OBJECTIVES: Multiple myeloma (MM) is a highly heterogeneous hematologic malignancy, with disease progression driven by cytogenetic abnormalities and a complex bone marrow microenvironment. This study aims to construct a prognostic model for MM based on transcriptomic data and lipid metabolism related genes (LRGs), and to identify potential drug targets for high-risk patients to support clinical decision-making. METHODS: In this study, 2 transcriptomic datasets covering 985 newly diagnosed MM patients were retrieved from the Gene Expression Omnibus (GEO) database. Univariate Cox regression and 101 machine learning algorithms were used for gene selection. An LRG-based prognostic model was constructed using Stepwise Cox (both directions) and random survival forest (RSF) algorithms. The association between the prognostic score and clinical events was evaluated, and model performance was assessed using time-dependent receiver operating characteristic (ROC) curves and the C-index. The added predictive value of combining prognostic scores with clinical variables and staging systems was also analyzed. Differentially expressed genes between high- and low-risk groups were identified using limma and clusterProfiler and subjected to pathway enrichment analysis. Drug sensitivity analysis was conducted using the Genomics of Drug Sensitivity in Cancer (GDSC) database and oncoPredict to identify potential therapeutic targets for high-risk patients. The functional role of key LRGs in the model was validated via in vitro cell experiments. RESULTS: An LRG-based prognostic model (LRG17) was successfully developed using transcriptomic data and machine learning. The model demonstrated robust predictive performance, with area under the curve (AUC) values of 0.962, 0.912, and 0.842 for 3-, 5-, and 7-year survival, respectively. Patients were stratified into high- and low-risk groups, with high-risk patients showing significantly shorter overall survival (OS) and event-free survival (EFS) (both P<0.001) and worse clinical profiles (e.g., lower albumin, higher β2-microglobulin and lactate dehydrogenase levels). Enrichment analysis revealed that high-risk patients were significantly enriched for pathways related to chromosome segregation and mitosis, whereas low-risk patients were enriched for immune response and immune cell activation pathways. Drug screening suggested that AURKA inhibitor BMS-754807 and FGFR3 inhibitor I-BET-762 may be more effective in high-risk patients. Functional assays demonstrated that silencing of key LRG PLA2G4A significantly inhibited cell viability and induced apoptosis. CONCLUSIONS LRGs serve as promising biomarkers for prognosis prediction and risk stratification in MM. The overexpression of chromosomal instability-related and high-risk genetic event-associated genes in high-risk patients may explain their poorer outcomes. Given the observed resistance to bortezomib and lenalidomide in high-risk patients, combination therapies involving BMS-754807 or I-BET-762 may represent effective alternatives.
Humans ; Multiple Myeloma/mortality* ; Prognosis ; Lipid Metabolism/genetics* ; Transcriptome ; Machine Learning ; Male ; Female ; Gene Expression Profiling ; Algorithms

Objective To observe the effect of specialist team-led walking-cognition dual-task train-ing combined with active self-disclosure on control and balance abilities in elderly patients with acute ischemic stroke(AIS).Methods A total of 90 elderly AIS patients treated in our hospital from January 2022 to January 2024 were enrolled and randomly assigned into the control group and the observation group,with 45 cases in each group.The control group received routine walk-ing training,while the observation group received specialist team-led walking-cognition dual-task training combined with active self-disclosure intervention.Control ability,balance ability,walking ability,cognitive function and psychological status were compared between the two groups.Results After intervention,the scores of Sheikh Trunk Control Scale and Fugl-Meyer Assessment(FMA),and the static balance score,dynamic balance score and total score of Berg Balance Scale(BBS)were significantly increased in both the observation and the control groups(P＜0.05),and all above scores were obviously higher in the former group than the latter one(P＜0.01).The two groups also obtained notably shorter single-and dual-task walking time after intervention,but there were no statistical difference in the single-task walking time in both groups before and after intervention(P＞0.05).After intervention,the observation group had significantly shorter dual-task walking time(22.87±7.36 s vs 27.52±8.71 s,P=0.008)and lower walking time cost of dual task[(11.16±4.07)％vs(25.61±7.82)％,P=0.000]when compared with the control group.After intervention,the scores of Mini-Mental Status Examination were increased,and the scores of Hamilton Depression Rating Scale and Hamilton Anxiety Rating Scale were decreased in the two groups(P＜0.05).Conclusion Specialist team-led walking-cognition dual-task training com-bined with active self-disclosure intervention can effectively improve trunk control ability,balance ability,walking ability,cognitive function and psychological state in elderly AIS patients,has cer-tian clinical application value.

