Miracle-dz/UniFAR-FTUs huggingface dataset:
A Transfer Learning Method for Detecting Alzheimer's Disease Based on Speech and Natural Language Processing

Alzheimer's disease (AD) is a neurodegenerative disease that is difficult to be detected using convenient and reliable methods. The language change in patients with AD is an important signal of their cognitive status, which potentially helps in early diagnosis. In this study, we developed a transfer learning model based on speech and natural language processing (NLP) technology for the early diagnosis of AD. The lack of large datasets limits the use of complex neural network models without feature engineering, while transfer learning can effectively solve this problem. The transfer learning model is firstly pre-trained on large text datasets to get the pre-trained language model, and then, based on such a model, an AD classification model is performed on small training sets. Concretely, a distilled bidirectional encoder representation (distilBert) embedding, combined with a logistic regression classifier, is used to distinguish AD from normal controls. The model experiment was evaluated on Alzheimer's dementia recognition through spontaneous speech datasets in 2020, including the balanced 78 healthy controls (HC) and 78 patients with AD. The accuracy of the proposed model is 0.88, which is almost equivalent to the champion score in the challenge and a considerable improvement over the baseline of 75% established by organizers of the challenge. As a result, the transfer learning method in this study improves AD prediction, which does not only reduces the need for feature engineering but also addresses the lack of sufficiently large datasets.
Monthly Motivational Interview Counseling and Nicotine Replacement Therapy for Smoking Parents of Pediatric Patients: A Randomized Controlled Trial

Background Parental smoking is the dominant source of passive smoke exposure in the pediatric population. The current randomized controlled trial (RCT) study aimed to evaluate the effectiveness of a multi-component smoking reduction intervention in parental smoking reduction and children's environmental tobacco smoke exposure reduction in clinical settings. Methods A single-blinded, 6-month randomized controlled trial recruited smoking parents (N = 210) of children who attended the pediatric wards or clinics at the Prince of Wales Hospital. Participants allocated to the intervention group (n = 105) received monthly motivational interviews on smoking reduction with emphasis on health hazards related to children's passive smoke exposure, 8-week nicotine replacement therapy, and referral to smoking cessation service if the parents preferred. The control group (n = 105) received simple verbal advice on smoking cessation. Primary outcomes were parental urine cotinine validated and self-reported ≥50% smoking reduction rates at 6 months. Results Smoking parents in the intervention group had significantly more biochemically validated ≥50% smoking reduction than the control: 27.1 vs. 10.0% (OR = 3.34, 95% CI: 1.16–9.62, P = 0.02). The rate of self-reported ≥50% smoking reduction was also significantly higher in the intervention group than the control: 51.9 vs. 20.2% (OR = 4.40, 95% CI: 2.38–8.12, P < 0.001). For secondary outcomes, the rate of parental self-reported smoking cessation was higher in the intervention arm: 10.5 vs. 1.0% (OR = 12.17, 95% CI: 1.54–96.07, P < 0.001), however, no differences were detected in biochemically validated cessation and changes in children's passive smoke exposure between the groups. Conclusion Monthly smoking reduction counseling together with nicotine replacement therapy is more effective than simple verbal cessation advice in the smoking reduction for parents of pediatric patients. However, this study did not demonstrate differences in smoking cessation or reduction in children's passive smoke exposure with a 6-month follow-up. Achievement of a smoke-free environment remains challenging. Trial Registration Clinicaltrials.gov, identifier: NCT03879889.
Associations of Polygenic Risk Score for Late-Onset Alzheimer's Disease With Biomarkers

Late-onset Alzheimer's disease (LOAD) is a common irreversible neurodegenerative disease with heterogeneous genetic characteristics. Identifying the biological biomarkers with the potential to predict the conversion from normal controls to LOAD is clinically important for early interventions of LOAD and clinical treatment. The polygenic risk score for LOAD (AD-PRS) has been reported the potential possibility for reliably identifying individuals with risk of developing LOAD recently. To investigate the external phenotype changes resulting from LOAD and the underlying etiology, we summarize the comprehensive associations of AD-PRS with multiple biomarkers, including neuroimaging, cerebrospinal fluid and plasma biomarkers, cardiovascular risk factors, cognitive behavior, and mental health. This systematic review helps improve the understanding of the biomarkers with potential predictive value for LOAD and further optimizing the prediction and accurate treatment of LOAD.
The Compassionate Engagement and Action Scales for Self and Others: Turkish Adaptation, Validity, and Reliability Study

