With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

The circadian clock plays a critical role in regulating various physiological processes, including gene expression, metabolic regulation, immune response, and the sleep-wake cycle in living organisms. Post-translational modifications (PTMs) are crucial regulatory mechanisms to maintain the precise oscillation of the circadian clock. By modulating the stability, activity, cell localization and protein-protein interactions of core clock proteins, PTMs enable these proteins to respond dynamically to environmental and intracellular changes, thereby sustaining the periodic oscillations of the circadian clock. Different types of PTMs exert their effects through distincting molecular mechanisms, collectively ensuring the proper function of the circadian system. This review systematically summarized several major types of PTMs, including phosphorylation, acetylation, ubiquitination, SUMOylation and oxidative modification, and overviewed their roles in regulating the core clock proteins and the associated pathways, with the goals of providing a theoretical foundation for the deeper understanding of clock mechanisms and the treatment of diseases associated with circadian disruption.
Protein Processing, Post-Translational/physiology* ; Circadian Rhythm/physiology* ; Humans ; Animals ; CLOCK Proteins/physiology* ; Circadian Clocks/physiology* ; Phosphorylation ; Acetylation ; Ubiquitination ; Sumoylation

Under the influence of long-term space flights and the confined space environment,it is very easy to induce space depression syndrome,mainly manifested as decreased emotional stability,sleep disorders,mental fatigue,etc.,which seriously affect the living conditions and working abilities of astronauts.The current treatment methods mainly focus on psychological support and drug intervention.Acupuncture has a good effect in treating depression.Therefore,starting from the TCM pathogenesis and modern medical pathogenesis of aerospace depression syndrome,we conducted literature retrieval from databases such as the Chinese Medical Classic,China National Knowledge Infrastructure(CNKI),Wanfang,VIP,PubMed,and Web of science.For the included literature,we adopted the stratified evidence scoring method and combined the TCM mechanism and modern medical mechanism of the effect of acupuncture.A prescription for acupuncture points was constructed to provide a basis for selecting acupuncture points for the prevention of aerospace depression syndrome through acupuncture.

Objective To report the genetic analysis of a family with a fetus suspected of Ellis-van Creveld(EVC)syndrome based on ultrasound findings such as ventricular septal defect(VSD),short long bones in the limbs and polydactyly,and to conduct a literature review to clarify the pathogenic cause.Methods A 27-year-old pregnant woman,who was pregnant for the first time and had no prior deliveries,was admitted to the prenatal diagnosis center of Shijiazhuang Obstetrics and Gynecology Hospital in October 2021.At 17 weeks of gestation,ultrasound detected multiple fetal malformations.The genomic DNA of the fetal proband's amniotic fluid cells and the parents'peripheral blood samples were sequentially subjected to chromosomal karyotype analysis,chromosomal microarray analysis(CMA),and whole exome sequencing(WES).Suspected pathogenic mutations were verified by Sanger sequencing in the proband and its parents.Subsequently,a Minigene in vitro experiment was used to analyze one splicing mutation.Meanwhile,databases such as PubMed were searched,and literature reports were combined for genetic analysis.Results Chromosomal karyotype analysis of the fetus showed no abnormalities,and CMA did not detect any copy number variation(CNV)with clinical significance.WES results revealed two mutations in the EVC gene(NM_153717.2)of the fetus:a nonsense mutation c.1405G>T(p.E469X)in exon 10 and a splicing mutation c.1886+5G>A in intron 13.Family verification using Sanger sequencing showed that the father was a carrier of the c.1405G>T(p.E469X)mutation in exon 10,and the mother was a carrier of the c.1886+5G>A mutation in intron 13.The compound heterozygous mutation of the fetus was inherited from the parents.According to the guidelines of the American College of Medical Genetics and Genomics(ACMG)for classifying genetic variations,c.1405G>T(p.E469X)was classified as likely pathogenic mutation(PVS1+PM2),and c.1886+5G>A was classified as likely pathogenic mutation(PM2+PM3_Strong).The Minigene experiment results showed that the c.1886+5G>A mutation caused a 115-bp segment retention in intron 13,further supporting its pathogenicity.Review of the literature showed that the typical clinical manifestations of EVC syndrome include short limbs,short ribs,postaxial polydactyly,nail and tooth dysplasia,and congenital heart defects.Gene mutations in EVC/EVC2 were found to be the main pathogenic cause through whole exome sequencing,with mutation types including missense mutations,large-scale duplications/deletions,in-frame microdeletions,nonsense mutations,frameshift mutations,and splicing mutations.Conclusions The compound heterozygous mutations in the EVC gene are the pathogenic cause of the fetus.The detection of these mutations expands the genetic variation spectrum of Ellis-van Creveld syndrome.

