Miracle-dz/UniFAR-FTUs huggingface dataset:
Prognostic Role of CD68+ and CD163+ Tumour-Associated Macrophages and PD-L1 Expression in Oral Squamous Cell Carcinoma: A Meta-Analysis

Background: Oral squamous cell carcinoma (OSCC) is a common malignant cancer in humans. An abundance of tumour associated macrophages (TAMs) create an immunosuppressive tumour microenvironment (TME). TAM markers (CD163 and CD68) are seen to serve as prognostic factors in OSCC. PD-L1 has seen to widely modulate the TME but its prognostic significance remains controversial. The aim of this meta-analysis is to evaluate the prognostic role of CD163+, CD68+ TAMs and PD-L1 in OSCC patients. Methods: Searches in PubMed, Scopus and Web of Science were performed; 12 studies were included in this meta-analysis. Quality assessment of included studies was performed according to REMARK guidelines. Risk of bias across studies was investigated according to the rate of heterogeneity. Meta-analysis was performed to investigate the association of all three biomarkers with overall survival (OS). Results: High expression of CD163+ TAMs were associated with poor overall survival (HR = 2.64; 95% Cl: [1.65, 4.23]; p < 0.0001). Additionally, high stromal expression of CD163+ TAMs correlated with poor overall survival (HR = 3.56; 95% Cl: [2.33, 5.44]; p < 0.00001). Conversely, high CD68 and PD-L1 expression was not associated with overall survival (HR = 1.26; 95% Cl: [0.76, 2.07]; p = 0.37) (HR = 0.64; 95% Cl: [0.35, 1.18]; p = 0.15). Conclusion: In conclusion, our findings indicate CD163+ can provide prognostic utility in OSCC. However, our data suggests CD68+ TAMs were not associated with any prognostic relevance in OSCC patients, whereas PD-L1 expression may prove to be a differential prognostic marker dependent on tumour location and stage of progression.
Utilization of—Omic technologies in cold climate hydrocarbon bioremediation: a text-mining approach

Hydrocarbon spills in cold climates are a prominent and enduring form of anthropogenic contamination. Bioremediation is one of a suite of remediation tools that has emerged as a cost-effective strategy for transforming these contaminants in soil, ideally into less harmful products. However, little is understood about the molecular mechanisms driving these complex, microbially mediated processes. The emergence of −omic technologies has led to a revolution within the sphere of environmental microbiology allowing for the identification and study of so called ‘unculturable’ organisms. In the last decade, −omic technologies have emerged as a powerful tool in filling this gap in our knowledge on the interactions between these organisms and their environment in vivo. Here, we utilize the text mining software Vosviewer to process meta-data and visualize key trends relating to cold climate bioremediation projects. The results of text mining of the literature revealed a shift over time from optimizing bioremediation experiments on the macro/community level to, in more recent years focusing on individual organisms of interest, interactions within the microbiome and the investigation of novel metabolic degradation pathways. This shift in research focus was made possible in large part by the rise of omics studies allowing research to focus not only what organisms/metabolic pathways are present but those which are functional. However, all is not harmonious, as the development of downstream analytical methods and associated processing tools have outpaced sample preparation methods, especially when dealing with the unique challenges posed when analyzing soil-based samples.
Health-promoting behaviors among middle-aged breast cancer survivors compared with matched non-cancer controls: A KNHANES VI-VII (2013–2018) study

