With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective: To design HBV DNA proficiency testing and system comparison samples with different concentration gradients, analyze their detection results in PCR detection systems, evaluate the nucleic acid detection capabilities of laboratories and differences between detection systems, and put forward suggestions for continuous quality improvement to participating laboratories. Methods: Three groups of randomly numbered proficiency testing samples (with HBV DNA reference concentrations of <2, 7.5, and 30 IU/mL respectively) were taken as the detection objects. Using nucleic acid test data from 11 provincial blood station laboratories as the source, the samples were grouped by detection system and laboratory successively, and statistical analysis was conducted. Results: Statistical analysis of the detection data of the three groups of samples based on detection systems and laboratories showed that from low to high concentration, the coincidence rate between the detection results of different detection systems and laboratories and the expected results showed an increasing trend: 38.89%, 85.90%, and 100.00%; the same system exhibited certain differences in performance among different laboratories. Conclusion: Through this proficiency testing and system comparison, it is found that there are certain differences in the detection capabilities of different laboratories and different nucleic acid test systems. Blood station laboratories should standardize processes, strengthen quality management and data analysis on the basis of being familiar with the detection performance of their detection systems, and at the same time strengthen the control of laboratory interference factors to continuously improve the nucleic acid detection capabilities of blood station laboratories.

Mild cognitive impairment due to Alzheimer′s disease is an inevitable pathological stage in the early development of Alzheimer′s disease, which can be classified as "microlumps in the brain collaterals" in traditional Chinese medicine. Based on the theory of latent toxin blocking collaterals, this article discusses the etiology and pathogenesis, clinical sequelae, and traditional Chinese medicine intervention strategies for mild cognitive impairment due to Alzheimer′s disease. The onset of mild cognitive impairment due to Alzheimer′s disease is very similar to the latent pathogen theory, which states that "the latent pathogen is latent and then develops, the poison is deep and difficult to cure, and the development can be recognized but the latent pathogen cannot be detected." Combining clinical experience, our team believes that the basic nature of the disease is a slight deficiency and a slight excess of symptoms. A slight deficiency of the five zang viscera and six fu viscera as root and a latent toxin colling collaterals of qi, fire, phlegm, and blood stasis as manifestaion. These usually start from the qi depression and develop into phlegm coagulation and blood stasis, then end up in latent toxin and gradually become the healthy qi deficiency. Therefore, the deficiency of vital qi and incubation of evil, latent toxin blocking collaterals the pathogenesis of early intervention of this disease should be carried out, upholding the idea that "the upper workman treats the disease before it is diagnosed." The principle of strengthening vital qi to eliminate pathogenic factors, slowing down and promoting pathogenic factors elimination, establishing the method of supporting correctness and wisdom, simultaneously detoxifying and clearing the blood stasis, pattern differentiation as the main and the disease differentiation as the first, combining the disease and pattern, and adjusting the macroscopic and microscopic, focusing simultaneously on eliminating and replenishing, dispel phlegm and remove blood stasis, achieve a strong vital qi and the elimination of evil, and enhance intelligence, delay or even block the progression of mild cognitive impairment due to Alzheimer′s disease, improve patients′ quality of life, and provide a theoretical basis for the early clinical prevention and treatment of Alzheimer′s disease.

Aim To investigate the effect of benzyl iso-thiocyanate (BITC) on the proliferation of mouse U14 cervical cancer cells and to explore the mechanism of cytotoxicity based on transcriptomic data analysis. Methods The effect of BITC on U14 cell activity was detected by MTT, nuclear morphological changes were observed by Hochest 33258 and fluorescent inverted microscope, cell cycle and apoptosis were determined by flow cytometry, and the transcriptome database of U14 cells before and after BITC (20 μmol · L

Objective To investigate whether E.coli infection increases surgical site infection and postoperative fever in comparison with other pathogens.Methods A retrospective cohort study was conducted on 506 patients who underwent urethral segment resection and end anastomosis for the bulb or posterior urethral stenosis in our department during 2011 and 2019.According to occurrence of postoperative surgical site infection(SSI)or postoperative fever(POF),they were divided into SSI group(n=19)and non-SSI group(n=487),as well as POF group(n=61)and non-POF group(n=445 patients)respectively.Multivariate logistic regression analysis and LASSO algorithm were used to screen the potential risk factors.According to the results of positive preoperative urine culture in 302 patients,they were subsequently divided into E.coli infection group(n=80)and other pathogen infection group(n=222),and after reducing potential bias with propensity score matching,finally 48 patients were assigned into E.coli infection group,and 192 into other pathogen infection groups.The differences in occurrences of SSI and POF were compared between the above 2 groups of patients.Results Multivariate logistic regression analysis and LASSO algorithm revealed that positive preoperative urine culture was an independent risk factor for predicting SSI(P=0.012)and POF(P＜0.01).Among the 302 patients with positive results in preoperative urine culture,E.coli infections was in the first rank,accounting for 26.5％.After propensity score matched treatment,the incidence of SSI in the E.coli group and other pathogen groups was 29.2％and 2.1％,respectively(P＜0.01).The incidence of POF was also higher in the E.coli infection group than the other pathogen infection group(27.1％vs 13.5％,P=0.02).Conclusion Preoperative E.coli infection may increase the risk of SSI and POF after urethroplasty when compared with other pathogen infections.

In recent years, artificial intelligence (AI) technology represented by deep learning (DL) has developed rapidly, and smart medical care has become one of the most important application areas of AI. As the most accurate noninvasive test to assess myocardial blood flow, myocardial perfusion imaging (MPI) has important clinical values. At present, the use of DL algorithms to establish learning models for MPI images is still in the research stage, and more external verification and iterative updates are needed before it can be widely used in real time clinical practice. In this article, the application of DL algorithms in MPI is comprehensively elaborated to provide a basis and direction for further research.

