Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

A redox-responsive hyaluronic acid-vitamin E polyethylene glycol succinate nanoparticle loaded with paclitaxel (HA-SS-TPGS@PTX) was designed to investigate its mechanism for overcoming multidrug resistance (MDR) in non-small cell lung cancer (NSCLC) in vitro. HA-SS-TPGS@PTX nanoparticles were prepared using an emulsion-ultrasonication method. Techniques such as flow cytometry and confocal laser scanning microscopy (CLSM) were employed to study their effects on apoptosis induction, mitochondrial function, and the regulation of P-glycoprotein (P-gp) expression in PTX-resistant lung cancer cells (A549/T). Results showed that HA-SS-TPGS@PTX nanoparticles significantly inhibited the proliferation of A549/T cells in vitro, with an IC50 of 1.35 μg/mL. The nanoparticles entered the cells via CD44 receptor-mediated endocytosis. The high intracellular concentration of glutathione (GSH) triggered the release of PTX and TPGS, which subsequently induced a decrease in mitochondrial membrane potential, leading to apoptosis. Meanwhile, HA-SS-TPGS@PTX also inhibited P-gp expression and ATP consumption, thereby blocking drug efflux. The design of HA-SS-TPGS@PTX provides a new strategy for overcoming MDR in NSCLC.

Tacrolimus is an immunosuppressant that was clinically used for organ transplantation in the 1990s. In the early 2000s, tacrolimus began to be used to treat pediatric kidney diseases in China. This article reviews the therapeutic effects, clinical dosages, and treatment methods of tacrolimus in the treatment of steroid-resistant, steroid-dependent, frequently relapsing, different pathological types, and monogenic mutation-related childhood nephrotic syndrome. It explores the clinical guiding role of machine learning in tacrolimus treatment for childhood nephrotic syndrome, aiming to provide references for the clinical research and application of tacrolimus in pediatric kidney diseases.

OBJECTIVES: To investigate the application value of thromboelastography (TEG) in assessing coagulation function in children with severe hemophilia A (HA) after emicizumab (EMI) therapy. METHODS: A retrospective analysis was performed on the activated partial thromboplastin time (APTT) and TEG testing results of 17 children with severe HA before and after EMI treatment at Shenzhen Children's Hospital from January 2023 to July 2024. Correlation analysis was conducted between coagulation factor VIII (FVIII) equivalent activity and reaction time (R value) measured by TEG. RESULTS: After EMI treatment, the mean bleeding rate for children with severe HA was 1.6 events per year, with 15 children (88%) without spontaneous bleeding or joint bleeding. The children with severe HA showed a significant reduction in APTT after EMI treatment (P<0.05), with a significantly shorter APTT than the normal control group (P<0.05). There was no correlation between APTT and FVIII equivalent activity after treatment (P>0.05). After EMI treatment, TEG parameters, including R value, kinetic time, alpha angle (α), maximum amplitude, clot strength, and coagulation index, shifted from a hypocoagulable state before treatment to a nearly normal state after treatment (P<0.05). The R value demonstrated a strong negative correlation with FVIII equivalent activity (r=-0.758, P<0.05). CONCLUSIONS The bleeding condition of children with severe HA can be effectively controlled after EMI treatment. Routine APTT testing cannot reflect true coagulation function, whereas TEG testing is clinically valuable in assessing the coagulation function of children with severe HA undergoing EMI treatment.
Humans ; Thrombelastography ; Hemophilia A/physiopathology* ; Male ; Child ; Antibodies, Bispecific/therapeutic use* ; Antibodies, Monoclonal, Humanized/therapeutic use* ; Blood Coagulation/drug effects* ; Child, Preschool ; Retrospective Studies ; Female ; Partial Thromboplastin Time ; Adolescent ; Infant

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

OBJECTIVES: To explore the mechanism by which histone deacetylase 1 (HDAC1) regulates steroid-induced apoptosis of mouse osteocyte-like MLO-Y4 cells. METHODS: MLY-O4 cells were treated with 400 nmol/L trichostatin A (TSA) or 1 mmol/L dexamethasone for 24 h or transfected with a HDAC1-overexpressing vector prior to TSA or dexamethasone treatment. The changes in the expressions of HDAC1, SP1, cleaved caspase-3 and Bax, SP1 acetylation level, cell proliferation, and cell apoptosis were examined. The interaction between HDAC1 and SP1 was determined with immunoprecipitation assay and Western blotting. RESULTS: Treatment with dexamethasone significantly increased cell apoptosis, enhanced the expressions of cleaved caspase-3 and Bax, reduced HDAC1 expression, and suppressed proliferation of MLO-Y4 cells. Both TSA and dexamethasone obviously increased SP1 acetylation level and the expression of SP1 in MLO-Y4 cells. HDAC1 overexpression in the cells significantly attenuated the effect of TSA and dexamethasone, promoted cell proliferation, lowered the expressions of SP1, cleaved caspase-3 and Bax, and inhibited dexamethasone-induced cell apoptosis. Immunoprecipitation assay and Western blotting demonstrated the interaction between HDAC1 and SP1 in the cells. CONCLUSIONS HDAC1 inhibits dexamethasone-induced apoptosis and promotes proliferation of cultured mouse osteocytes by suppressing SP1 expression via promoting its deacetylation.
Animals ; Apoptosis/drug effects* ; Mice ; Histone Deacetylase 1/genetics* ; Osteocytes/drug effects* ; Sp1 Transcription Factor/metabolism* ; Acetylation ; Dexamethasone/pharmacology* ; Cell Proliferation/drug effects* ; Caspase 3/metabolism* ; Cell Line ; Hydroxamic Acids/pharmacology* ; bcl-2-Associated X Protein/metabolism*

Whole-genome sequencing, serotype typing, MLST typing, population genetic structure analysis, and core-genome single nucleotide polymorphism (cgSNP) analysis were performed on 23 strains of mucoid Haemophilus influenzae collected from the Laboratory Center of Hunan Children′s Hospital from January 2021 to December 2022. Drug susceptibility tests were conducted using the automated microbial identification and susceptibility analysis system AF-600, and virulence genes and drug resistance genes were analyzed based on the whole-genome sequences. Based on the serotype typing of whole-genome sequencing, all 23 strains were Haemophilus influenzae type b (Hib). MLST analysis revealed that the 23 strains belonged to six ST types, among which 10 strains (43.5%) were ST386, 5 strains (21.7%) were ST18, and 2 strains (8.7%) were the newly discovered ST2887. Bayesian population structure analysis (BAPS) showed three distinct populations. The results of the virulence gene analysis showed that the carriage rates of genes encoding capsule-related proteins and those associated with bacterial immune regulation and inflammatory signaling pathways were all 100%. However, the ompP5 gene related to bacterial adhesion, and the hgpC and hxuA genes related to bacterial protein metabolism were all present in the newly discovered ST2887. The in vitro drug susceptibility test results of 23 strains of mucoid Hib showed that the resistance rates to ampicillin, cefuroxime, and Trimethoprim-sulfamethoxazole were 13.0%(3 strains), 13.0%(3 strains), and 87.0%(20 strains), respectively. They were sensitive to other beta-lactam drugs. All the 23 strains of mucoid Haemophilus influenzae infected children were Hib, and the main ST types were ST386 and ST18. It is very important to advocate Hib vaccination.