ObjectiveNon-invasive magnetic stimulation technology has been widely used in the treatment of Alzheimer’s disease (AD), but there is a lack of convenient and timely methods for evaluating and providing feedback on the effectiveness of the stimulation, which can be used to guide the adjustment of the stimulation protocol. This study aims to explore the possibility of heart rate variability (HRV) in diagnosing AD and guiding AD magnetic stimulation intervention techniques. MethodsIn this study, we used a 40 Hz, 10 mT pulsed magnetic field to expose AD mouse models to whole-body exposure for 18 d, and detected the behavioral and electroencephalographic signals before and after exposure, as well as the instant electrocardiographic signals after exposure every day. ResultsUsing one-way ANOVA and Pearson correlation coefficient analysis, we found that some HRV indicators could identify AD mouse models as accurately as behavioral and electroencephalogram(EEG) changes (P<0.05) and significantly distinguish the severity of the disease (P<0.05), including rMSSD, pNN6, LF/HF, SD1/SD2, and entropy arrangement. These HRV indicators showed good correlation and statistical significance with behavioral and EEG changes (r>0.3, P<0.05); HRV indicators were significantly modulated by the magnetic field exposure before and after the exposure, both of which were observed in the continuous changes of electrocardiogram (ECG) (P<0.05), and the trend of the stimulation effect was more accurately observed in the continuous changes of ECG. ConclusionHRV can accurately reflect the pathophysiological changes and disease degree, quickly evaluate the effect of magnetic stimulation, and has the potential to guide the pattern of magnetic exposure, providing a new idea for the study of personalized electromagnetic neuroregulation technology for brain diseases.

Generative Artificial Intelligence ishows a broad application prospect in the field of healthcare and has become an important technical means to promote the development of medical informatization.It addresses the multi-faceted challenges of medical record documentation,including efficiency,quality,and doctor-patient communica-tion.It analyzes the adaptability and feasibility of Generative Artificial Intelligence in different clinical scenarios of intelli-gent medical record generation.Additionally,it explores the issues present in current applications and proposes corre-sponding solutions,providing references for the effective application and continuous optimization of Generative Artifi-cial Intelligence in medical record documentation.This provides a theoretical foundation for further expanding the appli-cation scenarios of automatic medical record documentation in China's healthcare industry.

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

Cholesterol on the cell membrane plays a crucial role in regulating membrane proteins,influencing cell functions,and the occurrence and development of tumors.The CD44 receptor protein is closely associated with tumor invasion and metastasis.Therefore,developing biosensors capable of in-situ simultaneous monitoring of cholesterol and CD44 receptor protein on the cell membrane is of great significance for disease diagnosis.In this study,a spatially resolved strategy dual-signal multifunctional electrochemiluminescence(ECL)sensor was designed.The positive potential luminescent probe(ALC)was prepared by combining gold nanostars with luminol and cholesterol oxidase(ChOx),and the negative potential luminescent probe(CZA)was prepared by combining carbon quantum dots(CQD)with ZIF-8 and gold nanoparticles(AuNPs).The dual probes were fixed on dual working electrodes respectively to construct a spatial resolution dual signal sensor,and the signals were independently output with K2S2O8 as co-reactant.When the measurement signal of ALC probe was enhanced due to enzymatic catalysis of cholesterol,CZA synchronously output the internal reference signal,realizing ratio ECL detection of cholesterol,with a linear range of 50 nmol/L-1600 μmol/L and a detection limit of 20 nmol/L.Furthermore,after the double probes were respectively modified with folic acid(FA)and hyaluronic acid(HA),a spatially resolved dual-functional cell sensor was constructed by capturing human hepatoma cells HepG2 through ligand-receptor specific recognition.This sensor enabled the simultaneous monitoring of cholesterol-ChOx catalytic reaction and CD44-HA recognition on the cell membrane,as well as the quantitative detection of cancer cells and cholesterol on the cell membrane.The results showed that the linear detection range for HepG2 cell was 100-10000 cell/mL.By reducing cholesterol on the cell membrane using methyl-β-cyclodextrin(MβCD)downregulated CD44 expression,it was found that the cholesterol content was positively correlated with CD44 expression on the cell membrane.The control experiments showed that the analysis method was feasible.The designed ECL sensor could be used to detect cholesterol ratiometrically and provided a new method for the simultaneous analysis of multiple functional molecules in cells.

