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.

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.

PURPOSE: Although there are significant differences between China and the United States (US) in trauma medical services, there has been no direct comparative research on the epidemiological data of trauma centers between the 2 countries. This study aims to fill this research gap by directly comparing trauma centers in China and the US, providing valuable data and insights for the development of trauma centers in both countries, promoting academic exchange and cooperation internationally, and enhancing the level of global trauma medical care. METHODS: This is a multicenter retrospective descriptive study. Data were collected for trauma patients with an injury severity score ≥16 treated from September 2013 to September 2019 at 2 hospital trauma centers in these 2 countries. Detailed clinical data (including injury mechanism, age, injury site, injury severity score, pre-hospital transport time, whether blood transfusion was performed, whether resuscitative thoracotomy was conducted, hospital and intensive care unit stay duration, the number of organ donor patients, mortality rates, and costs) were meticulously compiled and retrospectively analyzed to identify differences between the 2 trauma centers. The comparison was conducted using SPSS 23 software. Continuous variables are reported as median (Q₁, Q₃), and Mann Whitney U test is used to compare the median of continuous variables. Use clinically relevant critical points to classify continuous variables, with categorical variables represented as n (%), and comparisons were made between the 2 groups using the χ² test or Fisher's exact test. Statistical significance was defined as a 2-sided p < 0.05. RESULTS: These results point to significant differences in trauma center capacity, pre-hospital transport times, treatment procedures, hospital stay duration, mortality rates, and costs between the 2 centers. The volume of patients in trauma centers is less in China (2465 vs. 5288). Pre-hospital transport time was notably longer in China (180 min vs. 14 min), and the rate of emergency blood transfusions was lower in China (18.4% vs. 50.6%), Emergency thoracotomy was not performed in China but was conducted in 9.8% of cases in the US. Hospitalization costs were significantly lower in China than in the US ($5847 vs. $75,671). CONCLUSION There are clear differences in trauma center capacity (number of patients treated), pre-hospital transport time, age distribution of injured patients, injury mechanisms, injury sites, whether emergency thoracotomy is performed, hospital costs, and length of stay between the 2 trauma centers in China and America. Understanding these differences can help us further recognize the characteristics of Eastern and Western trauma patients.
Humans ; China/epidemiology* ; Trauma Centers/statistics & numerical data* ; Retrospective Studies ; United States/epidemiology* ; Male ; Female ; Wounds and Injuries/therapy* ; Middle Aged ; Adult ; Injury Severity Score ; Length of Stay/statistics & numerical data* ; Treatment Outcome

Objective:To investigate the correlation between upper limb grip strength and total body bone mineral density(BMD)us-ing public data.Methods:During the 2011-2012 and 2013-2014 cycles of National Health and Nutrition Examination Surveys,a total of 5148 participants with grip strength,BMD,and multiple potential confounding factors were identified,and baseline levels were cal-culated after weighting.R language survey package was used for the multiple linear regression analysis to investigate the correlation be-tween grip strength and BMD,and then stratified analysis was performed based on sex and age.The rcssci package was used for curve fitting to analyze the curve relationship between the two indicators.Results:A total of 5 148 participants(2 493 male participants and 2 655 female participants)were included in this study.The overall grip strength was(77.48±0.40)kg,with a value of(93.98±0.45)kg for male participants and(59.71±0.24)kg for female participants;overall left upper limb grip strength was(37.75±0.21)kg,with a value of(28.89±0.12)kg for female participants and(45.98±0.24)kg for male participants;overall right upper limb grip strength was(39.73±0.20)kg,with a value of(30.83±0.13)kg for female participants and(48.00±0.23)kg in male par-ticipants.Overall left grip strength values of body mass index was 46.87±0.33,with a value of 53.65±0.46 for male participants and 39.56±0.26 for female participants(P<0.000 1);overall right grip strength values of body mass index was 49.37±0.33,with a value of 56.01±0.47 for male participants and 42.21±0.26 for female participants;overall mean grip strength index was 48.12±0.33,with a value of 54.83±0.46 for male participants and 40.89±0.26 for female participants;overall BMD was(1.11±0.00)g/cm2,with a value of(1.15±0.00)g/cm2 in male participants and(1.08±0.00)g/cm2 in female participants.After exclusion of confounding factors,grip strength showed a significant positive correlation with total BMD(P<0.000 1),and in addition,age was negatively correlated with BMD.Black race(with Mexican descent as reference),college graduation or above(with the participants not graduated from high school as reference),body height,and body mass index(BMI)were positively correlated with BMD.Stratified analysis showed that age,sex,and BMI had interaction with BMD.The curve fitting results showed that there was only a linear relationship between grip strength and BMD(P<0.001),but there was an L-shaped curve relationship between grip strength index(mainly of the left side)and BMD.With the increases in grip strength and grip strength index,BMD increased in a linear and L-shaped curve(BMD increased slowly with the increase in grip strength index),with a variation range of 0.1 g/cm2.Conclusion:Grip strength of both upper limbs and grip strength index(mainly of the left side)are positively correlated with BMD,and BMD shows a linear relationship with grip strength and an L-shaped curve relationship with grip strength index.The results of this study further support the correlation between grip strength and BMD and provide important empirical data for understanding the impact of grip strength on BMD,which has important significance for further research on the regulatory mechanism of BMD and the prevention and treatment of osteoporosis.

