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.

ObjectiveTo investigate the current awareness and optimization recommendations on pneumonia with unknown etiology (PUE) surveillance among Shanghai healthcare professionals, and to provide evidence for the improvement of the surveillance system. MethodsIn December 2024, healthcare professional participants from diverse medical and health institutions were randomly selected within each stratum using a stratified cluster sampling method in all 16 districts of Shanghai for questionnaire surveys on their knowledge and suggestions for optimization of the PUE surveillance system. Descriptive statistics analyses, multivariate logistic regressions, and content analyses were used for data analyses. ResultsA total of 385 survey subjects were involved in the study, including 119 professional staffs from disease prevention and control centers and 266 from medical institutions. Those who understood the case definition for PUE correctly accounted for 67.01% (258/385). Multivariate regression model analyses showed that female gender (aOR=2.22, 95%CI: 1.36‒3.66), professionals from disease control institutions (aOR=2.02, 95%CI: 1.12‒3.72), and those who self-assessed as being familiar with the monitoring system (aOR=2.18, 95%CI:1.23‒3.89) had better understanding of the definition. Overall, 89.61% (345/385) of the survey subjects acknowledged the necessity of the surveillance system. Small number of cases meeting the case definition (54.46%, 214/379), insufficient diagnostic awareness (39.84%, 151/379), and lack of incentives for case reporting (29.29%, 111/379) were major problems for the current surveillance system, with variations observed across different types of institutions. Suggested segments for optimizing the surveillance system included monitoring purpose, case definition, form of monitoring and reporting procedure, organization mechanism, and epidemiological investigation and response. ConclusionThe necessity of PUE surveillance is commonly recognized among healthcare workers. However, the existing system falls short in terms of mastery of case definition and overall surveillance adaptability. There is an urgent need for optimization and improvement to enhance the capacity for preventing and controlling emerging and sudden respiratory infectious diseases.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Objective To establish a highly sensitive and specific method for detecting human DNA based on real time quantitative PCR(qPCR)technique for the rapid detection of potential DNA con-tamination sources in DNA laboratories.Methods Primers and probes were designed with Primer Ex-pressTM software using the reference sequence of human 18S rRNA gene as a template,and the opti-mal prime-probe combination was screened by matrix method.The PCR products of the target se-quence of human 18S rRNA gene were used to construct the plasmid,and a plasmid standard was used to draw the standard curve of the qPCR system.According to the Minimum Information for Pub-lication of Quantitative Real-time PCR Experiments(MIQE)guidelines,the specificity,sensitivity,re-peatability and application effect of the qPCR system were evaluated.Results The sensitivity of the qPCR system established in this study was 5.3×10-5 ng/μL,which showed good specificity for human DNA samples.The correlation coefficient of the qPCR system was-0.999,and amplification efficiency was 100％.Both the intra-batch and inter-batch variation coefficients were less than 2％.Conclusion The established human DNA detection method based on qPCR technique has good specificity,high sen-sitivity,and robust stability.It can be used for rapid detection of DNA contamination and daily moni-toring of the accumulated human DNA in the laboratory environment.

[This corrects the article DOI: 10.1016/j.apsb.2022.03.002.].

Antibiotic adjuvants offer a promising strategy for restoring antibiotic sensitivity, expanding antibacterial spectra, and reducing required dosages. Previously, compound 15 was identified as a potential adjuvant for Polymyxin B (PB) against multidrug-resistant (MDR) Pseudomonas aeruginosa DK2; however, its clinical utility was hindered by high cytotoxicity, uncertain in vivo efficacy, and an unclear synergetic mechanism. To address these challenges, we synthesized and evaluated a series of novel benzamide derivatives, with A22 emerging as a particularly promising candidate. A22 demonstrated potent synergistic activity to PB, minimal cytotoxicity, improved water solubility, and broad-spectrum synergism of polymyxins against various clinically isolated MDR Gram-negative strains. In vivo studies using Caenorhabditis elegans and mouse models further confirmed the efficacy of A22. Moreover, A22 effectively suppressed the development of PB resistance in Pseudomonas aeruginosa DK2. Mechanistic investigations revealed that A22 enhances polymyxins activity by inducing reactive oxygen species production, reducing ATP levels, increasing NOX activity, and inhibiting biofilm formation, leading to bacterial death. These findings position A22 as a highly promising candidate for the development of polymyxin adjuvants, offering a robust approach to combating MDR Gram-negative bacterial infections.