Objective To systematically evaluate the efficacy and safety of three-dimensional visualization technology in assisting ablation therapy for hepatocellular carcinoma.Methods This study was conducted according to PRISMA guidelines,with a PROSPERO registration number of CRD42023488398.PubMed,Embase,Web of Science,the Cochrane Library,CNKI,Wanfang Data,VIP,and CBM were searched for Chinese and English articles on three-dimensional visualization technology in assisting ablation therapy for hepatocellular carcinoma published up to March 2023.After quality assessment and data extraction of the studies included,RevMan 5.4 software was used to perform the meta-analysis.Results A total of 11 studies were included,with 972 patients in total,among whom 447 underwent ablation assisted by three-dimensional visualization technology(3D group)and 525 underwent ablation assisted by traditional two-dimensional imaging technology(2D group).The meta-analysis showed that compared with the 2D group,the 3D group had significantly higher success rate of first-time ablation treatment(odds ratio[OR]=5.43,95%confidence interval[CI]:2.64—11.18,P<0.001),technical efficiency(OR=6.15,95%CI:3.23—11.70,P<0.001),and complete ablation rate(OR=2.50,95%CI:1.08—5.78,P=0.03),as well as significantly lower incidence rate of major complications(OR=0.45,95%CI:0.24—0.87,P=0.02),local recurrence rate(OR=0.35,95%CI:0.17—0.72,P=0.004),and local tumor progression rate(OR=0.29,95%CI:0.16—0.50,P<0.001),while there was no significant difference in the incidence rate of mild complications between the two groups(P>0.05).Conclusion Three-dimensional visualization technology is safe and feasible in assisting ablation therapy for hepatocellular carcinoma and can improve ablation rate and reduce the incidence rate of serious complications,local recurrence rate,and local tumor progression rate,thereby showing an important application value in clinical practice.

Artificial intelligence(AI)is a strategic technology leading a new round of technological revolution and industrial transformation.It is forward-looking,important and necessary to apply AI technology to the medical field.At present,the research and development of intelligent data monitoring equipment,intelligent medical instruments,disease auxiliary diagnosis and treatment platforms,auxiliary diagnosis and treatment integrated systems and other technologies have been widely carried out,and related products are gradually used in auxiliary medical prevention,diagnosis,treatment,and rehabilitation.Based on the recent development of AI technology in the medical field,the application status of intelligent auxiliary diagnosis and treatment equipment in three fields of intelligent monitoring equipment,virtual psychological diagnosis and treatment platforms,and traditional Chinese medicine auxiliary diagnosis and treatment instruments was summarized to provide reference for AI to connect disease and health,and realize the intersection of AI and medical disciplines.

Medical device imaging data augmentation is a method of expanding existing datasets by generating new data samples,which is of great significance for improving the performance of artificial intelligence(AI)medical device-related models and clinical application effects.However,traditional data augmentation methods are usually limited by the quality,realism,and diversity of generated samples.Denoising diffusion probabilistic model(DDPM)is a generative model based on the noise diffusion process,and its main idea is to generate samples with high quality by modelling the sampling process of the target distribution as a process of progressive denoising from the noise distribution.The basic principles and working mechanisms of DDPM were reviewed,the application scenarios of this method in AI medical device data augmentation were analyzed,and its advantages,challenges,and future development directions were explored to provide a reference for the field of AI medical device data augmentation.

Background::The association and its population heterogeneities between low-density lipoprotein cholesterol (LDL-C) and all-cause and cardiovascular mortality remain unknown. We aimed to examine the dose-dependent associations of LDL-C levels with specific types of cardiovascular disease (CVD) mortality and heterogeneities in the associations among different population subgroups.Methods::A total of 2,968,462 participants aged 35-75 years from China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) (2014-2019) were included. Cox proportional hazard models and Fine-Gray subdistribution hazard models were used to estimate associations between LDL-C categories (<70.0, 70.0-99.9, 100.0-129.9 [reference group], 130.0-159.9, 160.0-189.9, and ≥190.0 mg/dL) and all-cause and cause-specific mortality.Results::During a median follow-up of 3.7 years, 57,391 and 23,241 deaths from all-cause and overall CVD were documented. We observed J-shaped associations between LDL-C and death from all-cause, overall CVD, coronary heart disease (CHD), and ischemic stroke, and an L-shaped association between LDL-C and hemorrhagic stroke (HS) mortality ( P for non-linearity <0.001). Compared with the reference group (100.0-129.9 mg/dL), very low LDL-C levels (<70.0 mg/dL) were significantly associated with increased risk of overall CVD (hazard ratio [HR]: 1.10, 95% confidence interval [CI]: 1.06-1.14) and HS mortality (HR: 1.37, 95% CI: 1.29-1.45). Very high LDL-C levels (≥190.0 mg/dL) were associated with increased risk of overall CVD (HR: 1.51, 95% CI: 1.40-1.62) and CHD mortality (HR: 2.08, 95% CI: 1.92-2.24). The stronger associations of very low LDL-C with risk of CVD mortality were observed in individuals with older age, low or normal body mass index, low or moderate 10-year atherosclerotic CVD risk, and those without diagnosed CVD or taking statins. Stronger associations between very high LDL-C levels and all-cause and CVD mortality were observed in younger people. Conclusions::People with very low LDL-C had a higher risk of all-cause, CVD, and HS mortality; those with very high LDL-C had a higher risk of all-cause, CVD, and CHD mortality. On the basis of our findings, comprehensive health assessment is needed to evaluate cardiovascular risk and implement appropriate lipid-lowering therapy for people with very low LDL-C.