Flap transplantation is a critical surgical strategy for the reconstruction of tissue defects caused by trauma, tumor resection, and congenital malformations, and its survival rate directly determines surgical efficacy and patient prognosis. Following transplantation, flaps inevitably undergo ischemia-reperfusion (I/R) injury, during which oxidative stress, inflammatory responses, and metabolic disturbances are intricately intertwined, ultimately leading to cellular injury and tissue necrosis. Recent studies have demonstrated that multiple forms of programmed cell death—including apoptosis, pyroptosis, ferroptosis, necroptosis, and PANoptosis—play central roles in flap I/R injury. The extensive crosstalk and molecular interactions among these pathways form a highly complex cell death network. Specifically, apoptosis is mediated by the imbalance of Bcl-2 family proteins and the activation of cysteine-dependent aspartate-specific protease (caspase) cascades; pyroptosis is driven by the NLRP3-caspase-1-GSDMD axis, resulting in membrane pore formation and the release of pro-inflammatory cytokines; ferroptosis is characterized by iron-dependent lipid peroxidation and dysfunction of glutathione peroxidase 4 (GPX4); necroptosis is triggered by the receptor-interacting serine/threonine-protein kinase 1 (RIPK1)-RIPK3-MLKL signaling complex, leading to membrane rupture; and PANoptosis represents an integrated form of inflammatory cell death that coordinates multiple death pathways. Importantly, these forms of programmed cell death are not independent but are interconnected through extensive signaling crosstalk. Key regulatory molecules, including caspase-8, reactive oxygen species (ROS), nuclear factor-κB (NF-κB), and nuclear factor erythroid 2-related factor 2 (Nrf2), collectively modulate the dynamic balance among these pathways. Therefore, the multidimensional interplay and spatiotemporal dynamics of programmed cell death constitute a fundamental pathological basis of flap I/R injury. This review systematically summarizes the latest advances in the mechanisms and interactions of various programmed cell death pathways in flap I/R injury, aiming to elucidate the underlying regulatory network. These insights may provide novel theoretical foundations for optimizing flap protection strategies, improving flap survival, and promoting tissue repair.

AIM: To investigate the association between dyslipidemia and macular hard exudates(HEs)in non-proliferative diabetic retinopathy(NPDR)secondary to type 2 diabetes mellitus(T2DM).METHODS: NPDR patients attending the outpatient ophthalmology clinic from January 2021 to December 2023 were selected and divided into three groups according to the severity of macular HEs. Group A: None or minimal HEs; Group B: Definite HEs; Group C: Prominent HEs. Total cholesterol(TC), triglycerides(TG), low-density lipoprotein cholesterol(LDL-C), high-density lipoprotein cholesterol(HDL-C), lipoprotein(a)[Lp(a)] levels and other lipid-related indicators were routinely measured. The correlation between these indicators and HEs was analyzed.RESULTS:Group A(24 eyes)consisted of 9 males and 15 females with the mean age of 54.71±6.15 y, group B(52 eyes)consisted of 20 males and 32 females with the mean age of 55.08±6.27 y, group C(14 eyes)consisted of 9 males and 5 females with the mean age of 53.93±6.08 y. The concentration of TC, TG, LDL-C and Lp(a)was highest in group C, followed by group B and lowest in group A with statistically significant differences(P<0.001). There were no statistically significant differences between the three groups for fasting plasma glucose(FPG), glycated hemoglobin A1c(HbA1c), creatinine(Cr), and HDL-C(P>0.05). The results of multivariate Logistic regression analysis showed that elevated levels of TC, TG, LDL-C, and Lp(a)were associated with the presence of macular HEs. Receiver operating characteristiccurve analysis showed that the area under the curve(AUC)for TC, TG, LDL-C, Lp(a), and their combination in predicting macular HEs in NPDR were 0.785, 0.718, 0.784, 0.742, and 0.911, respectively, with the combined model demonstrating the highest predictive performance.CONCLUSION: Dyslipidemia is closely associated with the development and progression of macular HEs in patients with NPDR and T2DM. The levels of TC, TG, LDL-C, and Lp(a)were correlated with the severity of macular HEs, suggesting that dyslipidemia may be involved in the pathological process of macular HEs formation.

