Miracle-dz/UniFAR-FTUs huggingface dataset:
Patterns of Domain-Specific Learning Among Medical Undergraduate Students in Relation to Confidence in Their Physiology Knowledge: Insights From a Pre–post Study

Research Focus The promotion of domain-specific knowledge is a central goal of higher education and, in the field of medicine, it is particularly essential to promote global health. Domain-specific knowledge on its own is not exhaustive; confidence regarding the factual truth of this knowledge content is also required. An increase in both knowledge and confidence is considered a necessary prerequisite for making professional decisions in the clinical context. Especially the knowledge of human physiology is fundamental and simultaneously critical to medical decision-making. However, numerous studies have shown difficulties in understanding and misconceptions in this area of knowledge. Therefore, we investigate (i) how preclinical medical students acquire knowledge in physiology over the course of their studies and simultaneously gain confidence in the correctness of this knowledge as well as (ii) the interrelations between these variables, and (iii) how they affect the development of domain-specific knowledge. Method In a pre–post study, 169 medical students’ development of physiology knowledge and their confidence related to this knowledge were assessed via paper-pencil questionnaires before and after attending physiology seminars for one semester. Data from a longitudinal sample of n = 97 students were analyzed using mean comparisons, regression analyses, and latent class analyses (LCAs). In addition, four types of item responses were formed based on confidence and correctness in the knowledge test. Results We found a significant and large increase in the students’ physiology knowledge, with task-related confidence being the strongest predictor (apart from learning motivation). Moreover, a significantly higher level of confidence at t2 was confirmed, with the level of prior confidence being a strong predictor (apart from knowledge at t2). Furthermore, based on the students’ development of knowledge and confidence levels between measurement points, three empirically distinct groups were distinguished: knowledge gainers, confidence gainers, and overall gainers. The students whose confidence in incorrect knowledge increased constituted one particularly striking group. Therefore, the training of both knowledge and the ability to critically reflect on one’s knowledge and skills as well as an assessment of their development in education is required, especially in professions such as medicine, where knowledge-based decisions made with confidence are of vital importance.
Protective Effect of Maternal First-Trimester Low Body Mass Index Against Macrosomia: A 10-Year Cross-Sectional Study

Objective We aimed to assess whether maternal first-trimester low body mass index (BMI) has a protective effect against macrosomia. Methods This was a cross-sectional study from January 1, 2011, to June 30, 2021, and 84,900 participants were included. The predictive performance of maternal first-trimester and parental pre-pregnancy BMI for macrosomia was assessed using the area under the receiver-operating characteristics curve (AUC). Multivariate logistic regression analyses were performed to evaluate the independent effect of maternal first-trimester low BMI on macrosomia. Interactions were investigated to evaluate the potential variation of the effect of first-trimester low BMI across different groups. Furthermore, interactions were also examined across groups determined by multiple factors jointly: a) gestational diabetes mellitus (GDM)/GDM history status, parity, and maternal age; and b) GDM/GDM history status, fetal sex, and season of delivery. Results The proportion of macrosomia was 6.14% (5,215 of 84,900). Maternal first-trimester BMI showed the best discrimination of macrosomia (all Delong tests: P < 0.001). The protective effect of maternal first-trimester low BMI against macrosomia remained significant after adjusting for all confounders of this study [adjusted odds ratios (aOR) = 0.37, 95% CI: 0.32–0.43]. Maternal first-trimester low BMI was inversely associated with macrosomia, irrespective of parity, fetal sex, season of delivery, maternal age, and GDM/GDM history status. The protective effect was most pronounced among pregnant women without GDM/GDM history aged 25 to 29 years old, irrespective of parity (multipara: aOR = 0.32, 95% CI: 0.22–0.47; nullipara: aOR = 0.32, 95% CI: 0.24–0.43). In multipara with GDM/GDM history, the protective effect of low BMI was only observed in the 30- to 34-year-old group (aOR = 0.12, 95% CI: 0.02–0.86). For pregnant women without GDM/GDM history, the protective effect of maternal first-trimester low BMI against macrosomia was the weakest in infants born in winter, irrespective of fetal sex (female: aOR = 0.45, 95% CI: 0.29–0.69; male: aOR = 0.39, 95% CI: 0.28–0.55). Conclusion Maternal first-trimester low BMI was inversely associated with macrosomia, and the protective effect was most pronounced among 25- to 29-year-old pregnant women without GDM/GDM history and was only found among 30- to 34-year-old multipara with GDM/GDM history. The protective effect of maternal first-trimester low BMI against macrosomia was the weakest in winter among mothers without GDM/GDM history.
Green Bond Index Prediction Based on CEEMDAN-LSTM

