[Objective] To retrospectively analyse the serological characteristics of hemolytic transfusion reactions caused by Rh and Kidd antibodies, and to provide reference for safe, timely, and effective blood transfusion. [Methods] Two cases of patients with RhCcEe and Kidd blood type who experienced allogeneic transfusion at Dazhou Central Hospital were selected. A series of immunohematological tests were performed, including ABO, RhDCcEe and Kidd blood typing, unexpected antibody screening and identification, crossmatching, direct antiglobulin test, acid elution test, and capillary centrifugation to separate the patient's own red blood cells from donated red blood cells. [Results] Unexpected antibody screening, antibody identification, and direct antiglobulin test were positive in both patients. Case 1 had anti-Jk in the plasma, but no specific antibodies were found in the eluate. Case 2 had anti-c and E in the plasma, and anti-E was detected in the eluate. High-speed capillary centrifugation revealed corresponding antigen-positive erythrocytes at the distal end of the blood samples of both patients. [Conclusion] Case 1 received Kidd allogeneic red blood cells, and case 2 received RhCcEe allogeneic red blood cells, and both patients developed the corresponding unexpected antibodies, which led to the occurrence of immune haemolytic blood transfusion reaction.

Objective To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. Methods The study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including random forest (RF), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results (1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%.Conclusion Electronic nose combined with machine learning not only has the potential capabilities to differentiate the benign and malignant pulmonary nodules, but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.

ObjectiveTo discuss the clinical manifestations and image features of Neuromyelitis Optica Spectrum Disorder （NMOSD）with respiratory insufficiency. We present a retrospective review about the use of double filtration plasmapheresis in the treatment of the acute attack of NMOSD in these patients. MethodsAll of our patients with central respiratory insufficiency who suffered attacks of NMOSD were retrospectively considered for inclusion. Extended Disability Status Scale（EDSS）scores were compared within six months after double membrane filtration plasma exchange. ResultsThe clinical data of the six patients included were analyzed. Magnetic Resonance Imaging confirmed that the demyelinating plaques in our patients could involve the medulla oblongata and upper spinal cord. They were managed by plasma exchange given as an initial therapy. The clinical symptoms improved significantly and the patients were successfully withdrawn from the ventilator，with EDSS scores significantly reduced （P<0.001）. ConclusionDemyelination of medulla oblongata and upper spinal cord in NMOSD may lead to acute life-threatening respiratory compromise， and early initiation of double filtration plasmapheresis can be a safe and effective treatment.

Under the trend of increasing aging， integrated elderly care and medical services is an important measure to optimize the supply of elderly care services and promote the good death of the elderly. Using the cooperative production theory and the classical grounded theory， a qualitative analysis was conducted on 38 cases of elderly palliative care and 25 cases of hospital-based palliative care under the integrated elderly care and medical services model from a hospital in Nanning City using Nvivo 20.0 software. This paper found that the integrated elderly care and medical services mode emphasized the deep integration of medical and elderly care services by integrating resources and improving service efficiency， to achieve the basic experience of comprehensive health care for the elderly. The promotion of these experiences has a positive significance for building a multi-agent cooperative production system， strengthening personnel training， perfecting the performance distribution mechanism， and further promoting the development of the national palliative care pilot.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Aim To study the effect of emetine on in-sulin secretion through glucagon-like peptide-1 receptor(GLP-1R).Methods Isolating rat islets were used to carry out insulin secretion experiment.Islets were incubated with different concentrations of emetine(2,10,50 μmol·L-1),different concentrations of glu-cose solution(2.8,11.1,16.7 mmol·L-1)or spe-cific GLP-1R antagonist Exendin(9-39).The amount of insulin secretion in the supernatant of each group was determined by an enzyme-linked radioimmunoas-say.Small molecule compounds were docked to GLP-1R(PDB code:5NX2)using SYBYL-X2.0 software.Results Emetine could promote insulin secretion in high glucose(11.1 mmol·L-1)in a dose-dependent manner.In low glucose(2.8 mmol·L-1),insulin secretion did not change after intervention of emetine.But in high glucose(11.1,16.7 mmol·L-1),insu-lin secretion significantly increased under the treatment of emetine in a glucose-dependent manner.The doc-king score of emetine and GLP-1R was Total Score=6.82,C Score=5,indicating that emetine had a good binding affinity with GLP-1R.Using Exendin(9-39)to block GLP-1R,the insulinotropic effect of emetine was reduced.Conclusion Emetine could promote in-sulin secretion,which is related to the activation of GLP-1R.

