Algorithm for community security risk assessment and influencing factors analysis by back propagation neural network.

This paper aims to accurately assess and effectively manage various security risks in the community and overcome the challenges faced by traditional models in handling large amounts of features and high-dimensional data. Hence, this paper utilizes the back propagation neural network (BPNN) to optimize the security risk assessment model. A key challenge of researching community security risk assessment lies in accurately identifying and predicting a range of potential security threats. These threats may encompass natural disasters, public health crises, accidents, and social security issues. The intricate interplay of these risk factors, combined with the dynamic nature of community environments, presents difficulties for traditional risk assessment methodologies to address effectively. Initially, this paper delves into the factors influencing safety incidents within communities and establishes a comprehensive system of safety risk assessment indicators. Leveraging the adaptable and generalizable nature of the BPNN model, the paper proceeds to optimize the BPNN model, enhancing the security risk assessment model through this optimization. Subsequent comparison experiments with traditional models validate the rationality and effectiveness of the proposed model, with hidden layer nodes set at various levels like 10, 15, 20, 25, 30, and 35. These traditional models include Convolutional Neural Network (CNN), Long Short-Term Memory Network (LSTM), Bidirectional Encoder Representations from Transformers (BERT), Generative Pre-trained Transformer (GPT), and eXtreme Gradient Boosting (XGBOOST). Experimental findings demonstrate that with 20 hidden layer nodes, the optimized model achieves a remarkable final recognition accuracy of 99.1 %. Moreover, the optimized model exhibits significantly lower final function loss compared to models with different node numbers. Increasing the number of hidden layer nodes may diminish the optimized model's fit and accuracy. Comparison with traditional models reveals that the average accuracy of the optimized model in community risk identification reaches 98.5 %, with a maximum accuracy of 99.6 %. This marks an improvement of 9%-11 % in recognition accuracy across various risk factors compared to traditional models. Regarding system response time and resource utilization, the optimized model exhibits a response time ranging from 100 ms to 120 ms and consistently lower resource utilization rates across all scenarios, underscoring its efficiency in community security risk assessment. In conclusion, this experiment sheds light on the underlying mechanisms and patterns of community safety risk formation, offering novel perspectives and methodologies for researching community safety risk assessment. The paper concludes by presenting recommendations and strategies for addressing community safety risks based on experimental analysis.

Cucumber (Cucumis sativus L.) translationally controlled tumor protein interacts with CsRab11A and promotes activation of target of rapamycin in response to Podosphaera xanthii.

The target of rapamycin (TOR) kinase serves as a central regulator that integrates nutrient and energy signals to orchestrate cellular and organismal physiology in both animals and plants. Despite significant advancements having been made in understanding the molecular and cellular functions of plant TOR kinases, the upstream regulators that modulate TOR activity are not yet fully elucidated. In animals, the translationally controlled tumor protein (TCTP) is recognized as a key player in TOR signaling. This study reveals that two TCTP isoforms from Cucumis sativus, when introduced into Arabidopsis, are instrumental in balancing growth and defense mechanisms against the fungal pathogen Golovinomyces cichoracearum. We hypothesize that plant TCTPs act as upstream regulators of TOR in response to powdery mildew caused by Podosphaera xanthii in Cucumis. Our research further uncovers a stable interaction between CsTCTP and a small GTPase, CsRab11A. Transient transformation assays indicate that CsRab11A is involved in the defense against P. xanthii and promotes the activation of TOR signaling through CsTCTP. Moreover, our findings demonstrate that the critical role of TOR in plant disease resistance is contingent upon its regulated activity; pretreatment with a TOR inhibitor (AZD-8055) enhances cucumber plant resistance to P. xanthii, while pretreatment with a TOR activator (MHY-1485) increases susceptibility. These results suggest a sophisticated adaptive response mechanism in which upstream regulators, CsTCTP and CsRab11A, coordinate to modulate TOR function in response to P. xanthii, highlighting a novel aspect of plant-pathogen interactions.

Candida albicans accelerates atherosclerosis by activating intestinal hypoxia-inducible factor2α signaling.