Green bonds, which are designed to finance for environment-friendly or sustainable projects, have attracted more and more investors’ attention. However, the study in this field is still relatively limited, especially in forecasting the market’s future trends. In this paper, a hybrid model combining CEEMDAN and LSTM is introduced to predict green bond market in China (represented by CUFE-CNI High Grade Green Bond Index). In order to evaluate the performance of our model, we also use EMD to decompose the green bond index. Our empirical result suggests that, compared with EMD-LSTM and LSTM models, CEEMDAN-LSTM is the most accurate model in green bond index forecasting. Meanwhile, we find that indices from the crude oil market and green stock market are both effective predictors, which also provides ground on the correlations between the green bond market and other financial markets.
Individual Sensory Modality Dominance as an Influential Factor in the Prefrontal Neurofeedback Training for Spatial Processing: A Functional Near-Infrared Spectroscopy Study

Neurofeedback is a neuromodulation technique used to improve brain function by self-regulating brain activity. However, the efficacy of neurofeedback training varies widely between individuals, and some participants fail to self-regulate brain activity. To overcome intersubject variation in neurofeedback training efficacy, it is critical to identify the factors that influence this type of neuromodulation. In this study, we considered that individual differences in cognitive ability may influence neurofeedback training efficacy and aimed to clarify the effect of individual working memory (WM) abilities, as characterized by sensory modality dominance, on neurofeedback training efficacy in healthy young adults. In particular, we focused on the abilities of individuals to retain internal (tactile or somatosensory) or external (visual) body information in their WM. Forty participants performed functional near-infrared spectroscopy-based neurofeedback training aimed at producing efficient and lower-level activity in the bilateral dorsolateral prefrontal cortex and frontopolar cortex. We carried out a randomized, sham-controlled, double-blind study that compared WM ability before and after neurofeedback training. Individual WM ability was quantified using a target searching task that required the participants to retain spatial information presented as vibrotactile or visual stimuli. Participants who received feedback information based on their own prefrontal activity showed gradually decreasing activity in the right prefrontal area during the neurofeedback training and demonstrated superior WM ability during the target searching task with vibrotactile stimuli compared with the participants who performed dummy neurofeedback training. In comparison, left prefrontal activity was not influenced by the neurofeedback training. Furthermore, the efficacy of neurofeedback training (i.e., lower right prefrontal activity and better searching task performance) was higher in participants who exhibited tactile dominance rather than visual dominance in their WM. These findings indicate that sensory modality dominance in WM may be an influential neurophysiological factor in determining the efficacy of neurofeedback training. These results may be useful in the development of neurofeedback training protocols tailored to individual needs.
Association Between CD4/CD8 Ratio Recovery and Chronic Kidney Disease Among Human Immunodeficiency Virus-Infected Patients Receiving Antiretroviral Therapy: A 17-Year Observational Cohort Study

