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In this research, we study the thermal buckling performance of multi-scale hybrid laminated nanocomposite (MHLC) disk (MHLCD) subjected hygro-mechanical loading. The matrix material is reinforced with carbon nanotubes (CNTs) or carbon fibers (CF) at the nano- or macro-scale, respectively. The disk is modeled based on higher order shear deformation theory. We present a modified Halpin–Tsai model to predict the effective properties of the MHLCD. The minimum total potential energy principle is employed to establish the governing equations of the system, which is finally solved by the generalized differential quadrature method. To validate the approach, numerical results are compared with available results from the literature. Subsequently, a comprehensive parameter study is carried out to quantify the influence of different parameters such as stiffness of the substrate, patterns of temperature increase, moisture coefficient, stacking sequence of the CFs, weight fraction and distribution patterns of CNTs, outer radius to inner radius ratio and inner radius to thickness ratio on the response of the plate. Some new results related to critical buckling of an MHLCD are also presented, which can serve as benchmark solutions for future investigations.

The post-coronavirus disease 2019 (COVID-19) pulmonary sequelae have garnered public concern. We conducted a multicenter cross-sectional study in outpatient and health exam populations from 23 clinical centers (including university-affiliated/provincial general hospitals, municipal general hospitals, county hospitals, and specialized hospitals) in China (2019−2023), to assess temporal trends and potential influencing factors in the detection of CT-diagnosed pulmonary nodules, pleural effusion, pneumonia, and suspected lung tumors, cancer and viral pneumonia, clarifying pandemic impacts on lung health. Dynamic comparisons across key phases including initial outbreak, vaccine rollout, population-wide vaccination, and major adjustment of pandemic control policies, were performed. This study analyzed 1,616,750 clinical samples (1,102,605 outpatient, 514,145 health examination; 885,945 males, 730,805 females). Pulmonary nodule detection rose progressively, with surges in 2020−2021 and 2023, plateauing in 2021−2022. Outpatients and males showed steeper increases. University-affiliated/provincial hospitals had sharpest increases vs. municipal and county tiers. Specialized hospitals matched general hospital rates. AI boosted detection rates. CT-suspected lung tumors/cancer remained low and stable, unrelated to nodule trends. These results underscore 2019−2023 pulmonary nodule detection surges linked to SARS-CoV-2 infections and AI adoption. COVID-19 vaccination did not accelerate detection but may have slowed it short-term. Long-term studies on infection, vaccine impacts and pandemic-detected nodules’ outcomes are urgently needed.

To create a risk model of aging-related long non-coding RNAs (arlncRNAs) and determine whether they might be useful as markers for risk stratification, prognosis prediction, and targeted therapy guidance for patients with lung adenocarcinoma (LUAD). Data on aging genes and lncRNAs from LUAD patients were obtained from Human Aging Genomic Resources 3 and The Cancer Genome Atlas, and differential co-expression analysis of established differentially expressed arlncRNAs (DEarlncRNAs) was performed. They were then paired with a matrix of 0 or 1 by cyclic single pairing. The risk coefficient for each sample of LUAD individuals was obtained, and a risk model was constructed by performing univariate regression, least absolute shrinkage and selection operator regression analysis, and univariate and multivariate Cox regression analysis. Areas under the curve were calculated for the 1-, 3-, and 5-year receiver operating characteristic curves to determine Akaike information criterion-based cutoffs to identify high- and low-risk groups. The survival rate, correlation of clinical characteristics, malignant-infiltrating immune-cell expression, ICI-related gene expression, and chemotherapeutic drug sensitivity were contrasted with the high- and low-risk groups. We found that 99 DEarlncRNAs were upregulated and 12 were downregulated. Twenty pairs of DEarlncRNA pairs were used to create a prognostic model. The 1-, 3-, and 5-year survival curve areas of LUAD individuals were 0.805, 0.793, and 0.855, respectively. The cutoff value to classify patients into two groups was 0.992. The mortality rate was higher in the high-risk group. We affirmed that the LUAD outcome-related independent predictor was the risk score (p < 0.001). Validation of tumor-infiltrating immune cells and ICI-related gene expression differed substantially between the groups. The high-risk group was highly sensitive to docetaxel, erlotinib, gefitinib, and paclitaxel. Risk models constructed from arlncRNAs can be used for risk stratification in patients with LUAD and serve as prognostic markers to identify patients who might benefit from targeted and chemotherapeutic agents.

Model algorithms were used in constructing the risk coefficient model of necroptosis-related long non-coding RNA in identifying novel potential biomarkers in the prediction of the sensitivity to chemotherapeutic agents and prognosis of patients with lung adenocarcinoma (LUAD). Clinic and transcriptomic data of LUAD were obtained from The Cancer Genome Atlas. Differently expressed necroptosis-related long non-coding RNAs got identified by performing both the univariate and co-expression Cox regression analyses. Subsequently, the least absolute shrinkage and selection operator technique was adopted in constructing the nrlncRNA model. We made a comparison of the areas under the curve, did the count of the values of Akaike information criterion of 1-year, 2-year, as well as 3-year receiver operating characteristic curves, after which the cut-off value was determined for the construction of an optimal model to be used in identifying high risk and low risk patients. Genes, tumor-infiltrating immune cells, clinical correlation analysis, and chemotherapeutic agents data of both the high-risk and low-risk subgroups were also performed. We identified 26 DEnrlncRNA pairs, which were involved in the Cox regression model constructed. The curve areas under survival periods of 1 year, 2 years, and 3 years of patients with LUAD were 0.834, 0.790, and 0.821, respectively. The cut-off value set was 2.031, which was used in the identification of either the high-risk or low-risk patients. Poor outcomes were observed in patients belonging to the high-risk group. The risk score was the independent predictor of the LUAD outcome (p < 0.001). The expression levels of immune checkpoint and infiltration of specific immune cells were anticipated by the gene risk model. The high-risk group was found to be highly sensitive to docetaxel, erlotinib, cisplatin, and paclitaxel. The model established through nrlncRNA pairs irrespective of the levels of expression could give a prediction on the LUAD patients’ prognosis and assist in identifying the patients who might gain more benefit from chemotherapeutic agents.