Aim This study aims to translate the Compassionate Engagement and Action Scales (CEAS) into Turkish and to test their subsequent validity, reliability, and psychometric properties. Turkey is one of the blended cultures with eastern and western elements under the influence of traditional religion. This cultural diversity brings about a rich context to study compassion and its relationship to mental health. The scales assess the ability to be sensitive to suffering and engage and then take helpful actions in compassion. The motivation for compassionate engagement and action is measured at three ‘flows’ as follows: (1) compassion for others; (2) compassion from others; and (3) compassion for self. Methods The sample consists of 525 college students aged 18 years or older. The participants completed the CEAS Turkish Form for Others, Self and from Others, Self-Compassion Scale Short Form, Compassionate Love Scale, and Self-Criticism Scale. Results The confirmatory factor analyses were conducted using AMOS version 27 to examine the validity of the three scales with two different factor structures each. All the three models show good fits to the data. The Cronbach’s alpha coefficient for the CEAS for Others and for Self and from Others are good to excellent (between 0.70 and 0.95 for all subscales). Compassion for self, compassion for others, and compassion from others correlated modestly. Conclusion It can be concluded that the Turkish version of the Compassionate Engagement and Action Scales for Others and Self and from Others has sufficient psychometric properties and can be used as a reliable and valid measure to assess compassionate engagement and action.
Periprostatic Adipose Tissue Microenvironment: Metabolic and Hormonal Pathways During Prostate Cancer Progression

The periprostatic adipose tissue (PPAT) is a site of invasion of prostate cancer (PCa) and is part of the microenvironment. It was shown that PPAT secretes factors and fatty acids (FAs) that alter the microenvironment of the PCa. The PPAT secretome of patients with PCa-T3 stage (PPAT-T3) has a metabolic profile enriched in several pathways related to energy production, indicating a greater energy requirement by the tumor, when compared to that of patients in the PCa-T2 stage (PPAT-T2). PPAT-T3 also shows enrichment in pathways related to hormone response, polyamine synthesis, and control of protein synthesis, through amino acid, RNA, and nucleotide metabolism. PPAT-T2 and PPAT-BPH secretomes have less complex metabolic profile, both related with energy balance, while PPAT-BPH has hormone response through insulin pathway. Undoubtedly, a deeper characterization of the human PPAT will lead to a better understanding of the disease and possibly allow new stratification factors and the design of a specific therapy that targets crucial components of the tumor microenvironment as another way to treat or control the disease.
A general thermal model of machine tool spindle

As the core component of machine tool, the thermal characteristics of the spindle have a significant influence on machine tool running status. Lack of an accurate model of the spindle system, particularly the model of load–deformation coefficient between the bearing rolling elements and rings, severely limits the thermal error analytic precision of the spindle. In this article, bearing internal loads, especially the function relationships between the principal curvature difference F(ρ) and auxiliary parameter nδ, semi-major axis a, and semi-minor axis b, have been determined; furthermore, high-precision heat generation combining the heat sinks in the spindle system is calculated; finally, an accurate thermal model of the spindle was established. Moreover, a conventional spindle with embedded fiber Bragg grating temperature sensors has been developed. By comparing the experiment results with simulation, it indicates that the model has good accuracy, which verifies the reliability of the modeling process.
Schlemm’s Canal Endothelium Cellular Connectivity in Giant Vacuole and Pore Formation in Different Flow-type Areas: A Serial Block-Face Scanning Electron Microscopy Study