The gut microbiota is closely linked to atherosclerosis. However, the role of intestinal fungi, essential members of the complex microbial community, in atherosclerosis is poorly understood. Herein, we show that gut fungi dysbiosis is implicated in patients with dyslipidemia, characterized by higher levels of Candida albicans (C. albicans), which are positively correlated with plasma total cholesterol and low-density lipoprotein-cholesterol (LDL-C) levels. Furthermore, C. albicans colonization aggravates atherosclerosis progression in a mouse model of the disease. Through gain- and loss-of-function studies, we show that an intestinal hypoxia-inducible factor 2α (HIF-2α)-ceramide pathway mediates the effect of C. albicans. Mechanistically, formyl-methionine, a metabolite of C. albicans, activates intestinal HIF-2α signaling, which drives increased ceramide synthesis to accelerate atherosclerosis. Administration of the HIF-2α selective antagonist PT2385 alleviates atherosclerosis in mice by reducing ceramide levels. Our findings identify a role for intestinal fungi in atherosclerosis progression and highlight the intestinal HIF-2α-ceramide pathway as a target for atherosclerosis treatment.

Risk of drug-induced delirium in older patients- a pharmacovigilance study of FDA adverse event reporting system database.

BACKGROUND: Drug-induced delirium is one of the numerous known risk factors associated with increased morbidity and mortality in older patients. The objective of this study was to evaluate the risk of drug-related delirium in older patients based on the FDA Adverse Event Reporting System (FAERS). RESEARCH DESIGN AND METHODS: Delirium reports in older patients (age ≥65) from 2004 quarter 1 through 2021 quarter 3 extracted from the FAERS database using Open Vigil 2.1. The reported odds ratio and the proportional r7eported ratio were calculated to detect the adverse reaction signal of delirium. Combined with published evidence, suspected drugs were categorized as known, possible, or new potential delirium-risk-increasing drugs. RESULTS: Of the 130,885 reports (including 28,850 delirium events and 1,857 drug) analyzed for this study, 314 positive signal drugs were detected. Positive signal drugs are mainly concentrated on the drug of nervous system [n = 149, ROR 3.60, 95% CI (3.56-3.64)], cardiovascular system [n = 35, ROR 1.45, 95% CI (1.43-1.47)], alimentary tract and metabolism [n = 35, ROR 1.25, 95% CI (1.23-1.26)] and anti-infectives for systemic use [n = 27, ROR 1.70, 95% CI (1.66-1.74)]. Of the positive signal drugs, 26.11% (82/314) were known delirium-risk increasing drugs [ROR 4.12, 95%CI (3.85-4.41)], 44.90% (141/314) were possible [ROR 3.59, 95%CI (3.37-3.83)] and 28.98% (91/314) were new potential [ROR 3.68, 95%CI (3.22-4.21)]. CONCLUSION: Drug-induced delirium risk is prevalent in the older patients according to the FAERS. The risk level of drug-induced delirium should be taken into account to optimize drug therapy in clinical practice.

Serum vitamin D concentrations and sleep disorders: insights from NHANES 2011-2016 and Mendelian Randomization analysis.

OBJECTIVE: This investigation seeks to examine the association between serum vitamin D concentrations and the prevalence of sleep disorders, additionally elucidating the causal relationship via Mendelian Randomization (MR) analysis. MATERIALS AND METHODS: This research employed data from the National Health and Nutrition Examination Survey (NHANES) 2011-2016, focusing on adults aged 20-50 years reporting sleep disorders. The research encompassed 4913 American adults. Weighted multivariable logistic regression models and cubic spline analyses were utilized to evaluate the association between serum vitamin D concentrations and the incidence of sleep disorders. Additionally, a two-sample Mendelian Randomization analysis was performed to evaluate the potential causal link between serum vitamin D concentrations and the risk of sleep disorders. RESULTS: Within the 2011-2016 NHANES cohort of the U.S. population, a notable inverse association was detected between serum vitamin D concentrations and sleep disorders (ß = - 3.81, 95% CI: - 6.10 to - 1.52, p = 0.003). After multivariate adjustments, a higher incidence of sleep disorders was associated with lower vitamin D Concentrations (OR 1.52, 95% CI 1.10-2.10, trend p = 0.014). Restricted cubic spline regression analysis indicated a linear association between serum vitamin D concentrations and sleep disorders(non-linearity p > 0.05). Lastly, the two-sample MR analysis yielded evidence supporting a potential causal connection between serum vitamin D concentrations and sleep disorders, with each unit increase in genetically predicted serum vitamin D reducing the odds ratio to 0.78 (95% CI 0.61-0.99, p = 0.044). CONCLUSIONS: These results imply that lower vitamin D concentrations in the population might correlate with a heightened risk of sleep disorders, suggesting the importance of considering vitamin D supplementation when treating sleep disorders.