This study aimed to compare health-promoting behaviors between middle-aged breast cancer survivors and matched non-cancer controls. We conducted a retrospective, cross-sectional, matched case-control study using data from Korean National Health and Nutrition Examination Surveys (KNHANES) VI-VII (2013–2018) to compare health-promoting behaviors. We selected breast cancer survivors aged 40 to 65 who completed the surveys, and each case was matched with 5 non-cancer controls (1:5) based on propensity scores. With multivariable logistic regression, middle-aged breast cancer survivors were compared with controls in terms of their last screening for a second primary cancer (SPC), current smoking status, alcohol consumption, aerobic physical activity (PA), sedentary time, and self-reported diet control. The final study sample consisted of 117 middle-aged breast cancer survivors and 585 non-cancer controls after propensity score matching (PSM). In the multivariable analysis, middle-aged breast cancer survivors were less likely to consume alcohol (odds ratio [OR] 0.58, 95% confidence interval [CI], 0.35–0.95), more likely to engage in aerobic PA (OR, 1.60; 95% CI, 1.01–2.54), and more likely to self-report diet control (OR, 2.12; 95% CI, 1.27–3.53). There were no significant intergroup differences in SPC screening uptake within 2 years, smoking status, or sedentary times. There is a need to educate middle-aged breast cancer survivors about SPC screening, smoking cessation, and minimizing sedentariness to reduce the risks of associated with breast cancer recurrence, SPCs, and comorbid chronic diseases.
Diversity in the Factors Associated with ADL-Related Disability among Older People in Six Middle-Income Countries: A Cross-Country Comparison

The low- and middle-income countries (LMICs) are experiencing rapid population ageing, yet knowledge about disability among older populations in these countries is scarce. This study aims to identify the prevalence and factors associated with disability among people aged 50 years and over in six LMICs. Cross-sectional data from the World Health Organization (WHO) Study on global AGEing and adult health Wave 1 (2007–2010) in China, Ghana, India, Mexico, the Russian Federation, and South Africa was used. Multivariable logistic regression analyses were undertaken to examine the association between sociodemographic factors, health behaviours, chronic conditions, and activities of daily living (ADL) disability. The prevalence of disability among older adults ranged from 16.2% in China to 55.7% in India. Older age, multimorbidity, and depression were the most common factors related to disability in all six countries. Gender was significant in China (OR = 1.14, 95% CI: 1.01–1.29), Ghana (OR = 1.22, 95% CI: 1.01–1.48) and India (OR = 1.65, 95% CI: 1.37–1.99). Having no access to social capital was significantly associated with ADL disability in China (OR = 2.57, 95% CI: 1.54–4.31) and South Africa (OR = 4.11, 95% CI: 1.79–9.43). Prevalence data is valuable in these six ageing countries, with important evidence on mitigating factors for each. Identifying determinants associated with ADL disability among older people in LMICs can inform how to best implement health prevention programmes considering different country-specific factors.
Application of a selective hospitalization model in the clinical practice of breast surgery

This study aimed to explore the clinical application of a selective hospitalization model in breast disease specialties and to evaluate its effectiveness. Information of patients registered in the selective hospitalization model and those registered in the direct model between October 1, 2020, and October 31, 2022, were collected. The hospitalization days and expenses of patients admitted through distinct modes and divergent medical categories were examined. After completing relevant examinations during the selected hospitalization period, 708 patients were admitted to our medical group for further treatment during the study period. Furthermore, 401 patients underwent hospitalization procedures immediately after the initial visit and received additional treatment after completing pertinent examinations during hospitalization. For patients who underwent benign surgery after admission, there was a significant difference in the length of hospital stay between patients admitted through selective hospitalization and those admitted directly (P < .001); however, there was no significant difference in total hospital expenses (P = .895). For patients who underwent malignant surgery after admission, there were significant differences in the length of hospital stay (P < .001) and total cost of hospitalization (P = .015). There was no significant difference in the length of hospital stay between the 2 groups of patients initially admitted for neoadjuvant chemotherapy (P = .589); however, the total cost of hospitalization significantly differed (P < .001). The selective hospitalization model can reduce medical expenses and the average length of hospital stay. This new hospitalization model is more flexible and allows for the inclusion of outpatient examination costs in subsequent hospitalization medical insurance reimbursement, greatly reducing the financial burden on patients. It is worthy of further exploration, optimization, and promotion.
Crossover point and maximal fat oxidation training effects on blood lipid metabolism in young overweight women: a pilot study