This article reports a successful case of preimplantation genetic testing (PGT) in a patient with autosomal dominant polycystic kidney disease type 2 (PKD2) combined with Robertsonian translocation. The patient carried a heterozygous frameshift mutation ( PKD2 c.428del, p.Gly143Alafs*90) and a Robertsonian translocation between chromosomes 14 and 15. Through combined PGT for monogenic disorders, structural rearrangements and aneuploidy screening, one euploid blastocyst free of the PKD2 mutation was selected from six embryos for transfer, resulting in the successful delivery of a healthy female infant. Follow-up until June 2025 confirmed normal developmental milestones. This case demonstrates that PGT can effectively mitigate dual genetic risks (monogenic disease and chromosomal abnormality), providing critical clinical insights for optimizing reproductive outcomes in patients with complex genetic backgrounds.

Small animal multimodal biomedical imaging refers to the integration of multiple imaging techniques within the same system or device to acquire comprehensive physiological and pathological information of small animals, such as mice and rats. With the continuous advancement of biomedical research, this cutting-edge technology has attracted extensive attention. Multimodal imaging techniques, based on diverse imaging principles, overcome the limitations of single-modal imaging through information fusion, significantly enhancing the overall system's sensitivity, temporal/spatial resolution, and quantitative accuracy. In the future, the integration of new materials and artificial intelligence will further boost its sensitivity and resolution. Through interdisciplinary innovation, this technology is expected to become the core technology of personalized medicine and expand its applications to drug development, environmental monitoring, and other fields, thus reshaping the landscape of biomedical research and clinical practice. This review summarized the progress on the application and investigation of multimodal biomedical imaging techniques, and discussed its development in the future.
Animals ; Multimodal Imaging/trends* ; Rats ; Mice ; Artificial Intelligence ; Diagnostic Imaging/methods* ; Magnetic Resonance Imaging ; Tomography, X-Ray Computed

OBJECTIVE: To explore the effect of acupuncture therapy on dysphagia in patients with Parkinson's disease. METHODS: This randomized controlled study lasted 42 days and included 112 patients with Parkinson's disease and dysphagia. Participants were randomly assigned to the experimental and control groups (56 cases each group) using the completely randomized design, all under routine treatment. The experimental group was given acupuncture therapy. The primary outcome was Penetration-Aspiration Scale (PAS). The secondary outcomes were (1) Standardized Swallowing Assessment (SSA), and (2) nutritional status including body mass index (BMI), serum albumin, prealbumin, and hemoglobin. Adverse events were recorded as safety indicators. RESULTS: One participant quitted the study midway. There were no significant differences in baseline assessment (P>0.05). After treatment, both groups showed significant improvement in PAS, SSA and nutritional status except for BMI of the control group. There were significant differences between the two groups in the PAS for both paste and liquid, SSA (25.18±8.25 vs. 20.84±6.92), BMI (19.97±3.34 kg/m²vs. 21.26 ±2.38 kg/m²), serum albumin (35.16 ±5.29 g/L vs. 37.24 ±3.98 g/L), prealbumin (248.33 ±27.72 mg/L vs. 261.39 ±22.10 mg/L), hemoglobin (119.09±12.53 g/L vs. 126.67±13.97 g/L) (P<0.05). There were no severe adverse events during the study. CONCLUSION: The combination of routine treatment and acupuncture therapy can better improve dysphagia and nutritional status in patients with Parkinson's disease, than routine treatment solely. (registration No. CLINICALTRIAL gov NCT06199323).
Humans ; Parkinson Disease/therapy* ; Deglutition Disorders/physiopathology* ; Acupuncture Therapy/adverse effects* ; Male ; Female ; Aged ; Middle Aged ; Treatment Outcome ; Nutritional Status ; Body Mass Index

