ObjectiveTo investigate whether Huanglian Jiedutang （HLJD） and its major active constituents （geniposide， baicalin， and berberine） can inhibit the inflammatory response of BV2 cells under lipopolysaccharide （LPS） stimulation via the high-mobility group protein B1 （HMGB1）/Toll-like receptor 4 （TLR4）/nuclear factor-κB （NF-κB） signaling pathway， and to explore differences in therapeutic efficacy among the three monomers， their combined formula， and HLJD under equal content ratios. MethodsBV2 microglial cells were used as the primary experimental model. Cell viability was assessed using the cell counting kit-8 （CCK-8） method to examine the effects of different concentrations of dimethyl sulfoxide （DMSO， 0.8%， 0.4%， 0.2%， 0.1%， and 0.05%） on cell viability. IncuCyte was employed to monitor the growth of cells under different concentrations of HLJD （200， 100， 50， 25， 12.5， 6.25 mg·L^-1）. Nitric oxide （NO） assay was used to screen the optimal HLJD concentration. High-performance liquid chromatography （HPLC） determined the content of geniposide， baicalin， and berberine in HLJD， and experimental groups were subsequently established according to the relative proportions of these constituents. CCK-8 assay evaluated cell viability under different treatments. Enzyme-linked immunosorbent assay （ELISA） measured levels of inflammatory factors （TNF-α， IL-1β， IL-6， IL-10） in the supernatant. Flow cytometry assessed the effects of treatments on M1-type polarization of BV2 cells. Western blot determined the expression levels of HMGB1， TLR4， and NF-κB-related proteins. ResultsCompared with the blank group， DMSO at concentrations ≤0.2% did not affect cell viability within 48 h. BV2 cell growth plateaued at 24 h after treatment with 200 mg·L^-1 HLJD. Under stimulation with 2 mg·L^-1 LPS， this concentration of HLJD effectively reduced NO release， and 6 h pre-treatment had a stronger inhibitory effect on NO than direct administration. HPLC results showed that 1 mg of HLJD freeze-dried powder contained approximately 24 μg of geniposide， 15 μg of baicalin， and 30 μg of berberine. Based on these ratios， experimental groups were blank， LPS （2 mg·L^-1）， HLJD （200 mg·L^-1）， monomer combination， geniposide （4.8 mg·L^-1）， baicalin （3 mg·L^-1）， and berberine （6 mg·L^-1）. The monomer combination group consisted of all three active constituents dissolved together. LPS and HLJD or its active constituents did not affect cell viability compared with the blank group. LPS significantly increased TNF-α， IL-1β， IL-6， and IL-10 in the supernatant （P<0.01）. HLJD and its active constituents significantly reduced pro-inflammatory factors TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01） while upregulating anti-inflammatory IL-10 （P<0.01）， with the monomer combination showing the strongest effect （P<0.05， P<0.01）. Compared with the blank group， LPS significantly increased the proportion of CD80⁺CD86⁺ （M1-type） BV2 cells （P<0.01）. HLJD and its constituents partially inhibited M1 polarization （P<0.05， P<0.01）， with the monomer combination exhibiting the most pronounced effect （P<0.05， P<0.01）. Compared with the blank group， LPS upregulated HMGB1， TLR4， and NF-κB-related proteins （P<0.01）， whereas HLJD and its active constituents significantly reduced their expression （P<0.05， P<0.01）， with the monomer combination having the strongest regulatory effect （P<0.05， P<0.01）. ConclusionHLJD and its major active constituents （geniposide， baicalin， berberine） can inhibit LPS-induced inflammatory responses in BV2 cells. The combination of the three active constituents demonstrates the most potent anti-inflammatory effect， significantly attenuating M1-type polarization of BV2 cells via the HMGB1/TLR4/NF-κB signaling pathway.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that seriously affects the health of the elderly, and the early diagnosis is crucial to slow down the progression of the disease. This review systematically examines the integrative applications of multimodal digital technologies in early AD identification, encompassing cognitive assessment, neuroimaging analysis, biomarker detection, and polygenic risk prediction, with the goal of enhancing diagnostic accuracy and operational efficiency. It was found that artificial intelligence-driven digital tools significantly improved screening efficiency by capturing subtle behavioral patterns and physiological signatures. Machine learning algorithms integrated with multimodal neuroimaging data optimize sensitivity in detecting structural brain abnormalities, while combinatorial analysis of digital biomarkers enables high-precision staging of AD pathology. Recent advancements highlight the critical role of digital technologies in facilitating multimodal biomarker integration and streamlining diagnostic workflows. The convergence of these innovative approaches provides a robust framework for early AD screening, offering patients accessible and efficient diagnostic pathways.

