Objective To systematically evaluate the risk factors for postoperative delirium (POD) in patients undergoing pneumonectomy. Methods PubMed, Web of Science, Cochrane Library, CNKI, Wanfang, and VIP databases were searched from the inception to November 7, 2024 for cross-sectional studies, case-control studies, and cohort studies on POD in patients undergoing pneumonectomy. Two researchers independently screened the literature, extracted data, and evaluated the quality of the literature. RevMan 5.4.1 software was used for meta-analysis. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the literature. Results A total of 12 studies were included, with 5 574 patients. The NOS scores of the literature were all≥6 points. Meta-analysis results showed that age (≥60 years) [OR=2.43, 95%CI (2.01, 2.93), P<0.01], American Society of Anesthesiologists (ASA) classification (Ⅳ) [OR=8.74, 95%CI (5.23, 14.61), P<0.01], history of diabetes [OR=12.81, 95%CI (10.45, 15.71), P<0.01], history of cerebrovascular disease [OR=3.00, 95%CI (2.46, 3.67), P<0.01], depression [OR=7.27, 95%CI (5.46, 9.67), P<0.01], squamous cell carcinoma [OR=4.79, 95%CI (1.83, 12.51), P<0.01], malnutrition [OR=5.25, 95%CI (3.35, 8.25), P<0.01], sleep disorders [OR=2.79, 95%CI (2.28, 3.42), P<0.01], and duration of one-lung ventilation during surgery [OR=1.32, 95%CI (1.11, 1.57), P<0.01] were all risk factors for POD, while high body mass index (BMI) [OR=0.96, 95%CI (0.95, 0.97), P<0.01] was a protective factor for POD. Conclusion Age (≥60 years), ASA classification (Ⅳ), history of diabetes, history of cerebrovascular disease, depression, squamous cell carcinoma, malnutrition, sleep disorders, and duration of one-lung ventilation during surgery are independent risk factors for POD, while high BMI is a protective factor.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

OBJECTIVE To systematically evaluate the efficacy and safety of tislelizumab in the treatment of advanced non- small cell lung cancer （NSCLC）. METHODS Computerized searches were conducted in PubMed， Embase， the Cochrane Library， CNKI， Wanfang and other Chinese and English databases to collect randomized controlled trials （RCTs） on tislelizumab for advanced NSCLC. The search period was from the establishment of the databases to December 2024. After strictly screening the literature， extracting data and conducting quality evaluations in accordance with the inclusion and exclusion criteria， a meta-analysis was performed using RevMan 5.3 and Stata 16.0 software. RESULTS A total of 18 RCTs involving 2 337 patients were included， with 1 283 in the experimental group and 1 054 in the control group. The meta-analysis results showed that the objective response rate [RR＝1.61， 95%CI （1.48， 1.75）， P＜0.000 01]， disease control rate [RR＝1.21， 95%CI （1.13， 1.29）， P＜0.000 01]， progression free survival [HR＝0.55， 95%CI （0.45， 0.66）， P＜0.000 01]， and overall survival [HR＝0.78， 95%CI（0.62， 0.97）， P＝0.03] were significantly better in the experimental group than in the control group. There was no statistically significant difference in the incidence of adverse reactions between the two groups [RR＝1.00， 95%CI （0.73， 1.37）， P＝1.00]； among the common adverse reactions， only the incidence of liver function impairment was significantly higher in the experimental group than in the control group [RR＝1.30， 95%CI （1.10， 1.54）， P＜0.01]. CONCLUSIONS Tislelizumab in combination with chemotherapy or targeted drugs significantly improves the efficacy in patients with advanced NSCLC without increasing the risk of adverse reactions overall. However， liver function should be closely monitored during treatment.