Early detection and prognosis evaluation for hepatocellular carcinoma by circulating tumour DNA methylation: A multicentre cohort study.

BACKGROUND: Early diagnosis of hepatocellular carcinoma (HCC) can significantly improve patient survival. We aimed to develop a blood-based assay to aid in the diagnosis, detection and prognostic evaluation of HCC. METHODS: A three-phase multicentre study was conducted to screen, optimise and validate HCC-specific differentially methylated regions (DMRs) using next-generation sequencing and quantitative methylation-specific PCR (qMSP). RESULTS: Genome-wide methylation profiling was conducted to identify DMRs distinguishing HCC tumours from peritumoural tissues and healthy plasmas. The twenty most effective DMRs were verified and incorporated into a multilocus qMSP assay (HepaAiQ). The HepaAiQ model was trained to separate 293 HCC patients (Barcelona Clinic Liver Cancer (BCLC) stage 0/A, 224) from 266 controls including chronic hepatitis B (CHB) or liver cirrhosis (LC) (CHB/LC, 96), benign hepatic lesions (BHL, 23), and healthy controls (HC, 147). The model achieved an area under the curve (AUC) of 0.944 with a sensitivity of 86.0% in HCC and a specificity of 92.1% in controls. Blind validation of the HepaAiQ model in a cohort of 523 participants resulted in an AUC of 0.940 with a sensitivity of 84.4% in 205 HCC cases (BCLC stage 0/A, 167) and a specificity of 90.3% in 318 controls (CHB/LC, 100; BHL, 102; HC, 116). When evaluated in an independent test set, the HepaAiQ model exhibited a sensitivity of 70.8% in 65 HCC patients at BCLC stage 0/A and a specificity of 89.5% in 124 patients with CHB/LC. Moreover, HepaAiQ model was assessed in paired pre- and postoperative plasma samples from 103 HCC patients and correlated with 2-year patient outcomes. Patients with high postoperative HepaAiQ score showed a higher recurrence risk (Hazard ratio, 3.33, p < .001). CONCLUSIONS: HepaAiQ, a noninvasive qMSP assay, was developed to accurately measure HCC-specific DMRs and shows great potential for the diagnosis, detection and prognosis of HCC, benefiting at-risk populations.

Advancing e-commerce user purchase prediction: Integration of time-series attention with event-based timestamp encoding and Graph Neural Network-Enhanced user profiling.

In recent years, the global e-commerce landscape has witnessed rapid growth, with sales reaching a new peak in the past year and expected to rise further in the coming years. Amid this e-commerce boom, accurately predicting user purchase behavior has become crucial for commercial success. We introduce a novel framework integrating three innovative approaches to enhance the prediction model's effectiveness. First, we integrate an event-based timestamp encoding within a time-series attention model, effectively capturing the dynamic and temporal aspects of user behavior. This aspect is often neglected in traditional user purchase prediction methods, leading to suboptimal accuracy. Second, we incorporate Graph Neural Networks (GNNs) to analyze user behavior. By modeling users and their actions as nodes and edges within a graph structure, we capture complex relationships and patterns in user behavior more effectively than current models, offering a nuanced and comprehensive analysis. Lastly, our framework transcends traditional learning strategies by implementing advanced meta-learning techniques. This enables the model to autonomously adjust learning parameters, including the learning rate, in response to new and evolving data environments, thereby significantly enhancing its adaptability and learning efficiency. Through extensive experiments on diverse real-world e-commerce datasets, our model demonstrates superior performance, particularly in accuracy and adaptability in large-scale data scenarios. This study not only overcomes the existing challenges in analyzing e-commerce user behavior but also sets a foundation for future exploration in this dynamic field. We believe our contributions provide significant insights and tools for e-commerce platforms to better understand and cater to their users, ultimately driving sales and improving user experiences.