ObjectiveTo explore the differences in the accumulation of secondary metabolites of Dendrobium nobile cultivated on epiphytic stones and trees， so as to elucidate the scientific connotation of "only those that grow on stones has superior quality"， and provide a direction for the cultivation and quality evaluation of D. nobile. MethodsUltra-performance liquid chromatography-triple quadrupole/linear ion trap mass spectrometry（UPLC-QTRAP-MS/MS）-based widely targeted metabolomics was used to detect the metabolites of D. nobile cultivated on epiphytic stones and trees. And the combination of principal component analysis（PCA）， hierarchical cluster analysis（HCA）， and orthogonal partial least squares-discriminant analysis（OPLS-DA） was performed for multivariate statistical analysis of metabolites. Differential metabolites were screened by variable importance in the projection（VIP） value≥1 and log₂fold change（FC）≥1 or ≤-1， and Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analysis was conducted. ResultsA total of 1 267 metabolites were identified in the stems of D. nobile from the two cultivation modes， dominated by flavonoids（292）， phenolic acids（284）， and alkaloids（189）. Through OPLS-DA screening， 473 differential metabolites were obtained. Compared to epiphytic tree-cultivated D. nobile， epiphytic stone-cultivated D. nobile exhibited upregulation of flavonoids， phenolic acids， alkaloids， lignans and coumarins， while quinones and terpenoids were down-regulated. The differential metabolites mainly included flavonoid glycosides and alkaloids， and these differential metabolites significantly contributed to characterizing the two cultivation patterns. KEGG enrichment analysis revealed significant enrichment in pathways of flavone and flavonol biosynthesis， flavonoid biosynthesis， tyrosine metabolism， and phenylalanine metabolism in epiphytic stone-cultivated D. nobile. ConclusionEpiphytic stone cultivation is beneficial for the accumulation of phenolic acids， flavonoids， and alkaloids in D. nobile， indicating that the "only those that grow on stones has superior quality" documented in the materia medica has certain scientific basis， and the findings also provide a reference for quality evaluation and discrimination research between epiphytic stone and tree cultivated D. nobile.

ObjectiveTo investigate the processing technology of calcined Haematitum based on the concept of quality by design（QbD） and to assess its health risk. MethodsTaking whole iron content， Fe²⁺ dissolution content and looseness as critical quality attributes（CQAs）， and calcination temperature， calcination time， spreading thickness and particle size as critical process parameters（CPPs） determined by the failure mode and effect analysis（FMEA）， the processing technology of calcined Haematitum was optimized by orthogonal test combined with analytic hierarchy process-criteria importance through intercriteria correlation（AHP-CRITIC） hybrid weighting method. The contents of heavy metals and harmful elements were determined by inductively coupled plasma mass spectrometry， and the health risk assessment was carried out by daily exposure（EXP）， target hazard quotient（THQ） and lifetime cancer risk（LCR）， and the theoretical value of the maximum limit was deduced. ResultsThe optimal processing technology for calcined Haematitum was calcination at 650 ℃， calcination time of 1 h， particle size of 0.2-0.5 cm， spreading thickness of 1 cm， and vinegar quenching for 1 time［Haematitum-vinegar（10：3）］. The contents of 5 heavy metals and harmful elements in 13 batches of calcined Haematitum were all decreased with reductions of up to 5-fold. The cumulative THQ of 2 batches of samples was>1， while the cumulative THQ of all batches of Haematitum was>1. The LCR of As in 1 batches of Haematitum was 1×10^-6-1×10^-4， and the LCR of the rest was<1×10^-6， and the LCRs of calcined Haematitum were all<1×10^-6， indicating that the carcinogenic risk of calcined Haematitum was low， but special attention should still be paid to Haematitum medicinal materials. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg were formulated as 1 014， 25， 17， 27， 7 mg·kg^-1. ConclusionThe optimized processing technology of calcined Haematitum is stable and feasible， and the contents of heavy metals and harmful elements are reduced after processing. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg are formulated to provide a scientific basis for the formulation of standards for the limits of harmful elements in Haematitum.