Glaucoma is associated with increased resistance in the conventional aqueous humor (AH) outflow pathway of the eye. The majority of resistance is thought to reside in the juxtacanalicular connective tissue (JCT) region of the trabecular meshwork and is modulated by the inner wall (IW) endothelial cells of Schlemm’s canal (SC). The IW cells form connections with the underlying JCT cells/matrix, and these connections are thought to modulate outflow resistance. Two ways by which AH crosses the IW endothelium are through: 1) the formation of outpouchings in IW cells called giant vacuoles (GVs) and their intracellular pores (I-pores), and 2) intercellular pores between two adjacent IW cells (B-pores). AH outflow is segmental with areas of high-, low-, and non-flow around the circumference of the eye. To investigate whether changes in cellular connectivity play a role in segmental outflow regulation, we used global imaging, serial block-face scanning electron microscopy (SBF-SEM), and 3D reconstruction to examine individual IW cells from different flow areas of ex vivo perfused normal human donor eyes. Specifically, we investigated the differences in cellular dimensions, connections with JCT cells/matrix, GVs, and pores in SC IW cells between high-, low-, and non-flow areas. Our data showed that: 1) IW cell-JCT cell/matrix connectivity was significantly decreased in the cells in high-flow areas compared to those in low- and non-flow areas; 2) GVs in the cells of high-flow areas had significantly fewer connections beneath them compared to GVs in the cells of low- and non-flow areas; 3) Type IV GVs (with I-pores and basal openings) had significantly fewer connections beneath them compared to Type I GVs (no I-pore or basal opening). Our results suggest that a decreased number of cellular connections between the IW and JCT in high-flow areas is associated with increased numbers of GVs with I-pores and larger Type IV GVs observed in previous studies. Therefore, modulating the number of cellular connections may affect the amount of high-flow area around the eye and thereby modulate AH outflow.
Appropriateness of Antibiotic Prescriptions in Chinese Primary Health Care and the Impact of the COVID-19 Pandemic: A Typically Descriptive and Longitudinal Database Study in Yinchuan City

Background: The appropriateness of antibiotic prescriptions in primary care has not been well evaluated in China in recent years. Furthermore, the impact of coronavirus disease 2019 (COVID-19) on antibiotic prescriptions has not yet been investigated in China. We aimed to assess the appropriateness of antibiotic prescriptions and to evaluate the potential association between the COVID-19 pandemic and antibiotic prescriptions in primary care settings of Yinchuan, a city in China. Methods: This study included 155 primary care institutions and 10,192,713 outpatient visits. Outpatient prescriptions were classified as appropriate, potentially appropriate, inappropriate, or not linked to any diagnosis for antibiotic use following a validated evaluation scheme. Interrupted time-series analyses were performed to assess the effects of the COVID-19 pandemic on antibiotic prescriptions in Chinese primary care facilities. Results: During the study period, 1,287,678 (12.6%, 95% confidence interval [12.6–12.7]) of 10,192,713 outpatient visits in primary care resulted in antibiotic prescriptions. Among 1,287,678 antibiotic prescriptions, 653,335 (50.7% [50.6–50.9]) were inappropriate, 463,081 (36.0% [35.8–36.1]) were potentially appropriate, 171,056 (13.3% [13.1–13.5]) were appropriate, and 206 could not be linked to any diagnosis. Furthermore, patient, physician, and institutional factors were associated with inappropriate antibiotic prescriptions; there was an overall decreasing trend in the proportions of inappropriate antibiotic prescriptions, with the highest level in 2017 (67.1% [66.8–67.5]) and the lowest in 2021 (40.8% [40.3–41.3]). A total of 1,416,120 individual antibiotics were prescribed, of which 1,087,630 (76.8%) were broad-spectrum and 777,672 (54.9%) were classified in the World Health Organization’s “Watch” category. In addition, the COVID-19 pandemic was associated with changes of −2.8% (−4.4 to −1.3) in the level and 0.3% (0.2–0.3) in the monthly trend of antibiotic prescription rates, as well as changes of −5.9% (−10.2 to −1.5) in the level and 1.3% (1.0–1.6) in the monthly trend of the proportions of inappropriate antibiotic prescriptions. Conclusion: More than half of the antibiotic prescriptions were inappropriate during the study period in primary care in Yinchuan. The COVID-19 pandemic may be associated with a decrease in the overall and inappropriate use of antibiotics in primary care settings in China.
Gene Mutations Associated With Clinical Characteristics in the Tumors of Patients With Breast Cancer