Hydrangea-like TiO2/Bi2MoO6 porous nanoflowers triggering highly sensitive electrochemical immunosensing to tumor marker.

Rapid and sensitive detection of carcinoembryonic antigen (CEA) is of great significance for cancer patients. Here, molybdenum (Mo) was doped into bismuth oxide (Bi2O3) by one-pot hydrothermal method forming porous tremella Bi2MoO6 nanocomposites with a larger specific surface area than the spherical structure. Then, a new kind of hydrangea-like TiO2/Bi2MoO6 porous nanoflowers (NFs) was prepared by doping titanium into Bi2MoO6, where titanium dioxide (TiO2) grew in situ on the surface of Bi2MoO6 nanoparticles (NPs). The hydrangea-like structure provides larger specific surface area, higher electron transfer ability and biocompatibility as well as more active sites conducive to the attachment of anti-carcinoembryonic antigen (anti-CEA) to TiO2/Bi2MoO6 NFs. A novel label-free electrochemical immunosensor was then constructed for the quantitative detection of CEA using TiO2/Bi2MoO6 NFs as sensing platform, showing a good linear relationship with CEA in the concentration range 1.0 pg/mL ~ 1.0 mg/mL and a detection limit of 0.125 pg/mL (S/N = 3). The results achieved with the designed immunosensor are comparable with many existing immunosensors used for the detection of CEA in real samples.

The Prevalence of Hyperuricemia and the Association Between Hyperuricemia and Age in Patients with Psychiatric Disorders to a General Hospital: A Cross-Section Study.

Purpose: In clinical work, it has been found that the prevalence of hyperuricemia (HUA) is significantly higher in younger patients with psychiatric disorders, but there are few studies in this area. The present study aims to evaluate the prevalence of HUA and the relationship between the HUA and age in hospitalized patients with psychiatric disorders in the real world, and to provide a theoretical basis for clinical staff to pay attention to the metabolic indicators of younger patients and for future related studies. Methods: This is a cross-sectional evaluation of a cohort of 1761 patients with psychiatric disorders of hospitalized. The categories of disorders designed for study included: Depression, Bipolar disorder, Schizophrenia, Anxiety, Obsessive-Compulsive disorder, Acute and transient psychotic disorder, Dissociative(conversion) disorders, Conduct disorders and Tic disorders. In addition, based on age, the participants are stratified into three groups. The authors used Kruskal-Wallis tests, chi-square tests, and multiple linear logistic regression to verify the relationship between HUA and age among hospitalized patients with psychiatric disorders. Results: Overall, the estimated prevalence of HUA was 35.4%. The prevalence of HUA was significantly higher in individuals with 17 years and under compared to those with 45 years and above (P < 0.001). After adjusting for confounders, the prevalence of HUA remained higher at 17 years and under than at 45 years and above. Bipolar disorder can lead to an increased prevalence of HUA (P<0.05). Conclusion: The prevalence of HUA was higher in hospitalized patients with psychiatric disorders, and the prevalence was inversely proportional to age.

Zinc-Ion Anchor Induced Highly Reversible Zn Anodes for High Performance Zn-Ion Batteries.

