combination (RF algorithm, 7 basic descriptors + PSD + MorganFPs + nodes + topologies) with the best prediction accuracy (R=0.87) for predicting the performance of MOFs was found. Finally, 4 optimal pore structures for the design of high propylene adsorption performance materials were summarized, which mainly contain cylindrical channels and spherical cavities similar in size to the target gas. The microscopic control of pore structures obtained from our bottom-up approach is useful for the development of MOFs and other nanoporous materials which can be used for ''one-step'' separation of propylene from C3 mixtures in various industrial situations.

Abstract Metasurfaces utilize engineered nanostructures to achieve control on all possible dimensions of light, encouraging versatile applications, including beam steering, multifunctional lensing, and multiplexed holograms. Towards the quantum optical regime for metasurfaces, although significant efforts have been put into generating and analyzing specific quantum states, control schemes to further manipulate these quantum states or information are still limited. Here, based on a metasurface, we propose and experimentally demonstrate a continuous heralding scheme to remotely control a vortex beam with high robustness to noise using polarization-entangled photon pairs. Our metasurface entangles polarization and orbital angular momentum (OAM) and the polarization selection on heralding photon erases the which-OAM information on signal photon. It induces an interference of two different OAM states remotely, manifesting a continuous orbital rotation. Our results show that metasurfaces have potential applications in quantum communication and information processing in entangling information with increasing complexity in the content.

BackgroundExposure to perfluoroalkyl and polyfluoroalkyl substances (PFAS) during pregnancy might affect thyroid-related hormone levels in pregnant women. However, most previous studies focused on the effects of PFAS containing 8-10 carbon atoms, and few studies have estimated the associations between PFAS with longer carbon chain and thyroid-related hormone levels. ObjectiveTo examine the associations between PFAS exposure and thyroid-related hormones in pregnant women. MethodsThe present study was based on the Jiashan Birth Cohort from September 2016 to April 2018. We analyzed 13 PFAS in maternal blood samples (n=781) by high-performance liquid chromatography-tandem mass spectrometry, as well as total triiodothyronine (T3), total thyroxine (T4), free T3 (FT3), free T4 (FT4), thyroid stimulating hormone (TSH), thyroglobulin antibody (TG-Ab), and thyroid peroxidase antibody (TPOAb) by electrochemiluminescence immunoassay. PFAS were divided into three groups:low concentration, medium concentration and high concentration according to the tertile of their concentrations. We estimated the associations between PFAS concentrations and thyroid-related hormones in pregnant women by multiple linear regression. ResultsIn the multiple linear regression models, a change in perfluorododecanoic acid (PFDoA) concentrations from the low concentration group to the high concentration group was associated with a −0.10 (95%CI: −0.20, 0) nmol·L−1 change in T3, −0.15 (95%CI: −0.28, −0.02) pmol·L−1 change in FT3, and −3.02 (95%CI: −5.66, −0.39) pmol·L−1 change in FT4, respectively. A change in perfluorotridecanoic acid (PFTrDA) concentrations from the low concentration group to the high concentration group was associated with a −0.10 (95%CI: −0.20, 0) nmol·L−1 change in T3. Compared with the low concentration group, the concentration of T4 in the medium concentration group of perfluorohexane sulfonate (PFHxS) increased by 6.10 (95%CI: 0.44, 11.75) nmol·L−1. No statistically significant associations were found between PFAS and TSH concentration. The negative associations of PFAS with thyroid-related hormones were more pronounced in pregnant women with positive TG-Ab and/or TPOAb. ConclusionExposure to PFAS during pregnancy may affect thyroid-related hormone homeostasis in pregnant women, and the effect is stronger in TG-Ab and/or TPOAb-positive pregnant women.

Abstract Background Older adults with physical disability need long-term services and support, which incur enormous costs. However, supportive environments may reduce disability and promote aging in place. It is unclear how the physical and social environment affect different types of functional impairments and influence the performance of activities of daily living (ADL) in physically disabled older adults. Objective The purpose of this study was to examine the relationship between person, environmental factors, and ADL performance among physically disabled older adults living at home. Methods This was a cross-sectional study. Using long-term care insurance claims data from a pilot city in China, we used a structural equation model to assess the potential paths among person, environmental factors, and ADL performance. Results Education and income had different influences on the social environment and physical environment. The functional impairments had significant effects on ADL performance, either directly or through physical environment (with handrails) and social environment (family support). Conclusions The present findings offer crucial evidence for understanding the interactions between a person and the environment, as well as their influence on physical ADLs, suggesting the importance of a supportive environment and a subpopulation-targeting strategy for disabled older adults.

