Neurological disorders, including Alzheimer’s disease (AD), Parkinson’s disease (PD), cerebral ischemia, and multiple sclerosis (MS), impose an escalating global health burden and remain largely incurable. These disorders arise from multifactorial and interconnected pathological processes, such as chronic neuroinflammation, oxidative stress, protein misfolding and aggregation, demyelination, and neurovascular dysfunction. Despite substantial advances in elucidating disease-associated molecular mechanisms, current therapeutic strategies are predominantly symptomatic and fail to effectively halt or reverse disease progression. This limitation highlights the urgent need to identify endogenous regulatory molecules capable of coordinating neuronal survival, synaptic maintenance, inflammatory control, and tissue repair within the central nervous system (CNS). Pleiotrophin (PTN) is a heparin-binding, growth-associated cytokine that has emerged as a key regulator of neural development, plasticity, and regeneration. Structurally, PTN contains multiple high-affinity heparin-binding domains that facilitate interactions with extracellular matrix components and cell surface proteoglycans, enabling spatially restricted and context-dependent signaling. Through these molecular properties, PTN functions as a multifunctional organizer of neural growth, plasticity, and tissue remodeling across developmental and adult stages. Its diverse biological effects are executed through a multi-receptor signaling system that integrates extracellular cues with intracellular programs governing cellular survival, migration, and differentiation. Notably, PTN displays a highly dynamic and cell type-specific expression pattern in the central nervous system, being enriched in neural progenitor cells during development and later restricted to discrete neuronal populations, neural stem cells, and non-neuronal niche cells—including astrocytes, pericytes, and vascular endothelial cells—which serve as critical sources of PTN under physiological and pathological conditions. PTN expression is tightly regulated during development and exhibits pronounced plasticity in response to pathological stimuli. Under physiological conditions, PTN is transiently expressed during critical windows of neural growth and synaptogenesis, supporting neuron-glia interactions and myelin formation. In contrast, in pathological contexts such as amyloid β-protein (Aβ) accumulation in AD, dopaminergic neuron degeneration in PD, demyelination in MS, and ischemic brain injury, PTN expression is frequently dysregulated, suggesting an active role in disease-associated remodeling rather than a passive bystander effect. Importantly, accumulating evidence indicates that PTN exerts a dual and context-dependent influence on neurological disorders. On the one hand, aberrant PTN signaling may contribute to maladaptive responses, including sustained glial activation, dysregulated neuroinflammation, extracellular matrix remodeling, and enhanced Aβ deposition. On the other hand, PTN displays robust neuroprotective and reparative functions by promoting neuronal survival, enhancing oligodendrocyte maturation and remyelination, and stimulating post-injury angiogenesis, thereby facilitating tissue repair and functional recovery. At the mechanistic level, PTN signaling is characterized by extensive cross-talk among receptor-dependent pathways. Activation of anaplastic lymphoma kinase (ALK) triggers canonical PI3K-AKT-mTOR and MAPK cascades that support neuronal survival and axonal integrity. PTN binding to protein tyrosine phosphatase receptor type Z1 (PTPRZ1) induces conformational inhibition of its phosphatase activity, resulting in increased phosphorylation of downstream effectors such as β-catenin, Fyn, and Src, which regulate neuronal migration and synaptic stabilization. Syndecan-3 (SDC3) functions as both a co-receptor and an independent signaling mediator by capturing extracellular PTN, amplifying ALK- and PTPRZ1-dependent signaling, and directly modulating cytoskeletal dynamics through PKC and ERK pathways. In parallel, PTN interaction with αVβ3 integrin contributes to remodeling of the neurovascular niche, linking angiogenesis with neurogenesis and neural repair. From a translational perspective, therapeutic strategies targeting PTN can be broadly classified into 3 categories: direct enhancement of PTN signaling through exogenous protein supplementation or gene therapy-mediated upregulation, pharmacological modulation of PTN-associated receptor pathways and downstream signaling nodes, and exploitation of PTN as a dynamic biomarker to inform disease stratification and therapeutic responsiveness. These complementary approaches underscore the growing interest in PTN-centered interventions across a spectrum of neurological disorders. In summary, PTN functions not merely as a classical trophic factor but as a central signaling hub integrating inflammatory regulation, neural regeneration, and vascular remodeling within the CNS. This review aims to synthesize current insights into PTN’s molecular architecture, multi-receptor signaling mechanisms, and disease-specific functions, and to highlight emerging therapeutic strategies targeting PTN. By conceptualizing PTN as a dynamic modulator of neuronal resilience rather than a static biomarker, we propose that precise modulation of PTN signaling may offer promising avenues for therapeutic development in neurodegenerative and neuroinflammatory diseases.

