Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative efficacy of remotely delivered mindfulness-based eating awareness training versus behavioral-weight loss counseling during COVID-19

Introduction Dysregulated eating (emotional eating, cue-elicited eating, and dietary restraint and restriction) has been linked to being overweight or obese. The present investigation used a random controlled trial (RCT) to test the differential efficacy of remotely delivered Mindfulness-Based Eating Awareness Training (MB-EAT) and Behavioral Weight Loss (BWL) counseling. Methods The sample was recruited through advertisements that offered help to people “with problems controlling their eating” or “interested in improving their relationship with food” (n = 135). Results Retention was low in both groups (42%), but not dissimilar to retention rates reported in related clinical trials delivered “in person. ” Among the participants who completed treatment, we found no between-group differences in any of the treatment outcomes, but participants in both groups experienced significant increases in eating-related mindfulness [Mindful Eating Questionnaire (MEQ) and awareness [Multidimensional Assessment of Interoceptive Awareness (MAIA), and significant decreases in unhealthy eating patterns [Dutch Eating Behavior Questionnaire (DEBQ); Binge Eating Scale (BES), and weight over the course of treatment. Participants in both groups also experienced increases in self-reported depression and anxiety symptoms [Hospital Anxiety and Depression Scale (HADS)], although these increases likely reflected normative changes observed in the population at large during COVID-19. Discussion Overall, the results suggest that dysregulated eating and weight loss intervention delivered remotely via teleconference can be effective.
Functional limitation as a mediator of the relationship between multimorbidity on health-related quality of life in Australia: evidence from a national panel mediation analysis

Objective The inverse relationships between chronic disease multimorbidity and health-related quality of life (HRQoL) have been well-documented in the literature. However, the mechanism underlying this relationship remains largely unknown. This is the first study to look into the potential role of functional limitation as a mediator in the relationship between multimorbidity and HRQoL. Methods This study utilized three recent waves of nationally representative longitudinal Household, Income, and Labor Dynamics in Australia (HILDA) surveys from 2009 to 2017 (n = 6,814). A panel mediation analysis was performed to assess the role of functional limitation as a mediator in the relationship between multimorbidity and HRQoL. The natural direct effect (NDE), indirect effect (NIE), marginal total effect (MTE), and percentage mediated were used to calculate the levels of the mediation effect. Results This study found that functional limitation is a significant mediator in the relationship between multimorbidity and HRQoL. In the logistic regression analysis, the negative impact of multimorbidity on HRQoL was reduced after functional limitation was included in the regression model. In the panel mediation analysis, our results suggested that functional limitation mediated ~27.2% (p < 0.05) of the link between multimorbidity and the composite SF-36 score for HRQoL. Functional limitation also mediated the relationship between the number of chronic conditions and HRQoL for each of the eight SF-36 dimensions, with a proportion mediated ranging from 18.4 to 28.8% (p < 0.05). Conclusion Functional status has a significant impact on HRQoL in multimorbid patients. Treatment should concentrate on interventions that improve patients' functioning and mitigate the negative effects of multimorbidity.
The effects of green space and physical activity on muscle strength: a national cross-sectional survey with 128,759 Chinese adults

Background Muscle strength is closely related to chronic noncommunicable diseases; specifically, a decline in handgrip strength (HS) is predominant globally. Exposure to green space—built environment components used for health intervention—reportedly decreases the risk of certain diseases and all-cause mortality. However, evidence in this area is limited. Objective We aimed to explore the association between green space exposure and muscle strength and ascertain the combined effect of physical activity and green space exposure on muscle strength. Method Data from 128,759 participants (aged 20–79 years) were obtained using a complex stratified multistage probability cluster sampling design. The green space was assessed as normalized difference vegetation index (NDVI) data for a 500-m buffer zone based on the geolocation information of sampling sites. We used a questionnaire to investigate transportation, occupation, physical activity, leisure-time exercise behaviors, and sedentary time within a usual week of the preceding year. The outcome was low relative HS, defined as HS-to-body weight ratio, and the percentage of men and women with relative HS in the lower third. We defined adequate physical activity as 150 min of moderate-intensity or 75 min of vigorous physical activity per week and calculated the weighted proportion of participants with insufficient physical activity. Categorical variables of NDVI and physical activity were used as exposure variables and their interrelationship was evaluated in a generalized linear mixed model (GLMM) to estimate the odds ratios (ORs) and 95% confidence intervals (95% CI). We measured interaction on an additive or multiplicative scale using a GLMM to test the interaction between green space exposure and physical activity. All analyses were performed for the total sample and subgroups (urban and rural). Result The high NDVI group had a lower risk of low relative HS than the low NDVI group (OR [95% CI]: 0.92 [0.88–0.95]). The sufficient physical activity group had a lower risk of low relative HS than the insufficient physical activity group (OR [95% CI]: 0.85 [0.81–0.88]). There was an interactive effect on the additive scale (relative excess risk owing to interaction: 0.29, 95% CI 0.22–0.36, p < 0.001) between green space exposure and physical activity. Conclusion High NDVI and adequate physical activity were protective factors against low relative HS in Chinese adults. Increasing green space exposure and physical activity together may have a greater potentiating effect on muscle strength improvement than these two protective factors individually. Green spaces should be incorporated into city design or built environments.
Impact of meteorological conditions, canopy shading and leaf removal on yield, must quality, and norisoprenoid compounds content in Franciacorta sparkling wine