Underwater target detection is an important part of national defense, which is related to national defense security. Underwater target recognition technology based on deep learning has made great progress in recent years, but there are still some problems, such as the feature is not obvious, the contour is not obvious, and so on. This paper introduces the current situation of underwater target recognition based on deep learning, analyzes the commonly used deep learning methods, and provides a new idea for the further research of underwater target recognition based.

Communal space is regarded as essential for human well-being in high-rise developments in Asia and increasing attention has been given to the underlying mechanism of its effects in light of the ongoing COVID-19 pandemic. From the perspective of person–place processes, this paper explores ‘sense of place’ and its possible mediating effects on the relationship between communal space and the mental health of residents in high-rise public housing. An analysis of data from a questionnaire survey conducted in Hong Kong and Guangzhou revealed differentiated mechanisms according to local context and age group. Sense of place and its subcomponents mediated the connection between communal space and mental health in Hong Kong but not in Guangzhou. More specifically, place identity, place attachment and place dependence had stronger effects among older residents in HK than younger ones. The findings from this study can inform evidence-based planning and decision-making for public housing policy for health-oriented environments in high-density cities.

Objective. To systematically evaluate the value of lymphocytes, platelets, and interleukin-6 in predicting the mortality of patients with coronavirus disease 2019 (COVID-19) and to provide medical evidence for the long-term prognosis of patients with COVID-19. Methods. The latest studies published until July 1, 2021, were retrieved from databases including PubMed, Embase, and Cochrane Library to analyze the ability of lymphocyte and platelet counts as well as interleukin-6 levels to predict mortality in patients with COVID-19. Two reviewers independently screened the literature and extracted data, then evaluated the risk of bias of included studies using the Newcastle–Ottawa Scale (NOS), and used Stata 15.0 software for meta-analysis. Results. A total of nine studies were included, involving 4340 patients. There were 1330 patients in the death group and 3010 patients in the survival group. Meta-analysis showed that, compared with the survival group, lymphocyte counts in the death group were significantly lower (SMD = −0.64, 95% CI: −0.86–−0.43, p<0.01), platelet counts were significantly lower (SMD = −0.47, 95% CI: −0.67–−0.27, p<0.01), and interleukin-6 levels were significantly higher (SMD = 1.07, 95% CI: 0.62–1.53, p<0.01). Conclusion. Lymphocyte and platelet counts, as well as interleukin-6 levels, can help predict the mortality of patients with COVID-19. Due to the limitation of the number and quality of the included studies, these conclusions need to be validated by additional high-quality studies.

The specific heat of propylene glycol has been measured at temperatures from 0.1 K to 6 K. The magnitude and the temperature dependence of the specific heat are similar to that found in other fragile glasses.

Intercellular signaling is indispensable for single cells to form complex biological structures, such as biofilms, tissues and organs. The genetic tools available for engineering intercellular signaling, however, are quite limited. Here we exploit the chemical diversity of biological small molecules to de novo design a genetic toolbox for high-performance, multi-channel cell–cell communications and biological computations. By biosynthetic pathway design for signal molecules, rational engineering of sensing promoters and directed evolution of sensing transcription factors, we obtain six cell–cell signaling channels in bacteria with orthogonality far exceeding the conventional quorum sensing systems and successfully transfer some of them into yeast and human cells. For demonstration, they are applied in cell consortia to generate bacterial colony-patterns using up to four signaling channels simultaneously and to implement distributed bio-computation containing seven different strains as basic units. This intercellular signaling toolbox paves the way for engineering complex multicellularity including artificial ecosystems and smart tissues. Intercellular signalling is fundamental for the formation of complex structures from single cells. Here the authors design six orthogonal cell–cell signalling channels for cell consortia communication and bio-computation.

The overuse of antibiotics in animal husbandry is a primary driver of antimicrobial resistance, creating a pressing need for safe and effective natural alternatives. This study systematically evaluated the potential of the edible aromatic plant Elsholtzia cypriani as a comprehensive alternative by investigating its chemical composition, bioactivities, and preliminary safety. Methods included solvent extraction and systematic chromatographic fractionation from the plant aerial parts, complemented by a series of in vitro assays assessing anti-inflammatory, antioxidant, and antibacterial properties, along with an acute toxicity study. A total of thirty compounds were isolated and their structures were elucidated, including two new and twenty-eight known compounds reported for the first time in this species. Key isolates, such as ethyl caffeate and luteolin, demonstrated significant anti-inflammatory activity, antioxidant capacity, and antibacterial action against pathogens like Escherichia coli. Acute toxicity assessment revealed no adverse effects at the tested dosage. In conclusion, E. cypriani is rich in diverse bioactive compounds which exhibit direct antimicrobial, anti-inflammatory, and antioxidant activities in vitro, and shows a favorable preliminary safety profile. This work systematically establishes the chemical and pharmacological basis for this plant, highlighting its potential for further development and evaluation as a multifunctional natural feed additive.