Chronic pain is a complex condition shaped by long-standing alterations in both physiological and psychological processes. Rather than representing a simple continuation of acute nociceptive signaling, chronic pain is increasingly understood as the outcome of progressive dysregulation within distributed neural systems that govern sensation, affect, motivation, and cognitive control. Neuroimaging and electrophysiological studies indicate that this state is accompanied by extensive plastic changes in deep brain structures and large-scale networks. Beyond well-described central sensitization processes, chronic pain is characterized by disrupted oscillatory rhythms and altered connectivity within large-scale brain networks, including thalamo-cortical circuits and prefrontal-limbic-reward networks. These findings support a conceptual shift from viewing chronic pain as a focal, lesion-driven phenomenon toward recognizing it as a disorder of distributed network pathology. Pharmacological treatments remain central to clinical practice, yet their long-term efficacy is often limited and frequently accompanied by substantial side effects. The ongoing concerns about opioid-related risks and the inadequate therapeutic response in a subset of patients highlight the need for safe, non-pharmacological approaches that can address not only pain but also comorbid disturbances in mood, sleep, and social functioning. Neuromodulation provides a promising path toward mechanism-based and non-pharmacological management of chronic pain by employing physical or chemical stimulation to alter the excitability and synchrony of specific neural populations within central, peripheral, and autonomic systems. While invasive deep brain stimulation demonstrates that targeting deep brain structures can be effective, its clinical application is restricted by surgical risks and cost, highlighting the importance of non-invasive techniques capable of reaching deep targets. Current non-invasive approaches, such as transcranial electric stimulation, are constrained by limited penetration depth and insufficient spatial precision. These limitations hinder reliable engagement of deep regions implicated in pain, including the thalamus and nucleus accumbens, and tend to produce broad, non-specific modulation of cross-network oscillatory activity. Temporal interference (TI) stimulation has emerged as a means of overcoming these obstacles. By delivering interacting high-frequency currents that generate a low-frequency envelope within the head, TI enables focal stimulation of deep targets while minimizing superficial current delivery. Recent multiscale modeling and animal studies indicate that TI exploits the nonlinear rectification properties of neuronal membranes in response to high-frequency carriers, as well as their phase-locked responses to low-frequency envelopes, to generate “peak-focused” electric fields in deep regions under relatively low superficial current loads. Moreover, TI appears to exhibit potential advantages in terms of cell-type selectivity and rhythm-specific engagement, including differential responses across neuronal subtypes and distinct coupling to θ-, β-, and γ-band oscillations. These features suggest a promising avenue for correcting abnormal rhythms and network dynamics that contribute to chronic pain. This review summarizes current knowledge of the neural mechanisms underlying chronic pain and recent advances in TI research. It examines functional disturbances across key pain-related regions and networks, outlines the principles and technical characteristics of TI, and discusses potential deep-brain targets and stimulation strategies relevant to chronic pain. Evidence to date indicates that TI, with its non-invasiveness, tolerability, and capacity for precise deep brain modulation, holds great promise for the management of treatment-resistant chronic pain and may evolve into a new generation of precise and efficient non-pharmacological analgesic strategies.