ObjectiveTo investigate the processing technology of calcined Haematitum based on the concept of quality by design（QbD） and to assess its health risk. MethodsTaking whole iron content， Fe²⁺ dissolution content and looseness as critical quality attributes（CQAs）， and calcination temperature， calcination time， spreading thickness and particle size as critical process parameters（CPPs） determined by the failure mode and effect analysis（FMEA）， the processing technology of calcined Haematitum was optimized by orthogonal test combined with analytic hierarchy process-criteria importance through intercriteria correlation（AHP-CRITIC） hybrid weighting method. The contents of heavy metals and harmful elements were determined by inductively coupled plasma mass spectrometry， and the health risk assessment was carried out by daily exposure（EXP）， target hazard quotient（THQ） and lifetime cancer risk（LCR）， and the theoretical value of the maximum limit was deduced. ResultsThe optimal processing technology for calcined Haematitum was calcination at 650 ℃， calcination time of 1 h， particle size of 0.2-0.5 cm， spreading thickness of 1 cm， and vinegar quenching for 1 time［Haematitum-vinegar（10：3）］. The contents of 5 heavy metals and harmful elements in 13 batches of calcined Haematitum were all decreased with reductions of up to 5-fold. The cumulative THQ of 2 batches of samples was>1， while the cumulative THQ of all batches of Haematitum was>1. The LCR of As in 1 batches of Haematitum was 1×10^-6-1×10^-4， and the LCR of the rest was<1×10^-6， and the LCRs of calcined Haematitum were all<1×10^-6， indicating that the carcinogenic risk of calcined Haematitum was low， but special attention should still be paid to Haematitum medicinal materials. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg were formulated as 1 014， 25， 17， 27， 7 mg·kg^-1. ConclusionThe optimized processing technology of calcined Haematitum is stable and feasible， and the contents of heavy metals and harmful elements are reduced after processing. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg are formulated to provide a scientific basis for the formulation of standards for the limits of harmful elements in Haematitum.

Japanese encephalitis virus(JEV)usually evades the inhibitory effect of the innate immunity factor type Ⅰ interferon(Ⅰ-IFN)when it infects human cells and tissues.The virus then causes a series of serious symptoms,such as spasticity,neurodegenerative lesions,neuroinflammation,and even death.Generally,JEV escapes innate immunity by inhibiting IFN-α/β production and the interferon Janus kinase-signal transducer and activator of transcription signaling pathway.Because of this special immune escape mechanism,various mouse infection models have been constructed for the study of the pathogenesis of and therapeutic regimens for JEV infections.In this review,based on an exposition of the IFN immune escape mechanism of JEV,we systematically introduce the concept of JEV-infected mouse models and analyze the characteristics of these models and the degree to which they simulate human symptoms.The intention is to develop various new JEV-infected mouse models based on potential new research targets and provide novel ideas for animal models for JEV research.