Climate change is a major concern in agriculture; in grapevine production, climate change can affect yield and wine quality as they depend on the complex interactions between weather, plant material, and viticultural techniques. Wine characteristics are strongly influenced by microclimate of the canopy affecting primary and secondary metabolites of the grapevine. Air temperature and water availability can influence sugar and acid concentration in grapes and relative wines, and their content of volatile compounds such as norisoprenoids. This becomes relevant in sparkling wine production where grapes are generally harvested at a relatively low pH, high acidity, and low sugar content and where the norisoprenoids significantly contributes to the final aroma of the wine. The effect of climate change on grapevine and wine, therefore, calls for the implementation of on-field adaptation strategies. Among them canopy management through leaf removal and shading have been largely investigated in the wine growing sector. The present study, conducted over 4 years (2010-2013) aims at investigating how leaf removal and artificial shading strategies affect grape maturation, must quality and the production of norisoprenoids, analyzed using an untargeted approach, in sparkling wine. Specifically, this paper investigates the effect of meteorological conditions (i.e., water availability and temperatures) and the effect of leaf removal and shading on Vitis vinifera L. cv. Chardonnay and Pinot noir, which are suitable to produce sparkling wine in the DOCG Franciacorta wine growing area (Lombardy, Italy). The effect of leaf removal and shading practices on norisoprenoids has been the focus of the study. No defoliation and artificial shading treatments play an important role in the preservation of the acidity in warm seasons and this suggests calibrating defoliation activities in relation to the meteorological trend without standardized procedures. This is particularly relevant in the case of sparkling wine, where the acidity is essential to determine wine quality. The enhanced norisoprenoid aromas obtained with a total defoliation represent a further element to direct defoliation and shading strategies. The obtained results increase knowledge about the effect of different defoliation and artificial shading applications in relation to meteorological condition supporting the management decision-making in the Franciacorta wine growing area.
Coarse spatial resolution remote sensing data with AVHRR and MODIS miss the greening area compared with the Landsat data in Chinese drylands

The warming-wetting climates in Chinese drylands, together with a series of ecological engineering projects, had caused apparent changes to vegetation therein. Regarding the vegetation greening trend, different remote sensing data had yielded distinct findings. It was critical to evaluate vegetation dynamics in Chinese drylands using a series of remote sensing data. By comparing the three most commonly used remote sensing datasets [i.e., MODIS, Advanced Very High Resolution Radiometer (AVHRR), and Landsat], this study comprehensively investigated vegetation dynamics for Chinse drylands. All three remote sensing datasets exhibited evident vegetation greening trends from 2000 to 2020 in Chinese drylands, especially in the Loess Plateau and Northeast China. However, Landsat identified the largest greening areas (89.8%), while AVHRR identified the smallest greening area (58%). The vegetation greening areas identified by Landsat comprise more small patches than those identified by MODIS and AVHRR. The MODIS data exhibited a higher consistency with Landsat than with AVHRR in terms of detecting vegetation greening areas. The three datasets exhibited high consistency in identifying vegetation greening in Northeast China, Loess Plateau, and Xinjiang. The percentage of inconsistent areas among the three datasets was 39.56%. The vegetation greening areas identified by Landsat comprised more small patches. Sensors and the atmospheric effect are the two main reasons responsible for the different outputs from each NDVI product. Ecological engineering projects had a great promotion effect on vegetation greening, which can be detected by the three NDVI datasets in Chinese drylands, thereby combating desertification and reducing dust storms.
The human neurosecretome: extracellular vesicles and particles (EVPs) of the brain for intercellular communication, therapy, and liquid-biopsy applications

