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Background: Postoperative non-small cell lung cancer (NSCLC) patients frequently encounter a deteriorated quality of life (QOL), disturbed immune response, and disordered homeostasis. Si-Jun-Zi Decoction (SJZD), a well-known traditional Chinese herbal formula, is frequently employed in clinical application for many years. Exploration is underway to investigate the potential therapeutic effect of SJZD for treating postoperative NSCLC. Objective: To assess the efficacy of SJZD on QOLs, hematological parameters, and regulations of gut microbiota in postoperative NSCLC patients. Methods: A prospective observational cohort study was conducted, enrolling 65 postoperative NSCLC patients between May 10, 2020 and March 15, 2021 in Yueyang Hospital, with 33 patients in SJZD group and 32 patients in control (CON) group. The SJZD group comprised of patients who received standard treatments and the SJZD decoction, while the CON group consisted of those only underwent standard treatments. The treatment period was 4 weeks. The primary outcome was QOL. The secondary outcomes involved serum immune cell and inflammation factor levels, safety, and alterations in gut microbiota. Results: SJZD group showed significant enhancements in cognitive functioning (P = .048) at week 1 and physical functioning (P = .019) at week 4. Lung cancer-specific symptoms included dyspnea (P = .001), coughing (P = .008), hemoptysis (P = .034), peripheral neuropathy (P = .019), and pain (arm or shoulder, P = .020, other parts, P = .019) eased significantly in the fourth week. Anemia indicators such as red blood cell count (P = .003 at week 1, P = .029 at week 4) and hemoglobin (P = .016 at week 1, P = .048 at week 4) were significantly elevated by SJZD. SJZD upregulated blood cell cluster differentiation (CD)3+ (P = .001 at week 1, P < .001 at week 4), CD3+CD4+ (P = .012 at week 1), CD3+CD8+ (P = .027 at week 1), CD19+ (P = .003 at week 4), increased anti-inflammatory interleukin (IL)-10 (P = .004 at week 1, P = .003 at week 4), and decreased pro-inflammatory IL-8 (P = .004 at week 1, p = .005 at week 4). Analysis of gut microbiota indicated that SJZD had a significant impact on increasing microbial abundance and diversity, enriching probiotic microbes, and regulating microbial biological functions. Conclusions: SJZD appears to be an effective and safe treatment for postoperative NSCLC patients. As a preliminary observational study, this study provides a foundation for further research.

Improving feed efficiency (FE) is essential for enhancing productivity, reducing production costs, and minimizing environmental impacts in the swine industry. Fecal microbiota and their metabolites play important roles in nutrient metabolism and energy utilization. This study aimed to investigate the fecal microbiota and associated metabolites in pigs with divergent feed conversion ratios (FCR). Fecal samples were collected from 20 Duroc × (Landrace × Yorkshire) (DLY) commercial pigs exhibiting extremely high (HFCR, n = 10) and low (LFCR, n = 10) FCR for analysis using 16S rRNA gene sequencing and liquid chromatography–mass spectrometry (LC-MS). The microbiota analysis revealed significantly higher abundances of Ruminococcus, Prevotella, Akkermansia, and Eubacterium in LFCR pigs (p < 0.05), while pathogenic bacteria predominated in HFCR pigs (p < 0.05). LC-MS metabolomics identified significant variations in metabolites involved in steroid hormone biosynthesis and primary bile acid metabolism between the two groups (p < 0.05). Spearman correlation analysis further demonstrated significant positive correlations between Ruminococcaceae_NK4A214_group and [Eubacterium]_coprostanogenes_group with bile acid metabolites, as well as between Akkermansia and steroid hormone synthesis (p < 0.05). These findings suggest a potential role for specific microbes and metabolites that are associated with feed efficiency, and warrant validation in pig feeding trials and fecal microbiota transplantation (FMT).

The southeastern Tibet region is characterized by rugged terrain and relative isolation, which has significantly constrained the development of agriculture. However, due to the extremely limited archaeological and historical records available, its important role in the history of agricultural development in Tibet has been overlooked. This study focuses on the Linzhi and Changdu regions of southeastern Tibet, integrating limited archival, historical, and documentary data. By reconstructing historical settlement patterns and population data, this study estimates the arable land area during the Tubo, Yuan, Ming, and Qing dynasties. Using a grid-based model, it reconstructs the distribution patterns of arable land during these periods, aiming to provide a reference for the development of agriculture in Tibet. The research findings indicate the following: (1) During historical periods, settlements in southeastern Tibet were primarily distributed in flat, resource-rich alluvial plains at medium to high altitudes. Settlement types exhibited spatial differentiation: Post stations were primarily situated along major transportation routes that connected river valleys, as well as at high mountain passes. Temples tended to occupy moderately steep slopes, while manors were concentrated in low-lying valleys. (2) During the Tubo, Yuan, Ming, and Qing periods, the total arable land area and cultivation rate in southeastern Tibet were generally low, with total arable land areas of 28,085 hm2, 29,449 hm2, 25,319 hm2, and 24,371 hm2, respectively, and cultivation rates of 0.12%, 0.13%, 0.11%, and 0.11%, respectively. (3) Farmland was predominantly distributed along the Yarlung Zangbo, Jinsha, Lancang, and Nu Rivers and their broader tributary valleys. Natural constraints resulted in a highly fragmented farmland distribution.

