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 systematically evaluate the risk prediction models for anastomotic leakage (AL) in patients with esophageal cancer after surgery. Methods A computer-based search of PubMed, EMbase, Web of Science, Cochrane Library, Chinese Medical Journal Full-text Database, VIP, Wanfang, SinoMed and CNKI was conducted to collect studies on postoperative AL risk prediction model for esophageal cancer from their inception to October 1st, 2023. PROBAST tool was employed to evaluate the bias risk and applicability of the model, and Stata 15 software was utilized for meta-analysis. Results A total of 19 literatures were included covering 25 AL risk prediction models and 7373 patients. The area under the receiver operating characteristic curve (AUC) was 0.670-0.960. Among them, 23 prediction models had a good prediction performance (AUC>0.7); 13 models were tested for calibration of the model; 1 model was externally validated, and 10 models were internally validated. Meta-analysis showed that hypoproteinemia (OR=9.362), postoperative pulmonary complications (OR=7.427), poor incision healing (OR=5.330), anastomosis type (OR=2.965), preoperative history of thoracoabdominal surgery (OR=3.181), preoperative diabetes mellitus (OR=2.445), preoperative cardiovascular disease (OR=3.260), preoperative neoadjuvant therapy (OR=2.977), preoperative respiratory disease (OR=4.744), surgery method (OR=4.312), American Society of Anesthesiologists score (OR=2.424) were predictors for AL after esophageal cancer surgery. Conclusion At present, the prediction model of AL risk in patients with esophageal cancer after surgery is in the development stage, and the overall research quality needs to be improved.

The occurrence of diabetes mellitus （DM） is closely related to insulin resistance and islet β cell dysfunction. Modern studies have found that macrophages are widely present in the liver，fat，skeletal muscle，islets， and other tissues and organs. Macrophage M1/M2 polarization plays an important role in the occurrence and development of diabetes mellitus and its related complications by intervening in inflammatory response，improving insulin resistance，and promoting tissue repair. Most of the traditional Chinese medicines that regulate the activation and polarization of macrophages are Qi-replenishing and Yin-nourishing，heat-clearing， and detoxicating medicinal，which are consistent with the etiology and pathogenesis of diabetes and its related complications. Therefore，by summarizing the mechanisms between macrophage activation，polarization， and insulin resistance in various tissues，this paper reviewed traditional Chinese medicine and its effective components and compounds in improving diabetes mellitus and its related complications through multi-channel regulation of macrophage polarization and regulation of M1/M2 ratio，providing references for the future treatment of DM and its related complications with traditional Chinese medicine.

OBJECTIVE To explore the main factors influencing the blood concentration of duloxetine， and provide a scientific basis for the individualized use of duloxetine. METHODS Retrospective analysis was conducted on 434 inpatients with depressive disorders at the First Hospital of Hebei Medical University， who were treated with duloxetine and underwent blood concentration monitoring between January 2022 and April 2024. The study examined the impact of various factors， including gender， age， body mass index （BMI）， gene phenotypes， combined medication， drug type （original/generic）， and genotyping results of gene single nucleotide polymorphism loci， on blood concentration and the concentration-to-dose （C/D） after dose adjustment. RESULTS The blood concentration of duloxetine was 76.65 （45.57， 130.31） ng/mL， and C/D was 0.96 （0.63， 1.60） ng·d/（mL·mg）. The blood concentration of duloxetine was positively correlated with the daily dose of administration （R2＝0.253 7， P＜0.001）. Blood concentration of duloxetine in 38.94% of patients exceeded the recommended range specified in the guidelines. Gender， age， BMI， combined use of CYP2D6 enzyme inhibitors， and CYP2D6 and CYP1A2 phenotypes had significant effects on C/D of duloxetine （P＜0.05）. CONCLUSIONS The patient’s age， gender， BMI， combined medication， and genetic phenotypes are closely related to the blood concentration of duloxetine.

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.

