Locally advanced non-small cell lung cancer (NSCLC) is a highly heterogeneous disease. For patients with driver gene-negative, unresectable NSCLC, traditional treatment primarily involves concurrent chemoradiotherapy. With the advent of the immunotherapy era, integrated treatment strategies combining concurrent chemoradiotherapy with immunotherapy have significantly improved therapeutic outcomes and substantially extended survival periods. This article summarizes the interaction mechanisms and clinical research progress of radiotherapy, chemotherapy, and immune checkpoint inhibitors in the treatment of NSCLC. This review also provides perspectives on the development of therapies in the future and predictive biomarkers, serving as a reference for treatment options for patients with unresectable locally advanced NSCLC.

Brain metastases are the most common intracranial tumors, and their incidence is increasing with the improvement of systemic treatments and survival rates. Optimal treatment usually requires a multidisciplinary approach, including radiotherapy, surgical resection, chemotherapy, targeted therapy, and immunotherapy. Stereotactic radiotherapy, compared to whole-brain radiotherapy, offers improved local control rates and reduced risk of neurocognitive impairment, and has become a new standard option for the treatment of brain metastases. Additionally, the widespread use of targeted and immune therapies in brain metastases has significantly improved the survival of some patients. This article reviews and integrates recent literature on the treatment of brain metastases and analyzes the role of stereotactic radiotherapy in comprehensive treatment, aiming to provide a reference for the selection of clinical treatment plans.

Maternal health during pregnancy has a direct impact on the risk and severity of neurodevelopmental disorders (NDDs) in the offspring, especially in the case of drug exposure. However, little progress has been made to assess the risk of drug exposure during pregnancy due to ethical constraints and drug use factors. We collected and manually curated sub-pathways and pathways (sub-/pathways) and drug information to propose an analytical framework for predicting drug candidates. This framework linked sub-/pathway activity and drug response scores derived from gene transcription data and was applied to human fetal brain development and six NDDs. Further, specific and pleiotropic sub-/pathways/drugs were identified using entropy, and sex bias was analyzed in conjunction with logistic regression and random forest models. We identified 19 disorder-associated and 256 regionally pleiotropic and specific candidate drugs that targeted risk sub-/pathways in NDDs, showing temporal or spatial changes across fetal development. Moreover, 5443 differential drug-sub-/pathways exhibited sex-biased differences after filling in the gender labels. A user-friendly NDDP visualization website ( https://ndd-lab.shinyapps.io/NDDP ) was developed to allow researchers and clinicians to access and retrieve data easily. Our framework overcame data gaps and identified numerous pleiotropic and specific candidates across six disorders and fetal developmental trajectories. This could significantly contribute to drug discovery during pregnancy and can be applied to a wide range of traits.
Humans ; Female ; Pregnancy ; Neurodevelopmental Disorders/metabolism* ; Male ; Prenatal Exposure Delayed Effects ; Fetal Development/drug effects* ; Drug Discovery/methods* ; Brain/metabolism*

ObjectiveTo understand the epidemic characteristics of influenza in Beijing from 2023 to 2024, and to provide a scientific basis for the prevention and control of influenza. MethodsData on influenza-like illness (ILI) from secondary level and above hospitals, etiology surveillance data, and influenza clusters outbreaks data from 2023‒2024 were used to analyze the epidemic trend and pathogenic characteristics of influenza. Furthermore, an influenza comprehensive index was used to categorize the epidemic intensity at the severity level. ResultsA total of 2 065 857 ILI cases were reported in 2023‒2024 epidemic season, and the percentage of ILI was 3.67%. The age group of 5‒14 years accounted for the highest proportion of ILI (30.48%). A total of 41 766 throat swabs from ILI were detected, with a positive rate of 17.28%.A (H3N2) (51.86%) and B Victoria (41.93%) were the most prevalent subtypes of influenza virus. Clustered influenza outbreaks occurred mainly in primary schools (57.78%) and middle schools (35.55%), mainly caused by the influenza A (H3N2) subtype (85.93%). According to the influenza comprehensive index (I), the period of influenza activity and above (I>0.5) lasted for a total of 37 weeks, accounting for 71.15% of the entire influenza season. ConclusionCompared with previous years, the epidemic level of influenza in Beijing was increased in 2023‒2024, and the peak time became earlier. The comprehensive index method can objectively evaluate the level of influenza epidemic and provide suggestions for the future prevention and control of influenza in Beijing.