Purpose: To determine the effects of weight reduction schemes using the exercise intensities corresponding to maximal fat oxidation (FATmax) and crossover point (COP). The effects of different intervention protocols on blood lipid metabolism were compared to explore how fat can be consumed and used more efficiently and provide a theoretical basis for weight loss through exercise. Methods: This study included 30 young overweight women randomly divided into the COP, FATmax, and control groups. Participants in the COP and FATmax groups exercised for 45 min four times a week for 8 weeks after the individual treadmill exercise test. The control group did not perform any exercise. Results: After 8 weeks of training, participants in the COP group significantly decreased weight (2.6 ± 3.3 kg), body mass index (0.91 ± 1.26 kg/m2), body fat percentage (1.21% ± 1.50%), and fat mass (1.90 ± 2.30 kg) (p < 0.05). They also had significantly decreased hip circumference (4.8 ± 3.3 cm), serum apolipoprotein B (ApoB) levels (15.48 ± 14.19 mg/dL), and ApoB/apolipoprotein AI (ApoAI) ratios (0.47 ± 0.37) (p < 0.01). However, their serum ApoAI levels were significantly increased (14.18 ± 10.24 mg/dL; p < 0.01). Participants in the FATmax group had significantly decreased hip circumference (2.4 ± 2.0 cm), serum ApoB levels (14.49 ± 11.00 mg/dL), and ApoB/ApoAI ratios (0.59 ± 0.30) (p < 0.01) but significantly increased serum ApoAI levels (29.53 ± 13.29 mg/dL; p < 0.01). No significant changes in physiological indexes were observed in participants in the control group. Conclusion: Personalised exercise intervention positively affected central obesity, effectively improving blood lipid metabolism and fat oxidation, reducing cardiovascular disease risk in young overweight women. COP training improved weight and body composition better than the FATmax exercise, while the latter provided greater improvements in serum ApoAI levels.
Language Experience Predicts Eye Movements During Online Auditory Comprehension

Experience-based theories of language processing suggest that listeners use the properties of their previous linguistic input to constrain comprehension in real time (e.g. MacDonald & Christiansen, 2002; Smith & Levy, 2013; Stanovich & West, 1989; Mishra, Pandey, Singh, & Huettig, 2012). This project investigates the prediction that individual differences in experience will predict differences in sentence comprehension. Participants completed a visual world eye-tracking task following Altmann and Kamide (1999) which manipulates whether the verb licenses the anticipation of a specific referent in the scene (e.g. The boy will eat/move the cake). Within this paradigm, we ask (1) are there reliable individual differences in language-mediated eye movements during this task? If so, (2) do individual differences in language experience correlate with these differences, and (3) can this relationship be explained by other, more general cognitive abilities? Study 1 finds evidence that language experience predicts an overall facilitation in fixating the target, and Study 2 replicates this effect and finds that it remains when controlling for working memory, inhibitory control, phonological ability, and perceptual speed.
modern style in AASTeX 61 SPECTRAL IMAGE CLASSIFICATION WITH DEEP LEARNING

We present the Spectral Image Typer (SPIT), a convolutional neural network (CNN) built to classify spectral images. In contrast to traditional, rules-based algorithms which rely on meta data provided with the image (e.g. header cards), SPIT is trained solely on the image data. We have trained SPIT on 2004 human-classified images taken with the Kast spectrometer at Lick Observatory with types of Bias, Arc, Flat, Science and Standard. We include several pre-processing steps (scaling, trimming) motivated by human practice and also expanded the training set to balance between image type and increase diversity. The algorithm achieved an accuracy of 98.7% on the held-out validation set and an accuracy of 98.7% on the test set of images. We then adopt a slightly modified classification scheme to improve robustness at a modestly reduced cost in accuracy (98.2%). The majority of mis-classifications are Science frames with very faint sources confused with Arc images (e.g. faint emission line galaxies) or Science frames with very bright sources confused with Standard stars. These are errors that even a well-trained human is prone to make. Future work will increase the training set from Kast, will include additional optical and near-IR instruments, and may expand the CNN architecture complexity. We are now incorporating SPIT in the PYPIT data reduction pipeline (DRP) and are willing to facilitate its inclusion in other DRPs.
Research on DTC System with Variable Flux for Switched Reluctance Motor

