Myelodysplastic syndrome (MDS) is a chronic hematologic disorder characterized by ineffective hematopoiesis, dysplasia of one or more cell lines with or without definite genetic changes. Its diagnosis requires a comprehensive analysis combining morphology, immunology, cytogenetics, and molecular biology findings. In recent years, the development of second-generation sequencing (NGS) has provided great assistance in exploring the molecular pathogenesis of hematological malignancies and guidance for clinical practice. Mutations of a series of gene involved in RNA splicing, DNA methylation, transcriptional regulation, signal transduction, chromatin modification and cohesin complex have been identified as important mechanisms for the development of MDS, among which some mutations have been found to play important roles in the diagnosis, treatment, and prognosis of MDS. This article has provided a comprehensive review the the common molecular genetic abnormalities involved in MDS.
Humans ; Myelodysplastic Syndromes/diagnosis* ; Mutation ; DNA Methylation ; RNA Splicing ; High-Throughput Nucleotide Sequencing

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.

Prolonged disorders of consciousness(pDoC)are complex and prolonged conditions that severely impact patient prognosis and remain a clinical treatment challenge.In recent years,neural regulation-based awakening therapies have been widely applied in the assessment and treatment of pDoC patients.Repetitive transcranial magnetic stimulation(rTMS)technology can regulate neural activity and improve patients'consciousness states,demonstrating positive awakening effects for pDoC patients.However,the optimal stimulation parameters and awakening mechanisms of rTMS remain unclear.This article reviews the pathological mechanisms of pDoC,clinical applications of rTMS at different targeting sites and stimulation frequencies,and focuses on exploring how rTMS promotes consciousness recovery through neural mechanisms such as altering neural pathways,reshaping brain networks,promoting synaptic plasticity and neurotransmitter release,regulating neurotrophic factor expression,and modulating cerebral hemodynamics.Based on artificial intelligence,the article also prospects the future clinical research applications of rTMS.

Objective To establish a model to predict the severity of patients with COVID-19 associated diarrhea by analyzing the differences of laboratory detection indicators in different grades of patients with COVID-19 associated diarrhea.Methods A total of 649 COVID-19 patients combined with diarrhea hospitalized in Wuhan Huoshenshan Hospital from February 2020 to April 2020 were retrospectively selected,and the patients with obvious causes of diarrhea had been excluded.They were further divided into the common group(n=282),severe group(n=314),and critical group(n=53),and the differences in clinical and laboratory indicators among the three groups were compared.The XGBoost model was established,and its diagnostic efficacy in predicting the severity of patients with COVID-19 associated diarrhea was evaluated by the ROC curve.Results There were statistically significant differences in blood routine test,liver function,electrolytes,fecal occult blood and other laboratory indicators among the three groups of COVID-19 associ-ated diarrhea(P＜0.05).The white blood cell count,absolute value and percentage of neutrophils,and levels of serum lactate dehydro-genase(LDH),α-hydroxybutyrate dehydrogenase(α-HBDH),γ-glutamyl transpeptidase(GGT),B-type natriuretic peptide,and blord glucose(Glu)in the critical group were significantly higher than those in the common group and severe group(P＜0.05),while the percentages of lymphocytes,monocytes,eosinophils,and basophils,and chloride concentration were significantly lower than those in the common group and severe group(P＜0.05).The results of the ROC curve showed that the prediction model constructed by eight indicators,including C-reactive protein(CRP),LDH,interleukin-6(IL-6),Glu,PT％activity,chloride(Cl-),D-dimer(DD),and procalcitonin(PCT),had significant predictive value for critical patients(AUCROC=0.939),but no obvious predictive value for the patients in the common group(AUCROC=0.630)and severe group(AUCROC=0.553).Conclusion The COVID-19 patients com-bined with diarrhea have a higher probability of developing severe or critical conditions compared with those without diarrhea.The indi-cators such as CRP,LDH,IL-6,Glu,PT％activity,Cl-,DD,and PCT have significant predictive value on whether the COVID-19 patients combined with diarrhea turn to critical illness.

Objective To systematically evaluate the effectiveness of acupuncture in treating chronic cough and analyze its acupoint selection patterns.Methods Randomized controlled trials(RCTs)on acupuncture for chronic cough were retrieved from databases including CNKI,VIP,Wan Fang Data,CBM,PubMed,and Web of Science,Cochrane Library and Embase from their inception to April 2025.Original data from the included studies were extracted.Meta-analysis was performed to compare the acupuncture treatment group with the western medicine control group[using leukotriene receptor antagonists(LTRAs)and/or glucocorticoids]on outcomes including cough symptom scores,serum tumor necrosis factor-α(TNF-α)levels,pulmonary function indicators[forced vital capacity(FVC)and forced expiratory volume in the first second(FEV1)],overall clinical effectiveness,and incidence of adverse reactions.Publication bias was assessed using funnel plots,and descriptive analysis of the acupoint prescriptions from the included studies was conducted using Rstudio software to summarize the patterns of acupoint selection for chronic cough.Results A total of 10 studies involving 806 patients were included.Meta-analysis results showed that acupuncture was superior to the western medicine control group in improving cough symptom scores,reducing serum TNF-α levels,enhancing pulmonary function(FVC and FEV1),increasing overall clinical effectiveness,and reducing adverse reactions,with statistically significant differences.Further analysis of the 10 included studies revealed that the most frequently used acupoints were Feishu(BL13)(n=9 times),Zusanli(ST36)(n=7 times),Lieque(LU7)(n=6 times),and Pishu(BL20)(n=5 times).The most frequently utilized meridians were the Bladder Meridian of Foot-Taiyang(BL)(n=10 times),the Stomach Meridian of Foot-Yangming(ST)(n=7 times),and the Lung Meridian of Hand-Taiyin(LU)(n=7 times).Acupoints were primarily located on the lower back(36.92%),upper limbs(26.15%),and lower limbs(21.53%).Conclusion Acupuncture is effective in treating chronic cough.The acupoint prescriptions for chronic cough should follow the principles of symptomatic point selection and anterior-posterior point pairing,emphasizing the back-shu and front-mu point pairing method,as well as the upper-lower point pairing method.Points are predominantly selected from the Bladder meridian(BL),lung meridian(LU),and stomach meridian(ST).