Ferritin is widely present in various organisms and is responsible for storing excess iron to maintain iron balance in vivo.Due to its inherent targeting ability,natural cavity structure,reversible self-assembly,high biocompatibility,and easy modification,ferritin is considered to be an ideal delivery system,which is widely used in many fields.This review summarizes the biological characteristics,functionalization,drug loading strategies,research progress and application prospects of ferritin-based nanocarrier systems in biomedical fields,such as drug delivery,biocatalysis,photodynamic therapy,medical imaging and vaccine research,aiming to provide some reference for related biomedical research based on ferritin delivery systems.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.

Background With urbanization and residential space expansion, ecological environment and human health issues have become hot social topics. Forest health, as a way of seeking health in nature, has begun to receive public attention in the context of the gradually increasing sub-healthy population and various psychological and physical diseases at a young age. Objective To systematically evaluate the effects of forest therapy on selected physical and mental health indicators. Methods Relevant research literature was retrieved from domestic and international databases (China National Knowledge Infrastructure, Wanfang Database, China Biomedical Literature Service System, Web of Science, ScienceDirect, PubMed, Embase, and Cochrane Library), with a time range from database establishment to January 31, 2023. Relevant data were extracted for meta-analysis to explore the relationship between forest therapy and selected psychological and physiological indicators. Results A total of 85 articles were included, and the meta-analysis results showed that better scores of Profile of Mood States, Positive and Negative Affect Scale, Beck Depression Inventory, and State Trait Anxiety Scale were found in the forest group than those in the urban group (P<0.05); the levels of systolic blood pressure, diastolic blood pressure, heart rate, sympathetic nerve indicator [ln (LF/HF)], salivary cortisol, and serum inflammatory factors were lower in the forest group than in the urban group, while parasympathetic nerve indicator [ln (HF)] level was higher in the forest group than in the urban group (P<0.05). The results of subgroup analysis showed that the changes in heart rate (SMD=−1.62, 95%CI: −2.41, −0.82), ln (HF) (SMD=1.29, 95%CI: 0.73, 1.85), ln (LF/HF) (SMD=−1.49, 95%CI: −2.13, −0.86), and salivary cortisol (SMD=−0.53, 95%CI: −0.81, −0.25) were more significant when the duration of forest therapy was ≤ 0.5 h, the recovery effect on emotional state was better in the >0.5~3 h group (such as tension SMD=−2.40, 95%CI: −3.21, 1.59), and the reduction effects on systolic blood pressure (SMD=−0.53, 95%CI: −1.03, −0.03) and diastolic blood pressure (SMD=−0.42, 95%CI: −0.88, 0.04) were better in the >3 h group. Seated meditation showed better recovery effects on multiple indicators of Profile of Mood States (such as fatigue SMD=−2.26, 95%CI: −3.07, −1.45), while walking showed better recovery effects on physiological indicators such as blood pressure (systolic blood pressure SMD=−0.57, 95%CI: −1.07, −0.06; diastolic blood pressure SMD=−0.72, 95%CI: −1.36, −0.07) and heart rate (SMD=−1.51, 95%CI: −2.38, -0.64). Except for blood pressure, the health benefits of forest therapy in the younger age group were generally better than those in the middle-aged and elderly group. Conclusion Relaxed and comfortable psychological feeling is reported when practicing forest therapy; it can lower blood pressure and heart rate, regulate the autonomic nervous system; it can also reduce the release of stress hormones and lower serum levels of inflammatory factors, exerting an auxiliary recovery effect on cardiovascular and immune system disorders. At the same time, the therapy duration, form, and age of the subjects have a certain impact on the effects of forest therapy practice.