Objective Radiation-induced brain injury (RIBI) is a common complication of radiotherapy for the head and neck tumors, and the current treatment methods are limited. Repetitive transcranial magnetic stimulation (rTMS), as a non-invasive neural regulation technique, has shown great potential in neuroprotection. However, the parameter selection and biological safety of rTMS in the prevention and treatment of RIBI have not been reported. Methods Using a mouse model of RIBI, this study employed three rTMS frequencies (5, 10, and 25 Hz) for intervention. Biochemical and pathological assays were conducted to identify the optimal stimulation parameter. Subsequently, this parameter was used to evaluate the biological safety in normal mice. Results Under the conditions of this experiment, rTMS interventions with all three frequencies could reduce the levels of serum brain injury markers (NSE and S100B) and inflammatory factors in mice (P < 0.001), and alleviate the morphological and structural damage of hippocampal tissue. The 10 Hz rTMS could significantly promote hippocampal neurogenesis in RIBI mice (P < 0.05). Furthermore, 10 Hz rTMS showed no significant effects on the cognitive function and mood of normal mice. The intervention did not significantly change the morphology and structure of the main organs, blood biochemical indicators, and the level of hippocampal neurogenesis in mice. Conclusion The 10 Hz rTMS is optimal for the prevention and treatment of RIBI with high biological safety.

Objective To investigate the impact of continuous nebulization therapy after lung transplantation on pulmonary function and related complications in lung transplant recipients. Methods A retrospective analysis was conducted on the general data of 71 recipients who underwent allogeneic lung transplantation at the Department of Thoracic Surgery, the First Affiliated Hospital of Zhengzhou University, from June 2013 to December 2024. Recipients were divided into observation group (those who continued nebulization therapy for more than 3 months after discharge) and control group (those who discontinued nebulization therapy on their own). The main observation indicators were pulmonary function indicators at 6 months after surgery, including forced expiratory volume in the first second as a percentage of predicted value (FEV₁% pred), forced vital capacity as a percentage of predicted value (FVC% pred), ratio of forced expiratory volume in the first second to forced vital capacity as a percentage of predicted value (FEV₁/FVC% pred), forced expiratory flow at 25%, 50% and 75% of forced vital capacity as a percentage of predicted value, and the percentage of predicted value of corrected carbon monoxide diffusion capacity measured by single-breath method, as well as the ratio of corrected carbon monoxide diffusion capacity to alveolar volume as a percentage of predicted value. Additionally, the annual incidence of postoperative pulmonary infections, survival rate and the rate of no severe airway complications were analyzed. Results At 6 months after lung transplantation, the FEV₁% pred and FVC% pred of the observation group were better than those of the control group [FEV₁% pred was 76% (60%, 91%) vs. 67% (62%, 78%), FVC% pred was (75 ± 13)% vs. (69 ± 11)%, both P<0.05]. The observation group had a lower annual incidence of pulmonary infections compared to the control group (P = 0.023), with a risk of 0.485 times that of the control group. There were no statistically significant differences between the two groups in median survival time and the rate of no severe airway complications (both P>0.05). Conclusions Continuous nebulization therapy after lung transplantation may effectively improve pulmonary function, reduce the annual incidence of pulmonary infections, and play a positive role in the long-term maintenance of pulmonary function.

To clarify the occurrence and distribution of broad bean wilt virus 2(BBWV2) on Rehmannia glutinosa, this study collected 87 R. glutinosa samples with typical symptoms of viral disease such as chlorosis and crumple from Wenxian county and Wuzhi county in Jiaozuo city, Henan province and Qiaocheng district in Bozhou city, Anhui province. The BBWV2 CP target band was amplified from 37 R. glutinosa samples by RT-PCR technology. The total detection rate reached 42.5%, among which 43.0% was detected in samples from Henan province. The detection rate in samples from Anhui province was 37.5%. 37 BBWV2 CP sequences were obtained by cloning and sequencing of BBWV2 positive samples(data has been submitted to GenBank, accession numbers: PP407959-PP407995), and the sequence analysis of these CP sequences with 91 other BBWV2 isolates in GenBank showed a high genetic diversity with a consistency rate of 70.8%-100%. Meanwhile, phylogenetic analysis showed that BBWV2 could be divided into three groups according to CP sequences, among which the BBWV2 in R. glutinosa isolates obtained in this study were all located in group 3. This study identified the differences in the occurrence, distribution, and genetic diversity of BBWV2 in R. glutinosa from Henan province and Anhui province and provided a theoretical basis for the prevention and control of BBWV2.
Rehmannia/virology* ; Phylogeny ; Plant Diseases/virology* ; China ; Molecular Sequence Data ; Fabavirus/classification*

