Lung cancer is the most common malignant tumor worldwide, ranking first in both incidence and mortality rates. According to the latest statistics from the International Agency for Research on Cancer (IARC), approximately 2.5 million new cases and around 1.8 million deaths from lung cancer occurred in 2022, placing a tremendous burden on global healthcare systems. The high mortality rate of lung cancer is closely linked to its subtle early symptoms, which often lead to diagnosis at advanced stages. This not only complicates treatment but also results in substantial economic losses. Current treatment options for lung cancer include surgery, radiotherapy, chemotherapy, targeted drug therapy, and immunotherapy. Among these, immunotherapy has emerged as the most groundbreaking advancement in recent years, owing to its unique antitumor mechanisms and impressive clinical benefits. Unlike traditional therapies such as radiotherapy and chemotherapy, immunotherapy activates or enhances the patient’s immune system to recognize and eliminate tumor cells. It offers advantages such as more durable therapeutic effects and relatively fewer toxic side effects. The main approaches to lung cancer immunotherapy include immune checkpoint inhibitors, tumor-specific antigen-targeted therapies, adoptive cell therapies, cancer vaccines, and oncolytic virus therapies. Among these, immune checkpoint inhibitors and tumor-specific antigen-targeted therapies have received approval from the U.S. Food and Drug Administration (FDA) for clinical use in lung cancer, significantly improving outcomes for patients with advanced non-small cell lung cancer. Although other immunotherapy strategies are still in clinical trials, they show great potential in improving treatment precision and efficacy. This article systematically reviews the latest research progress in lung cancer immunotherapy, including the development of novel immune checkpoint molecules, optimization of treatment strategies, identification of predictive biomarkers, and findings from recent clinical trials. It also discusses the current challenges in the field and outlines future directions, such as the development of next-generation immunotherapeutic agents, exploration of more effective combination regimens, and the establishment of precise efficacy prediction systems. The aim is to provide a valuable reference for the continued advancement of lung cancer immunotherapy.

In recent years, the deep integration of artificial intelligence (AI) into medical education has created new opportunities for teaching Biochemistry and Molecular Biology, while also offering innovative solutions to the pedagogical challenges associated with protein structure and function. Focusing on the case of anaplastic lymphoma kinase (ALK) gene mutations in non-small-cell lung cancer (NSCLC), this study integrates AI into case-based learning (CBL) to develop an AI-CBL hybrid teaching model. This model features an intelligent case-generation system that dynamically constructs ALK mutation scenarios using real-world clinical data, closely linking molecular biology concepts with clinical applications. It incorporates AI-powered protein structure prediction tools to accurately visualize the three-dimensional structures of both wild-type and mutant ALK proteins, dynamically simulating functional abnormalities resulting from conformational changes. Additionally, a virtual simulation platform replicates the ALK gene detection workflow, bridging theoretical knowledge with practical skills. As a result, a multidimensional teaching system is established—driven by clinical cases and integrating molecular structural analysis with experimental validation. Teaching outcomes indicate that the three-dimensional visualization, dynamic interactivity, and intelligent analytical capabilities provided by AI significantly enhance students’ understanding of molecular mechanisms, classroom engagement, and capacity for innovative research. This model establishes a coherent training pathway linking “fundamental theory-scientific research thinking-clinical practice”, offering an effective approach to addressing teaching challenges and advancing the intelligent transformation of medical education.

The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

Background As one of the key populations in the prevention and treatment of iodine deficiency disorders, it is important to continuously monitor the iodine nutritional level of school-age children. The current reference interval for thyroid volume in China is based on age only, without taking into account differences in individual developmental levels, and the distribution of thyroid volume may vary regionally due to economic, demographic, and environmental factors. The current reference cut-off points for thyroid volume proposed by the World Health Organization are not based on the Chinese population. Objective To understand the iodine nutritional status and distribution of thyroid volume (Tvol) among children aged 8-10 years in Huangpu District, Shanghai, China, to identify impact factors of Tvol, and to propose a reference range upper limit for local thyroid health surveillance, so as to provide a basis for goiter control and prevention. Methods Six hundred children aged 8-10 years in Huangpu District were recruited in 2017, 2020, and 2023, and body height, weight, thyroid volume, urinary iodine, and iodine content of household edible salt were determined. A multilevel model was constructed using population density and area as regional variables, and age, body surface area (BSA), and body mass index (BMI) as potential impact factors for at the individual level, to assess their effects on thyroid volume. Quantile regression of thyroid volume was performed, and the 98th percentile (P₉₈) of thyroid volume was predicted based on age and BSA. Results The iodized salt coverage in the households of surveyed children in 2017, 2020, and 2023 was 72.0%, 57.0%, and 48.0%, respectively, and the iodized salt coverage decreased by year (χ²=24.31, P<0.001). The urinary iodine level of children in 2017 was higher than that in 2020 and 2023 (χ²=18.77, P<0.001). The Tvol medians of children in 2017, 2020, and 2023 were 2.29, 2.49, and 2.97 mL, respectively, and the Tvol increased by year (χ²=60.04, P<0.001). The proportion of goiter was higher in children in 2023 than in 2017 and 2020 (χ²=6.57, P<0.05). Sex differences were not statistically significant for urinary iodine levels, thyroid volume, and goiter. The median Tvol was 2.26, 2.58, and 2.76 mL in children of 8, 9, and 10 years old respectively, and the Tvol increased with age (χ²=49.02, P <0.001). Tvol was positively correlated with age, BSA, and BMI with correlation coefficients of 0.2846, 0.3723, and 0.2950, respectively. The final quantile regression model showed that the strongest effect of BSA was associated with the 98th percentile of Tvol. Multilevel models considering population density or area as regional variables failed to achieve convergence. Conclusion To establish the upper limit of the reference interval for thyroid volume of healthy children in Huangpu District, the effects of age and BSA should be considered at the individual level, and the upper limit of the normal interval for goiter screening is suggested to be the 98th percentile value of BSA at the same age. In addition, the adaptability of population density and regional area as indicators of regional aggregation of thyroid volume distribution still needs to be further explored.

