Ecological cultivation is an important way for the sustainable production of traditional Chinese medicine in the context of the carbon peaking and carbon neutrality goals. Facility cultivation and simulative habitat cultivation modes have been developed and applied to develop the endangered Dendrobium huoshanense on the basis of protection. However, the differences in the greenhouse gas emissions and global warming potential of these cultivation modes remain unexplored, which limits the accurate assessment of carbon-friendly ecological cultivation modes of D. huoshanense. Greenhouse gas emission flux monitoring based on the static chamber method provides an effective way to solve this problem. Therefore, this study conducted a field experiment in the facility cultivation and simulative habitat cultivation modes at a D. huoshanense cultivation base in Dabie Mountains, Anhui Province. From April 2023 to March 2024, samples of greenhouse gases were collected every month, and the concentrations of CO_2, CH_4, and N_2O of the samples were then detected by gas chromatography. The greenhouse gas emission fluxes, cumulative emissions, and global warming potential were further calculated, and the following results were obtained.(1)The two cultivation modes of D. huoshanense showed significant differences in greenhouse gas emission fluxes, especially the CO_2 emission flux, with a pattern of facility cultivation>simulative habitat cultivation [(35.60±11.70)mg·m~(-2)·h~(-1) vs(2.10±4.59)mg·m~(-2)·h~(-1)].(2) The annual cumulative CO_2 emission flux in the case of facility cultivation was significantly higher than that of simulative habitat cultivation[(3 077.00±842.00)kg·hm~(-2) vs(221.00±332.00)kg·hm~(-2)], while no significant difference was found in annual cumulative CH_4 and N_2O emission fluxes.(3) The facility cultivation mode had a significantly higher global warming potential than the simulative habitat cultivation mode [(3 053.00±847.00)kg·hm~(-2) vs(196.00±362.00)kg·hm~(-2)]. Overall, the simulative habitat cultivation of D. huoshanense has obvious carbon-friendly characteristics compared with facility cultivation, which is in line with the concept of ecological cultivation of medicinal plants. This study is of great reference significance for the implementation and promotion of the ecological cultivation mode of D. huoshanense under carbon peaking and carbon neutrality goals.
Dendrobium/chemistry* ; Greenhouse Gases/metabolism* ; Carbon/analysis* ; Ecosystem ; Carbon Dioxide/metabolism* ; China ; Global Warming

Objective To explore an experimental protocol for differentiating human-induced pluripotent stem cells(iPSCs)into highly pure midbrain dopaminergic(DA)neurons.Methods By optimizing a blend of small molecules and recombinant human growth factors,iPSCs were induced to differentiate into ventral midbrain floor plate DA progenitor cells and subsequently into mature substantia nigra pars compacta DA neurons.Throughout the differentiation process,Real-time PCR and immunofluorescent staining were utilized as a method for quality assessment.Results iPSCs firstly differentiate into dopaminergic precursor cells,and then gradually differentiate into DA neurons expressing tyrosine hydroxylase(TH).Conclusion The protocol successfully yields approximately high purity tyrosine hydroxylase-positive(TH+)DA neurons.This differentiation technique offers an effective cellular model for studying the physiological mechanisms and pathogenesis of Parkinson's disease,providing valuable insights for future research and potential therapeutic strategies.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Objective:To investigate the effects of traditional Chinese curve-correcting and rotation-reducing spinal manipulation on biomechanical parameters and factors influencing herniated disc resorption in lumbar disc herniation(LDH).Methods:A retrospective analysis of 51 LDH patients treated between January 2022 and May 2024 was conducted.Lumbosacral parameters(vertebral rotation angle[α],disc angle[β],sacral slope[SS],lumbar lordosis[LL])were measured via MRI before treatment and at final follow-up.Disc resorption was assessed using Michigan State University(MSU)classification.Multivariate logistic regression identified factors associated with resorption.Results:Post-treatment α angle significantly decreased(3.02°→1.86°,P=0.002),while SS(28.4°→30.0°,P＜0.001)and LL angles(31.0°→35.12°,P＜0.001)increased;Disc resorption occurred in 56.86％(29/51)of patients.Longer disease course(OR=0.79,95％CI:0.69-0.91)and disc calcification(OR=0.03,95％CI:0.00-0.25)were independent inhibitors of resorption(P＜0.001).Conclusion:Spinal manipulation restores lumbosacral biomechanics by reducing vertebral rotation and increasing lumbar curvature,with higher resorption rates in patients with short duration(≤6 months),non-calcified discs,and MSU type 2-3 herniations.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Objective:To investigate the effects of traditional Chinese curve-correcting and rotation-reducing spinal manipulation on biomechanical parameters and factors influencing herniated disc resorption in lumbar disc herniation(LDH).Methods:A retrospective analysis of 51 LDH patients treated between January 2022 and May 2024 was conducted.Lumbosacral parameters(vertebral rotation angle[α],disc angle[β],sacral slope[SS],lumbar lordosis[LL])were measured via MRI before treatment and at final follow-up.Disc resorption was assessed using Michigan State University(MSU)classification.Multivariate logistic regression identified factors associated with resorption.Results:Post-treatment α angle significantly decreased(3.02°→1.86°,P=0.002),while SS(28.4°→30.0°,P＜0.001)and LL angles(31.0°→35.12°,P＜0.001)increased;Disc resorption occurred in 56.86％(29/51)of patients.Longer disease course(OR=0.79,95％CI:0.69-0.91)and disc calcification(OR=0.03,95％CI:0.00-0.25)were independent inhibitors of resorption(P＜0.001).Conclusion:Spinal manipulation restores lumbosacral biomechanics by reducing vertebral rotation and increasing lumbar curvature,with higher resorption rates in patients with short duration(≤6 months),non-calcified discs,and MSU type 2-3 herniations.