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

Objective:This study aimed to clarify clinicopathologic characteristics, postoperative complications, and related risk factors of elderly patients with gastric cancer.Methods:A total of 395 patients(≥65 years old)who underwent radical gastrectomy for gastric cancer in Beijing Hospital from January 2014 to December 2021 were enrolled in this study.The patients were divided into the common elderly group(age<80 years, n=340)and the high-age group(age ≥ 80 years, n=55). Postoperative complications were classified into medical and surgical types.The clinicopathological characteristics and complications were compared between the two groups.Logistic regression models(univariate and multivariate)were used to identify the risk factors for postoperative complications.Results:The common elderly group was 65-79 years old(mean age: 71.5±4.3 years), with 263 male(77.4%); The high-age group was 80-89 years old(mean age: 82.6±2.6 years), with 42 male(76.4%). The comorbidity rate and the number of comorbidities in the high-age group were significantly higher than those in the common elderly group.The American Society of Anesthesiologists(ASA)scores and nutritional risk screening(NRS)2002 scores in the high-age group were significantly higher than those in the common elderly group(both P<0.05), and the activities of daily living(ADL)scores in the high-age group were significantly lower than that in the common elderly group( P<0.001). There were no statistically significant differences in tumor location, degree of differentiation, pathological type, T stage, and N stage between the two groups(all P>0.05). The overall postoperative complication rate in the high-age group was significantly higher than that in the common elderly group(38.2% vs.24.7%, P=0.036); the medical complications were significantly increased in the high-age group(21.8% vs.10.9%, P=0.022), whereas the surgical complications did not increase significantly(25.5% vs.17.1%, P=0.135). Multivariate analysis revealed that the number of comorbidities ≥2( HR=2.502, 95% CI: 1.275-4.911, P=0.008), preoperative NRS 2002 scores ≥5( HR=2.714, 95% CI1.294-5.693, P=0.008), and preoperative ADL scores<100( HR=2.012, 95% CI1.010-4.009, P=0.047)were independent risk factors for medical complications.Additionally, ASA grade ≥ 3( HR=2.586, 95% CI: 1.444-4.632, P=0.001)and proximal or distal gastrectomy( HR=2.397, 95% CI: 1.237-4.574, P=0.009)were independent risk factors for surgical complications. Conclusions:The occurrence of postoperative medical complications in very elderly patients with gastric cancer undergoing radical surgery has increased, while the rate of surgical complications has not increased.Moreover, advanced age itself is not an independent risk factor for postoperative complications.More attention should be paid to medical complications, and the management of commodities and nutritional support should be strengthened during the perioperative period.

Objective:To describe the hotspots and application trends of artificial intelligence (AI) in epidemiology in the past decade and analyze its advantages and challenges.Methods:The literatures with AI and epidemiology related keywords were systematically retrieved from Web of Science and China National Knowledge Infrastructure from 2014 to 2024. CiteSpace was used for bibliometric analysis of publication volume, keyword co-occurrence, clustering, emergence and cited literature co-occurrence analysis.Results:A total of 5 389 English papers and 1 659 Chinese papers were included, showing an increasing publication trend. High-frequency Chinese keywords included prediction, influencing factor, and machine learning, while English keywords frequently used were machine learning, prediction, and artificial intelligence. The Chinese keywords formed 14 clusters such as epidemiological characteristic, dietary pattern, and elderly individual, and the English keywords formed 21 clusters including prediction model, risk factor, and adult. In international studies, health policy, COVID-19, and digital health were the emerging frontier keywords. Eleven core papers were selected, covering key areas like traffic accident risk assessment, public health big data application, and deep learning in medical diagnosis.Conclusions:This study systematically summarized the research hotspots and development trends of AI applications in epidemiology over the past decade by using bibliometric methods, which indicated that current AI-based epidemiological studies are still in the exploratory phase, with the coexisting of both advantages and challenges. Continued attention should be paid to the future development of this field.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.