Objective To systematically analyze the characteristics of the disease burden of hypertensive heart disease (HHD) in the elderly (≥60 years) globally and in China from 1990 to 2021, and to predict its future trends from 2022 to 2040, with the aim of providing data support for optimizing comprehensive prevention and control strategies for HHD. Methods Based on the Global Burden of Disease (GBD) 2021 database, the number of prevalent cases and disability-adjusted life years (DALYs) of HHD in the elderly were extracted for the world, China, and five regions categorized by sociodemographic index (SDI). Joinpoint regression was used to analyze the temporal trends of age-standardized prevalence rate and age-standardized DALYs rate of HHD in the elderly. A three-factor decomposition method was applied to evaluate the relative contributions of aging, population growth, and epidemiological changes to the variations in the elderly HHD burden. Additionally, a Bayesian age-period-cohort model was used to predict the elderly HHD burden from 2022 to 2040. Results In 2021, the number of prevalent elderly HHD cases reached 10 283 000 globally and 3 412 400 in China, representing increases of 179.20% and 159.20% respectively, compared with 1990. The DALYs of elderly HHD were 18 812 700 person-years globally and 4 731 400 person-years in China, rising by 76.08% and 29.45% respectively from 1990. Meanwhile, the growth rates of the number of prevalent cases and DALYs of elderly HHD varied across different SDI regions. From 1990 to 2021, the age-standardized prevalence rate of elderly HHD in China, as well as the age-standardized DALYs rate of elderly HHD both globally and in China, showed significant downward trends (all average annual percentage changes<0, all P<0.001). In 2021, the 70-74 years age group accounted for the highest proportion of prevalent cases and DALYs of elderly HHD, both globally and in China. Decomposition analysis revealed that population growth was the dominant factor driving the increase in the elderly HHD burden across all regions. The prediction model results indicated that the number of prevalent cases and DALYs of elderly HHD would continue to rise globally and in China from 2022 to 2040, with the growth rate of the elderly HHD burden in China between 2021 and 2040 expected to exceed the global average. Conclusion Over the past 32 years, although the age-standardized disease rates of elderly HHD have mainly shown a downward trend globally and in China, the absolute number of the disease burden has increased substantially. The projection model indicates a continued upward trajectory, with the growth rate in China higher than the global average. Therefore, there is an urgent need to implement precise prevention and control strategies to effectively mitigate the disease burden of elderly HHD.

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.

To address the growing challenge of an increasing number of elderly lung cancer patients amidst China's aging population and to fill the gap in quality control standards for surgical treatment in this special population, this study aimed to develop a standardized surgical evaluation system for elderly lung cancer patients tailored to China's national conditions. The system was established through a literature review, integrated the pathophysiological characteristics of elderly patients, and was constructed following review, feedback, and revision by experts from multiple thoracic surgery centers. Employing a 100-point scoring system, it comprises three primary domains: physical infrastructure and geriatric adaptability foundational conditions (10 points); management level and perioperative care models (20 points); and technical proficiency and clinical outcomes (70 points). The system places a strong emphasis on geriatric adaptability, proposing specific, quantifiable indicators for age-friendly facility modifications, control of elderly-specific complications, multidisciplinary collaboration, and standardized perioperative management. It provides a convenient and measurable assessment tool for quality control in the surgical treatment of elderly lung cancer in China, which is expected to promote the standardization and homogenization of diagnosis and treatment.