BACKGROUND:Dysfunction of macrophage efferocytosis can induce local and systemic inflammatory damage and is associated with a variety of obesity-related metabolic diseases.Moreover,compounds targeting efferocytosis have shown good therapeutic effects. OBJECTIVE:By reviewing the effects of obesity on macrophage efferocytosis,to analyze the key mechanism by which obesity inhibits efferocytosis,to summarize the research progress in compounds targeting efferocytosis to treat obesity-related metabolic diseases,so as to provide new ideas for fully understanding efferocytosis and its relationship with metabolic diseases,aiming to provide new strategies for disease prevention and treatment. METHODS:The English search terms were"efferocytosis,metabolism,obesity,obese,atherosclerosis,non-alcoholic steatohepatitis,neurodegeneration,tumor,osteoarthritis,diabetes,compound,medicine,treatment,"which were used for literature retrieval in PubMed and Web of Science.The Chinese search term was"efferocytosis,"which was used for literature retrieval in CNKI,VIP and WanFang datebases.Ninety-nine papers were finally included in the review analysis after a rigorous screening process. RESULTS AND CONCLUSION:In the process of efferocytosis,the"Find me"and"Eat me"processes involving a large number of apoptotic cell derived factors are mainly regulated by apoptotic cells.The efferocytosis factor involved in cytoskeletal remodeling and digestion are mainly derived from macrophages,which are crucial for efferocytosis activity.These results suggest that the"Find me"and"Eat me"factors mainly reflect the condition of apoptosis,and it is more scientific to select the expression of factors involved in cytoskeletal remodeling and digestion when evaluating the efferocytosis activity of macrophages.Obesity inhibits efferocytosis,and shows an inhibitory effect on most digestive factors,but has a stress-induced activation effect on most"Find me,""Eat me"and cytoskeletal recombination factors,which further indicates the decisive effect of digestive stage on efferocytosis and suggests that it is not reliable for some studies to evaluate the efferocytosis based on the increased expression of"Find me"and"Eat me"factors.Targeting cytokines in the digestive phase may be more effective when discussing future intervention strategies targeting macrophages efferocytosis.The efferocytosis activators of macrophages are effective in the treatment of various metabolic diseases,but the efferocytosis inhibitors in tumor tissue show good anticancer effects,suggesting that the role of efferocytosis should be rationally evaluated according to the characteristics of tissue inflammation.Efferocytosis is a relatively new concept proposed in 2003,with a short research history and complex efferocytosis factors.Current studies on obesity and efferocytosis only involve a tip of the iceberg and most of them are at a superficial level and a large number of scientific experiments are needed to further validate the mechanisms.

BACKGROUND:The pathogenesis of diabetic peripheral neuropathy has not yet been clarified,and TAM(Tyro3,Axl,and MerTK)receptor tyrosine kinases can control apoptotic cells and suppress inflammatory responses in the central nervous system. OBJECTIVE:To investigate the difference of Mer receptor tyrosine kinase(MerTK)levels in plasma and sciatic nerve tissue of Sprague-Dawley rats with type 2 diabetes and diabetic peripheral neuropathy,and to study the correlation between MerTK and diabetic peripheral neuropathy. METHODS:Forty male Sprague-Dawley were randomly divided into control group with 15 rats,type 2 diabetes group with 10 rats,and diabetic peripheral neuropathy group with 15 rats.The control group was fed with ordinary diet,while the experimental groups were fed with high-fat and high-sugar diet.After 6 weeks,intraperitoneal injection of streptozotocin at the minimum dose of 35 mg/kg was administered in the two experimental groups.After 14 days,tail vein blood was collected to detect blood glucose.If blood glucose≥16.7 mmol/L,the model of type 2 diabetes was successfully established.Rats in the diabetic peripheral neuropathy group continued to be fed with a high-sugar and high-fat diet for 8 weeks.The sciatic nerve conduction velocity of rats was detected through live isolation under anesthesia.Blood samples were collected from the abdominal aorta,and the sciatic nerve tissue was collected.Histological changes of nerve fibers in each group were observed under a light microscope to confirm the success of diabetic peripheral neuropathy modeling.ELISA was used to detect peripheral blood glucose,blood lipids and serum MerTK levels in rats;hematoxylin-eosin staining was used to observe the histological changes in the sciatic nerve;immunofluorescence,immunohistochemistry and western blot were used to detect the expression of MerTK in the sciatic nerve tissue. RESULTS AND CONCLUSION:The Sprague-Dawley rat models of type 2 diabetes and type 2 diabetes peripheral neuropathy were successfully constructed,and the modeling rate of diabetic peripheral neuropathy was 80%.Compared with the control group,the blood glucose levels of rats in the type 2 diabetes and diabetic peripheral neuropathy groups were significantly higher(P<0.000 1),while the blood glucose level in the diabetic peripheral neuropathy group was higher than that in the type 2 diabetes group;and the sciatic nerve conduction velocity was significantly decreased(P<0.05),which was lower in the diabetic peripheral neuropathy group than the type 2 diabetes group.Histological examination:Compared with the control group,the sciatic nerve nuclei were reduced in the type 2 diabetes group,with some vacuolar degeneration and phagocytosis;in the diabetic peripheral neuropathy group,the cell body was swollen,the nuclear spacing was increased,vacuolar degeneration was observed,and the myelin sheath was partitioned and unsmooth,and lattice-like axons appeared.Serum MerTK levels were significantly higher in the diabetic peripheral neuropathy group than the control group.Expression of MerTK in the sciatic nerve tissue was significantly upregulated in the diabetic peripheral neuropathy group compared with the control group(P<0.05).To conclude,elevated levels of MerTK in plasma and sciatic nerve tissue of rats with diabetic peripheral neuropathy are presumably related to its anti-inflammatory and immunomodulatory effects.