Eight compounds were isolated and purified from the ethyl acetate part of 70% acetone extract of Rehmannia glutinosa by various chromatographic techniques such as silica gel, MCI gel CHP-20, ODS, Toyopearl HW-40C, combined with TLC and semi-preparative HPLC. Their structures were elucidated by modern spectroscopy techniques (NMR, MS, UV, IR), and identified as neomartynoside A (1), osmanthuside B₆ (2), martynoside (3), isomartynoside (4), (E)-p-hydroxycinnamic acid (5), caffeic acid (6), ferulic acid (7), and methyl caffeate (8). Compound 1 is a new phenylethanol glycoside, which was identified as neomartynoside A. Compound 2 was isolated from Rehmannia glutinosa for the first time. In addition, compounds 2, 6 and 7 significantly increased relative glucose consumption, showing potential hypoglycemic activity.

Xanthine oxidase (XO) is an important therapeutic target for the treatment of hyperuricemia and gout. Based on the previously identified potent XO inhibitor 1, seventeen oxadiazoles and their ring-opening analogues were designed and synthesized via the bioisostere replacement strategy. Among them, compounds 2l, 2n, and 3b showed obvious XO inhibitory activity at the concentration of 10 μmol·L^-1, and compound 3b exhibited an IC₅₀ value of 1.45 μmol·L^-1.

[Objective] To explore the accuracy and feasibility of non-invasive prenatal diagnosis of fetal RhE genotype using cell-free fetal DNA (cff-DNA) from maternal peripheral blood. [Methods] A total of 134 pregnant women with single fetuses and RhE-negative blood group were selected from our hospital from November 2023 to August 2024. Free DNA extraction kit was used to extract free DNA from peripheral blood of pregnant women, and the RhE blood group genotype of free DNA was detected by real-time fluorescent quantitative PCR (RT-qPCR). If the qPCR amplification signal of the sample was negative, the methylated RASSF1A gene was amplified, and the positive amplification result was used as a sign of successful extraction of cff-DNA. Serological microcolumn gel method was used to detect the phenotype of RhE blood group in neonatal peripheral blood. [Results] Among the 134 maternal peripheral blood samples, the cff-DNA detection of RhE blood group phenotypes was consistent with the RhE blood group genotyping of neonatal peripheral blood in 133 cases, including 90 cases of Rhee genotype and 43 cases of RhE genotype, with diagnostic concordance rate of 99.3%, sensitivity of 97.7%, specificity of 100%, youden index of 0.977, area under ROC curve of 0.995, the Kappa value of 0.983, positive predictive value of 100%, and negative predictive value of 98.9%. The sample of 1 case failed to be detected. After the amplification of methylated RASSFIA gene, it was confirmed that the reason for the failure was that no cff-DNA was extracted from the sample. The diagnostic concordance rates of the first, second and third trimesters were 93.8% (15/16), 100% (51/51) and 100% (67/67), respectively. Fisher's exact test method was used to calculate the P value, which was P>0.05, indicating that there was no statistical significance in the difference of diagnostic concordance rate among the three pregnancy periods, and there was no difference in the detection concordance rate of this method in different pregnancy periods. [Conclusion] The use of cff-DNA in maternal peripheral blood for the detection of fetal RhE blood group genotype is an accurate and highly feasible non-invasive prenatal diagnostic method, which is helpful for the clinical diagnosis of fetal and neonatal hemolytic disease caused by anti-E antibody.