Objective To explore the predictive value of artificial intelligence (AI)-based lung nodule CT quantitative analysis for the invasion degree of lung adenocarcinoma spectrum lesions. Methods According to the invasion degree of lung adenocarcinoma spectrum lesions, patients with surgically and pathologically confirmed lung adenocarcinoma spectrum lesions from January to June 2023 in Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University were retrospectively collected and divided into a non-invasive group and an invasive group, including atypical adenomatous hyperplasia, adenocarcinoma in situ, and minimally invasive adenocarcinoma patients in the non-invasive group, and invasive adenocarcinoma patients in the invasive group. All enrolled patients underwent chest CT before surgery, and then the lung nodules were quantitatively analyzed using an AI-based computer-aided diagnosis system to compare the related quantitative parameters of lung nodules that have been surgically removed and pathologically confirmed as lung adenocarcinoma spectrum lesions between the two groups. The relationship between various CT quantitative features and the invasion degree of lung adenocarcinoma spectrum lesions was analyzed. Results A total of 149 patients (149 lesions) were included, including 42 males and 107 females, aged 29-81 (56.35±10.75) years. There were 72 patients in the non-invasive group and 77 patients in the invasive group. Statistical differences were observed between the two groups in long diameter, short diameter, volume, surface area, mass, maximum cross-sectional area, 3D long diameter, maximum CT value, minimum CT value, average CT value, entropy, kurtosis, skewness, malignancy probability and other indicators (P<0.05). Multivariate binary logistic regression analysis showed that long diameter [OR=1.687, 95%CI (1.364, 2.085), P<0.001], average CT value [OR=1.006, 95%CI (1.002, 1.009), P=0.002], and malignancy probability [OR=1.034, 95%CI (1.005, 1.063), P=0.020] were independent risk factors for the invasion degree of lung adenocarcinoma. The predictive model combining the above parameters demonstrated optimal performance, with an area under the receiver operating characteristic curve of 0.951, sensitivity of 0.818, and specificity of 0.972. Using a Nomogram to quantify the three independent risk factors, the cross-validation was performed to evaluate the stability of the model, and the average C-index of cross-validation was 0.950, with each fold C-index >0.75, indicating that the prediction performance of the model was stable, and the calibration curve and decision curve indicated good predictive performance. Conclusion The visualization prediction model constructed by AI-based quantitative analysis of lung nodules in CT demonstrates significant discriminative effectiveness in the assessment of invasiveness in lung adenocarcinoma spectrum lesions. This visualization prediction model can provide a quantitative decision-making basis for the preoperative identification of the degree of invasiveness in lung adenocarcinoma spectrum lesions.

Objective: To investigate the technical considerations and clinical value of plasma exchange (PE) in the treatment of cardiohepatic syndrome (CHS). Methods: A 76-year-old male patient with CHS was treated. The patient’s underlying conditions included valvular heart disease (severe mitral and tricuspid regurgitation), chronic heart failure (cardiac function class IV) complicated with liver failure [total bilirubin (TBIL) up to 590.6 μmol/L; alanine aminotransferase (ALT) up to 325.4 IU/L; aspartate aminotransferase (AST) up to 190.4 IU/L]. Due to poor response to conventional anti-heart failure and hepatoprotective therapy, three sessions of stepwise PE (total volume 6 400 mL) were performed. A "calcium-fluid balance-hemodynamics“ trinity monitoring system was established during treatment, comprising:1) prophylactic calcium supplementation (continuous calcium infusion at 5 mL/h initiated before PE); 2) dynamic blood gas monitoring (ionized calcium measured every 30-60 min with calcium dose adjusted accordingly); 3) individualized fluid balance setting (75%-90%); 4) standby norepinephrine (0.02-0.1 μg/kg/min). Results: Complications such as hypocalcemia (lowest 0.83 mmol/L) and hypotension (lowest 65/38 mmHg) occurred during treatment. Hemodynamics were stabilized by adjusting calcium supplementation, regulating fluid balance, and concomitant use of vasoactive agents. After treatment, B-type natriuretic peptide (BNP) decreased by 42.0% (from 7 122.53 pg/mL to 4 128.77 pg/mL), TBIL decreased by 69.7% (from 590.6 μmol/L to 178.7 μmol/L), ALT decreased by 91.8% (from 325.4 IU/L to 26.7 IU/L), and AST decreased by 83.2% (from 190.4 IU/L to 31.9 IU/L). Conclusion: PE based on the "calcium-fluid balance-hemodynamics" trinity monitoring system can improve cardiac and liver function in patients with CHS.