ObjectiveTo investigate the ameliorating effect of Xiao Chaihutang combined with Erchen Tang （XAE） on metabolic-associated fatty liver disease （MAFLD） in mice and the influence of this therapy on the silent information regulator 1 （SIRT1）/peroxisome proliferator-activated receptor γ coactivator-1α （PGC-1α）/peroxisome proliferator-activated receptor α （PPARα） signaling pathway. MethodsForty-eight C57BL/6 mice were randomized into six groups： normal （CHOW）， atorvastatin （ATO， 0.05 g·kg^-1）， high-fat diet （HFD）， low-dose XAE （XAE-L， 10 g·kg^-1）， medium-dose XAE （XAE-M， 20 g·kg^-1）， and high-dose XAE （XAE-H， 40 g·kg^-1）. Each group contained 8 mice. Except the CHOW group， the other groups of mice were fed a HFD for the modeling of MAFLD. The experiment lasted for 20 weeks. Starting from the 13th week， mice were administered corresponding agents daily by gavage， and the mice in both the CHOW and HFD groups received equal volumes of purified water. At the end of the experiment， cardiac blood， liver， and adipose tissue samples were collected. Pathological staining was performed on the liver and adipose tissue separately. The levels of alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， high-density lipoprotein cholesterol （HDL-C）， low-density lipoprotein cholesterol （LDL-C）， triglycerides （TG）， and total cholesterol （TC） in the serum， as well as TG and TC in the liver， were determined. Additionally， the mRNA levels of fatty acid synthetase （FASN）， stearoyl-CoA desaturase 1 （SCD1）， sterol regulatory element-binding protein 1c （SREBP-1c）， SIRT1， PPARα， PGC-1α， interleukin 6 （IL-6）， interleukin-1β （IL-1β）， and tumor necrosis factor-α （TNF-α） in the liver were measured by real-time PCR. The protein levels of SIRT1， PGC-1α， PPARα， and CPT1α in the mouse liver tissue were determined by Western blot. ResultsCompared with the CHOW group， the HFD group exhibited increased body weight， liver weight， and white adipose tissue weight （P<0.01）. After XAE intervention， these parameters were reduced compared with those in the HFD group （P<0.01）. Pathological section results showed that the morphology of hepatocytes and epididymal white adipocytes in the model mice was significantly improved after XAE intervention， with decreases in both the number and volume of lipid droplets. Furthermore， the XAE groups had lower levels of AST， ALT， HDL-C， LDL-C， TG， and TC in the serum and TG and TC in the liver than the HFD group （P<0.05，P<0.01）. Moreover， XAE administration downregulated the mRNA levels of lipid synthesis-related genes （FASN and SCD1） （P<0.05） and upregulated the mRNA levels of lipid oxidation-related genes （SIRT1， PPARα， and PGC-1α） （P<0.05，P<0.01）. Additionally， the protein levels of SIRT1， PGC-1α， PPARα， and CPT1α in the liver were upregulated after XAE treatment compared with those in the HFD group （P<0.05，P<0.01）. ConclusionXAE exerts a therapeutic effect on MAFLD by activating the SIRT1/PGC-1α/PPARα signaling pathway.

Objective:To detect the expression levels of long non-coding RNAs(lncRNA)in elderly patients with pulmonary tuberculosis(PTB)and those with non-tuberculous lung diseases(non-TB), and to assess the performance of these lncRNA in the differential diagnosis of PTB.Methods:A total of 300 elderly patients with suspected PTB were recruited from Beijing Chest Hospital between January 2024 and September 2024, and were further divided into the PTB group and the non-TB lung disease group based on the results of mycobacterium tuberculosis(MTB)pathogenicity testing.Peripheral blood mononuclear cells were isolated using a lymphocyte separation solution, and RNA was extracted using the TRIzol method.Nine lncRNAs, previously identified as differentially expressed in PTB through our group's microarray analysis, were selected and detected by real-time fluorescence quantitative polymerase chain reaction to evaluate the expression levels of these lncRNAs between the PTB and non-TB lung disease groups.The overall patients were randomly divided into training and validation sets in a 7∶3 ratio.Lasso regression was employed to select the characteristic variables, and a random forest algorithm was then used to construct the lncRNA diagnostic portfolio.Receiver operating characteristic(ROC)curves were generated to evaluate the diagnostic performance of individual lncRNAs and the combined panel in differentiating elderly patients with PTB from those with other non-TB lung diseases.Results:A total of 201 cases were included, with 105 confirmed elderly patients diagnosed with PTB(52.2%)and 96 elderly patients suffering from non-TB lung disease(47.8%).Compared to the elderly patients with non-TB lung disease, the expression levels of ENST00000417346.1, ENST00000620744.1, lncRNA PWP1, ENST00000583184.1, lncRNA ABHD17B, ENST00000607464.1, ENST00000516057.1, and NR_003000 were significantly downregulated in the PTB patients, whereas the expression level of lncRNA BCL2L10 was significantly upregulated in the PTB patients.ROC analysis revealed that the area under the curve(AUC)for each lncRNA ranged from 0.659 to 0.848.The diagnostic panel, which included NR_003000, ENST00000607464.1, ENST00000583184.1, and ENST00000620744.1 as determined by Lasso analysis, exhibited AUC values of 0.917 and 0.906 in the training and validation sets, respectively.The performance of this panel was superior to that of each individual lncRNA.Conclusions:The random forest model, which incorporates NR_003000, ENST00000607464.1, ENST00000583184.1, and ENST00000620744.1, demonstrates potential in differentiating between PTB and non-TB lung diseases.