ObjectiveTo apply and systematically evaluate the care-need grading assessment tool for adults with disabilities in welfare institutions. MethodsFrom June to July, 2025, four disability care institutions in Shanghai were selected, and a total of 1 002 adults with disabilities were assessed using the self-developed care-need grading assessment tool for adults with disabilities in welfare institutions. The application effectiveness of the tool was evaluated by analyzing the classification results of care need grading and the reclassification in grade distribution. The application validity was assessed through score differences across functional dimensions, reduced-dimension clustering scatter plots for each grade, and external variables. The application efficiency was evaluated based on the average assessment duration and learning curves. The application utility value was assessed through the distribution characteristics and mapping relationships of service lists across different grades. ResultsThe distribution across disability levels was 84 in Level 1, 298 in Level 2, 92 in Level 3, 246 in Level 4, and 282 in Level 5, indicating a trend where individuals from higher levels in the original system shifted toward the middle and lower levels of the new system. The tool demonstrated strong discriminatory power across the four functional dimensions (P < 0.001), indicating favorable discriminant validity. The five classified levels exhibited clear clustering boundaries in the reduced-dimension space, reflecting robust structural validity. The classification results were consistent with theoretical expectations regarding external variables, including age, disability type, disability grade, number of comorbidities, and primary clinical diagnoses (P < 0.05), demonstrating sound external validity. The median assessment duration was 5.80 minutes, with a significant learning effect (P = 0.037), showcasing high efficiency. Finally, service lists tailored to different care levels were developed, where service content exhibited graded differences across care levels and accurately mapped the care-need characteristics of each grade, reflecting substantial utility value. ConclusionThis tool can classify the care needs of adults with disabilities into five levels, with sound validity and high assessment efficiency; while the resulting service lists for different care levels can be used to guide practical implementation, which can be used for the graded assessment of care needs among adults with disabilities.

Objective To investigate the classification capability of a deep learning classification model based on biparametric mag-netic resonance imaging(bpMRI)for clinically significant prostate cancer(csPCa)and clinically insignificant prostate cancer(cisPCa).Methods A retrospective analysis was conducted on the data of 565 prostate bpMRI patients.A deep learning classification model was established for csPCa.The patients were randomly divided into training set(452 cases)and internal test set(113 cases)at a ratio of 8︰2.Internal validation was performed,followed by external validation(external validation set)using data from 120 patients across four different hospitals.The area under the curve(AUC)of the receiver operating characteristic(ROC)curve,F1 score,precision,sensi-tivity,specificity,accuracy,and calibration curves were used to evaluate the model.Decision curve analysis(DCA)was also applied to assess the clinical benefit of the model.Results The deep learn-ing classification model for csPCa classification demonstrated the following performance across the training set,internaltest set,and external validation set:sensitivity of 0.986,0.887,and 0.750;specificity of 0.967,0.850,and 0.976;precision of 0.963,0.839,and 0.818;accuracy of 0.974,0.862,and 0.792;F1 score of 0.974,0.862,and 0.783;and AUC of 0.998,0.896,and 0.883,respec-tively.The calibration curves for all three datasets showed high consistency between predicted and actual probabilities.DCA indicated that the highest net benefit threshold probabilities for the training set,internal test set,and external validation set were 0.2-0.7,0.2-0.6,and 0.2-0.5,respectively.Conclusion The deep learning classification model demonstrated excellent performance in classifying csPCa and exhibited good generalizability,which is worhty of clinical application.