Background Clinical characteristics including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 (HER2) are important biomarkers in the treatment of breast cancer, but how genomic mutations affect their status is rarely studied. This study aimed at finding genomic mutations associated with these clinical characteristics. Methods There were 160 patients with breast cancer enrolled in this study. Samples from those patients were used for next-generation sequencing, targeting a panel of 624 pan-cancer genes. Short nucleotide mutations, copy number variations, and gene fusions were identified for each sample. Fisher’s exact test compared each pair of genes. A similarity score was constructed with the resulting P-values. Genes were clustered with the similarity scores. The identified gene clusters were compared to the status of clinical characteristics including ER, PR, HER2, and a family history of cancer (FH) in terms of the mutations in patients. Results Gene-by-gene analysis found that CCND1 mutations were positively correlated with ER status while ERBB2 and CDK12 mutations were positively correlated with HER2 status. Mutation-based clustering identified four gene clusters. Gene cluster 1 (ADGRA2, ZNF703, FGFR1, KAT6A, and POLB) was significantly associated with PR status; gene cluster 2 (COL1A1, AXIN2, ZNF217, GNAS, and BRIP1) and gene cluster 3 (FGF3, FGF4, FGF19, and CCND1) were significantly associated with ER status; gene cluster 2 was also negatively associated with a family history of cancer; and gene cluster 4 was significantly negatively associated with age. Patients were classified into four corresponding groups. Patient groups 1, 2, 3, and 4 had 24.1%, 36.5%, 38.7%, and 41.3% of patients with an FDA-recognized biomarker predictive of response to an FDA-approved drug, respectively. Conclusion This study identified genomic mutations positively associated with ER and PR status. These findings not only revealed candidate genes in ER and PR status maintenance but also provided potential treatment targets for patients with endocrine therapy resistance.
Genetic Polymorphisms in microRNA Genes Targeting PI3K/Akt Signal Pathway Modulate Cervical Cancer Susceptibility in a Chinese Population

Polymorphisms in microRNA (miRNA) genes could influence the expression of miRNAs that regulate the PI3K/Akt signalling pathway and play crucial roles in cancer susceptibility. To investigate the association of single nucleotide polymorphisms (SNPs) in miRNA genes of PI3K/Akt with cervical intraepithelial neoplasia (CIN) and cervical cancer (CC), nine SNPs located in miRNA genes were selected for genotyping, and the association of these SNPs with CIN and CC risk was evaluated. A total of 1,402 participants were enrolled in the current study, including 698 healthy individuals in the control group, 431 patients with CC, and 273 patients with CIN. Nine SNPs in miRNA genes (rs107822 in miR-219a, rs10877887 in let-7i, rs2292832 in miR-149, rs353293 in miR-143, rs3746444 in miR-499, rs3803808 in miR-132, rs4078756 in miR-10b, rs629367 in let-7a, and rs7372209 in miR-26a) were genotyped using MassArray, and the association of these SNPs with CIN and CC were analysed. The results showed that the frequencies of rs107822 in miR-219a and rs2292832 in miR-149 were significantly different between the control and CC groups (p < 0.005). The C allele of rs107822 in miR-219a was associated with an increased risk of CC (OR = 1.29, 95%CI:1.09–1.54) whereas the C allele of rs2292832 in miR-149 was associated with a decreased risk of CC (OR = 0.77, 95%CI:0.64–0.92). The results of inheritance model analysis showed that the best-fit inheritance models for rs107822 and rs2292832 were log-additive. The 2CC + CT genotype of rs107822 could be a risk factor for CC when compared with the TT genotype (OR = 1.28, 95%CI:1.08–1.51). The 2CC + CT genotype of rs2292832 could be a protective factor against CC when compared with the TT genotype (OR = 0.76, 95%CI:0.64–0.92). However, no association of these SNPs with CIN was found in the current study. Our results suggest that rs107822 in the promoter region of miR-219a and rs2292832 in pre-miR-149 region are associated with the risk of CC.
Construction and Evaluation of Recombinant Pseudorabies Virus Expressing African Swine Fever Virus Antigen Genes

