Objective To systematically evaluate the factors affecting taste alteration in patients undergoing cancer chemotherapy.Methods PubMed,Cochrane Library,Web of Science,CINAHL,Embase,CBM,CNKI,WanFang Data and VIP were searched from the establishment until August 1,2024.The retrieved literature was independently screened,evaluated and the data were extracted by 2 researchers,and statistical analysis was performed using Stata 17.0 software.Results A total of 18 studies were included,involving 4 686 patients.The incidence of taste changes is 73.46％.Totally 9 influencing factors were extracted through quantitative analysis,including oral mucositis(OR=1.98),dry mouth(OR=1.82),nausea(OR=3.05),loss of appetite(OR=2.41),use of triple antiemetic drugs(OR=2.45),gynecological cancers(OR=0.67),lung cancer(OR=0.57),paclitaxel types of chemotherapy d rugs(OR=2.86),and smoking(β=9.38).Conclusion The alteration of taste in cancer chemotherapy patients is in-fluenced by multiple factors.Nurses should regularly and dynamically assess changes in taste and implement individualized and refined nursing interventions in clinical practice to prevent or delay the development of taste alterations,thereby improving patients' quality of life and treatment adherence.

Objective To explore the dual coping experience of nursing dependence among middle-aged and young patients with enterostomy and their primary caregivers from the perspective of family resilience,in order to provide evidence for improving the experience of nursing dependence and promoting family resilience.Methods Us-ing the phenomenological research method in qualitative research,18 young and middle-aged enterostomy patients and their primary caregivers were selected for semi-structured interviews with purpose sampling method,and the in-terview data were analyzed by content analysis method.Results A total of 4 themes and 8 sub-themes were ex-tracted.Theme 1:heavy dependence-elastic fatigue-weak resilience(patients avoid stomas,depression,caregivers help-lessly accepting;patients role reinforcement,excessive dependence,caregivers exhaustion);theme 2:moderate depen-dence-elastic adjustment-strong resilience trend(active exploration,mutual understanding,perceived support;focus ad-justment,mutual dependence,positive relationship);theme 3:mild dependence-elastic space-strong resilience(self-con-trollable feeling,quick adaptation,mutual growth;facing calmly,cherishing life,reshaping value);theme 4:no depen-dence-gradual loss of elasticity-weak resilience trend(refusal to seek help,self isolation,relationship cracks;frustration in seeking help,self-protection,relationship alienation).In this article,we proposed a preliminary family resilience model for patients with enterostomy.Conclusion The dual coping and family resilience of the patients with en-terostomy and their primary caregivers are different and dynamic.Family-centered support should be applied to strengthen the positive coping and improve the level of family resilience.In addition,this study also tried to pro-pose a family resilience model for patients with enterostomy based on nursing dependence,in order to enrich the connotation of family resilience.

Objective By systematically reviewing the development of policies related to rural doctors and their evolution patterns,and by quantitatively analyzing the policy tools and their effectiveness levels,it aim to provide a strategic basis and reference for the high-quality development of China's rural doctor workforce.Methods 60 policies related to rural doctors enacted at the national level from March 2009 to May 2024 were collected,and a three-dimensional analysis framework based on"policy tool-policy period-policy effectiveness"was adopted to analyse the development of rural doctors in China.Results Among the 245 coded policy instruments,demand-type policy instruments accounted for the highest proportion (38.38％),followed by supply-type (31.02％) and environment-type is the least (30.61％).The types of policies are mainly circular,and the number of policies issued fluctuates significantly,with the number of policies issued during the period of high-quality development being the highest in the four periods,and the policies issued during the period of deepening and consolidation being the most specific.Conclusion It is necessary to scientifically grasp the law of evolution of policy orientation and the trend of evolution of policy instruments,rationally adjust the internal structure of policy instruments,and enhance the relevance and synergy of the policy system in order to improve the cohesion of policy effectiveness.

Objective To test the hypothesis that backward crawling and forward crawling share similar inter-joint coordination patterns,thus providing potential evidence for the application of backward crawling in rehabilitation training.Methods The acceleration signals in the X,Y,and Z directions for 9 joints(including bilateral wrists,elbows,shoulders,knees,and hips)in 9 volunteers during forward and backward crawling were collected using a custom signal acquisition system,and the pressure signals were also recorded when the palms contacted the ground.The collected acceleration signals were preprocessed,segmented into cycles,and vectorized.Based on the pressure signals,a single crawling cycle was divided into support phase and swing phase.In addition,principal component analysis was applied to extract inter-joint coordination in limbs at various scales(sagittal,coronal,and transverse planes).Pearson correlation coefficients of inter-joint coordination patterns were compared between forward and backward crawling in support period,swing period,and full cycle.Results The correlation coefficients for coordination patterns in the full cycle at the transverse plane scale were 0.813 5(PC1)and 0.837 5(PC2),and the correlation coefficient of the support period PC2 was 0.901 8.At the sagittal plane scale,the correlation coefficient of the support period PC1 was 0.948 5.Conclusion The study provides preliminary evidence that limb motion coordination patterns during backward crawling are similar to those observed during forward crawling.Future research will further explore the effects of backward crawling on functional rehabilitation in individuals with motor impairments.