Chronic pain is a complex condition shaped by long-standing alterations in both physiological and psychological processes. Rather than representing a simple continuation of acute nociceptive signaling, chronic pain is increasingly understood as the outcome of progressive dysregulation within distributed neural systems that govern sensation, affect, motivation, and cognitive control. Neuroimaging and electrophysiological studies indicate that this state is accompanied by extensive plastic changes in deep brain structures and large-scale networks. Beyond well-described central sensitization processes, chronic pain is characterized by disrupted oscillatory rhythms and altered connectivity within large-scale brain networks, including thalamo-cortical circuits and prefrontal-limbic-reward networks. These findings support a conceptual shift from viewing chronic pain as a focal, lesion-driven phenomenon toward recognizing it as a disorder of distributed network pathology. Pharmacological treatments remain central to clinical practice, yet their long-term efficacy is often limited and frequently accompanied by substantial side effects. The ongoing concerns about opioid-related risks and the inadequate therapeutic response in a subset of patients highlight the need for safe, non-pharmacological approaches that can address not only pain but also comorbid disturbances in mood, sleep, and social functioning. Neuromodulation provides a promising path toward mechanism-based and non-pharmacological management of chronic pain by employing physical or chemical stimulation to alter the excitability and synchrony of specific neural populations within central, peripheral, and autonomic systems. While invasive deep brain stimulation demonstrates that targeting deep brain structures can be effective, its clinical application is restricted by surgical risks and cost, highlighting the importance of non-invasive techniques capable of reaching deep targets. Current non-invasive approaches, such as transcranial electric stimulation, are constrained by limited penetration depth and insufficient spatial precision. These limitations hinder reliable engagement of deep regions implicated in pain, including the thalamus and nucleus accumbens, and tend to produce broad, non-specific modulation of cross-network oscillatory activity. Temporal interference (TI) stimulation has emerged as a means of overcoming these obstacles. By delivering interacting high-frequency currents that generate a low-frequency envelope within the head, TI enables focal stimulation of deep targets while minimizing superficial current delivery. Recent multiscale modeling and animal studies indicate that TI exploits the nonlinear rectification properties of neuronal membranes in response to high-frequency carriers, as well as their phase-locked responses to low-frequency envelopes, to generate “peak-focused” electric fields in deep regions under relatively low superficial current loads. Moreover, TI appears to exhibit potential advantages in terms of cell-type selectivity and rhythm-specific engagement, including differential responses across neuronal subtypes and distinct coupling to θ-, β-, and γ-band oscillations. These features suggest a promising avenue for correcting abnormal rhythms and network dynamics that contribute to chronic pain. This review summarizes current knowledge of the neural mechanisms underlying chronic pain and recent advances in TI research. It examines functional disturbances across key pain-related regions and networks, outlines the principles and technical characteristics of TI, and discusses potential deep-brain targets and stimulation strategies relevant to chronic pain. Evidence to date indicates that TI, with its non-invasiveness, tolerability, and capacity for precise deep brain modulation, holds great promise for the management of treatment-resistant chronic pain and may evolve into a new generation of precise and efficient non-pharmacological analgesic strategies.

Objective To use a physics-informed neural network(PINN)-based model to predict hemodynamics in intracranial aneurysms and address the problems of long simulation time and high computational cost in traditional computational fluid dynamics(CFD)simulations.Methods The PINN model was trained using only the computational domain coordinates and sparse velocity measurement points from CFD data of clinical patients.The predicted blood flow velocity,pressure,and wall shear stress(WSS)from the PINN model were compared with CFD simulation results.Results The proposed method was used to test and validate data from four different patients.For velocity prediction,the average mean absolute error(MAE),average mean relative error(MRE),average mean squared error(MSE)was 4.60％,6.61％,and 0.229％,respectively.For WSS prediction,the average MAE,MRE and MSE was 5.54％,8.58％,and 0.510％,respectively.The PINN model demonstrated a good generalization capability across different aneurysm models and could reduce the computation time of hemodynamics from several hours to just a few seconds.Conclusions The PINN model can effectively compensate for incomplete measurement data through physical constraints,even when boundary conditions are unknown and measurement data are sparse.It can rapidly and accurately simulate the hemodynamics of intracranial aneurysms.This method has the potential to provide effective support for clinical risk prediction in intracranial aneurysms.

Objective To explore the characteristic changes in white matter microstructure in Parkinson's disease(PD)patients via automated fiber quantification(AFQ)technology,providing a basis for the identification and diagnosis of PD,and to analyze the feasibility of combining the AFQ method with support vector machine(SVM)in the diagnosis of PD.Methods Forty patients with primary PD(PD group)and 20 healthy controls(HC)(HC group)were prospectively selected.The AFQ technology was applied for white matter fiber tract analysis.Statistical analyses were performed using FSL(v6.0)software and SPSS 27.0 software.Independent-sample t-tests were conducted for comparisons between groups in AFQ analysis.The AFQ method was used to analyze the relationship between diffusion tensor imaging(DTI)parameters and Montreal Cognitive Assessment(MoCA)scores.Results(1)The results of AFQ analysis revealed that compared with the HC group,the PD group exhibited significantly lower fractional anisotropy(FA)values in the right cingulum bundle,left cingulum bundle hippocampus,and left uncinate fasciculus,with no differences in the FA values of the remaining 17 fiber tracts.Moreover,PD group demonstrated higher mean diffusivity(MD)values in the left cingulum bundle,left cingulum bundle hippocampus,left inferior frontal occipital fasciculus,left inferior longitudinal fasciculus,left superior longitudinal fasciculus,and left uncinate fasciculus.These differences were statistically significant(P<0.05),while no significant differences were found in the MD values of the remaining 14 fiber tracts.Furthermore,the MD values of the left inferior frontal occipital fasciculus,and left inferior longitudinal fasciculus were negatively correlated with the MoCA scores.(2)The classification results of SVM showed that the best results were achieved when combining the differential nodes of FA and MD as classification features,with an area under the curve(AUC)of 0.922,an accuracy of 84.81%,a sensitivity of 87.50%,and a specificity of 82.05%.Conclusion The DTI parameters in PD patients can serve as potential biomarkers for diagnosis.The AFQ methods provides an effective approach for detecting alterations white matter tract integrity,offering important insights for the identification and diagnosis of PD.The best results are achieved when combining the differential nodes of FA and MD as classification features.