Emerging evidence suggests that brain derived extracellular vesicles (EVs) and particles (EPs) can cross blood-brain barrier and mediate communication among neurons, astrocytes, microglial, and other cells of the central nervous system (CNS). Yet, a complete understanding of the molecular landscape and function of circulating EVs & EPs (EVPs) remain a major gap in knowledge. This is mainly due to the lack of technologies to isolate and separate all EVPs of heterogeneous dimensions and low buoyant density. In this review, we aim to provide a comprehensive understanding of the neurosecretome, including the extracellular vesicles that carry the molecular signature of the brain in both its microenvironment and the systemic circulation. We discuss the biogenesis of EVPs, their function, cell-to-cell communication, past and emerging isolation technologies, therapeutics, and liquid-biopsy applications. It is important to highlight that the landscape of EVPs is in a constant state of evolution; hence, we not only discuss the past literature and current landscape of the EVPs, but we also speculate as to how novel EVPs may contribute to the etiology of addiction, depression, psychiatric, neurodegenerative diseases, and aid in the real time monitoring of the “living brain”. Overall, the neurosecretome is a concept we introduce here to embody the compendium of circulating particles of the brain for their function and disease pathogenesis. Finally, for the purpose of inclusion of all extracellular particles, we have used the term EVPs as defined by the International Society of Extracellular Vesicles (ISEV).
Bioinformatics and Raman spectroscopy-based identification of key pathways and genes enabling differentiation between acute myeloid leukemia and T cell acute lymphoblastic leukemia

Acute myeloid leukemia (AML) and T cell acute lymphoblastic leukemia (T-ALL) are two of the most prevalent hematological malignancies diagnosed among adult leukemia patients, with both being difficult to treat and associated with high rates of recurrence and mortality. In the present study, bioinformatics approaches were used to analyze both of these types of leukemia in an effort to identify characteristic gene expression patterns that were subsequently validated via Raman spectroscopy. For these analyses, four Gene Expression Omnibus datasets (GSE13204, GSE51082, GSE89565, and GSE131184) pertaining to acute leukemia were downloaded, and differentially expressed genes (DEGs) were then identified through comparisons of AML and T-ALL patient samples using the R Bioconductor package. Shared DEGs were then subjected to Gene Ontology (GO) enrichment analyses and were used to establish a protein-protein interaction (PPI) network analysis. In total, 43 and 129 upregulated and downregulated DEGs were respectively identified. Enrichment analyses indicated that these DEGs were closely tied to immune function, collagen synthesis and decomposition, inflammation, the synthesis and decomposition of lipopolysaccharide, and antigen presentation. PPI network module clustering analyses further led to the identification of the top 10 significantly upregulated and downregulated genes associated with disease incidence. These key genes were then validated in patient samples via Raman spectroscopy, ultimately confirming the value of these genes as tools that may aid the differential diagnosis and treatment of AML and T-ALL. Overall, these results thus highlight a range of novel pathways and genes that are linked to the incidence and progression of AML and T-ALL, providing a list of important diagnostic and prognostic molecular markers that have the potential to aid in the clinical diagnosis and treatment of these devastating malignancies.
Middle and high school girls’ attitude to science, technology, engineering, and mathematics career interest across grade levels and school types

The aim of this study is to examine Kazakh female students’ interest in STEM professions. A convenient sampling method was used to determine the participants from 10 girls’ schools in Almaty city in Kazakhstan. 522 girls from grades 7th to 11th provided answers to the “STEM Career Interest Survey” which was administered online. Collected data was analyzed to see how girls’ STEM carries interest change according to the type of school and grade level, along with locating the correlations between their interests and their end-term marks in each STEM subject. MANOVA analysis showed that girls’ career interests in different STEM subjects are changing for different school levels across types of schools. Through ANOVA analysis we showed that only girls’ math interest significantly changed across school levels. Post-hoc analyses indicated that seventh level students’ interest in math was statistically higher than eighth and ninth level students. For the school type variable, ANOVA analysis showed that only girls’ technology and engineering interests were significantly different across school types. In other words, girls in Nazarbayev Intellectual Schools (NIS) were significantly more interested in technology and engineering careers than public school girls while for science and mathematics there was no difference between the two types of schools. Additionally, at the 8th and 11th school levels NIS girls have a higher interest in science while at the 10th level public school girls have higher scores. Finally, we detected significant correlations of modest amplitude between girls’ STEM were analyzed rest and their achievement in physics, math, chemistry, and biology. This study will allow supporting teachers and school administrators in their efforts to encourage girls to pursue STEM studies and careers, and we hope it will also help researchers to orient their efforts in providing them with fertile and durable solutions.
Classification of gait phases based on a machine learning approach using muscle synergy