Background: CD4/CD8 ratio is considered as an emerging biomarker for human immunodeficiency virus (HIV)-related diseases. However, the relationship of CD4/CD8 ratio recovery and chronic kidney disease (CKD), and whether cumulative antiretroviral therapy (ART) is effective in the CD4/CD8 ratio recovery and in reducing CKD incidence among HIV patients remain unclear. Methods A 17-year observational cohort study was conducted on all HIV-infected patients receiving ART in Guangxi, China. Kaplan–Meier analysis was used to investigate the cumulative CKD incidence. Cox regression and propensity score matching (PSM) were used to evaluate the association between CD4/CD8 ratio recovery and CKD incidence, and the effect of ART regimens on CD4/CD8 ratio recovery and CKD incidence. Results A total of 59,268 eligible individuals contributing 285,143 person-years of follow-up, with an overall CKD incidence of 9.65%. After ART, patients who developed CKD showed higher mortality than those with normal kidney function (12.48 vs. 7.57%, p < 0.001). Patients whose CD4/CD8 ratio did not recover to 0.7 had a higher CKD incidence than the patients who recovered (aHR = 2.84, 95% CI 2.63–3.07), similar to the PSM analysis (aHR = 3.13, 95% CI 2.85–3.45). Compared with the PI-based and INSTI-based regimens, NNRTI-based regimen had a better CD4/CD8 ratio recovery rate (27.04, 16.16, and 29.66%, respectively) and a lower CKD incidence (17.43, 16.16, and 7.31%, respectively). Conclusion This large-scale real-world setting provide new evidence that the CD4/CD8 ratio recovery is associated with lower CKD incidence in HIV-infected patients receiving ART. NNRTI-based is a better choice for CD4/CD8 ratio recovery and reducing the risk of CKD.
Using the Model, Lead, and Test Technique and “GoTalk NOW” App to Teach Children With Intellectual and Developmental Delays to Correctly Request

Augmentative and alternative communication systems have been successfully used to help pupils with intellectual and developmental disabilities for functional communication skills. Whereas the effects of the GoTalk NOW application (app) available on the iPad have been investigated, no such study has been conducted in Saudi Arabia. This study investigated the effects of the “model, lead, and test” (MLT) technique paired with the GoTalk NOW app, which is used to teach four children with intellectual and developmental delays to correctly request. The participants were four children (three boys and one girl) from 6 to 8 years of age with intellectual and developmental disabilities. A multiple baseline design was implemented across all participants. All four participants made clear progress using the GoTalk NOW app on the iPad, and implementation of the MLT technique was successful in helping the participants request correctly and independently. This study provided a practical, effective, and easy-to-use method for special education teachers to teach children with disabilities. It contributes to expand the range of teaching options for children with intellectual and developmental disabilities.
Enhancing Performance of Breast Ultrasound in Opportunistic Screening Women by a Deep Learning-Based System: A Multicenter Prospective Study

Purpose To validate the feasibility of S-Detect, an ultrasound computer-aided diagnosis (CAD) system using deep learning, in enhancing the diagnostic performance of breast ultrasound (US) for patients with opportunistic screening-detected breast lesions. Methods Nine medical centers throughout China participated in this prospective study. Asymptomatic patients with US-detected breast masses were enrolled and received conventional US, S-Detect, and strain elastography subsequently. The final pathological results are referred to as the gold standard for classifying breast mass. The diagnostic performances of the three methods and the combination of S-Detect and elastography were evaluated and compared, including sensitivity, specificity, and area under the receiver operating characteristics (AUC) curve. We also compared the diagnostic performances of S-Detect among different study sites. Results A total of 757 patients were enrolled, including 460 benign and 297 malignant cases. S-Detect exhibited significantly higher AUC and specificity than conventional US (AUC, S-Detect 0.83 [0.80–0.85] vs. US 0.74 [0.70–0.77], p < 0.0001; specificity, S-Detect 74.35% [70.10%–78.28%] vs. US 54.13% [51.42%–60.29%], p < 0.0001), with no decrease in sensitivity. In comparison to that of S-Detect alone, the AUC value significantly was enhanced after combining elastography and S-Detect (0.87 [0.84–0.90]), without compromising specificity (73.93% [68.60%–78.78%]). Significant differences in the S-Detect’s performance were also observed across different study sites (AUC of S-Detect in Groups 1–4: 0.89 [0.84–0.93], 0.84 [0.77–0.89], 0.85 [0.76–0.92], 0.75 [0.69–0.80]; p [1 vs. 4] < 0.0001, p [2 vs. 4] = 0.0165, p [3 vs. 4] = 0.0157). Conclusions Compared with the conventional US, S-Detect presented higher overall accuracy and specificity. After S-Detect and strain elastography were combined, the performance could be further enhanced. The performances of S-Detect also varied among different centers.
Glycoprotein 96 in Peritoneal Dialysis Effluent-Derived Extracellular Vesicles: A Tool for Evaluating Peritoneal Transport Properties and Inflammatory Status