Unstable Zn interface with serious detrimental parasitic side-reactions and uncontrollable Zn dendrites severely plagues the practical application of aqueous zinc-ion batteries. The interface stability was closely related to the electrolyte configuration and Zn2+ depositional behavior. In this work, a unique Zn-ion anchoring strategy is originally proposed to manipulate the coordination structure of solvated Zn-ions and guide the Zn-ion depositional behavior. Specifically, the amphoteric charged ion additives (denoted as DM), which act as zinc-ion anchors, can tightly absorb on the Zn surface to guide the uniform zinc-ion distribution by using its positively charged -NR4 + groups. While the negatively charged -SO3 - groups of DM on the other hand, reduces the active water molecules within solvation sheaths of Zn-ions. Benefiting from the special synergistic effect, Zn metal exhibits highly ordered and compact (002) Zn deposition and negligible side-reactions. As a result, the advanced Zn||Zn symmetric cell delivers extraordinarily 7000 hours long lifespan (0.25 mA cm-2, 0.25 mAh cm-2). Additionally, based on this strategy, the NH4V4O10||Zn pouch-cell with low negative/positive capacity ratio (N/P ratio=2.98) maintains 80.4 % capacity retention for 180 cycles. A more practical 4 cm*4 cm sized pouch-cell could be steadily cycled in a high output capacity of 37.0 mAh over 50 cycles.

Long-term saline water irrigation affected soil carbon and nitrogen cycling functional profiles in the cotton field.

Saline water irrigation (SWI) plays an important role in alleviating water resource shortages. At the same time, the salt input of irrigation water affects soil microorganisms which participate in various ecological processes of terrestrial ecosystems. However, the responses of soil microbial functional potential to long-term SWI remains unclear. Therefore, Metagenomics method was utilized in cotton fields under long-term SWI to reveal the microbial functional profiles associated with soil carbon and nitrogen cycles. Results indicated that SWI impacted the microbial functional profiles of soil carbon and nitrogen cycles in the cotton fields significantly. Especially, irrigation water salinity inhibited the relative abundances of sacC and vanB, which are soil carbon degradation genes. SWI also affected the functional gene abundance of nitrogen degradation, dissimilatory nitrate reduction, and nitrification. Moreover, SWI significantly increased the abundance of Candidatus_Cloacimonetes in both carbon and nitrogen cycles. In the discussion, we used person analysis found that soil salinity, pH, and ammonium nitrogen were important factors affecting the abundance of functional genes and microbial taxa. Overall, this study indicated that long-term SWI significantly influenced specific microbial functional genes and taxa abundance, which may lead to predictable outcomes for soil carbon and nitrogen cycling, and is of great importance in exploring the impact of SWI on soil environments.

The Pharmacogenetic Variability Associated With the Pharmacokinetics and Pharmacodynamics of Rivaroxaban in Healthy Chinese Subjects: A National Multicenter Exploratory Study.

PURPOSE: This study aimed to explore the pharmacogenetic variability associated with the pharmacokinetics (PK) and pharmacodynamics (PD) of rivaroxaban in healthy Chinese subjects. METHODS: This was a multicenter study that included 304 healthy adults aged 18 to 45 years with unknown genotypes. All participants were administered a single dose of rivaroxaban at 10 mg, 15 mg, or 20 mg. PK and PD parameters were measured, and exome-wide association analysis was conducted. FINDINGS: Sixteen SNPs located on 11 genes influenced the AUC0-t. Among these, the 3 most influential genes were MiR516A2, PARP14, and MIR618. Thirty-six SNPs from 28 genes were associated with the PD of rivaroxaban. The 3 most influential genes were PKNOX2, BRD3, and APOL4 for anti-Xa activity, and GRIP2, PLCE1, and MLX for diluted prothrombin time (dPT). Among them, BRD3 played an important role in both the PK and PD of rivaroxaban. Anti-Xa activity (ng/mL) differed significantly among subjects with BRD3 rs467387: 145.1 ± 55.5 versus 139.9 ± 65.1 versus 164.0 ± 68.6 for GG, GA, and AA carriers, respectively (P = 0.0002). IMPLICATIONS: This study found that that the regulation of the BRD3 gene might affect the PK and PD of rivaroxaban, suggesting that it should be studied as a new pharmacologic target. The correlation between this gene locus and clinical outcomes has yet to be verified in patients undergoing clinical treatment.