Objective To investigate the expression pattern of IQGAP2 in renal cell carcinoma tissues and cell lines,and to analyze its effects on the proliferation and migration of renal cell carcinoma cells.Methods Firstly,GEO database was used to screen differentially expressed genes between renal cell carcinoma tissues,and GEPIA,TIMER2.0 were used to analyze the expression level of IQGAP2 in renal cell carcinoma tissue.Subse-quently,knockdown(siRNA)and overexpression plasmids of IQGAP2 were constructed and transfected into ACHN and 786-O cell lines to perform a series of functional experiments to evaluate the effect of IQGAP2 on the malignant biological behavior of renal carcinoma cells.qRT-PCR and Western Blot were used to detect the expres-sion of EMT(epithelial-mesenchymal transition)related proteins after knockdown and overexpression of IQGAP2.Results In renal cell carcinoma tissues,the relative expression of IQGAP2 was significantly lower than in adja-cent normal tissues(P<0.001).Transfection of si-IQGAP2 in ACHN and 786-O cells effectively downregulated the mRNA and protein expression levels of IQGAP2(P<0.01),while transfection with an overexpression plasmid significantly upregulated its mRNA and protein expression(P<0.001).Further studies revealed that overexpression of IQGAP2 significantly inhibited the proliferation(P<0.05)and migration(P<0.01)of ACHN and 786-O cells,whereas knockdown of IQGAP2 enhanced their proliferation(P<0.05,P<0.001)and migration(P<0.01).Through qRT-PCR and Western blot analyses of EMT-related proteins,it was found that reduced expression of IQGAP2 promoted the epithelial-mesenchymal transition(EMT)process in renal cancer cells.Conclusions The expression of IQGAP2 is low in renal cell carcinoma tissues and cells,and the decrease of the expression level can promote the EMT process of renal cell carcinoma cells,and then enhance the proliferation and migration of renal cell carcinoma cells.IQGAP2 plays an important tumor suppressor role in renal cell carcinoma.

Objective To investigate the mechanism of serine protease inhibitor A3N(SerpinA3N)in alleviating reti-nal neural injury in diabetic mice by inhibiting Müller cell inflammation.Methods Thirty-six db/db mice(72 eyes)were randomly divided into the db/db group,the db/db+SerpinA3N-overexpressing adeno-associated virus(AAV-SerpinA3N)group,and the db/db+empty vector adeno-associated virus(NC-SerpinA3N)group,with 12 mice in each group.Twelve age-matched healthy male littermate mice were randomly selected as the healthy control group(db/m group).Mice in each group were sacrificed 4 weeks after the corresponding treatments.Immunofluorescence staining was used to detect the co-localization of SerpinA3N and glial fibrillary acidic protein(GFAP)in the mouse retina.Hematoxylin-eosin(HE)staining was used to observe histopathological changes in the retinal tissue.TUNEL staining was used to detect the apoptosis of reti-nal ganglion cells(RGCs).Immunohistochemistry was used to detect GFAP expression.ELISA was used to measure the levels of inflammatory factors[interleukin(IL)-1 β,IL-6,IL-18,and tumor necrosis factor-α(TNF-α)]in the retinal tis-sue.The predicted target genes of SerpinA3N were imported into the STRING database to construct a protein-protein inter-action(PPI)network.The highest-scoring target was selected based on the scores for molecular docking.Western blot was used to detect the expression levels of SerpinA3N,nuclear factor kappa B(NF-κB),and spleen