Objective To observe the therapeutic effect and mechanism of external application with Shilian Powder combined with oral administration of Shumai Capsules for the treatment of rats with diabetic foot ulcer(DFU).Methods Eight male rats with successfully modeled foot ulcer(DF)were used as the control group.While 24 male rats with successfully modeled DFU were randomly divided into DFU group,Shumai Capsules group and Shilian Powder combined with Shumai Capsules group,with eight rats in each group.After the corresponding interventions,we determined the wound healing rate,histopathological changes of wound,levels of inflammatory factors such as interleukin(IL)-6,IL-1β and vascular endothelial growth factor(VEGF)in serum,levels of Apelin and Relaxin,and protein expressions of phosphatidylinositol 3-kinase(PI3K),protein kinase B(AKT)and VEGF in wound tissue,as well as mRNA expressions of PI3K,AKT,Relaxin and Apelin.Results Compared with the control group,the DFU group showed a significant decrease in wound healing rate,VEGF level in serum and wound,wound Relaxin level,protein and mRNA levels of wound AKT(P<0.05),and a significant increase in serum IL-6 and IL-1β levels,wound Apelin level,wound PI3K protein and mRNA levels(P<0.05),and the reduced wound granulation tissue and formation of new capillaries and increased inflammatory cell infiltration were seen under the microscope.Compared with the DFU group,the wound healing rate,VEGF level in serum and wound,wound Relaxin and Apelin levels,protein and mRNA levels of wound PI3K and AKT in the Shumai Capsules group and Shilian Powder combined with Shumai Capsules group were significantly increased(P<0.05),and serum IL-6 and IL-1β levels were significantly decreased(P<0.05),and the increased wound granulation tissue and formation of new capillaries and reduced inflammatory cell infiltration were seen under the microscope.Compared with the Shumai Capsules group,the wound healing rate,wound VEGF level,wound Relaxin and Apelin levels,protein and mRNA levels of wound PI3K and AKT in Shilian Powder combined with Shumai Capsules group were significantly increased(P<0.05),and the serum IL-6 and IL-1β levels were significantly decreased(P<0.05),and the increased wound granulation tissue and formation of new capillaries and reduced inflammatory cell infiltration were seen under the microscope.Conclusion External application with Shilian Powder combined with oral administration of Shumai Capsules can promote the wound healing in rats with DFU,its mechanism is related to the activation of PI3K/AKT/Relaxin/Apelin signaling pathway.

AIM:To investigate the therapeutic effects and potential mechanism of pachymic acid(PA)on li-popolysaccharide(LPS)-induced acute kidney injury(AKI)in mice.METHODS:(1)Genes related to AKI were screened using the DAVID database.Core genes were identified by intersecting related genes and analyzed using Cyto-scape software.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analyses were performed through the DAVID database for the cross-targets.Molecular docking and activity assays were conducted on the primary core targets.(2)A total of 100 C57BL/6J mice were randomly divided into five groups:normal control(NC),model(LPS),solvent control(LPS+DMSO),and treatment groups(LPS+PA-10 and LPS+PA-20),with 20 mice in each group.The LPS-AKI model was established by intraperitoneal injection of 18 mg/kg LPS.The treatment groups received 10 mg/kg and 20 mg/kg PA,respectively,and the solvent control group was administered an equivalent dose of DMSO.Mice were euthanized 24 h after injection.Serum was collected for biochemical analysis,and Western blot was used to detect neutro-phil gelatinase-associated lipocalin(NGAL),kidney injury molecule-1(KIM-1),caspase-3,cleaved caspase-3,interleu-kin-1β(IL-1β),and monocyte chemoattractant protein-1(MCP-1)protein expression.RT-qPCR was employed to detect inflammatory factor mRNA levels.Molecular docking was used to simulate the optimal binding site of PA to caspase-3.En-zyme activity assays were performed to assess caspase protein activity,and renal lesions were observed via hematoxylin and eosin(HE)staining.Apoptosis was detected by TUNEL staining.RESULTS:(1)Thirty-one potential targets of PA against AKI were identified through network pharmacology.GO and KEGG enrichment analyses indicated that these tar-gets were primarily involved in immune response,inflammatory processes,apoptosis and survival,angiogenesis and hemo-dynamics,oxidative stress,and endoplasmic reticulum stress.Key targets included CASP3(caspase-3),PTGS2,BCL2,CCL2,and CYP219.(2)PA treatment improved renal function and reduced tubular epithelial injury.It significantly de-creased NGAL,KIM-1,and cleaved caspase-3 protein levels,as well as inflammatory factors TNF-α,IL-1β,and MCP-1 mRNA and protein expression.PA also reduced apoptosis of renal tubular epithelial cells.Enzyme activity assays and mo-lecular docking revealed that PA exerted its anti-apoptotic effect by directly binding to caspase-3,thereby inhibiting its ac-tivation by caspase-8.CONCLUSION:PA demonstrated a therapeutic effect in LPS-AKI,potentially through the inhibi-tion of inflammatory factor synthesis and release,as well as the inhibition of caspase-3 activation by caspase-8,reducing apoptosis in renal tubular epithelial cells.