OBJECTIVE To construct three-class （insufficient， normal， excessive） and two-class （insufficient， normal） models for predicting plasma concentration of valproic acid （VPA）， and compare the performance of these two models， with the aim of providing a reference for formulating clinical medication strategies. METHODS The clinical data of 480 patients who received VPA treatment and underwent blood concentration test at the Xi’an International Medical Center Hospital were collected from November 2022 to September 2024 （a total of 695 sets of data）. In this study， predictive models were constructed for target variables of three-class and two-class models. Feature ranking and selection were carried out using XGBoost scores. Twelve different machine learning algorithms were used for training and validation， and the performance of the models was evaluated using three indexes: accuracy， F1 score， and the area under the working characteristic curve of the subject （AUC）. RESULTS XGBoost feature importance scores revealed that in the three-class model， the importance ranking of kidney disease and electrolyte disorders was higher. However， in the two-class model， the importance ranking of these features significantly decreased， suggesting a close association with the excessive blood concentration of VPA. In the three-class model， Random Forest method performed best， with F1 score of 0.704 0 and AUC of 0.519 3 on the test set； while in the two-class model， CatBoost method performed optimally， with F1 score of 0.785 7 and AUC of 0.819 5 on the test set. CONCLUSIONS The constructed three-class model has the ability to predict excessive VPA blood concentration， but its prediction and model generalization abilities are poor； the constructed two-class model can only perform classification prediction for insufficient and normal blood concentration cases， but its model performance is stronger.

Objective:To develop a treatment-related quality of life scale for Chinese patients with multiple myeloma (MM) and to test its reliability and validity.Methods:The initial scale was constructed through a literature search, Delphi expert correspondence, and cognitive testing. This study conducted a preliminary survey of 379 patients with MM and a formal survey of 865 patients from the hematology departments of 155 hospitals nationwide from February 2024 to March 2024. The final scale was obtained after conducting item analysis and reliability and validity tests on the initial scale.Results:The constructed scale contains 36 items covering six domains: physiological, psychological, social, treatment side effects, general health, and others. In the preliminary survey, the Cronbach’s alpha coefficient of each item ranged from 0.597 to 0.939, and the test-retest reliability was 0.747 ( P<0.001). Exploratory factor analysis extracted eight common factors with a cumulative variance contribution of 60.058%. In the formal survey, the Cronbach’s alpha coefficient of each item ranged from 0.484 to 0.930, and the test-retest reliability was 0.835 ( P<0.001). Confirmatory factor analysis revealed a comparative fit index of 0.750, a root-mean-square error of approximation of 0.090, and a root-mean-square residual of 0.067. Conclusion:The treatment-related quality of life scale for Chinese patients with MM designed in this study exhibited good reliability and validity, reflecting the impact of treatment on the quality of life of patients. This scale can provide a reference to clinicians for assessing the disease status of patients.

This article reports a successful case of preimplantation genetic testing (PGT) in a patient with autosomal dominant polycystic kidney disease type 2 (PKD2) combined with Robertsonian translocation. The patient carried a heterozygous frameshift mutation ( PKD2 c.428del, p.Gly143Alafs*90) and a Robertsonian translocation between chromosomes 14 and 15. Through combined PGT for monogenic disorders, structural rearrangements and aneuploidy screening, one euploid blastocyst free of the PKD2 mutation was selected from six embryos for transfer, resulting in the successful delivery of a healthy female infant. Follow-up until June 2025 confirmed normal developmental milestones. This case demonstrates that PGT can effectively mitigate dual genetic risks (monogenic disease and chromosomal abnormality), providing critical clinical insights for optimizing reproductive outcomes in patients with complex genetic backgrounds.