The innate immune system detects cellular stressors and microbial infections, activating programmed cell death (PCD) pathways to eliminate intracellular pathogens and maintain homeostasis. Among these pathways, pyroptosis, apoptosis, and necroptosis represent the most characteristic forms of PCD. Although initially regarded as mechanistically distinct, emerging research has revealed significant crosstalk among their signaling cascades. Consequently, the concept of PANoptosis has been proposed—an inflammatory cell death pathway driven by caspases and receptor-interacting protein kinases (RIPKs), and regulated by the PANoptosome, which integrates key features of pyroptosis, apoptosis, and necroptosis. The core mechanism of PANoptosis involves the assembly and activation of the PANoptosome, a macromolecular complex composed of three structural components: sensor proteins, adaptor proteins, and effector proteins. Sensors detect upstream stimuli and transmit signals downstream, recruiting critical molecules via adaptors to form a molecular scaffold. This scaffold activates effectors, triggering intracellular signaling cascades that culminate in PANoptosis. The PANoptosome is regulated by upstream molecules such as interferon regulatory factor 1 (IRF1), transforming growth factor beta-activated kinase 1 (TAK1), and adenosine deaminase acting on RNA 1 (ADAR1), which function as molecular switches to control PANoptosis. Targeting these switches represents a promising therapeutic strategy. Furthermore, PANoptosis is influenced by organelle functions, including those of the mitochondria, endoplasmic reticulum, and lysosomes, highlighting organelle-targeted interventions as effective regulatory approaches. Cardiovascular diseases (CVDs), the leading global cause of morbidity and mortality, are profoundly impacted by PCD. Extensive crosstalk among multiple cell death pathways in CVDs suggests a complex regulatory network. As a novel cell death modality bridging pyroptosis, apoptosis, and necroptosis, PANoptosis offers fresh insights into the complexity of cell death and provides innovative strategies for CVD treatment. This review summarizes current evidence linking PANoptosis to various CVDs, including myocardial ischemia/reperfusion injury, myocardial infarction, heart failure, arrhythmogenic cardiomyopathy, sepsis-induced cardiomyopathy, cardiotoxic injury, atherosclerosis, abdominal aortic aneurysm, thoracic aortic aneurysm and dissection, and vascular toxic injury, thereby providing critical clinical insights into CVD pathophysiology. However, the current understanding of PANoptosis in CVDs remains incomplete. First, while PANoptosis in cardiomyocytes and vascular smooth muscle cells has been implicated in CVD pathogenesis, its role in other cell types—such as vascular endothelial cells and immune cells (e.g., macrophages)—warrants further investigation. Second, although pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) are known to activate the PANoptosome in infectious diseases, the stimuli driving PANoptosis in CVDs remain poorly defined. Additionally, methodological challenges persist in identifying PANoptosome assembly in CVDs and in establishing reliable PANoptosis models. Beyond the diseases discussed, PANoptosis may also play a role in viral myocarditis and diabetic cardiomyopathy, necessitating further exploration. In conclusion, elucidating the role of PANoptosis in CVDs opens new avenues for drug development. Targeting this pathway could yield transformative therapies, addressing unmet clinical needs in cardiovascular medicine.

Objective: To evaluate the application of blood conservation measures in obstetric patients with different red blood cell transfusion volumes and to assess the impact of different transfusion volumes on postpartum outcomes. Methods: A retrospective investigation was conducted on 448 obstetric patients who received blood transfusions at the Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine from January 2016 to December 2022. Patients were divided into four groups (1-2 units group, 3-4 units group, 5-6 units group, and >6 units group) based on the volumes of red blood cells (RBCs) transfused during and within 7 days after delivery. The maternal physiological indicators, pre- and postpartum laboratory test indicators, obstetric complications, application of blood conservation measures, use of blood products, and postpartum outcomes were reviewed. The clinical characteristics, application of blood conservation measures, and their impact on postpartum outcomes were compared among different transfusion groups. Results: There were statistically significant differences in the multivariate logistic analysis of history of previous cesarean section (OR=1.781), eclampsia/pre-eclampsia/(OR=1.972) and postpartum blood loss>1 000 mL（OR=1.699）(P<0.05) among different transfusion groups. In terms of blood conservation measures, the more RBCs transfused, the higher the rate of mothers receiving blood conservation measures such as balloon occlusion, arterial ligation, autologous blood transfusion with a cell saver, and hysterectomy. With the increase in the volume of RBCs transfusion, the demand for fresh frozen plasma（FFP）, cryoprecipitate, and platelet transfusions also increased. The hospitalization days for the four groups of parturients were 6.0 (4.0-9.0), 7.5 (5.0-14.8), 7.0 (4.5-13.0) and 11.0 (9.0-20.5), respectively (P<0.05) and the rates of ICU transfer were 2.0% (5/250), 9.4% (12/128),18.2% (6/33) and 51.4% (19/37), respectively (P<0.05). Both increased significantly with the increase in the volume of RBCs transfusion, and the differences between groups were statistically significant. Conclusion: Parturients who received higher volume of RBCs had multiple risks factors for bleeding before childbirth, had higher postpartum blood loss, and had a higher rate of application of various blood conservation measures. In addition, an increase in the volume of RBCs transfusion may have adverse effects on postpartum recovery.