focus-forming virus proviral integration oncogene(Spi1)proteins in the retinal tissue.Results Immunofluorescence staining showed co-lo-calized expression of SerpinA3N and GFAP in the retinal tissue.Compared with the db/m group,the db/db,db/db+NC-SerpinA3N,and db/db+AAV-SerpinA3N groups showed decreased retinal thickness and RGC count,and increased number of TUNEL-positive cells,relative GFAP-positive expression intensity,levels of all inflammatory factors,and expression lev-els of NF-κB and Spi1 proteins,while SerpinA3N protein expression was decreased(all P＜0.05).Compared with the db/db group,the db/db+AAV-SerpinA3N group showed increased retinal thickness and RGC count,and decreased number of TUNEL-positive cells,relative GFAP-positive expression intensity,levels of all inflammatory factors,and expression levels of NF-κB and Spi1 proteins,while SerpinA3N protein expression was increased(all P＜0.05).Compared with the db/db+AAV-SerpinA3N group,the db/db+NC-SerpinA3N group showed decreased retinal thickness and RGC count,and increased number of TUNEL-positive cells,relative GFAP-positive expression intensity,levels of all inflammatory factors,and ex-pression levels of NF-κB and Spi1 proteins,while SerpinA3N protein expression was decreased(all P＜0.05).The PPI re-sults indicated an interaction between SerpinA3N and Spi1.Molecular docking results showed that Spi1 could form hydro-gen bonds with residues surrounding SerpinA3N.Conclusion Overexpression of SerpinA3N can inhibit Müller cell in-flammation and ameliorate retinal neural injury in diabetic mice,and the mechanism may be associated with the inhibition of the Spi1/NF-κB signaling pathway.

Objective To investigate the classification capability of a deep learning classification model based on biparametric mag-netic resonance imaging(bpMRI)for clinically significant prostate cancer(csPCa)and clinically insignificant prostate cancer(cisPCa).Methods A retrospective analysis was conducted on the data of 565 prostate bpMRI patients.A deep learning classification model was established for csPCa.The patients were randomly divided into training set(452 cases)and internal test set(113 cases)at a ratio of 8︰2.Internal validation was performed,followed by external validation(external validation set)using data from 120 patients across four different hospitals.The area under the curve(AUC)of the receiver operating characteristic(ROC)curve,F1 score,precision,sensi-tivity,specificity,accuracy,and calibration curves were used to evaluate the model.Decision curve analysis(DCA)was also applied to assess the clinical benefit of the model.Results The deep learn-ing classification model for csPCa classification demonstrated the following performance across the training set,internaltest set,and external validation set:sensitivity of 0.986,0.887,and 0.750;specificity of 0.967,0.850,and 0.976;precision of 0.963,0.839,and 0.818;accuracy of 0.974,0.862,and 0.792;F1 score of 0.974,0.862,and 0.783;and AUC of 0.998,0.896,and 0.883,respec-tively.The calibration curves for all three datasets showed high consistency between predicted and actual probabilities.DCA indicated that the highest net benefit threshold probabilities for the training set,internal test set,and external validation set were 0.2-0.7,0.2-0.6,and 0.2-0.5,respectively.Conclusion The deep learning classification model demonstrated excellent performance in classifying csPCa and exhibited good generalizability,which is worhty of clinical application.