OBJECTIVE To investigate the epidemiological characteristics of respiratory human adenovirus(H AdV)infections in hospitalized children in Ningbo,and to provide data for formulating infection prevention and control strategies for HAdV.METHODS A total of 65 022 children hospitalized with respiratory infections at the Women and Children's Hospital of Ningbo University from Jul.2019 to Dec.2024 were selected as the study sub-jects.Multiple reverse transcription-polymerase chain reaction(RT-PCR)and capillary electrophoresis were used to detect 11 non-bacterial pathogens.Basic and clinical information of the children was collected for analysis.RESULTS A total of 65 022 specimens were tested,with 4 292 cases tested positive for HAdV positivity,yielding a positive rate of 6.60％.The lowest positive rate was observed in 2023(3.22％),while the highest was in 2024(13.97％).Compared to the years 2019-2023,the overall HAdV positive rate was high in 2024,peaking at 26.80％in Jun.,indicating an outbreak.The total HAdV positive rate was higher in boys(6.82％)than in girls(6.32％)(P=0.006).The highest HAdV positive rate was observed in the 2 to＜6 age group(9.00％),while the lowest was in the 0 to＜1 age group(2.33％).Among the HAdV-positive specimens,2 658 cases(61.93％)were single infections,and 1 634 cases(38.07％)were co-infections.The non-bacterial respiratory pathogens with the highest co-infection rates were human rhinovirus(34.09％),Mycoplasma pneumoniae(20.44％)and human parainfluenza virus(5.75％).CONCLUSIONS A n outbreak of HAdV infections is observed among hospitalized children in Ningbo in 2024.Higher positive rates are found in boys aged 2 to＜6 years,with a certain proportion of co-infections.

Objective To explore the potential causal relationship between opioids and chronic renal failure(CRF)using Mendelian randomization analysis.Methods Screening for single nucleotide polymorphisms(SNPs)strongly associated with opioids and CRF firstly,causality was analyzed by using two-sample Mendelian randomization methods,heterogeneity,horizontal pleiotropy and sensitivity analyses were then performed.Results A total of 41 opioid-related SNPs were screened in this study,inverse variance weighting analysis suggested that opioid use is a risk factor for CRF(OR=1.15,95％CI:1.04-1.27,P＜0.01).The heterogeneity test showed that there was no heterogeneity in the SNPs,and the horizontal multivariate analysis and sensitivity analysis confirmed the robustness of the results.Conclusion Genetically,the study suggests a positive causal association between opioids and CRF,opioid use is a risk factor for CRF.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that seriously affects the health of the elderly, and the early diagnosis is crucial to slow down the progression of the disease. This review systematically examines the integrative applications of multimodal digital technologies in early AD identification, encompassing cognitive assessment, neuroimaging analysis, biomarker detection, and polygenic risk prediction, with the goal of enhancing diagnostic accuracy and operational efficiency. It was found that artificial intelligence-driven digital tools significantly improved screening efficiency by capturing subtle behavioral patterns and physiological signatures. Machine learning algorithms integrated with multimodal neuroimaging data optimize sensitivity in detecting structural brain abnormalities, while combinatorial analysis of digital biomarkers enables high-precision staging of AD pathology. Recent advancements highlight the critical role of digital technologies in facilitating multimodal biomarker integration and streamlining diagnostic workflows. The convergence of these innovative approaches provides a robust framework for early AD screening, offering patients accessible and efficient diagnostic pathways.

To report a case of Stormorken syndrome(STRMK)diagnosed in adulthood and to study its clinical,pathological and genetic characteristics.The individual was a 31-year-old male whose symptoms started from childhood with epilepsy as initial symptom.He gradually developed progressive muscle weakness and atrophy.The patient's clinical data,laboratory results,and imaging studies were collected.A biopsy on the patient's left gastrocnemius muscle was conducted.Simultaneously,whole-exome sequencing on both the patient and his parents was performed.The physical examination of the patient showed short stature,proximal muscle weakness with lower limb predominance,accompanied by joint contracture and scoliosis.Abdominal CT examination revealed asplenia and magnetic resonance image(MRI)showed obvious fat infiltration in the bilateral lower limb muscle.Muscle biopsy was consistent with tubular-aggregate myopathy.Genetic test indicated that the patient had a c.326A>G(p.His109Arg)heterozygous mutation in the stromal interaction molecule 1(STIM1)gene,a known pathogenic mutation.This study further enables neurologists to gain a better understanding of this rare disease.