African swine fever (ASF) is a highly contact infectious disease caused by the African swine fever virus (ASFV). The extremely complex structure and infection mechanism make it difficult to control the spread of ASFV and develop the vaccine. The ASFV genome is huge with many antigenic genes. Among them, CP204L (p30), CP530R (pp62), E183L (p54), B646L (p72), and EP402R (CD2v) are involved in the process of the virus cycle, with strong immunogenicity and the ability to induce the body to produce neutralizing antibodies. In this study, the recombinant virus rBartha-K61-pASFV that expresses the above ASFV antigen genes was constructed by Red/ET recombineering technology using pseudorabies virus (PRV) vaccine strain Bartha-K61. Western blot analysis showed that the ASFV antigen gene was expressed and the recombinant virus showed good genetic stability and proliferation characteristics in 15 continuous generations on porcine kidney (PK15) cells. The results of immunoassay of piglets and mice showed that rBartha-K61-pASFV had good immunogenicity and could induce higher antibody levels in the body. Therefore, PRV was a promising viral vector for expressing the ASFV antigen gene, and all the experiments in this study laid a foundation for the further development of a new viral vector vaccine of ASFV.
Hypocholesterolemia and Inflammatory Biomarkers Act as Predictors of Severe Vitamin D Deficiency in Patients With Crohn’s Disease: A Clinical Analysis of 862 Patients in China

Background In this study, we enrolled 862 patients with Crohn’s disease (CD) in China to investigate the correlation between serum vitamin D (SVD) and serum lipids, inflammatory biomarkers, and important clinical parameters. Materials and Methods 25(OH)D was measured by LS/MS/MS. Correlation analysis, chi-square tests, and logistic regression analysis were performed to determine the correlations between vitamin D and potential risk factors when vitamin D levels were lower than 10 ng/mL or 20 ng/mL. Results The incidence of severe vitamin D deficiency (SVD < 10 ng/mL) in patients with CD was significantly higher than that in healthy controls (28.9 vs. 9.5%). Multinomial logistic regression analysis showed that penetrating disease [odds ratio (OR) = 2.18], low levels of high-density lipoprotein cholesterol (HDL) (OR = 1.91), high erythrocyte sedimentation rate (OR = 1.73), and platelet count (PLT) (OR = 2.71) were regarded as predictors of severe vitamin D deficiency, while only PLT (OR = 1.90) and HDL (OR = 1.76) were considered as predictors of mild vitamin D deficiency (SVD 10–20 ng/mL). Conclusion Our results confirm a higher incidence of severe vitamin D deficiency in patients with CD in China and show that vitamin D deficiency could result from the combined effects of penetrating disease, inflammation, and low levels of HDL.
Development and Validation of TACE Refractoriness-Related Diagnostic and Prognostic Scores and Characterization of Tumor Microenvironment Infiltration in Hepatocellular Carcinoma

Background Transcatheter arterial chemoembolization LIHC, Liver hepatocellular carcinoma; (TACE) is a valid therapeutic method for hepatocellular carcinoma (HCC). However, many patients respond poorly to TACE, thus leading to an adverse outcome. Therefore, finding new biomarkers for forecasting TACE refractoriness occurrence and prognosis becomes one of the current research priorities in the field of HCC treatment. Materials and Methods Based on microarray datasets and a high-throughput sequencing dataset, the TACE refractoriness–related genes (TRGs) were identified by differential expression analysis. LASSO and Cox regression were applied to construct TACE refractoriness diagnostic score (TRD score) and prognostic score (TRP score) and validated their accuracy in external datasets. Functional correlation of TRP score was analyzed by gene set variation analysis and Gene Ontology. CIBERSORT and IMMUNCELL AI algorithms were performed to understand the correlation between the two scores and immune activity. We further carried out the efficacy analysis of immunotherapy and targeted drugs in the different TRP score groups. Furthermore, a nomogram was built by integrating various independent prognostic factors and validated its effectiveness in different datasets. Results We identified 487 TRGs combined with GSE104580 and TCGA datasets. Then four novel TRGs (TTK, EPO, SLC7A11, and PON1) were screened out to construct TRD score and TRP score models, and both two scores had good predictive ability in external datasets. Tumors with high TRP score show an immunosuppressive phenotype with more infiltrations of regulatory T cells and macrophages. Immunotherapy and chemotherapy response evaluation revealed patients with a high TRP score demonstrated well reactions to immune checkpoint inhibitors (ICIs) and sorafenib. TRP score, TNM stage, and cancer type were brought into the combined nomogram with optimum prediction. Conclusions Our research provided dependable and simplified methods for patients with HCC to assess tumors’ susceptibility to TACE refractoriness and prognosis and guide patients’ clinical therapy choices.