AIM To investigate the mechanism of Shaoyao Gancao Decoction in preventing meglumine diatrizoate-induced post-ERCP pancreatitis in rats through autophagy regulation.METHODS The rats were randomized into the normal group,the model group,the low-dose and high-dose Shaoyao Gancao Decoction(1.5,3.0 g/kg),and the indomethacin suppository group.A rat model of post-ERCP pancreatitis was induced by meglumine diatrizoate injection into the pancreatic duct under continuous pressure.The rats had their pancreatic tissues stained with HE to observe the pathological alterations,inflammatory cell infiltration,hemorrhage and necrosis;their serum levels of IL-1β,IL-6,IL-8,TNF-α,AMS,and IL-10 identified by ELISA;their autophagic vacuoles in pancreatic acinar cells observed by transmission electron microscopy;their pancreatic protein expressions of Beclin1,LC3B,p62,TRAF2 and p-JNK detected by IHC and Western blot;and their pancreatic mRNA expressions of Beclin1 and TRAF2 detected by RT-qPCR.RESULTS Compared with the model group,the high-dose Shaoyao Gancao Decoction group displayed no obvious hemorrhage;improvement in edema of acinar and interstitial cells;obviously less cellular inflammatory infiltration;substantially decreased serum levels of IL-1β,IL-6,TNF-α and AMS(P＜0.05,P＜0.01);drastically reduced amount of autophagosomes in acinar cells;and down-regulated expressions of autophagy-related proteins Beclin1,LC3,p62,TRAF2 and p-JNK(P＜0.05,P＜0.01).CONCLUSION Shaoyao Gancao Decoction can prevent post-ERCP pancreatitis by ameliorating pancreatic tissue injury,decreasing serum inflammatory response level,and interfering with abnormal autophagy of pancreatic acinar cells.Its molecular mechanism may involve inhibition of TRAF2 protein expression and modulation of p-JNK activation.

Objective:To explore the effect of Lactobacillus reuteri on testicular injury in mice exposed to neonicotinoid insec-ticides(NNI).Methods:Fifteen C57BL/6 male mice were randomly divided into control group(CTRI.group),exposure group(NNI group)and Lactobacillus intervention group(NNI-L group).The mice in CTRL group were given 0.02ml/g of 0.5％carboxym-ethyl cellulose sodium solution by gavage for 14 days.The mice in NNI group were given 0.02 ml/g of NNI mixture by gavage for 14 days.The mice in NNI-L group were given 0.02 ml/g of NNI mixture by gavage and 5 × 108cfu/ml of Lactobacillus reuteri powder so-lution for 14 days.Then,the histomorphology and function of testicle were evaluated by hematoxylin-eosin staining,immunofluores-cence staining and RNA sequencing.Results:Compared with CTRL group,the thickness of testicular seminiferous epithelium in the NNI group was significantly thinner.And the decline in the number of spermatogenic cells and sperm was observed.And the expression of spermatogonial stem cell marker UCHL1 was down-regulated which was significantly improved in NNI-L group compared with the NNI group.The abnormal expressions of hormone and sperm methylation related genes in testis of NNI group were detected by RNA sequen-cing,with significant down-regulation being found in NPFF and IGF2.While the expression of HSD3B8 was significantly up-regulated.The abnormal expression of these genes could be significantly improved after oral administration of Lactobacillus reuteri.Conclusion:Testicular spermatogenesis and endocrine function can be damaged by NNI exposure.And oral administration of Lactoba-cillus reuteri protects testis from the adverse effects of NNI toxicity.

In the central nervous system (CNS), the myelin sheath, a specialized membrane structure that wraps around axons, is formed by oligodendrocytes through a highly coordinated spatiotemporal developmental program. The process begins with the directed differentiation of neural precursor cells into oligodendrocyte precursor cells (OPCs), followed by their migration, proliferation, differentiation, and maturation, ultimately leading to the formation of a multi-segmental myelin sheath structure. Recent single-cell sequencing research has revealed that this process involves the temporal regulation of over 200 key genes, with a regulatory network composed of transcription factors such as Sox10 and Olig2 playing a central role. The primary function of the myelin sheath is to accelerate nerve signal transmission and protect nerve fibers from damage. Its insulating properties not only increase nerve conduction speed by 50-100 times but also ensure the long-term functional integrity of the nervous system by maintaining axonal metabolic homeostasis and providing mechanical protection. The pathological effects of myelin sheath injury exhibit a cascade