Bacterial infection is a major threat to global public health,and can cause serious diseases such as bacterial skin infection and foodborne diseases.It is essential to develop a new method to rapidly di-agnose clinical multiple bacterial infections and monitor food microbial contamination in production sites in real-time.In this work,we developed a 4-mercaptophenylboronic acid gold nanoparticles(4-MPBA-AuNPs)-functionalized hydrogel microneedle(MPBA-H-MN)for bacteria detection in skin inter-stitial fluid.MPBA-H-MN could conveniently capture and enrich a variety of bacteria within 5 min.Surface enhanced Raman spectroscopy(SERS)detection was then performed and combined with ma-chine learning technology to distinguish and identify a variety of bacteria.Overall,the capture efficiency of this method exceeded 50％.In the concentration range of 1 × 10 7 to 1 × 10 10 colony-forming units/mL(CFU/mL),the corresponding SERS intensity showed a certain linear relationship with the bacterial concentration.Using random forest(RF)-based machine learning,bacteria were effectively distinguished with an accuracy of 97.87％.In addition,the harmless disposal of used MNs by photothermal ablation was convenient,environmentally friendly,and inexpensive.This technique provided a potential method for rapid and real-time diagnosis of multiple clinical bacterial infections and for monitoring microbial contamination of food in production sites.

Non-small cell lung cancer (NSCLC), as the predominant histological subtype of lung cancer, accounts for approximately 85% of all lung cancer cases. In recent years, immune checkpoint inhibitors (ICIs), represented by programmed death 1/programmed death ligand 1 (PD-1/PD-L1) inhibitors, have achieved breakthrough advancements in patients with driver gene-negative NSCLC. They have been established as a key component of first-line treatment regimens and have significantly improved clinical outcomes. However, limited clinical evidence has emerged showing the phenomenon of histological transformation from NSCLC to small cell lung cancer (SCLC) in patients experiencing disease progression after ICIs monotherapy or combination therapy. Systematic research data on the clinical characteristics, molecular biological basis, and subsequent treatment strategies for such transformation events are currently lacking. This article reports a case of SCLC transformation occurring in a patient with KRAS-mutated lung adenocarcinoma after 16 months of ICIs combination therapy and provides a systematic review of 22 similar published cases. The study demonstrates that small cell transformation is a critical mechanism of immunotherapy resistance, and transformed patients exhibit poor prognosis. The research emphasizes the importance of dynamic monitoring of neuron-specific enolase (NSE) and standardized repeat biopsies during treatment, providing a basis for clinical practice. This aids in enhancing the recognition and management capabilities for this rare histological transformation, ultimately improving patient outcomes.
Humans ; Immune Checkpoint Inhibitors/therapeutic use* ; Lung Neoplasms/immunology* ; Carcinoma, Non-Small-Cell Lung/immunology* ; Small Cell Lung Carcinoma/genetics* ; Male ; Middle Aged ; Female

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

Bacterial infection is a major threat to global public health, and can cause serious diseases such as bacterial skin infection and foodborne diseases. It is essential to develop a new method to rapidly diagnose clinical multiple bacterial infections and monitor food microbial contamination in production sites in real-time. In this work, we developed a 4-mercaptophenylboronic acid gold nanoparticles (4-MPBA-AuNPs)-functionalized hydrogel microneedle (MPBA-H-MN) for bacteria detection in skin interstitial fluid. MPBA-H-MN could conveniently capture and enrich a variety of bacteria within 5 min. Surface enhanced Raman spectroscopy (SERS) detection was then performed and combined with machine learning technology to distinguish and identify a variety of bacteria. Overall, the capture efficiency of this method exceeded 50%. In the concentration range of 1 × 10⁷ to 1 × 10¹⁰ colony-forming units/mL (CFU/mL), the corresponding SERS intensity showed a certain linear relationship with the bacterial concentration. Using random forest (RF)-based machine learning, bacteria were effectively distinguished with an accuracy of 97.87%. In addition, the harmless disposal of used MNs by photothermal ablation was convenient, environmentally friendly, and inexpensive. This technique provided a potential method for rapid and real-time diagnosis of multiple clinical bacterial infections and for monitoring microbial contamination of food in production sites.