 Abstract—When switched reluctance motor(SRM) is in the status of the traditional direct torque control(DTC) system, due to the high saturation nonlinearity of the electromagnetic relationships of switched reluctance motors, the torque ripple and the stator phase current are larger. In order to resolve the above problems, through the analysis and deduction for SRM flux model and the influence of characteristics of flux and speed on torque ripple, this paper presents a variable-flux control strategy with the three closed-loop structure based on the critical flux supersaturated speed. And a DTC system of SRM with variable flux and three closed-loop is built up in Matlab/simulink. Moreover, the DSP hardware experiment platform based on the TMS320F2812 is established to validate the performance of the improved algorithm. The simulation and experimental results show that the new scheme has an obvious effect on torque ripple reduction, and the three phase stator current is obviously reduced, which greatly reduces the stator winding copper consumption during the operation of SRM. Moreover, the improved system has good system stability.
Depression symptoms among adolescents in Morocco: a school-based cross-sectional study

Introduction depression in adolescents is a major health condition that can interfere with daily life, lead to suicidal thoughts and behavior, and affect a person throughout life. However, studies about adolescents´ depression in Morocco are scarce. The aim of this study was to determine the prevalence of depression symptoms among in-school adolescents from the region of Settat-Morocco, as well as assessing its relation to daytime sleepiness and poor academic achievement. Methods the researchers conducted a cross-sectional school-based study. The sample included participants aged 12-20 years, in either urban or rural areas. We selected 722 students through a proportionate stratified sampling procedure. The participants responded to multiple questionnaires that included the Patient Health Questionnaire-9, the Epworth Sleepiness Scale, a questionnaire assessing several sociodemographic and socioeconomic variables, and finally an academic achievement questionnaire. We analyzed the collected data using descriptive statistical methods, χ2 test, and odds ratios. Results forty-four point seven percent (44.7%) of the respondents had “moderately severe” to “severe depression symptoms” and 32.5% of the sample suffered from excessive daytime sleepiness. Nineteen point nine percent (19.9%) of the total sample reported having a poor academic achievement. Significant predictors for depression symptoms included “female gender” (OR = 2.06; p-value < 0.001), “having divorced parents” (OR = 6.00; p-value < 0.001), “poor academic achievement” (OR = 5.03; p-value < 0.001), and “excessive daytime sleepiness” (OR = 2.30; p-value = 0.002). Conclusion this study provides important information about Morocco adolescents´ depression symptoms. These findings can help in implementing school-based mental and sleep health programs that target the promotion of mental wellness, prevention of mental health problems, and reduction of adolescent suicide risk.
PUSHOVER ANALYSIS OF PLAN IRREGULAR MASONRY BUILDINGS

The paper investigates the seismic response of plan irregular masonry building structures in order to evaluate the magnitude of torsional coupling and the applicability of 3D pushover analysis for assessing the behavior under earthquakes. As a test example a simple plan asymmetric two-storey masonry building is selected. The nonlinear dynamic response obtained under both several generated records and selected earthquake ground motions is initially compared with the one obtained for a symmetric building variant. Subsequently, the nonlinear dynamic analysis results are compared with the pushover analysis results. The pushover analyses are performed up to the maximum top displacement obtained by the nonlinear dynamic analyses (measured at the mass center), computed for each earthquake record separately. The deflection profiles and damage at the stiff and the flexible building sides are compared with the peak response obtained by nonlinear dynamic analysis.
Machine learning approach for early onset dementia neurobiomarker using EEG network topology features

Introduction Modern neurotechnology research employing state-of-the-art machine learning algorithms within the so-called “AI for social good” domain contributes to improving the well-being of individuals with a disability. Using digital health technologies, home-based self-diagnostics, or cognitive decline managing approaches with neuro-biomarker feedback may be helpful for older adults to remain independent and improve their wellbeing. We report research results on early-onset dementia neuro-biomarkers to scrutinize cognitive-behavioral intervention management and digital non-pharmacological therapies. Methods We present an empirical task in the EEG-based passive brain-computer interface application framework to assess working memory decline for forecasting a mild cognitive impairment. The EEG responses are analyzed in a framework of a network neuroscience technique applied to EEG time series for evaluation and to confirm the initial hypothesis of possible ML application modeling mild cognitive impairment prediction. Results We report findings from a pilot study group in Poland for a cognitive decline prediction. We utilize two emotional working memory tasks by analyzing EEG responses to facial emotions reproduced in short videos. A reminiscent interior image oddball task is also employed to validate the proposed methodology further. Discussion The proposed three experimental tasks in the current pilot study showcase the critical utilization of artificial intelligence for early-onset dementia prognosis in older adults.
Role of FKBP5 and its genetic mutations in stress-induced psychiatric disorders: an opportunity for drug discovery