amplification pattern: acute demyelination leads to action potential conduction block, while chronic lesions may cause axonal damage and neuronal death in severe or long-term cases, ultimately resulting in irreversible neurological dysfunction with neurodegenerative characteristics. Multiple sclerosis (MS) is a neurodegenerative disease characterized by chronic inflammatory demyelination of the CNS. Clinically, the distribution of lesions in MS exhibits spatial heterogeneity, which is closely related to differences in the regenerative capacity of oligodendrocytes within the local microenvironment. Emerging evidence suggests that astrocytes form a dynamic “neural-immune-metabolic interface” and play a multidimensional regulatory role in myelin development and regeneration by forming heterogeneous populations composed of different subtypes. During embryonic development, astrocytes induce the targeted differentiation of OPCs in the ventricular region through the Wnt/β-catenin pathway. In the mature stage, they secrete platelet-derived growth factor AA (PDGF-AA) to establish a chemical gradient that guides the precise migration of OPCs along axonal bundles. Notably, astrocytes also provide crucial metabolic support by supplying energy substrates for high-energy myelin formation through the lactate shuttle mechanism. In addition, astrocytes play a dual role in myelin regulation. During the acute injury phase, reactive astrocytes establish a triple defense system within 72 h: upregulating glial fibrillary acidic protein (GFAP) to form scars that isolate lesions, activating the JAK-STAT3 regeneration pathway in oligodendrocytes via leukemia inhibitory factor (LIF), and releasing tumor necrosis factor-stimulated gene-6 (TSG-6) to inhibit excessive microglial activation. However, in chronic neurodegenerative diseases, the phenotypic transformation of astrocytes contributes to microenvironmental deterioration. The secretion of chondroitin sulfate proteoglycans (CSPGs) inhibits OPC migration via the RhoA/ROCK pathway, while the persistent release of reactive oxygen species (ROS) leads to mitochondrial dysfunction and the upregulation of complement C3-mediated synaptic pruning. This article reviews the mechanisms by which astrocytes regulate the development and regeneration of myelin sheaths in the CNS, with a focus on analyzing the multifaceted roles of astrocytes in this process. It emphasizes that astrocytes serve as central hubs in maintaining myelin homeostasis by establishing a metabolic microenvironment and signaling network, aiming to provide new therapeutic strategies for neurodegenerative diseases such as multiple sclerosis.

Objective To observe the difference of bone micro-structure in different regions of proximal femur,micro-CT scanning was performed on 30 proximal femur specimens to explain the mechanism of proximal femur fracture and to provide anatomical basis for prosthesis design.Methods Totally 30 intact proximal femur specimens were obtained from 60-80 year-old cadavers.Micro-CT scanning was used to measure the trabecular thickness(Tb.Th),trabecular number(Tb.N),trabecular space(Tb.Sp),connectivity(Conn)and bone mineral density(BMD)and other parameters in 7 regions of proximal femur,including proximal pressure trabecular(PPT),distal pressure trabecular(DPT),femoral head-neck junction(FHNJ),head and neck of femoral neck(HNFN),the base of femoral neck(BPFN),intertrochanteric line(IL)and greater trochanter(GT).Results The bone mineral density of IL and GT were higher than those of BPFN,FHNJ,DPT and PPT.The trabecular thickness of GT was the largest,followed by IL,BPFN and HNFN,and the smallest was FHNJ,DPT and PPT.The trabecular space of IL was larger than that of GT,and the data of both were larger than those of other parts,among which DPT and PPT were the smallest.The trabecular number of IL and GT were the smallest,BPFN,HNFN and FHNJ were larger,and DPT was the largest.The volume fraction of IL was the smallest,BPFN and HNFN were larger,DPT and PPT were the largest.Conclusion The bone density,trabecular thickness,bone volume,and total volume of GT and IL in the proximal femur of elderly patients are all relatively large,so the reason for the high incidence of fractures is not due to weak internal bone microstructure;The bone density,trabecular thickness,and trabecular gap at the proximal and distal ends of the vertical trabecular bone are relatively small.If it is necessary to perform core decompression for prosthesis filling at this location,the design should be conducive to the mechanical conduction of the prosthesis and the regeneration of surrounding bone tissue.