Background Extracellular vesicles (EVs) from peritoneal dialysis effluent (PDE), containing molecules such as proteins and microRNAs (miRNAs), may be potential biological markers to monitor peritoneal function or injury. Peritoneal inflammation is an important determinant of peritoneal solute transport rate (PSTR). Thus, the aim of this study is to determine whether the specific proteins capable of evaluating the PSTR could be found in PDE-EVs, and explore the underlying mechanism for the association between PSTR and peritoneal inflammation. Methods Sixty patients undergoing peritoneal dialysis (PD) were divided into two groups: high/high average transport (H/A) group (PET >0.65) and low/low average transport (L/A) group (PET <0.65). EVs derived from PDE (PDE-EVs) were isolated by ultracentrifugation. Proteomic analysis was performed to explore the differentially expressed proteins and identify the potential biomarkers in PDE-EVs from the two groups, and we focused on glycoprotein 96 (GP96) as it could be involved in the inflammatory process. The expression of GP96 in PDE-EVs and inflammatory cytokines was quantified by real-time PCR and enzyme-linked immunosorbent assay. The infiltration of macrophages and neutrophils into the peritoneum was detected using immunohistochemistry in a PD rat model. Results The expression of PDE-EVs-GP96 was significantly higher in the H/A group, and was positively correlated with the PSTR and the level of the inflammatory factor interleukin (IL)-6. GP96-enriched EVs enhanced the secretion of proinflammatory cytokines IL-1β, IL-6, tumor necrosis factor (TNF)-α, and IL-8 in macrophages, which was reversed by a pharmacological GP96-specific inhibitor (PU-WS13). The GP96 inhibitor also reduced local peritoneal inflammation by decreasing the infiltration of inflammatory cells and levels of proinflammatory cytokines (IL-6 and TNF-α) and chemokines (CCL2, CXCL1, and CXCL2) in a PD rat model. Conclusions PDE-EVs-GP96 is a new promising tool to evaluate the status of peritoneal inflammation and PSTR, and the mechanism may be related to affecting the inflammatory properties of macrophages.
Dissecting Breeders’ Sense via Explainable Machine Learning Approach: Application to Fruit Peelability and Hardness in Citrus

“Genomics-assisted breeding”, which utilizes genomics-based methods, e.g., genome-wide association study (GWAS) and genomic selection (GS), has been attracting attention, especially in the field of fruit breeding. Low-cost genotyping technologies that support genome-assisted breeding have already been established. However, efficient collection of large amounts of high-quality phenotypic data is essential for the success of such breeding. Most of the fruit quality traits have been sensorily and visually evaluated by professional breeders. However, the fruit morphological features that serve as the basis for such sensory and visual judgments are unclear. This makes it difficult to collect efficient phenotypic data on fruit quality traits using image analysis. In this study, we developed a method to automatically measure the morphological features of citrus fruits by the image analysis of cross-sectional images of citrus fruits. We applied explainable machine learning methods and Bayesian networks to determine the relationship between fruit morphological features and two sensorily evaluated fruit quality traits: easiness of peeling (Peeling) and fruit hardness (FruH). In each of all the methods applied in this study, the degradation area of the central core of the fruit was significantly and directly associated with both Peeling and FruH, while the seed area was significantly and directly related to FruH alone. The degradation area of albedo and the area of flavedo were also significantly and directly related to Peeling and FruH, respectively, except in one or two methods. These results suggest that an approach that combines explainable machine learning methods, Bayesian networks, and image analysis can be effective in dissecting the experienced sense of a breeder. In breeding programs, collecting fruit images and efficiently measuring and documenting fruit morphological features that are related to fruit quality traits may increase the size of data for the analysis and improvement of the accuracy of GWAS and GS on the quality traits of the citrus fruits.
Purification, Characterization, and Hydrolysate Analysis of Dextranase From Arthrobacter oxydans G6-4B