Objective To establish a model to predict the severity of patients with COVID-19 associated diarrhea by analyzing the differences of laboratory detection indicators in different grades of patients with COVID-19 associated diarrhea.Methods A total of 649 COVID-19 patients combined with diarrhea hospitalized in Wuhan Huoshenshan Hospital from February 2020 to April 2020 were retrospectively selected,and the patients with obvious causes of diarrhea had been excluded.They were further divided into the common group(n=282),severe group(n=314),and critical group(n=53),and the differences in clinical and laboratory indicators among the three groups were compared.The XGBoost model was established,and its diagnostic efficacy in predicting the severity of patients with COVID-19 associated diarrhea was evaluated by the ROC curve.Results There were statistically significant differences in blood routine test,liver function,electrolytes,fecal occult blood and other laboratory indicators among the three groups of COVID-19 associ-ated diarrhea(P＜0.05).The white blood cell count,absolute value and percentage of neutrophils,and levels of serum lactate dehydro-genase(LDH),α-hydroxybutyrate dehydrogenase(α-HBDH),γ-glutamyl transpeptidase(GGT),B-type natriuretic peptide,and blord glucose(Glu)in the critical group were significantly higher than those in the common group and severe group(P＜0.05),while the percentages of lymphocytes,monocytes,eosinophils,and basophils,and chloride concentration were significantly lower than those in the common group and severe group(P＜0.05).The results of the ROC curve showed that the prediction model constructed by eight indicators,including C-reactive protein(CRP),LDH,interleukin-6(IL-6),Glu,PT％activity,chloride(Cl-),D-dimer(DD),and procalcitonin(PCT),had significant predictive value for critical patients(AUCROC=0.939),but no obvious predictive value for the patients in the common group(AUCROC=0.630)and severe group(AUCROC=0.553).Conclusion The COVID-19 patients com-bined with diarrhea have a higher probability of developing severe or critical conditions compared with those without diarrhea.The indi-cators such as CRP,LDH,IL-6,Glu,PT％activity,Cl-,DD,and PCT have significant predictive value on whether the COVID-19 patients combined with diarrhea turn to critical illness.

There is controversy over the specific and non-specific components in the efficacy evaluation of acupuncture therapy.The placebo effect,as a key non-specific factor,needs to be clarified in terms of its mechanism and clinical value.This article reviewed the research progress in the placebo effect of acupuncture from three aspects:cognitive process,influencing factors,and mechanism.It focused on the regulatory effects of patient expectations,doctor-patient interaction,and individual differences on the effect,summarized key mechanisms such as endogenous opioid system,dopamine reward pathway,and neural projection of rostral anterior cingulate cortex to pontine nucleus,and pointed out the methodological limitations of current comfort acupuncture designs,in order to provide theoretical basis for the optimization of acupuncture clinical research models and the deepening of the effect mechanism.

Objective:To investigate the risk factors for deep venous thrombosis(DVT)in elderly patients with pulmonary tuberculosis.Methods:A total of 240 elderly patients(≥60 years old)with pulmonary tuberculosis, admitted to Beijing Chest Hospital from January 2020 to August 2024, were retrospectively analyzed.Based on the results of lower extremity venous ultrasound, the patients were divided into a DVT group(80 cases)and a non-DVT group(160 cases).The risk factors for DVT were analyzed using univariate and multivariate logistic regression.Results:Univariate analysis revealed that age, diabetes mellitus, chronic heart failure, prolonged bed rest, elevated D-dimer levels, decreased serum albumin, sputum positivity, and other factors were significantly more prevalent in the thrombosis group compared to the non-thrombosis group( P<0.05).Additionally, multivariate logistic regression analysis indicated that age ≥75 years( OR=2.15, 95% CI: 1.32-3.52), chronic heart failure( OR=2.90, 95% CI: 1.35-6.20), bed rest ≥7 days( OR=3.25, 95% CI: 1.75-6.05), D-dimer ≥3.0 mg/L( OR=5.05, 95% CI: 2.71-9.42), sputum positivity( OR=2.34, 95% CI: 1.28-4.29), and low albumin levels( OR=1.89, 95% CI: 1.17-3.06)were identified as risk factors for lower extremity DVT in elderly patients with pulmonary tuberculosis. Conclusions:The risk of DVT in elderly patients with pulmonary tuberculosis is closely associated with pathogen activity, abnormal coagulation function, and prolonged bed rest.The combination of D-dimer levels and sputum positivity can effectively screen for high-risk populations.Clinicians should prioritize early identification and intervention in these high-risk groups to reduce the incidence of DVT.

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.