FvMYB108, a MYB Gene from Fragaria vesca, Positively Regulates Cold and Salt Tolerance of Arabidopsis.

MYB (myoblast) protein comes in large quantities and a wide variety of types and plays a role in most eukaryotes in the form of transcription factors (TFs). One of its important functions is to regulate plant responses to various stresses. However, the role of MYB TFs in regulating stress tolerance in strawberries is not yet well understood. Therefore, in order to investigate the response of MYB family members to abiotic stress in strawberries, a new MYB TF gene was cloned from Fragaria vesca (a diploid strawberry) and named FvMYB108 based on its structural characteristics and evolutionary relationships. After a bioinformatics analysis, it was determined that the gene belongs to the R2R3-MYB subfamily, and its conserved domain, phylogenetic relationships, predicted protein structure and physicochemical properties, subcellular localization, etc. were analyzed. After qPCR analysis of the expression level of FvMYB108 in organs, such as the roots, stems, and leaves of strawberries, it was found that this gene is more easily expressed in young leaves and roots. After multiple stress treatments, it was found that the target gene in young leaves and roots is more sensitive to low temperatures and salt stimulation. After these two stress treatments, various physiological and biochemical indicators related to stress in transgenic Arabidopsis showed corresponding changes, indicating that FvMYB108 may be involved in regulating the plant's ability to cope with cold and high-salt stress. Further research has found that the overexpression of this gene can upregulate the expression of AtCBF1, AtCOR47, AtERD10, and AtDREB1A related to low-temperature stress, as well as AtCCA1, AtRD29a, AtP5CS1, and AtSnRK2.4 related to salt stress, enhancing the ability of overexpressed plants to cope with stress.

Millimeter wave-based patient setup verification and motion tracking during radiotherapy.

BACKGROUND: Position verification and motion monitoring are critical for safe and precise radiotherapy (RT). Existing approaches to these tasks based on visible light or x-ray are suboptimal either because they cannot penetrate obstructions to the patient's skin or introduce additional radiation exposure. The low-cost mmWave radar is an ideal solution for these tasks as it can monitor patient position and motion continuously throughout the treatment delivery. PURPOSE: To develop and validate frequency-modulated continuous wave (FMCW) mmWave radars for position verification and motion tracking during RT delivery. METHODS: A 77 GHz FMCW mmWave module was used in this study. Chirp Z Transform-based (CZT) algorithm was developed to process the intermediate frequency (IF) signals. Absolute distances to flat Solid Water slabs and human shape phantoms were measured. The accuracy of absolute distance and relative displacement were evaluated. RESULTS: Without obstruction, mmWave based on the CZT algorithm was able to detect absolute distance within 1 mm for a Solid Water slab that simulated the reflectivity of the human body. Through obstructive materials, the mmWave device was able to detect absolute distance within 5 mm in the worst case and within 3.5 mm in most cases. The CZT algorithm significantly improved the accuracy of absolute distance measurement compared with Fast Fourier Transform (FFT) algorithm and was able to achieve submillimeter displacement accuracy with and without obstructions. The surface-to-skin distance (SSD) measurement accuracy was within 8 mm in the anterior of the phantom. CONCLUSIONS: With the CZT signal processing algorithm, the mmWave radar is able to measure the absolute distance to a flat surface within 1 mm. But the absolute distance measurement to a human shape phantom is as large as 8 mm at some angles. Further improvement is necessary to improve the accuracy of SSD measurement to uneven surfaces by the mmWave radar.

Survival mechanisms of circulating tumor cells and their implications for cancer treatment.