How to effectively reduce the size of infant pose estimation network models is a key issue restricting the"home-use"of infant pose estimation technology. Therefore,a lightweight method for infant pose estimation in home scenarios is proposed. The method takes the lightweight network MobileNetV3 as the encoding backbone and utilizesa PixelShuffle up-sampling module in the decoder for reducing the quantity of model parameters. Meanwhile,coordinate attention mechanism is used to better capture location information and channel feature information,highlighting the feature information of small targets and occluded human keypoints. Besides,the parallel cross-correlation convolution is further modified to enhance the capability of feature information extraction. The method's performance is verified on the general pose estimation dataset (COCO) and the dedicated infant pose estimation dataset (SyRIP). The results show that,with a calculation volume (GFLOPs) of only 0.96,the method achieves average accuracies of 73.5％ and 91.0％ on COCO and SyRIP datasets,respectively,proving that it can significantly reduce the quantity of model parameters and calculation volume without sacrificing pose estimation accuracy. The proposed lightweight estimation model is expected to be deployed on home appliances such as smart terminals,thereby realizing intelligent estimation of abnormal infant poses in home scenarios.

Objective To explore the dual coping experience of nursing dependence among middle-aged and young patients with enterostomy and their primary caregivers from the perspective of family resilience,in order to provide evidence for improving the experience of nursing dependence and promoting family resilience.Methods Us-ing the phenomenological research method in qualitative research,18 young and middle-aged enterostomy patients and their primary caregivers were selected for semi-structured interviews with purpose sampling method,and the in-terview data were analyzed by content analysis method.Results A total of 4 themes and 8 sub-themes were ex-tracted.Theme 1:heavy dependence-elastic fatigue-weak resilience(patients avoid stomas,depression,caregivers help-lessly accepting;patients role reinforcement,excessive dependence,caregivers exhaustion);theme 2:moderate depen-dence-elastic adjustment-strong resilience trend(active exploration,mutual understanding,perceived support;focus ad-justment,mutual dependence,positive relationship);theme 3:mild dependence-elastic space-strong resilience(self-con-trollable feeling,quick adaptation,mutual growth;facing calmly,cherishing life,reshaping value);theme 4:no depen-dence-gradual loss of elasticity-weak resilience trend(refusal to seek help,self isolation,relationship cracks;frustration in seeking help,self-protection,relationship alienation).In this article,we proposed a preliminary family resilience model for patients with enterostomy.Conclusion The dual coping and family resilience of the patients with en-terostomy and their primary caregivers are different and dynamic.Family-centered support should be applied to strengthen the positive coping and improve the level of family resilience.In addition,this study also tried to pro-pose a family resilience model for patients with enterostomy based on nursing dependence,in order to enrich the connotation of family resilience.

Objective By systematically reviewing the development of policies related to rural doctors and their evolution patterns,and by quantitatively analyzing the policy tools and their effectiveness levels,it aim to provide a strategic basis and reference for the high-quality development of China's rural doctor workforce.Methods 60 policies related to rural doctors enacted at the national level from March 2009 to May 2024 were collected,and a three-dimensional analysis framework based on"policy tool-policy period-policy effectiveness"was adopted to analyse the development of rural doctors in China.Results Among the 245 coded policy instruments,demand-type policy instruments accounted for the highest proportion (38.38％),followed by supply-type (31.02％) and environment-type is the least (30.61％).The types of policies are mainly circular,and the number of policies issued fluctuates significantly,with the number of policies issued during the period of high-quality development being the highest in the four periods,and the policies issued during the period of deepening and consolidation being the most specific.Conclusion It is necessary to scientifically grasp the law of evolution of policy orientation and the trend of evolution of policy instruments,rationally adjust the internal structure of policy instruments,and enhance the relevance and synergy of the policy system in order to improve the cohesion of policy effectiveness.

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.