Objective To explore the incidence of long CO VID symptoms in patients infected with Omicron variant of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Methods According to the inclusion and exclu-sion criteria of literatures,relevant studies without language restrictions published up to 2024 were retrieved from both Chinese and English databases.The Chinese databases were China National Knowledge Infrastructure(CNKI),Wanfang Database,and VIP databases,and the foreign databases were PubMed,Embase,and Web of Science.Three-step screening was used to select literatures,and Stata 17.0 software was used for analysis.Results The incidence of at least one sequelae in patients infected with Omicron variant was 29.62％.The most common symptoms included fatigue(19.10％),joint or muscle pain(11.06％),memory loss(9.71％),brain fog(8.80％),cough(8.42％),headache(7.26％),and sore throat(6.68％).Subgroup analysis results showed that with the extension of follow-up(3 months vs 6 months),the incidence of smell or taste changes was significantly re-duced(7.22％vs 0.78％).The higher the proportion of women(＜50％vs 50％-65％vs＞65％),the higher the incidence of joint or muscle pain(1.09％vs 4.62％vs 19.53％);the greater the median age(≥45 years vs＜45 years),the higher the incidence of chest pain or chest distress(0.90％vs 3.86％),all with statistically significant differences(all P＜0.05).Conclusion Incidence of long COVID in Omicron-infected patients is high and can cause various symptoms.Follow-up time,median age and gender proportion have significant impacts on the incidence of some symptoms.

Objective:To explore the risk factors for central venous catheter (CVC) dysfunction in hemodialysis patients, construct a risk prediction model, and verify the model's predictive performance.Methods:The retrospective research method was adopted. From January 2021 to August 2023, convenience sampling was used to select 442 patients who underwent hemodialysis by CVC at the First Hospital of Shanxi Medical University, Shanxi Provincial People's Hospital, and Shanxi Bethune Hospital as the study subjects. Patients were divided into a modeling group ( n=309) and a validation group ( n=133) according to the order of time of CVC. The modeling group was divided into groups based on whether patients experienced catheter dysfunction. Multivariate Logistic regression was used to analyze the influencing factors of hemodialysis catheter dysfunction and construct a nomogram model. The model's predictive performance was evaluated using the calibration curve, area under the receiver operating characteristic curve ( AUC), and the Hosmer Lemeshow goodness of fit test. Results:Multivariate Logistic regression analysis showed that history of thrombosis, blood hypercoagulability, catheterization site, catheter-related infection, and catheterization duration were influencing factors for catheter dysfunction in hemodialysis ( OR=5.119, 5.174, 6.362, 2.913, and 5.353; all P<0.05). The above five factors were used as independent variables to construct a nomogram. Internal validation of the model showed that the Hosmer Lemeshow test was χ 2=10.828, P=0.212, and AUC was 0.837 [95% confidence interval (0.781, 0.893) ], and the calibration curve fitted well with the ideal curve. External validation of the model indicated that the Hosmer Lemeshow test was χ 2=1.944, P=0.925, and AUC was 0.825 [95% confidence interval (0.744, 0.906) ], and the calibration curve almost coincided with the ideal curve. Conclusions:The constructed nomogram can predict the risk of catheter dysfunction in hemodialysis patients and provide a reference for nursing staff to develop corresponding interventions.