Human coronaviruses (CoV) cause respiratory infections that range from mild to severe. CoVs are a large family of viruses with considerable genetic heterogeneity and a multitude of viral types, making preventing and treating these viruses difficult. Comprehensive treatments that inhibit CoV infections fulfill a pressing medical need and may be immensely valuable in managing emerging and endemic CoV infections. As the main protease (M pro ) is highly conserved across many CoVs, this protease has been identified as a route for broad CoV inhibition. We utilize the advanced generative chemistry platform Chemistry42 for de novo molecular design and obtained novel small-molecule, non-peptide-like inhibitors targeting the SARS-CoV-2 M pro . ISM3312 is identified as an irreversible, covalent M pro inhibitor from extensive virtual screening and structure-based optimization efforts. ISM3312 exhibits low off-target risk and outstanding antiviral activity against multiple human coronaviruses, including SARS-CoV-2, MERS-CoV, 229E, OC43, NL63, and HKU1 independent of P-glycoprotein (P-gp) inhibition. Furthermore, ISM3312 shows significant inhibitory effects against Nirmatrelvir-resistant M pro mutants, suggesting ISM3312 may contribute to reduced viral escape in these settings. Incorporating ISM3312 and Nirmatrelvir into antiviral strategy could improve preparedness and reinforce defenses against future coronavirus threats. A novel covalent inhibitor, ISM3312, targets the main protease of multiple human coronaviruses, including drug-resistant strains, and shows broad antiviral activity. It offers a promising therapeutic strategy against current and future coronavirus threats.

Objective: To observe the clinical efficacy of Chinese herbal medicine combined with Liuzijue exercise on the physiological symptoms and quality of life (QoL) in postoperative patients with early-stage lung cancer. Methods: One hundred and eighty-three lung cancer patients who underwent video-assisted thoracoscopic surgery (VATS) were categorize into either a traditional Chinese medicine treatment group (CM) or a control group (non-traditional Chinese medicine treatment, NC), among whom 73 underwent Chinese herbal medicine and Liuzijue therapy, while 110 underwent no comprehensive treatment with traditional Chinese medicine. The propensity score matching (PSM) method with a 1:2 ratio was used to balance the baseline characteristics and evaluate the efficacy of CM in improving postoperative symptoms and QoL. Results: Cough, dyspnea, chest pain, and fatigue were the most common clinical symptoms after VATS. Except for chest pain, they were all correlated with the scope of operation (P < .05). After PSM, 165 patients were identified in the matched cohort, and the covariates of gender, age, operative site, and scope of operation were balanced between the 2 groups (P > .05). In the domain of global health status, the improvement in QoL in CM was greater than that in NC (6.06 ± 15.83 vs −1.06 ± 14.68, P = .005). In terms of symptoms, improvements in cough (1.69 ± 3.15 vs 0.38 ± 2.63, P = .006), dyspnea during climbing stairs (−10.30 ± 16.82 vs −1.82 ± 17.97, P = .004), and pain (−0.76 ± 1.32 vs −0.08 ± 1.31, P = .002) in CM were better than in NC. Conclusion: Comprehensive treatment with traditional Chinese medicine (TCM) can provide therapeutic benefits in physiological rehabilitation after VATS for cancer.

Human common cold coronaviruses (CCCoVs, e.g., 229E, NL63, OC43, HKU1) hold critical yet underexplored significance in understanding coronavirus evolutionary dynamics and immune cross‐protection, offering insights for predicting emerging pathogens and developing pan‐coronavirus vaccines. However, research is hindered by the lack of animal models due to strict human‐specific tropism and the confounding effects of frequent co‐infections from clinical samples, which obscure virus‐specific pathogenesis. Although lung‐humanized mice have been used in SARS‐CoV‐2 studies, their application to CCCoVs remains unvalidated and relies on logistically challenging fresh human tissues. This study optimizes a transplantation strategy using cryopreserved human fetal lung tissue, achieving enhanced engraftment efficiency. And the refined model supports robust infection by all four major CCCoVs and demonstrates the therapeutic efficacy of Paxlovid against HKU1. Furthermore, comparative analysis reveals phenotypic distinctions in human immune cells between native mouse lungs and human lung implants in lung‐immune dual‐humanized mice. The model also enables validation of virus‐specific T cell responses and assessment of SARS‐CoV‐2 cross‐reactivity post‐HKU1 infection. Overall, this study establishes a scalable platform using cryopreserved tissues for respiratory virus research, overcoming prior limitations in modeling human‐specific tropism and dissecting immune‐pathogen interactions. Cryopreserved lung‐humanized mice overcome the dependency to fresh tissues and permit head‐to‐head profiling of all four human common cold coronaviruses versus SARS‐CoV‐2 infection; the model validates Paxlovid efficacy against HKU1 and, when coupled with human immune‐system engraftment, enables interrogation of lung‐resident human immunity and HKU1‐induced cross‐reactive T cells to SARS‐CoV‐2.