Objective To analyze the influencing factors of malaria infection of labor service exported to overseas in Langfang City, in order to establish a visualization tool to assist clinicians in predicting the risk of malaria. Methods A total of 4 774 expatriate employees of the Nibei Pipeline Project of the Pipeline Bureau from October 2021 to August 2023 were taken as the subjects, and the gender, age, overseas residence area and Knowledge of malaria controlscores of the study subjects were investigated by questionnaire survey, and the possible risk factors of malaria were screened by logistic regression model. At the same time, the nomogram prediction model was established, and the subjects were divided into the training group and the validation group at a ratio of 2:1, and the area under the curve (ROC) and the decision curve were plotted to evaluate the prediction ability and practicability of the prediction model in this study. Results Among the 4 774 study subjects, 96 cases of malaria occurred, and the detection rate was 2.01%. Junior school （OR=1.723，95% CI:1.361-2.173）， and residence in rural areas（OR=2.091，95%CI:1.760 -3.100）were risk factors (OR>1), while protective measures（OR=0.826，95% CI : 0.781 - 0.901） and high malaria education scores （OR=0.872，95% CI : 0.621 - 0.899）were protective factors.The nomogram prediction model results showed that the area under the curve of the nomogram prediction model in the training group was 0.94 (95% CI : 0.85 - 1.00), while the validation group was 0.93 (95% CI : 0.80 - 1.00). The results of the decision curve showed that when the threshold probability of the population was 0-0.9, the nomogram model was used to predict the risk of malaria occurrence with the highest net income. Conclusion The nomogram prediction model (including gender, education, region, protection and malaria education score) established and validated in this study is of great value for clinicians to screen high-risk patients with malaria.

Stroke is the main cause of death and disability among adults in China and is characterized by high incidence， disability， mortality， and recurrence rates. The combination of traditional Chinese and Western medicine has great potential in treating stroke and its sequelae. The classic traditional Chinese medicine prescription Da Chengqitang （DCQT） has a long history and proven efficacy in treating stroke. Clinically， DCQT is often used to treat stroke and its sequelae. However， the number and quality of clinical trials of DCQT in treating stroke need to be improved. Because of the insufficient basic research， the active ingredients and multi-target mechanism of action of DCQT remain unclear. Our research group has previously confirmed that DCQT can effectively reverse neurological damage， reduce iron deposition， and downregulate the levels of pro-inflammatory cytokines in the rat model of hemorrhagic stroke. The treatment mechanism is related to the nuclear factor erythroid 2-related factor 2 （Nrf2）-mediated signaling pathway and p38 mitogen-activated protein kinase （MAPK） signaling-mediated microglia activation. To clarify the pharmacodynamic basis and anti-stroke mechanism of DCQT， this article reviews the research progress in the treatment of stroke with DCQT in terms of clinical trials， pharmacodynamic material basis， safety evaluation， and mechanisms of absorbed components. This article summarizes 45 major phytochemical components of DCQT， 11 of which are currently confirmed absorbed components. Among them， emodin， rhein， chrysophanol， aloe-emodin， synephrine， hesperidin， naringin， magnolol， and honokiol can be used as quality markers （Q-markers） of DCQT. The mechanism of DCQT in treating stroke is complex， involving regulation of inflammatory responses， neuronal damage， oxidative stress， blood-brain barrier， brain-derived neurotrophic factor， and anti-platelet aggregation. This article helps to deeply understand the pharmacodynamic basis and mechanism of DCQT in treating stroke and provides a theoretical basis for the clinical application of DCQT in treating stroke and the development of stroke drugs.

Objective To analyze the virus subtypes, molecular evolutional and molecular transmission network features of the first confirmed mpox case in Huai’an City, Jiangsu Province, so as to provide insights into understanding of the transmission and evolution dynamics of mpox virus and formulation of the mpox control strategy in the city. Methods Genomic DNA was extracted from swabs of the first confirmed mpox case’s skin lesions in Huai’an City, and the amplicon sequencing library was constructed using the hypersensitive mpox virus whole-genome capture kit. High-throughput sequencing was performed using the GridION X5 nanopore sequencer on the Nanopore sequencing platform, and single nucleotide polymorphism (SNP) analysis of mpox virus genome sequences was performed following sequence assembly. In addition, phylogenetic analysis, genetic genealogy and molecular traceability analysis were performed. Results The virus whole genome sequence of the first confirmed mpox case was successfully obtained by high-throughput sequencing, with a full length of 197 182 bp, and was named hMpxV/China/JS-HA01/2023, which belonged to the clade IIb (West African clade) lineage B.1.3. Compared with the mpox virus reference sequence MPXV-M5312_HM12_Rivers-001 (GenBank accession number: NC_063383), the genome sequence of the Huai’an virus isolate carried 86 SNPs, including 40 SNPs in the coding region as non-synonymous mutations and 73 SNPs as nucleotide mutations caused by APOBEC3 (APOBEC3). Of the 97 mpox virus gene sequences, 79 sequences were included in the molecular network (81.44%), and the threshold of the genetic distance accessed to the network was 0.35/10⁵. There were two large molecular transmission clusters and one scattered cluster in the molecular transmission network of the mpox virus, andthehMpxV/China/JS-HA01/2023 sequence was located in the large cluster. The 97 gene sequences formed 92 haplotypes, including three shared haplotypes Hap_4, Hap_6 and Hap_38, and an exclusive haplotype Hap_1 of hMpxV/China/JS-HA01/2023 generated from mutation of the exclusive haplotype Hap_43, while the exclusive haplotype Hap_43 was generated from mutation of the shared haplotype Hap_38. Conclusions The whole genome sequence of the mpox virus isolated from the first confirmed mpox case in Huai’an City has been successfully obtained, and the molecular evolutionary and molecular transmission network characteristics of the virus have been preliminarily understood.