The accurate detection of the gait phase is crucial for monitoring and diagnosing neurological and musculoskeletal disorders and for the precise control of lower limb assistive devices. In studying locomotion mode identification and rehabilitation of neurological disorders, the concept of modular organization, which involves the co-activation of muscle groups to generate various motor behaviors, has proven to be useful. This study aimed to investigate whether muscle synergy features could provide a more accurate and robust classification of gait events compared to traditional features such as time-domain and wavelet features. For this purpose, eight healthy individuals participated in this study, and wireless electromyography sensors were attached to four muscles in each lower extremity to measure electromyography (EMG) signals during walking. EMG signals were segmented and labeled as 2-class (stance and swing) and 3-class (weight acceptance, single limb support, and limb advancement) gait phases. Non-negative matrix factorization (NNMF) was used to identify specific muscle groups that contribute to gait and to provide an analysis of the functional organization of the movement system. Gait phases were classified using four different machine learning algorithms: decision tree (DT), k-nearest neighbors (KNN), support vector machine (SVM), and neural network (NN). The results showed that the muscle synergy features had a better classification accuracy than the other EMG features. This finding supported the hypothesis that muscle synergy enables accurate gait phase classification. Overall, the study presents a novel approach to gait analysis and highlights the potential of muscle synergy as a tool for gait phase detection.
Evaluation of a short instrument for measuring health-related quality of life in oncological patients in routine care (HELP-6): an observational study

Purpose Patient-reported outcomes have not been sufficiently implemented into the routine care of cancer patients because the existing instruments are often too long and complex or not cancer-specific. The aim of this study is the determination of psychometric properties and item reduction of a newly developed health-related quality of life (HrQoL) questionnaire for use in oncological clinical routines. Methods This observational study with a repeated measurements design included oncological inpatients and outpatients. A total of 630 patients participated at the first point of measurement and 404 at the second point of measurement. To evaluate the instrument, we conducted hierarchical confirmative factor analyses and for further validation correlated the resulting factors with standardized and validated HrQoL measurements. Test–retest reliability and responsiveness to change were tested. Results The developed questionnaire “HELP-6” (“Hamburg Inventory for Measuring Quality of Life in Oncological Patients”) has a six-factor structure and has moderate-to-good convergent validity (r= −0.25 –−0.68). Test–retest reliability was moderate-to-good (r =0.56−0.81, p < 0.001). Indications for responsiveness to change were found for three dimensions. The final version of the questionnaire HELP-6 has six dimensions with one item each. Conclusion With the HELP-6 instrument for measuring HrQoL in cancer patients, we provide a short and practical patient-reported outcome instrument. Though responsiveness to change could not be confirmed for all dimensions in this study, the HELP-6 includes time-efficient completion and evaluation and is informative in relevant HrQoL dimensions of cancer patients. Therefore, the HELP-6 poses an important addition to inpatient and outpatient routine cancer care. Trial registration This study was registered at Open Science Framework (https://osf.io/y7xce/), on 9 June 2018.
Modeling information diffusion in social media: data-driven observations

Accurately modeling information diffusion within and across social media platforms has many practical applications, such as estimating the size of the audience exposed to a particular narrative or testing intervention techniques for addressing misinformation. However, it turns out that real data reveal phenomena that pose significant challenges to modeling: events in the physical world affect in varying ways conversations on different social media platforms; coordinated influence campaigns may swing discussions in unexpected directions; a platform's algorithms direct who sees which message, which affects in opaque ways how information spreads. This article describes our research efforts in the SocialSim program of the Defense Advanced Research Projects Agency. As formulated by DARPA, the intent of the SocialSim research program was “to develop innovative technologies for high-fidelity computational simulation of online social behavior . [focused] specifically on information spread and evolution. ” In this article we document lessons we learned over the 4+ years of the recently concluded project. Our hope is that an accounting of our experience may prove useful to other researchers should they attempt a related project.