Background and aim:Hepatic ischemia-reperfusion injury(IRI)is a significant challenge in liver trans-plantation,trauma,hypovolemic shock,and hepatectomy,with limited effective interventions available.This study aimed to investigate the role of leukocyte cell-derived chemotaxin 2(LECT2)in hepatic IRI and assess the therapeutic potential of Lect2-short hairpin RNA(shRNA)delivered through adeno-associated virus(AAV)vectors. Materials and methods:This study analyzed human liver and serum samples from five patients under-going the Pringle maneuver.Lect2-knockout and C57BL/6J mice were used.Hepatic IRI was induced by clamping the hepatic pedicle.Treatments included recombinant human LECT2(rLECT2)and AAV-Lect2-shRNA.LECT2 expression levels and serum biomarkers including alanine aminotransferase(ALT),aspartate aminotransferase(AST),creatinine,and blood urea nitrogen(BUN)were measured.Histological analysis of liver necrosis and quantitative reverse-transcription polymerase chain reaction were performed. Results:Serum and liver LECT2 levels were elevated during hepatic IRI.Serum LECT2 protein and mRNA levels increased post reperfusion.Lect2-knockout mice had reduced weight loss;hepatic necrosis;and serum ALT,AST,creatinine,and BUN levels.rLECT2 treatment exacerbated weight loss,hepatic necrosis,and serum biomarkers(ALT,AST,creatinine,and BUN).AAV-Lect2-shRNA treatment significantly reduced weight loss,hepatic necrosis,and serum biomarkers(ALT,AST,creatinine,and BUN),indicating thera-peutic potential. Conclusions:Elevated LECT2 levels during hepatic IRI increased liver damage.Genetic knockout or shRNA-mediated knockdown of Lect2 reduced liver damage,indicating its therapeutic potential.AAV-mediated Lect2-shRNA delivery mitigated hepatic IRI,offering a potential new treatment strategy to enhance clinical outcomes for patients undergoing liver-related surgeries or trauma.

mRNA vaccines and drugs enter host cells through delivery vectors and produce target proteins using the protein synthesis mechanism of cells. mRNA and target proteins can induce the body to produce innate immunity and adaptive immunity, and the target protein itself can also play a corresponding role. Tumor cells are inhibited and cleared under the above immune effects and target proteins. This article reviews the immunogenicity of mRNA, that is, the specific mechanism of stimulating the body to produce an immune response.At the same time, the main types of cells transfected by mRNA vaccine were briefly introduced. (1) Muscle cells, epidermal cells, dendritic cells and macrophages at the injection site; (2) immune cells in peripheral lymphoid organs;(3) liver cells and spleen cells, etc. Although transfected with a variety of cells, it is mainly enriched in immune cells and liver cells because immune cells express toll-like receptors and liver cells express low-density lipoprotein receptors. mRNA vaccines and drugs are mainly divided into non-replicating mRNA (nrmRNA),self-amplifying RNA (saRNA), trans-amplifying RNA (taRNA) and circular RNA (circRNA).This article reviews how these 4 types of vaccines and drugs work, and compares their advantages and disadvantages. Due to its inherent immunogenicity, instability, and low delivery efficiency in vivo, mRNA vaccines and drugs have been unable to enter the clinic. This article describes in detail how to reformation and modify the 5'cap, 5'UTR, 3'UTR, ORF, 3'Poly(A) and some nucleotides of mRNA to eliminate its immunogenicity and instability. Due to the low efficiency of the delivery carrier, the researchers optimized it. This article briefly introduces the application of non-viral vectors and their targeting, specifically involving the mechanism of action of various types of delivery vectors and their advantages and disadvantages, and summarizes some of the current targeting vectors. Targeted carriers can improve the delivery efficiency of mRNA to specific tissues and prevent side effects of systemic exposure, such as liver injury. The specific methods of using mRNA vaccines and drugs to treat cancer are as follows: mRNA can be used to encode and transcribe tumor-associated antigens, tumor-specific antigens (TSAs), therapeutic antibodies, cytokines, tumor suppressors, oncolytic viruses, CRISPR-Cas9, CARs and TCRs, so as to play an anti-tumor role. In this paper, the specific mechanism of the above methods and the current research and development of corresponding mRNA vaccines and drugs are briefly reviewed. The successful development of the COVID-19 mRNA vaccine has brought mRNA technology to the attention of the world and brought new and effective means for the prevention and treatment of cancer. mRNA vaccines and drugs have the advantages of short development cycle, dual immune mechanism, safety, high efficiency and large-scale production. At the same time, there are also many areas that need further improvement, such as the development of ideal target TSAs, the in-depth development of saRNA, taRNA and circRNA, the development of targeted nano-delivery for different tissues and organs, the expansion of mRNA administration routes, and the development of mRNA that can be stably stored at room temperature or even high temperature. These problems need to be further studied and solved. In addition to cancer therapy, mRNA vaccines and drugs can also be used in the treatment of infectious diseases, genetic diseases, regenerative medicine and anti-aging. mRNA vaccines and drugs are a very promising platform, and we believe that they will benefit cancer patients in the near future.