Metastasis remains the principal trigger for relapse and mortality across diverse cancer types. Circulating tumor cells (CTCs), which originate from the primary tumor or its metastatic sites, traverse the vascular system, serving as precursors in cancer recurrence and metastasis. Nevertheless, before CTCs can establish themselves in the distant parenchyma, they must overcome significant challenges present within the circulatory system, including hydrodynamic shear stress (HSS), oxidative damage, anoikis, and immune surveillance. Recently, there has been a growing body of compelling evidence suggesting that a specific subset of CTCs can persist within the bloodstream, but the precise mechanisms of their survival remain largely elusive. This review aims to present an outline of the survival challenges encountered by CTCs and to summarize the recent advancements in understanding the underlying survival mechanisms, suggesting their implications for cancer treatment.

Advances in Metabolism and Metabolic Toxicology of Quinoxaline 1,4-Di-N-oxides.

Quinoxaline 1,4-di-N-Oxides (QdNOs) have been used as synthetic antimicrobial agents in animal husbandry and aquaculture. The metabolism and potential toxicity have been also concerns in recently years. The metabolism investigations showed that there were 8 metabolites of Carbadox (CBX), 34 metabolites of Cyadox (CYA), 33 metabolites of Mequindox (MEQ), 35 metabolites of Olaquindox (OLA), and 56 metabolites of Quinocetone (QCT) in different animals. Among them, Cb3 and Cb8, M6, and O9 are metabolic residual markers of CBX, MEQ and OLA, which are associated with N → O reduction. Toxicity studies revealed that QdNOs exhibited severe tumorigenicity, cytotoxicity, and adrenal toxicity. Metabolic toxicology showed that toxicity of QdNOs metabolites might be related to the N → O group reduction, and some metabolites exhibited higher toxic effects than the precursor, which could provide guidance for further research on the metabolic toxicology of QdNOs and provide a wealth of information for food safety evaluation.

Prediction of the benign and malignant nature of masses in COPD background based on Habitat-based enhanced CT radiomics modeling: A preliminary study.

BACKGROUND: It is difficult to differentiate between chronic obstructive pulmonary disease (COPD)-peripheral bronchogenic carcinoma (COPD-PBC) and inflammatory masses. OBJECTIVE: This study aims to predict COPD-PBC based on clinical data and preoperative Habitat-based enhanced CT radiomics (HECT radiomics) modeling. METHODS: A retrospective analysis was conducted on clinical imaging data of 232 cases of postoperative pathological confirmed PBC or inflammatory masses. The PBC group consisted of 82 cases, while the non-PBC group consisted of 150 cases. A training set and a testing set were established using a 7:3 ratio and a time cutoff point. In the training set, multiple models were established using clinical data and radiomics texture changes within different enhanced areas of the CT mass (HECT radiomics). The AUC values of each model were compared using Delong's test, and the clinical net benefit of the models was tested using decision curve analysis (DCA). The models were then externally validated in the testing set, and a nomogram of predicting COPD-PBC was created. RESULTS: Univariate analysis confirmed that female gender, tumor morphology, CEA, Cyfra21-1, CT enhancement pattern, and Habitat-Radscore B/C were predictive factors for COPD-PBC (P< 0.05). The combination model based on these factors had significantly higher predictive performance [AUC: 0.894, 95% CI (0.836-0.936)] than the clinical data model [AUC: 0.758, 95% CI (0.685-0.822)] and radiomics model [AUC: 0.828, 95% CI (0.761-0.882)]. DCA also confirmed the higher clinical net benefit of the combination model, which was validated in the testing set. The nomogram developed based on the combination model helped predict COPD-PBC. CONCLUSION: The combination model based on clinical data and Habitat-based enhanced CT radiomics can help differentiate COPD-PBC, providing a new non-invasive and efficient method for its diagnosis, treatment, and clinical decision-making.

The joint effects of prenatal exposure to PM2.5 constituents and reduced fetal growth on children's accelerated growth in the first 3 years: a birth cohort study.