Differentially private synthetic data provide a powerful mechanism to enable data analysis while protecting sensitive information about individuals. In this thesis, we present a highly effective algorithmic approach for generating ε-differentially private synthetic data in a bounded metric space with near-optimal utility guarantees under the 1-Wasserstein distance. In particular, for a dataset X in the hypercube [0, 1] d, our algorithm generates synthetic dataset Y such that the expected 1-Wasserstein distance between the empirical measure of X and Y is O((εn)−1/d) for d ≥ 2, and is O(log2 (εn)(εn)−1) for d = 1. The accuracy guarantee is optimal up to a constant factor for d ≥ 2, and up to a logarithmic factor for d = 1. Our algorithm has a fast running time of O(εdn) for all d ≥ 1 and demonstrates improved accuracy compared to former results for d ≥ 2.However, when the data lie in a high-dimensional space, the accuracy of the synthetic data suffers from the curse of dimensionality. We further propose a differentially private algorithm to generate low-dimensional synthetic data efficiently from a high-dimensional dataset with a utility guarantee with respect to the 1-Wasserstein distance. A key step of our algorithm is a private principal component analysis (PCA) procedure with a near-optimal accuracy bound that circumvents the curse of dimensionality. Unlike the standard perturbation analysis, our analysis of private PCA works without assuming the spectral gap for the covariance matrix. For the data lying on a d′ -dimensional linear subspace, we successfully overcome the curse of high dimensionality and improve the accuracy to O(n−1/d′ ).We also consider the synthetic data generation with differential privacy under the online setting where data is continually released. For a data stream within the hypercube [0, 1]d and an infinite time horizon, we develop an online algorithm that generates a differentially private synthetic dataset at each time t. This algorithm achieves a near-optimal accuracy bound of O(log(t)t −1/d) for d ≥ 2 and O(log4.5 (t)t −1) for d = 1 in the 1-Wasserstein distance. This result extends the previous work on the continual release model for counting queries to Lipschitz queries. Compared to the offline case, where the entire dataset is available at once, our approach requires only an extra polynomially logarithmic factor in the accuracy bound.

Background There is no research to prove the association between irritability and lung cancer, our study performed a Mendelian randomization (MR) approach to elucidate the causal relationship of irritability with lung cancer risk. Methods Genome-wide association studies (GWAS) data of irritability, lung cancer and gastroesophageal reflux disease (GERD) were downloaded from a public database for two-sample MR analysis. Independent single-nucleotide polymorphisms (SNPs) associated with irritability and GERD were selected as instrumental variables (IVs). Inverse variance weighting (IVW) and weighted median method were used to analyze causality. Results There is an association between irritability and lung cancer risk (OR IVW  = 1.01, 95% CI = [1.00, 1.02], P  = 0.018; OR weighted median  = 1.01, 95% CI = [1.00, 1.02], P  = 0.046), and GERD might account for about 37.5% of the association between irritability and lung cancer. Conclusions This study confirmed the causal effect between irritability and lung cancer through MR analysis, and found that GERD played an essential mediating role in this relationship, which can partly indicate the role of the “inflammation-cancer transformation” process in lung cancer.

The COVID-19 pandemic, which was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a worldwide health crisis due to its transmissibility. SARS-CoV-2 infection results in severe respiratory illness and can lead to significant complications in affected individuals. These complications encompass symptoms such as coughing, respiratory distress, fever, infectious shock, acute respiratory distress syndrome (ARDS), and even multiple-organ failure. Animal models serve as crucial tools for investigating pathogenic mechanisms, immune responses, immune escape mechanisms, antiviral drug development, and vaccines against SARS-CoV-2. Currently, various animal models for SARS-CoV-2 infection, such as nonhuman primates (NHPs), ferrets, hamsters, and many different mouse models, have been developed. Each model possesses distinctive features and applications. In this review, we elucidate the immune response elicited by SARS-CoV-2 infection in patients and provide an overview of the characteristics of various animal models mainly used for SARS-CoV-2 infection, as well as the corresponding immune responses and applications of these models. A comparative analysis of transcriptomic alterations in the lungs from different animal models revealed that the K18-hACE2 and mouse-adapted virus mouse models exhibited the highest similarity with the deceased COVID-19 patients. Finally, we highlighted the current gaps in related research between animal model studies and clinical investigations, underscoring lingering scientific questions that demand further clarification.

Lung‐Immune Dual‐Humanized Mouse Using Cryopreserved Tissue The cover illustrates a frozen seed planted underground, symbolizing cryopreserved human fetal lung tissue transplanted into a mouse. Over time, it grows into a lung‐shaped tree, where the trunk represents the trachea, the branches represent the bronchi, and the leaves represent the alveoli. The left side portrays healthy lung tissue in vibrant green, while the right side depicts virus‐infected lung with yellowing and withering leaves. Together, the image highlights the developmental potential of cryopreserved tissue and its capacity to model viral infection and lung pathology in vivo. More details can be found in the Research Article by Shuai Ding, Jincun Zhao, Yan Li, and co‐workers (DOI: 10.1002/advs.202512097).