ObjectiveTo investigate the effect and mechanism of polysaccharide in water extract of Cyclocarya paliurus （CPWP） in inhibiting benign prostatic hyperplasia （BPH）. MethodsCPWP was obtained by heating reflux， aqueous extraction， alcohol precipitation， and freeze drying. The chemical composition and structural properties of CPWP were analyzed by high performance liquid chromatography with 1-pheny-3-methyl-5-pyrazolone pre-column derivatization and infrared spectroscopy. Male SD rats were randomly assigned into control， model， finasteride （ig 5 mg·kg^-1）， and low-， medium-， and high-dose （ig 50， 75， 100 mg·kg^-1） CPWP groups， with 8 rats in each group. The BPH model was established by subcutaneously injecting propionate testosterone in castrated rats. The rats in the drug intervention groups were administrated with corresponding drugs， and those in the control group were administrated with an equal volume of normal saline each day. After 30 consecutive days， the rats were sacrificed， and the prostate tissue was separated and weighed. The effects of drug interventions on the body weight， prostate wet weight， and prostate index of rats were examined. The prostate tissue was stained with hematoxylin-eosin （HE） for observation of pathological changes. Enzyme-linked immunosorbent assay was employed to measure the level of dihydrotestosterone （DHT）， and immunohistochemical staining was used to detect the expression of steroid 5 alpha-reductase 2 （SRD5A2） and Ki67 in the prostate tissue. ResultsCPWP was identified as a saccharide， with characteristic absorption peaks of saccharides. CPWP showed the total sugar content of 44.15% and molecular weight within the range of 5.5-78.8 kDa， being composed of mannose， rhamnose， galacturonic acid， glucose， galactose， xylose， and arabinose. Compared with the control group， the model group had significantly increased prostate wet weight and prostate index （P<0.01）， thick and tall prostate epithelial cells， increased internal wrinkles， papillary expansion into the cavity， an elevation in DHT level in the serum， and up-regulated expression of SRD5A2 and Ki67 in the prostate tissue （P<0.05， P<0.01）. Compared with the model group， both the finasteride and CPWP groups showed decreases in prostate wet weight and prostate index （P<0.05， P<0.01）， thinned prostate epithelial cells， with only a small portion of internal wrinkles and papillary expansion into the cavity， shortened papillary protrusions， lowered DHT level in the serum， and down-regulated expression of SRD5A2 and Ki67 in the prostate tissue （P<0.01）. Moreover， CPWP exerted effects in a dose-dependent manner. ConclusionCPWP inhibits BPH by regulating the expression of SRD5A2.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

In view of the few studies on the influence of Armillaria spp. infection on the content of the chemical components in different parts of Polyporus umbellatus sclerotia, this study determined the biomass of P. umbellatus sclerotia and the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in the separated cavity wall of the sclerotia and the uninfected part of the sclerotia in different harvesting years under the conditions of A. gallica and A. mellea infection respectively. According to the difference of content and dynamic changes of the polysaccharide and the steroid substances, the superior Armillaria sp. was screened to obtain the best harvest years of P. umbellatus. Using HPLC and UV-VIS spectrophotometry methods, the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in P. umbellatus sclerotia infected by the two Armillaria spp. in different years were determined. In addition, the differentially expressed genes related to P. umbellatus polysaccharide synthesis were screened according to the transcriptomic data of different parts of P. umbellatus after A. mellea infection. With the increase of years, the biomass of sclerotia infected by different Armillaria spp. had significant differences, and there were significant differences in the four components of sclerotia. The four components of the separated cavity wall of the sclerotia were significantly higher than those of the uninfected part. The best harvest time was the third year after cultivation. Transcriptomic analysis showed that the infection of Armillaria spp. could significantly promote polysaccharide synthesis, which provided a basis for polysaccharide content determination at the molecular level. The study clarified the influence of different Armillaria spp. infection on the accumulation of chemical components of P. umbellatus sclerotia, laying a foundation for exploring the symbiosis mechanism and provided a scientific clue for screening superior Armillaria sp. and guiding the artificial cultivation of P. umbellatus sclerotia.