Objective To develop a rehabilitation nursing model for knee osteoarthritis(KOA)of external treatment in traditional Chinese medicine(TCM).Methods Between February and June 2023,a preliminary KOA rehabilitation nursing model was developed through literature search and semi-structured interview method.Two rounds of Delphi consultations were conducted with the selected experts,to establish a rehabilitation nursing model for KOA of TCM external treatment.Results A total of 24 experts from different regions participated in the consultation.The final rehabilitation nursing model of TCM external treatment for KOA included 3 primary indicators,16 secondary indicators and 91 tertiary indicators.The response rates from the two rounds of expert consultation were 96.00%and 100.00%,respectively,and the rates of expert opinion proposal were 58.33%and 8.33%,respectively.The expert authority coefficient were 0.906 and 0.923.The two rounds of expert consultation were 0.137 and 0.236 in Kendall's coefficient of concordance(W),with statistically significant differences(both P<0.001).The importance scores of each item in the second inquiry ranged from 3.75 to 4.88,and the coefficient of variation ranged from 0.07 to 0.30,and the full score ratio ranged from 20.83%to 87.50%.Conclusion The rehabilitation nursing model for KOA of TCM external treatment developed in this study is significant,scientific and feasible.It provides a guidance for medical professionals.

Japanese encephalitis virus(JEV)usually evades the inhibitory effect of the innate immunity factor type Ⅰ interferon(Ⅰ-IFN)when it infects human cells and tissues.The virus then causes a series of serious symptoms,such as spasticity,neurodegenerative lesions,neuroinflammation,and even death.Generally,JEV escapes innate immunity by inhibiting IFN-α/β production and the interferon Janus kinase-signal transducer and activator of transcription signaling pathway.Because of this special immune escape mechanism,various mouse infection models have been constructed for the study of the pathogenesis of and therapeutic regimens for JEV infections.In this review,based on an exposition of the IFN immune escape mechanism of JEV,we systematically introduce the concept of JEV-infected mouse models and analyze the characteristics of these models and the degree to which they simulate human symptoms.The intention is to develop various new JEV-infected mouse models based on potential new research targets and provide novel ideas for animal models for JEV research.

Objective:To develop and validate the reliability and validity of the care giver assessment via observation (CGAO) in general hospital .Methods:From July 4, 2022 to June 24, 2023, a total of 120 adult inpatients with somatic diseases in Peking Union Medical College Hospital were selected by cluster sampling. All patients completed the CGAO, union physio-psycho-social assessment questionnaire (UPPSAQ-70) and patient health questionnaire-9 item (PHQ-9) assessment simultaneously. Exploratory factor analysis and item response theory analysis were used to explore the structural validity of CGAO by SPSS 26.0 software.The symptoms items and suicide risk assessed by UPPSAQ-70 and PHQ-9 were used as criteria to verify criterion validity.Results:Through exploratory factor analysis, a single-factor model could be constructed. The analysis based on item response theory suggested that it had a good fit with the single-factor stepwise response model ( χ2/ df=1.307, RMSEA=0.051, CFI=0.986, TLI=0.983). The CGAO total score was significantly positively correlated with the total scores of PHQ-9 and UPPSAQ-70 ( r=0.639, 0.518, both P<0.001). The Cronbach's α coefficient of the CGAO full scale was 0.735. Conclusion:CGAO has good reliability and validity in evaluating mental behavior of patients, and is suitable for early recognition of mental behavior abnormalities of inpatients in general hospitals.

Cell is the most basic unit of life,and normal metabolism is the key to cell growth and development.Reactive oxygen species(ROS)are important regulators of cell function,and hypoxi-a-inducible factor-1 alpha(HIF-1α)is a ROS receptor,which can activate transient receptor poten-tial vanilloid(TRPV)channel.TRPV is a sensor for temperature,pain,and osmotic pressure.Changes in the environment can induce changes in the activity of TRPV channel,which regulates various physiological and pathological processes of cells through its downstream signaling path-ways.Low temperature plasma can regulate cellular TRPV channel activity through HIF-1α.This article mainly reviews the effect of HIF-1α on cell function through TRPV channel,which has ref-erence significance for future research on various diseases related to TRPV channel and their pre-vention and treatment,as well as provides a new idea for using low temperature plasma technology to treat diseases through regulating TRPV channel.