Objective To investigate the therapeutic effects of proximal femoral nail antirotation(PFNA)assisted by robot navigation and PFNA guided by C-arm X-ray machine for the treatment of intertrochanteric fracture of femur(IFOF).Methods The 100 patients with unilateral IFOF in our hospital were selected as the study subjects.They were divided into the control group(50 cases)and the robot-assisted group(50 cases)according to random number table method.The control group was treated with PFNA internal fixation under C-arm X-ray machine fluoroscopy,and the robot-assisted group was treated with PFNA internal fixation assisted by robot navigation.Surgical indicators,fracture reduction and fracture healing,stress response indexes,hip joint function,quality of life score and incidence of surgery related complications were compared between the two groups.Results The operation time,total fluoroscopy time,nail placement time and fracture healing time of the robot-assisted group were shorter than those of the control group(P＜0.05);and the intraoperative blood loss,guide needle adjustment frequency,and fluoroscopy frequency of the robot-assisted group were less than those of the control group(P＜0.05).The fracture reduction and fracture healing in the robot-assisted group were better than those in the control group(P＜0.05).Two days after operation,the levels of serum norepinephrine(NE),angiotensin Ⅱ(Ang Ⅱ)and superoxide dismutase(SOD)in the two groups were higher than those before operation(P＜0.05),and the levels of serum NE,Ang Ⅱ and SOD in the robot-assisted group were lower than those in the control group(P＜0.05).The Harris score and 36-item short-form(SF-36)score of patients 7 days and 3 months after surgery in the two groups were higher than those before surgery(P＜0.05),and the above scores 3 months after surgery were higher than those 7 days after surgery(P＜0.05).Harris score and SF-36 score 7 days and 3 months after operation in the robot-assisted group were higher than those in the control group(P＜0.05).The incidence of complications in the robot-assisted group was lower than that in the control group(P＜0.05).Conclusion Compared with the C-arm X-ray machine fluoroscopy,the treatment of IFOF with PFNA assisted by robot navigation can further shorten the operation time,reduce the surgical trauma and the incidence of complications,achieve better effect of fracture reduction and healing,reduce stress response of the body,and improve hip joint function and quality of life for patients.

Objective To monitor the antifungal resistance of clinical isolates of Candida spp.in the East China region.Methods MALDI-TOF MS or molecular methods were used to re-identify the strains collected from January 2018 to December 2022.Antifungal susceptibility testing was performed using the broth microdilution method.The susceptibility test results were interpreted according to the breakpoints of 2022 Clinical and Laboratory Standards Institute(CLSI)documents M27 M44s-Ed3 and M57s-Ed4.Results A total of 3 026 strains of Candida were collected,65.33％of which were isolated from sterile body sites,mainly from blood(38.86％)and pleural effusion/ascites(10.21％).The predominant species of Candida were Candida albicans(44.51％),followed by Candida parapsilosis complex(19.46％),Candida tropicalis(13.98％),Candida glabrata(10.34％),and other Candida species(0.79％).Candida albicans showed overall high susceptibility rates to the 10 antifungal drugs tested(the lowest rate being 93.62％).Only 2.97％of the strains showed dose-dependent susceptibility(SDD)to fluconazole.Candida parapsilosis complex had a SDD rate of 2.61％and a resistance rate of 9.42％to fluconazole,and susceptibility rates above 90％to other drugs.Candida glabrata had a SDD rate of 92.01％and a resistance rate of 7.99％to fluconazole,resistance rates of 32.27％and 48.24％to posaconazole and voriconazole non-wild-type strains(NWT),respectively,and susceptibility rates above 90％to other drugs.Candida tropicalis had resistance rates of 29.55％and 26.24％to fluconazole and voriconazole,respectively,resistance rates of 76.60％and 21.99％to posaconazole and echinocandins non-wild-type strains(NWT),and a resistance rate of 2.36％to echinocandins.Conclusions The prevalence and species distribution of Candida spp.in the East China region are consistent with previous domestic and international reports.Candida glabrata exhibits certain degree of resistance to fluconazole,while Candida tropicalis demonstrates higher resistance to triazole drugs.Additionally,echinocandins resistance has emerged in Candida albicans,Candida glabrata,Candida tropicalis,and Candida parapsilosis.