Objective:To explore the non-bacterial pathogen distribution, epidemiological characteristics, and clinical features of acute respiratory infections in children in Sichuan Province.Methods:Using a retrospective cohort study method, this study selected hospitalized children diagnosed with acute respiratory infections at West China Second Hospital of Sichuan University from February 2019 to January 2021, and tested 13 pathogens using polymerase chain reaction (PCR)-fragment analysis. The children were divided into infant group (<1 year old), toddler group (1 year old ≤ age <3 years old), preschool group (3 years old ≤ age <6 years old) and school-age group (6 years old ≤ age <18 years old). The distribution of pathogen positive rates, seasonal epidemic characteristics, clinical characteristics, and some laboratory test indicators were analyzed in children. Statistical analysis was performed on the results using SPSS 22.0 software, with count data expressed as percentages and inter group comparisons using SPSS 22.0 software χ2 Inspection. Results:A total of 2 922 pediatric patients were included in this study, with 1 748 (59.8%) positive for pathogens detected. Among them, 1 391 (79.6%) were detected as a single pathogen, and 357 (20.4%) were detected as a mixture of two or more pathogens. The most commonly detected pathogens were rhinovirus (HRV) (39.7%), syncytial virus (RSV) (22.8%), and parainfluenza virus (PIV) (12.5%). Pathogen positivity is more common in children under 6 years old ( χ2=146.59, P<0.001), with a slightly higher positivity rate in male children (61.3%, 1 047/1 707) than in female children (57.7%, 701/1 215) ( χ2=3.91, P=0.048), and compared with pathogen negative children, positive children are more prone to symptoms such as cough, wheezing, and shortness of breath ( χ2=259.15, 366.06, 12.48, P<0.001). The distribution of different pathogens varies among children of different age groups, and HRV is more common in children aged 1-3 and 3-6 years old ( χ2=9.74, P<0.001), while RSV is more common in children under 1 year old ( χ2=178.63, P<0.001), while mycoplasma pneumoniae (MP) and influenza virus (InfA/B) are less common in children under 1 year old ( χ2=92.54, 12.90,22.21, P<0.01). The prevalence of multiple pathogens showed seasonal changes. HRV showed a high prevalence trend in spring and autumn, while the prevalence of RSV infection was mainly seen in autumn and winter festivals. The positive rate of different pathogens after the outbreak of novel coronavirus pneumonia was significantly lower than that before the outbreak ( χ2=252.68, P<0.001). Conclusion:The detection rate of non-bacterial respiratory pathogens in children in Sichuan Province from 2019 to 2021 is high, which is prone to symptoms such as cough, wheezing, and shortness of breath, with HRV and RSV being the main types. The positive rate of respiratory pathogens varies among different age groups, genders, and seasons.

Objective:To explore the non-bacterial pathogen distribution, epidemiological characteristics, and clinical features of acute respiratory infections in children in Sichuan Province.Methods:Using a retrospective cohort study method, this study selected hospitalized children diagnosed with acute respiratory infections at West China Second Hospital of Sichuan University from February 2019 to January 2021, and tested 13 pathogens using polymerase chain reaction (PCR)-fragment analysis. The children were divided into infant group (<1 year old), toddler group (1 year old ≤ age <3 years old), preschool group (3 years old ≤ age <6 years old) and school-age group (6 years old ≤ age <18 years old). The distribution of pathogen positive rates, seasonal epidemic characteristics, clinical characteristics, and some laboratory test indicators were analyzed in children. Statistical analysis was performed on the results using SPSS 22.0 software, with count data expressed as percentages and inter group comparisons using SPSS 22.0 software χ2 Inspection. Results:A total of 2 922 pediatric patients were included in this study, with 1 748 (59.8%) positive for pathogens detected. Among them, 1 391 (79.6%) were detected as a single pathogen, and 357 (20.4%) were detected as a mixture of two or more pathogens. The most commonly detected pathogens were rhinovirus (HRV) (39.7%), syncytial virus (RSV) (22.8%), and parainfluenza virus (PIV) (12.5%). Pathogen positivity is more common in children under 6 years old ( χ2=146.59, P<0.001), with a slightly higher positivity rate in male children (61.3%, 1 047/1 707) than in female children (57.7%, 701/1 215) ( χ2=3.91, P=0.048), and compared with pathogen negative children, positive children are more prone to symptoms such as cough, wheezing, and shortness of breath ( χ2=259.15, 366.06, 12.48, P<0.001). The distribution of different pathogens varies among children of different age groups, and HRV is more common in children aged 1-3 and 3-6 years old ( χ2=9.74, P<0.001), while RSV is more common in children under 1 year old ( χ2=178.63, P<0.001), while mycoplasma pneumoniae (MP) and influenza virus (InfA/B) are less common in children under 1 year old ( χ2=92.54, 12.90,22.21, P<0.01). The prevalence of multiple pathogens showed seasonal changes. HRV showed a high prevalence trend in spring and autumn, while the prevalence of RSV infection was mainly seen in autumn and winter festivals. The positive rate of different pathogens after the outbreak of novel coronavirus pneumonia was significantly lower than that before the outbreak ( χ2=252.68, P<0.001). Conclusion:The detection rate of non-bacterial respiratory pathogens in children in Sichuan Province from 2019 to 2021 is high, which is prone to symptoms such as cough, wheezing, and shortness of breath, with HRV and RSV being the main types. The positive rate of respiratory pathogens varies among different age groups, genders, and seasons.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.