AIM To study the chemical constituents from the sticks and leaves of Croton cascarilloides Raeusch.and their biological activities.METHODS The 95％ethanol extract from the sticks and leaves of C.cascarilloides was isolated and purified by MCI,silica gel,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.LPS-induced NO RAW264.7 cell model induced by LPS was used to evaluate its anti-inflammatory activity in vitro.GES-1 injury model induced by taurocholic acid was used to screen the gastric mucosal protection activity.RESULTS Fourteen compounds were isolated and identified as bullatantriol(1),(-)-boscialin(2),(+)-dehydrovomifoliol(3),3-(hydroxylacetyl)-indole(4),pinoresinol(5),3,7-dimethyl-octa-1,7-diene-3,6-ol(6),(+)-syringaresinol(7),curcasinlignan B(8),cleomiscosin C(9),cleomiscosinD(10),2,6-dimethyl-octa-1,7-dien-3,6-diol(11),vanillin(12),vanillic acid(13),methyl vanillate(14).Compound 4 had certain anti-inflammatory activity,with IC50 values of 73.62 μmol/L.The protective rates of 25 μmol/L compounds 1-4,6,9-12 and 14 on gastric mucosal epithelial cells were 30.07％,34.18％,23.91％,30.92％,17.51％,19.69％,31.76％,22.46％,30.56％and 14.49％,respectively.CONCLUSION Compounds 1-14 are isolated from this plant for the first time.Compound 4 shows anti-inflammatory activity,1-4,6,9-12 and 14 show different degrees of gastric mucosal epithelial cell protective activity.

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 investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To explore the characteristic changes in white matter microstructure in Parkinson's disease(PD)patients via automated fiber quantification(AFQ)technology,providing a basis for the identification and diagnosis of PD,and to analyze the feasibility of combining the AFQ method with support vector machine(SVM)in the diagnosis of PD.Methods Forty patients with primary PD(PD group)and 20 healthy controls(HC)(HC group)were prospectively selected.The AFQ technology was applied for white matter fiber tract analysis.Statistical analyses were performed using FSL(v6.0)software and SPSS 27.0 software.Independent-sample t-tests were conducted for comparisons between groups in AFQ analysis.The AFQ method was used to analyze the relationship between diffusion tensor imaging(DTI)parameters and Montreal Cognitive Assessment(MoCA)scores.Results(1)The results of AFQ analysis revealed that compared with the HC group,the PD group exhibited significantly lower fractional anisotropy(FA)values in the right cingulum bundle,left cingulum bundle hippocampus,and left uncinate fasciculus,with no differences in the FA values of the remaining 17 fiber tracts.Moreover,PD group demonstrated higher mean diffusivity(MD)values in the left cingulum bundle,left cingulum bundle hippocampus,left inferior frontal occipital fasciculus,left inferior longitudinal fasciculus,left superior longitudinal fasciculus,and left uncinate fasciculus.These differences were statistically significant(P<0.05),while no significant differences were found in the MD values of the remaining 14 fiber tracts.Furthermore,the MD values of the left inferior frontal occipital fasciculus,and left inferior longitudinal fasciculus were negatively correlated with the MoCA scores.(2)The classification results of SVM showed that the best results were achieved when combining the differential nodes of FA and MD as classification features,with an area under the curve(AUC)of 0.922,an accuracy of 84.81%,a sensitivity of 87.50%,and a specificity of 82.05%.Conclusion The DTI parameters in PD patients can serve as potential biomarkers for diagnosis.The AFQ methods provides an effective approach for detecting alterations white matter tract integrity,offering important insights for the identification and diagnosis of PD.The best results are achieved when combining the differential nodes of FA and MD as classification features.