Aromatic immunity in traditional Chinese medicine(TCM) is the medical knowledge accumulated in the process of people's struggling with diseases. It plays an important role in plague prevention, disease treatment, health preservation, and rehabilitation, and has profound TCM basic theoretical support and abundant modern scientific evidence. With the in-depth promotion of the Healthy China initiative and the succession of health needs in the post-COVID-19 era, how to practice the health concept of aromatic immunity in TCM and develop its health service resources with high quality has become an important proposition to be discussed urgently. This paper summarizes the cognitive process, puts forward the basic concept, discusses the scientific connotation and clinical application value, and looks forward to the future development trend of aromatic immunity in TCM, aiming to provide guidance for the development of great health products and promote the application of aromatic immunity in TCM in serving people's health.
Medicine, Chinese Traditional/methods* ; Humans ; COVID-19/immunology* ; China ; Drugs, Chinese Herbal/therapeutic use* ; SARS-CoV-2

Understory planting of medicinal plants is a new planting mode that connects Chinese herbal medicine(CHM) with forest resources.The complex and variable understory environmental factors will inevitably affect the yield and quality of understory CHM.This research summarized the research progress on understory planting of medicinal plants based on forest types and environmental factors within the forest from the perspectives of understory light, air temperature and humidity, soil characteristics, and the interaction between crops within the forest.The results showed that the complex and variable light, temperature and humidity, and soil factors(such as fertility, acidity and alkalinity, and microorganisms) under the forest could affect the yield and quality of medicinal plants to varying degrees through physiological activities such as photosynthesis and respiration, resulting in a significant increase or decrease in yield and quality compared to open field cultivation.In addition, the competition or mutual benefit between different crops within the forest could lead to differences in the yield and quality of understory medicinal plants compared to open field cultivation.A reasonable combination of planting could achieve resource sharing and complementary advantages.Therefore, conducting systematic research on the effects of understory environmental factors on the yield and content of medicinal plants with different growth and development characteristics can provide theoretical guidance and technical references for formulating comprehensive strategies for understory planting of medicinal plants, such as selecting suitable medicinal plant varieties, optimizing planting density, and conducting reasonable forest management, thus contributing to the sustainable development and ecological protection of CHM.
Plants, Medicinal/growth & development* ; Forests ; Soil/chemistry* ; Environment ; Ecosystem ; Temperature

Viral infectious diseases, characterized by their intricate nature and wide-ranging diversity, pose substantial challenges in the domain of data management. The vast volume of data generated by these diseases, spanning from the molecular mechanisms within cells to large-scale epidemiological patterns, has surpassed the capabilities of traditional analytical methods. In the era of artificial intelligence (AI) and big data, there is an urgent necessity for the optimization of these analytical methods to more effectively handle and utilize the information. Despite the rapid accumulation of data associated with viral infections, the lack of a comprehensive framework for integrating, selecting, and analyzing these datasets has left numerous researchers uncertain about which data to select, how to access it, and how to utilize it most effectively in their research.This review endeavors to fill these gaps by exploring the multifaceted nature of viral infectious diseases and summarizing relevant data across multiple levels, from the molecular details of pathogens to broad epidemiological trends. The scope extends from the micro-scale to the macro-scale, encompassing pathogens, hosts, and vectors. In addition to data summarization, this review thoroughly investigates various dataset sources. It also traces the historical evolution of data collection in the field of viral infectious diseases, highlighting the progress achieved over time. Simultaneously, it evaluates the current limitations that impede data utilization.Furthermore, we propose strategies to surmount these challenges, focusing on the development and application of advanced computational techniques, AI-driven models, and enhanced data integration practices. By providing a comprehensive synthesis of existing knowledge, this review is designed to guide future research and contribute to more informed approaches in the surveillance, prevention, and control of viral infectious diseases, particularly within the context of the expanding big-data landscape.
Big Data ; Humans ; Virus Diseases/virology* ; Artificial Intelligence