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 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.

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]

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.

Cancer is a complex disease associated with multiple gene mutations and malignant phenotypes, and multi-target drugs provide a promising therapy idea for the treatment of cancer. Natural products with abundant chemical structure types and rich pharmacological characteristics could be ideal sources for screening multi-target antineoplastic drugs. In this paper, 50 tumor-related targets were collected by searching the Therapeutic Target Database and Thomson Reuters Integrity database, and a multi-target anti-cancer prediction system based on mt-QSAR models was constructed by using naïve Bayesian and recursive partitioning algorithm for the first time. Through the multi-target anti-cancer prediction system, some dominant fragments that act on multiple tumor-related targets were analyzed, which could be helpful in designing multi-target anti-cancer drugs. Anti-cancer traditional Chinese medicine (TCM) and its natural products were collected to form a TCM formula-based natural products library, and the potential targets of the natural products in the library were predicted by multi-target anti-cancer prediction system. As a result, alkaloids, flavonoids and terpenoids were predicted to act on multiple tumor-related targets. The predicted targets of some representative compounds were verified according to literature review and most of the selected natural compounds were found to exert certain anti-cancer activity in vitro biological experiments. In conclusion, the multi-target anti-cancer prediction system is very effective and reliable, and it could be further used for elucidating the functional mechanism of anti-cancer TCM formula and screening for multi-target anti-cancer drugs. The anti-cancer natural compounds found in this paper will lay important information for further study.
Antineoplastic Agents/pharmacology* ; Bayes Theorem ; Drugs, Chinese Herbal/chemistry* ; Humans ; Medicine, Chinese Traditional ; Neoplasms/drug therapy*