Ferroptosis, a programmed cell death modality discovered and defined in the last decade, is primarily induced by iron-dependent lipid peroxidation. At present, it has been found that ferroptosis is involved in various physiological functions such as immune regulation, growth and development, aging, and tumor suppression. Especially its role in tumor biology has attracted extensive attention and research. Breast cancer is one of the most common female tumors, characterized by high heterogeneity and complex genetic background. Triple negative breast cancer (TNBC) is a special type of breast cancer, which lacks conventional breast cancer treatment targets and is prone to drug resistance to existing chemotherapy drugs and has a low cure rate after progression and metastasis. There is an urgent need to find new targets or develop new drugs. With the increase of studies on promoting ferroptosis in breast cancer, it has gradually attracted attention as a treatment strategy for breast cancer. Some studies have found that certain compounds and natural products can act on TNBC, promote their ferroptosis, inhibit cancer cells proliferation, enhance sensitivity to radiotherapy, and improve resistance to chemotherapy drugs. To promote the study of ferroptosis in TNBC, this article summarized and reviewed the compounds and natural products that induce ferroptosis in TNBC and their mechanisms of action. We started with the exploration of the pathways of ferroptosis, with particular attention to the System X_c^--cystine-GPX4 pathway and iron metabolism. Then, a series of compounds, including sulfasalazine (SAS), metformin, and statins, were described in terms of how they interact with cells to deplete glutathione (GSH), thereby inhibiting the activity of glutathione peroxidase 4 (GPX4) and preventing the production of lipid peroxidases. The disruption of the cellular defense against oxidative stress ultimately results in the death of TNBC cells. We have also our focus to the realm of natural products, exploring the therapeutic potential of traditional Chinese medicine extracts for TNBC. These herbal extracts exhibit multi-target effects and good safety, and have shown promising capabilities in inducing ferroptosis in TNBC cells. We believe that further exploration and characterization of these natural compounds could lead to the development of a new generation of cancer therapeutics. In addition to traditional chemotherapy, we discussed the role of drug delivery systems in enhancing the efficacy and reducing the toxicity of ferroptosis inducers. Nanoparticles such as exosomes and metal-organic frameworks (MOFs) can improve the solubility and bioavailability of these compounds, thereby expanding their therapeutic potential while minimizing systemic side effects. Although preclinical data on ferroptosis inducers are relatively robust, their translation into clinical practice remains in its early stages. We also emphasize the urgent need for more in-depth and comprehensive research to understand the complex mechanisms of ferroptosis in TNBC. This is crucial for the rational design and development of clinical trials, as well as for leveraging ferroptosis to improve patient outcomes. Hoping the above summarize and review could provide references for the research and development of lead compounds for the treatment for TNBC.

Objective: To explore the possibility of performing allogeneic platelet-rich plasma (PRP) treatment for patients who were not suitable for autologous PRP collection through case reports of two patients with refractory wounds treated with allogeneic PRP. Methods: The ABO-compatible allogeneic whole blood was centrifuged 3 times to obtain allogeneic PRP within 6 hours of blood collection. Then the qualified allogeneic PRP was applied to 2 cases of refractory wound on the same day. Results: The platelet concentration in allogeneic PRP was higher than 1 000×10 /L, and the test results of infectious diseases, as well as the mixing of red blood cells and white blood cells, met the standard of quality control. Both patients achieved satisfactory wound healing outcomes (3 d). Conclusions: For patients who were not suitable for autologous PRP treatment, allogeneic PRP might be a new option.