Pancreatic cancer is characterized by significant drug resistance,and despite continuous advancements in treatment regimens,the 5-year survival rate of patients remains low.The nuclear factor-κB(NF-κB)signaling pathway,frequently mutated in tumors,has been identified as a critical factor in triggering drug resistance.Multiple studies have demonstrated that strategies targeting NF-κB signaling transduction exhibit promising outcomes in pancreatic cancer treatment.Therefore,exploring the relationship between the NF-κB signaling pathway and drug resistance in pancreatic cancer has become a research hotspot in pancreatic cancer treatment.This review summarizes recent advances in the relationship between NF-κB signaling pathway and tumor drug resistance,as well as its role in pancreatic cancer treatment.Specifically,the mechanisms by which the NF-κB signaling pathway mediates drug resistance in pancreatic cancer are elaborated from two perspectives:chemotherapy and immunotherapy,aiming to provide insights for pancreatic cancer treatment and future research.

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

Generative Artificial Intelligence ishows a broad application prospect in the field of healthcare and has become an important technical means to promote the development of medical informatization.It addresses the multi-faceted challenges of medical record documentation,including efficiency,quality,and doctor-patient communica-tion.It analyzes the adaptability and feasibility of Generative Artificial Intelligence in different clinical scenarios of intelli-gent medical record generation.Additionally,it explores the issues present in current applications and proposes corre-sponding solutions,providing references for the effective application and continuous optimization of Generative Artifi-cial Intelligence in medical record documentation.This provides a theoretical foundation for further expanding the appli-cation scenarios of automatic medical record documentation in China's healthcare industry.

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Isocitrate dehydrogenase 1 (IDH1) R132H is the most common mutated gene in grade II-III gliomas and oligodendrogliomas. Instead of activating telomerase (a reverse transcriptase which using RNA as a template to extend telomere length), the majority of IDH1^R132H mutant glioma maintain telomere length through an alternative mechanism that relies on homologous recombination (HR), which is known as alterative lengthening of telomere (ALT).The phenotype of ALT mechanism include: ALT associated promyelocytic leukemia protein (PML) bodies (APBs); extrachromosomal telomeric DNA repeats such as C- and T-loops; telomeric sister chromatid exchange (T-SCE), etc. The mechanism of ALT activation is not fully understood. Recent studies have shown that mutation IDH1 contributes to ALT phenotype in glioma cells in at least three key ways. Firstly, the IDH1^R132H mutation mediates RAP1 down-regulation leading to telomere dysfunction, thus ensuring persistent endogenous telomeric DNA damage, which is important for ALT activation. Spontaneous DNA damage at telomeres may provide a substrate for mutation break-induced replication (BIR)‑mediated ALT telomere lengthening, and it has been demonstrated that RAP1 inhibits telomeric repeat-containing RNA, transcribed from telomeric DNA repeat sequences (TERRA) transcription to down-regulate ALT telomere DNA replication stress and telomeric DNA damage, thereby inhibiting ALT telomere synthesis. Similarly, in ALT cells, knockdown of telomere-specific RNaseH1 nuclease triggers TERRA accumulation, which leads to increased replication pressure. Overexpression of RNaseH1, on the other hand, attenuates the recombination capacity of ALT telomeres, leading to telomere depletion, suggesting that RAP1 can regulate the level of replication pressure and thus ALT activity by controlling TERRA expression. Secondly, the IDH1^R132H also alters the preference of the telomere damage repair pathway by down-regulating XRCC1, which inhibits the alternative non-homologous end joining (A-NHEJ) pathway at telomeres and alters cellular preference for the HR pathway to promote ALT. Finally, the IDH1^R132H has a decreased affinity for isocitric acid and NADP+ and an increased affinity for α ketoglutarate (α‑KG) and NADPH, so that the mutant IDH1^R132H catalyzes the hydrogenation of α‑KG to produce 2-hydroxyglutarate (2-HG)in a NADPH-dependent manner. Because 2-HG is structurally similar to α‑KG, which maintains the trimethylation level of H3k9me3 by competitively inhibiting the activity of the α‑KG-dependent histone demethylase KDM4B, and recruits heterochromatin protein HP1α to heterochromatinize telomeres, and promote ALT phenotypes in cooperation with the inactivating of ATRX. In addition, it has been shown that APBs contain telomeric chromatin, which is essentially heterochromatin, and HP1α is directly involved in the formation of APBs. Based on these studies, this article reviews the mechanism of IDH1^R132H mediated telomere dysfunction and the preference of DNA repair pathway at telomeres in cooperate with ATRX loss to promote ALT, which may provide references for clinical targeted therapy of IDH1^R132H mutant glioma.

Aim To investigate the differences in the role of different purinergic receptor subtypes at different sites in postoperative-hyperalgesic priming in mice. Methods A postoperative-hyperalgesic priming model was constructed by injecting PGE