BACKGROUND: Prenatal fine particulate matter (PM2.5) constituents exposure and reduced fetal growth may be risk factors for accelerated growth in early childhood, an important indicator for lifelong health. OBJECTIVE: The study investigated whether the joint effects are present between PM2.5 constituents and reduced fetal growth. METHODS: The study was embedded in a birth cohort in China, including 5424 mother-child pairs. Prenatal PM2.5 and its constituents' [organic carbon (OC), elementary carbon (EC), ammonium (NH4+), nitrate (NO3-), and sulfate (SO42-)] concentrations were estimated based on maternal residential addresses. Fetal growth was evaluated by fetal growth trajectory in utero and preterm birth (PTB), low birth weight (LBW), and small for gestational age (SGA). Children's accelerated growth was defined as body mass index (BMI) Z-score change of >0.67 between birth and 3 years. Generalized logistic regression was used to analyze the effects of prenatal PM2.5 constituents exposure and fetal growth on children's accelerated growth. Joint effect was tested on multiplicative scale and additive scale with the relative excess risk due to interaction (RERI). RESULTS: Children with lower fetal growth trajectory, PTB, LBW, and SGA had increased odds of children's accelerated growth, with odds ratios (ORs) ranging from 1.704 to 11.605. Compared with lower exposure (≤median), higher exposure (>median) of PM2.5, OC, and SO42- were significantly associated with increased odds of children's accelerated growth, varying in ORs from 1.163 to 1.478. Prenatal exposure to OC had joint effects with lower fetal growth on children's accelerated growth. We observed that the interaction was statistically significant on an additive scale in OC and lower fetal growth trajectory (RERI: 0.497, 95% CI: 0.033,0.962). IMPACT: Fine particulate matter (PM2.5) is a huge threat to human health worldwide, causing 6.7 million death globally in 2019. According to the theory of DOHaD, prenatal PM2.5 exposure could influence early childhood growth, which is important for lifelong health. We found that prenatal exposure to PM2.5, OC, and SO42- was associated with higher risk of accelerated childhood growth in the first 3 years. More importantly, reduced fetal growth moderated these associations. Our findings highlight the need for policies and interventions on PM2.5 constituents to improve lifelong health, especially for those vulnerable populations with reduced fetal growth.

Electroacupuncture Promotes Angiogenesis in Mice with Cerebral Ischemia by Inhibiting miR-7.

OBJECTIVE: To observe the angiogenesis effect of electroacupuncture (EA) at Shuigou acupoint (GV 26) in the treatment of cerebral ischemia, and explore the value of miRNA-7 (miR-7) in it. METHODS: First, 48 mice were randomly divided into sham operation, middle cerebral artery occlusion (MCAO) model, and EA treatment groups. Then 9 mice were divided into carrier control group, miR-7 knockout group and miR-7 overexpression group (n=3 each group). Finally, 20 mice were divided into model and carrier control group, model and miR-7 knockout group, EA treatment and carrier control group and EA treatment and miR-7 overexpression group, with 3-6 mice in each group. The MCAO model was established in the MCAO and EA groups. Neurological deficit score and 2,3,5-triphenyltetrazolium chloride (TTC) staining were used to evaluate the severity of cerebral ischemia. Hematoxylin-eosin staining was used to describe basic pathological changes. Immunohistochemistry was used to quantify cerebral microvessel density. Real-time PCR and Western blot were used to detect the expression of miR-7 and its downstream target genes Krüppel-like factor 4/vascular endothelial growth factor (KLF4/VEGF) and angiopoietin-2 (ANG-2) in the ischemic cerebral cortex. RESULTS: After EA, neurological deficit scores and infarction volumes decreased, and the density of cerebral microvessels increased. In the MCAO group, miR-7 expression was higher than that in the sham group (P<0.01). After EA at GV 26, miR-7 expression decreased (P<0.01) and the expression of downstream target genes KLF4/VEGF and ANG-2 increased as compared with the MCAO group (P<0.01). After EA combined with overexpression of miR-7, the expression of downstream target genes KLF4/VEGF and ANG-2 decreased compared to the control EA group (P<0.01). After miR-7 knockdown, the expression of KLF4/VEGF and ANG-2 increased (P<0.05 or P<0.01). CONCLUSIONS: EA could promote angiogenesis in MCAO mice likely by inhibiting the expression of miR-7 and relieving inhibition of downstream target genes KLF4/VEGF and ANG-2.