The concept and harms of hypothermia were introduced.The research progress of the intelligent warning equipment and model for hypothermia was reviewed,and the advantages and problems in practical application were analyzed.It's pointed out the intelligent warning equipment had to be improved in environmental adaptability,operational convenience and functio-nal stability and the model be enhanced in robustness,large-scale clinical validation and warning parameter accessibility.[Chinese Medical Equipment Journal,2024,45(5):86-94]

Objective:To identify the key genes involved in the development and progression of prostate cancer(PCa)and those associated with the prognosis of the malignancy.Methods:We obtained the single-cell sequencing data on 4 cases of PCa from the GSE156632 database.Using R language and the Seurat package,we performed cell clustering and annotation,selected the subpop-ulations of epithelial cells for differential analysis after quality control and cell type identification,and conducted enrichment analysis of the identified differential genes using the Hiplot website.Then we downloaded the single nucleotide polymorphism(SNP)loci corre-sponding to the expression quantitative trait loci(eQTL)of these genes from the UK Biobank(UKB)database,and the clinical data and corresponding gene expression data on PCa patients from The Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO),followed by univariate COX regression analysis of the impact of the genes on the prognosis of the patients after Mendelian ran-domization.Results:A total of 1 566 genes were identified and subjected to enrichment analysis,which indicated that the differenti-al genes might be enriched in the Ras,apoptosis and oxidative phosphorylation signaling pathways.Subsequent Mendelian randomiza-tion revealed 74 potential causal genes among the 1 566 genes,and univariate COX regression analysis of the 74 genes identified 4 pos-sibly related genes FAM3B,JUNB,TMEM59,and KRT5.Comparison of the results of Mendelian randomization and univariate COX regression showed that KRT5 might be the most important gene influencing PCa.Conclusion:FAM3B,JUNB,TMEM59 and KRT5 may play a role in the progression of PCa,and KRT5 may potentially serve as a prognostic predictor and therapeutic target for the malig-nancy.

Background: and Purpose Migraine is a condition that is often observed to run in families, but its complex genetic background remains unclear. This study aimed to identify the genetic factors influencing migraines and their potential association with the family medical history. Methods: We performed a comprehensive genome-wide association study of a cohort of 1,561 outpatients with migraine and 473 individuals without migraine in Taiwan, including Han Chinese individuals with or without a family history of migraine. By analyzing the detailed headache history of the patients and their relatives we aimed to isolate potential genetic markers associated with migraine while considering factors such as sex, episodic vs. chronic migraine, and the presence of aura. Results: We revealed novel genetic risk loci, including rs2287637 in DEAD-Box helicase 1 and long intergenic non-protein coding RNA 1804 and rs12055943 in engulfment and cell motility 1, that were correlated with the family history of migraine. We also found a genetic location downstream of mesoderm posterior BHLH transcription factor 2 associated with episodic migraine, whereas loci within the ubiquitin-specific peptidase 26 exonic region, dual specificity phosphatase 9 and pregnancy-upregulated non-ubiquitous CaM kinase intergenic regions, and poly (ADP-ribose) polymerase 1 and STUM were linked to chronic migraine. We additionally identified genetic regionsassociated with the presence or absence of aura. A locus between LINC02561 and urocortin 3 was predominantly observed in female patients. Moreover, three different single-nucleotide polymorphisms were associated with the family history of migraine in the control group. Conclusions This study has identified new genetic locations associated with migraine and its family history in a Han Chinese population, reinforcing the genetic background of migraine. The findings point to potential candidate genes that should be investigated further.