Introduction: Herpes zoster is caused by the reactivation of latent varicella infection within the sensory ganglia, caused by the varicella-zoster virus (VZV). The disease is classically characterized by a painful unilateral vesicular eruption. Complications of the disease include herpes zoster ophthalmicus, Ramsay Hunt syndrome, acute retinal necrosis, and post-herpetic neuralgia. In this paper, we discuss the epidemiology, pathogenesis, clinical features, diagnosis, management, and vaccination strategies of herpes zoster and post-herpetic neuralgia. Method: This paper was developed with input from specialists from Singapore’s public sectors—dermatologists, family physicians, and infectious diseases specialists. Results: The diagnosis of herpes zoster is clinical and can be aided with laboratory investigations. Early initiation of antivirals, within 72 h of onset, can reduce the severity and duration of the condition and decrease the intensity of pain. In patients with a high risk of post-herpetic neuralgia, early initiation of anticonvulsants or tricyclic antidepressants can be considered. Herpes zoster is highly preventable, with the advent of the recombinant zoster vaccine (RZV) providing an overall vaccine efficacy of 97.2%. Procedures such as epidural blocks and subcutaneous or intracutaneous injections of local anesthetics and steroids can be considered for patients with a high risk of post-herpetic neuralgia to reduce its incidence. Conclusion: This article serves as a guideline for clinicians in the diagnosis, investigations, management, and prevention of herpes zoster. With the majority of adults in Singapore currently at risk of developing herpes zoster due to varicella immunization being only introduced in 2020, it is important for clinicians to recognize and manage herpes zoster appropriately.

With the rapid growth of the economy, people are increasingly reliant on energy sources. However, in recent years, the energy crisis has gradually intensified. As a clean energy source, methane has garnered widespread attention for its development and utilization. This study employed both large-scale computational screening and machine learning to investigate the adsorption and diffusion properties of thousands of metal–organic frameworks (MOFs) in six gas binary mixtures of CH4 (H2/CH4, N2/CH4, O2/CH4, CO2/CH4, H2S/CH4, He/CH4) for methane purification. Firstly, a univariate analysis was conducted to discuss the relationships between the performance indicators of adsorbents and their characteristic descriptors. Subsequently, four machine learning methods were utilized to predict the diffusivity/selectivity of gas, with the light gradient boosting machine (LGBM) algorithm emerging as the optimal one, yielding R2 values of 0.954 for the diffusivity and 0.931 for the selectivity. Furthermore, the LGBM algorithm was combined with the SHapley Additive exPlanation (SHAP) technique to quantitatively analyze the relative importance of each MOF descriptor, revealing that the pore limiting diameter (PLD) was the most critical structural descriptor affecting molecular diffusivity. Finally, for each system of CH4 mixture, three high-performance MOFs were identified, and the commonalities among high-performance MOFs were analyzed, leading to the proposals of three design principles involving changes only to the metal centers, organic linkers, or topological structures. Thus, this work reveals microscopic insights into the separation mechanisms of CH4 from different binary mixtures in MOFs.

There is growing evidence that prenatal exposure to Per- and polyfluoroalkyl substances (PFAS) was associated with childhood obesity, but evidence on multiple adiposity measures including arm circumference (AC), and waist circumference (WC) among Chinese children is limited. We investigated the associations of prenatal exposure to PFAS with adiposity measures of children at 4 and 6 years of age in the Shanghai-Minhang Birth Cohort Study. A total of 573 mother-child pairs with maternal PFAS concentrations and at least one measurement of adiposity measures of children were included in the present study. Eleven PFAS were assessed in maternal fasting blood samples. Information on children's weight, height, AC, and WC was collected at follow-ups. Weight for age Z score (WAZ), body mass index for age Z score (BMIz), and children overweight were calculated based on the World Health Organization Child Growth Standards. Multivariate linear regression, Poisson regression with robust error variance, and Bayesian Kernel Machine Regression (BKMR) models were used to examine the associations of prenatal exposure to PFAS with children's adiposity measures. Eight PFAS with detection rates above 85 % were included in the analyses. In the multivariate linear regression models, maternal PFNA concentrations were associated with a greater AC (β = 0.29, 95 % Confidence Interval (CI): 0.04–0.55) in 4-year-old children and with an increase in WAZ (β = 0.26, 95 % CI: 0.06–0.46), BMIz (β = 0.31, 95 % CI: 0.09–0.53), AC (β = 0.49, 95 % CI: 0.08–0.90), and WC (β = 1.47, 95 % CI: 0.41–2.52) in 6-year-old children. We also observed the associations of maternal concentrations of PFOS, PFNA, PFUdA, and PFTrDA with the increased risk of children overweight in 6-year-old children. BKMR models further supported the findings from multivariate linear regression and Poisson regression models, and identified PFNA as the most important contributor. Moreover, the associations described above were generally more pronounced in girls. In conclusion, prenatal exposure to PFAS was associated with an increased risk of children's adiposity with a sex-specific manner, and PFNA contributed most to the associations after controlling for the effect of co-exposure to other PFAS compounds, especially among girls at 6 years of age.