Stress-induced mental health disorders are affecting many people around the world. However, effective drug therapy for curing psychiatric diseases does not occur sufficiently. Many neurotransmitters, hormones, and mechanisms are essential in regulating the body's stress response. One of the most critical components of the stress response system is the hypothalamus-pituitary-adrenal (HPA) axis. The FKBP prolyl isomerase 51 (FKBP51) protein is one of the main negative regulators of the HPA axis. FKBP51 negatively regulates the cortisol effects (the end product of the HPA axis) by inhibiting the interaction between glucocorticoid receptors (GRs) and cortisol, causing reduced transcription of downstream cortisol molecules. By regulating cortisol effects, the FKBP51 protein can indirectly regulate the sensitivity of the HPA axis to stressors. Previous studies have indicated the influence of FKBP5 gene mutations and epigenetic changes in different psychiatric diseases and drug responses and recommended the FKBP51 protein as a drug target and a biomarker for psychological disorders. In this review, we attempted to discuss the effects of the FKBP5 gene, its mutations on different psychiatric diseases, and drugs affecting the FKBP5 gene.
Interference of the Low-Energy Neutrons on Activation Cross-Section Measurement of the 186W(n, γ)187W Reaction

Abstract Based on analyses of previous experimental methods and results, the cross sections of the 186W(n, γ)187W reaction were measured in the neutron energy range from 0.50 to 1.50 MeV by the activation technique. Neutrons were produced through the T(p,n)3He reaction, and the cross sections of the 197Au(n, γ)198Au reaction were used to determine the absolute neutron flux. Experimental results agreed with the previous time-of-flight measurements but did not agree with the previous activation measurements. Without the tungsten resonance absorption foils, the measured cross sections of the 186W(n, γ)187W reaction by the activation method were shown to be larger than the corrected ones because of the interference of the low-energy neutrons.
Approximation algorithms for guarding holey polygons

Guarding edges of polygons is a version of art gallery problem.The goal is finding the minimum number of guards to cover the edges of a polygon. This problem is NP-hard, and to our knowledge there are approximation algorithms just for simple polygons. In this paper we present two approximation algorithms for guarding polygons with holes. Keywords: guarding, approximation algorithm, vertex guard, edge guard
A Mathematical Model to Investigate the Effects of Ceralasertib and Olaparib in Targeting the Cellular DNA Damage Response Pathway

The ataxia-telangiectasia and Rad3-related (ATR) inhibitor ceralasertib and the poly (ADP-ribose) polymerase (PARP) inhibitor olaparib have shown synergistic activity, in vitro, in the FaDu ATM-knockout cell line. It was found that combining these drugs with lower doses and for shorter treatment periods induced greater or equal toxicity in cancer cells than using either as a single agent. Here, we developed a biologically motivated mathematical model governed by a set of ordinary differential equations, considering the cell cycle–specific interactions of olaparib and ceralasertib. By exploring a range of different possible drug mechanisms, we have studied the effects of their combination as well as which drug interactions are the most prominent. After careful model selection, the model was calibrated and compared with relevant experimental data. We have used this developed model further to investigate other doses of olaparib and ceralasertib in combination, which can be potentially helpful in exploring optimized dosage and delivery. SIGNIFICANCE STATEMENT Drugs that target cellular DNA damage repair pathways are now being used as a new way to maximize the effect of multimodality treatments such as radiotherapy. Here, we develop a mathematical model to investigate the effects of ceralasertib and olaparib, two drugs that target DNA damage response pathways.