Objective:To detect the expression levels of long non-coding RNAs(lncRNA)in elderly patients with pulmonary tuberculosis(PTB)and those with non-tuberculous lung diseases(non-TB), and to assess the performance of these lncRNA in the differential diagnosis of PTB.Methods:A total of 300 elderly patients with suspected PTB were recruited from Beijing Chest Hospital between January 2024 and September 2024, and were further divided into the PTB group and the non-TB lung disease group based on the results of mycobacterium tuberculosis(MTB)pathogenicity testing.Peripheral blood mononuclear cells were isolated using a lymphocyte separation solution, and RNA was extracted using the TRIzol method.Nine lncRNAs, previously identified as differentially expressed in PTB through our group's microarray analysis, were selected and detected by real-time fluorescence quantitative polymerase chain reaction to evaluate the expression levels of these lncRNAs between the PTB and non-TB lung disease groups.The overall patients were randomly divided into training and validation sets in a 7∶3 ratio.Lasso regression was employed to select the characteristic variables, and a random forest algorithm was then used to construct the lncRNA diagnostic portfolio.Receiver operating characteristic(ROC)curves were generated to evaluate the diagnostic performance of individual lncRNAs and the combined panel in differentiating elderly patients with PTB from those with other non-TB lung diseases.Results:A total of 201 cases were included, with 105 confirmed elderly patients diagnosed with PTB(52.2%)and 96 elderly patients suffering from non-TB lung disease(47.8%).Compared to the elderly patients with non-TB lung disease, the expression levels of ENST00000417346.1, ENST00000620744.1, lncRNA PWP1, ENST00000583184.1, lncRNA ABHD17B, ENST00000607464.1, ENST00000516057.1, and NR_003000 were significantly downregulated in the PTB patients, whereas the expression level of lncRNA BCL2L10 was significantly upregulated in the PTB patients.ROC analysis revealed that the area under the curve(AUC)for each lncRNA ranged from 0.659 to 0.848.The diagnostic panel, which included NR_003000, ENST00000607464.1, ENST00000583184.1, and ENST00000620744.1 as determined by Lasso analysis, exhibited AUC values of 0.917 and 0.906 in the training and validation sets, respectively.The performance of this panel was superior to that of each individual lncRNA.Conclusions:The random forest model, which incorporates NR_003000, ENST00000607464.1, ENST00000583184.1, and ENST00000620744.1, demonstrates potential in differentiating between PTB and non-TB lung diseases.

Objective:This study aims to analyze the clinical data of elderly patients who experienced respiratory failure after undergoing thoracoscopic-assisted radical lung cancer surgery.The objectives are to identify the risk factors associated with respiratory failure and to investigate the clinical significance of independent risk factors for the early prediction of respiratory failure in this patient population.Methods:A total of 42 elderly patients who developed respiratory failure following thoracoscopic-assisted radical lung cancer surgery at our hospital between January 1, 2021, and December 31, 2023, were continuously collected to form the observation group.Concurrently, a control group was established by randomly selecting elderly lung cancer patients who did not experience respiratory failure during the same period, in a 1: 1 ratio.Clinical data were collected from both groups, and logistic univariate and multivariate analyses were conducted.A receiver operating characteristic(ROC)curve was employed to evaluate the area under the curve(AUC), as well as the sensitivity and specificity of independent risk factors and their combinations.Results:The history of diabetes, PCT levels, and surgical day intake have been identified as independent risk factors for respiratory failure.Multivariate analysis revealed that a history of diabetes( OR: 1.29, 95% CI: 0.89-1.69; P=0.012), PCT( OR: 1.75, 95% CI: 1.51-2.38; P=0.005), and surgical day intake( OR: 1.42, 95% CI: 1.14-1.76; P<0.001)were significantly associated with the occurrence of postoperative respiratory failure.The area under the curve(AUC)values for predicting respiratory failure were 0.679, 0.679, and 0.740, respectively.The sensitivity and specificity for a history of diabetes were 41.2% and 87.1%; for PCT, 64.7% and 64.5%; and for surgical day intake, 70.6% and 74.2%.Notably, a combined model incorporating these three indicators produced an AUC of 0.918, with a sensitivity of 94.1% and a specificity of 80.6%. Conclusions:Following thoracoscopic-assisted radical lung cancer surgery, elderly patients with a history of diabetes, elevated PCT levels, and a daily fluid intake exceeding 2000 ml on the day of surgery demonstrate significant clinical value for the early detection of respiratory failure.