Dextran has aroused increasingly more attention as the primary pollutant in sucrose production and storage. Although enzymatic hydrolysis is more efficient and environmentally friendly than physical methods, the utilization of dextranase in the sugar industry is restricted by the mismatch of reaction conditions and heterogeneity of hydrolysis products. In this research, a dextranase from Arthrobacter oxydans G6-4B was purified and characterized. Through anion exchange chromatography, dextranase was successfully purified up to 32.25-fold with a specific activity of 288.62 U/mg protein and a Mw of 71.12 kDa. The optimum reaction conditions were 55°C and pH 7.5, and it remained relatively stable in the range of pH 7.0–9.0 and below 60°C, while significantly inhibited by metal ions, such as Ni+, Cu2+, Zn2+, Fe3+, and Co2+. Noteworthily, a distinction of previous studies was that the hydrolysates of dextran were basically isomalto-triose (more than 73%) without glucose, and the type of hydrolysates tended to be relatively stable in 30 min; dextranase activity showed a great influence on hydrolysate. In conclusion, given the superior thermal stability and simplicity of hydrolysates, the dextranase in this study presented great potential in the sugar industry to remove dextran and obtain isomalto-triose.
A Physiologically Based Pharmacokinetic Model for Studying the Biowaiver Risk of Biopharmaceutics Classification System Class I Drugs With Rapid Elimination: Dexketoprofen Trometamol Case Study

Biowaiver based on the biopharmaceutics classification system (BCS) has been widely used in the global market for the approval of new generic drug products to avoid unnecessary in vivo bioequivalence (BE) studies. However, it is reported that three out of four formulations of dexketoprofen trometamol (DEX) tablets (BCS class I drug) failed the first BE study. The aim of this study was to determine whether the current biowaiver standard is reasonable for DEX. Thus, we successfully established a physiologically based pharmacokinetic (PBPK) model for DEX and examined the effects of dissolution, permeability, and gastric emptying time on DEX absorption under BCS-based biowaiver conditions using sensitivity analyses. Parameter sensitivity analysis showed that the dissolution rate in pH 1.2 media, permeability, and liquid gastric emptying time were sensitive parameters of Cmax. Therefore, gastric emptying variation was introduced into the PBPK model, and virtual BE studys were conducted on original research formulation and the formulation of the boundary dissolution rate (f2 = 50) prescribed by the biowaiver guideline. The virtual BE results showed dissolution rate changes within the biowaiver range will not cause high non-BE ratio, indicate waive of DEX generic drugs would not lead the risk of Cmax when generic products satisfy the requirements of biowaiver guideline. However, the effect of excipients on gastric emptying as a sensitive factor needs to be further studied when the rapid elimination of BCS class I drug is biowaived.
Tumor-Infiltrating Myeloid Cells Co-Express TREM1 and TREM2 and Elevated TREM-1 Associates With Disease Progression in Renal Cell Carcinoma

Myeloid-derived suppressor cells (MDSC) and tumor-associated macrophages (TAM) contribute to cancer-related inflammation and tumor progression. While several myeloid molecules have been ascribed a regulatory function in these processes, the triggering receptors expressed on myeloid cells (TREMs) have emerged as potent modulators of the innate immune response. While various TREMs amplify inflammation, others dampen it and are emerging as important players in modulating tumor progression—for instance, soluble TREM-1 (sTREM-1), which is detected during inflammation, associates with disease progression, while TREM-2 expression is associated with tumor-promoting macrophages. We hypothesized that TREM-1 and TREM-2 might be co-expressed on tumor-infiltrating myeloid cells and that elevated sTREM-1 associates with disease outcomes, thus representing a possibility for mutual modulation in cancer. Using the 4T1 breast cancer model, we found TREM-1 and TREM-2 expression on MDSC and TAM and that sTREM-1 was elevated in tumor-bearing mice in multiple models and correlated with tumor volume. While TREM-1 engagement enhanced TNF, a TREM-2 ligand was detected on MDSC and TAM, suggesting that both TREM could be functional in the tumor setting. Similarly, we detected TREM-1 and Trem2 expression in myeloid cells in the RENCA model of renal cell carcinoma (RCC). We confirmed these findings in human disease by demonstrating the expression of TREM-1 on tumor-infiltrating myeloid cells from patients with RCC and finding that sTREM-1 was increased in patients with RCC. Finally, The Cancer Genome Atlas analysis shows that TREM1 expression in tumors correlates with poor outcomes in RCC. Taken together, our data suggest that manipulation of the TREM-1/TREM-2 balance in tumors may be a novel means to modulate tumor-infiltrating myeloid cell phenotype and function.