Objective:To investigate the expression level of UBE2C in liver cancer tissues and its effect on the proliferation and invasion of hepatocellular carcinoma cells HepG2 after UBE2C silencing.Methods:The data set of liver cancer was downloaded from the TCGA database.Ac-cording to the median expression level of UBE2C mRNA in liver cancer tissues,all liver cancer pa-tients were divided into UBE2C higher(n=169)and lower expression group(n=205),respectively.The expression level of UBE2C mRNA in liver cancer tissues and its relationship with the patients prognosis was analyzed.COX regression was used to analyze the influencing factors of the liver cancer patients prognosis.The human hepatocellular carcinoma cell lines(HepG2,Huh7 and SMMC-7721)and human nromal hepatic epithelial cell line(THLE-3)were selected,and the ex-pression level of UBE2C in the four cell lines were detected by Western blot and real-time fluores-cence quantitative PCR,respectively.The HepG2 cell line was protein and mRNA expression leves divided into control group,NC group and si-UBE2C group according to UBE2C silencing.The ef-fects of UBE2C silencing on proliferation and invasion of HepG2 cell line were analyzed.Results:The expression level of UBE2C mRNA in liver cancer tissues and adjacent normal liver tissues were 4.342(3.239,5.635)and 0.905(0.587,1.230),respectively.Compared with adjacent normal liver tissues,UBE2C mRNA levels in liver cancer tissues were significantly higher(P＜0.001).The UBE2C mRNA expression levels in liver cancer tissues and paired adjacent normal liver tissues were 4.266(3.342,5.054)and 0905(0.587,1.230),respectively.Compared with paired adjacent normal liver tissues,UBE2C mRNA expression levels in liver cancer tissues were significantly higher(P＜0.001).The median survival time of UBE2C mRNA higher and lower expression groups was 48.85 months and 69.38 months.Compared with the lower expression group,the median survival time of UBE2C mRNA higher expression group was significantly shortened(P=0.045).T staging(T3/T4)and UBE2C expression(higher expression)were independent risk factors for poor prognosis in patients with liver cancer(P＜0.05).Compared with human liver epithelial cell line THLE-3,UBE2C protein and mRNA were significantly higher expressed in human hepatocellular carcinoma cell line HepG2,Huh7 and SMMC-7721(P＜0.05).The expression level of UBE2C protein and mRNA expression was the most significant in human hepatocellular carcinoma cell line HepG2 relative to cell line Huh7 and SMMC-7721.The CCK-8 results show that the cell proliferation rate in si-UBE2C group were significantly decreased protein and mRNA expression levels compared to control group and NC group at 72 h and 96 h,and the differences were significant(P＜0.05).The number of invasive cells in control group,NC group and si-UBE2C group were(23.12±3.45),(24.33±2.83)and(10.21±1.14),respectively.Compared with control group and NC group,the number of invasive cells in si-UBE2C group was significantly decreased(P＜0.05).Conclusion:UBE2C was higher expressed in liver cancer,and can be used as a biomarker for poor prognosis of patients with liver cancer.After silencing of UBE2C gene can significantly inhibit proliferation and invasion of HepG2.

The continued aging of the population has led to a surge in long-term care needs for the elderly.Proactive preparation for future care(PFC)for the elderly can effectively meet the care needs caused by aging,improve their physical and mental health,and promote the elderly to maximize their physiological,psychological and social functions,finally realizing healthy aging.This paper reviews the theoretical basis,concept connotation,measurement tools,influencing factors and intervention strategies of PFC for the elderly,and puts forward the prospects for future research,so as to provide references for potential mechanism and empirical research of PFC for Chinese seniors.