Miracle-dz/UniFAR-FTUs huggingface dataset:
Clarifying Relations Between ADHD and Functional Impairment in Adulthood: Utilization of Network and Machine Learning Approaches

Using network analysis and random forest regression, this study identified attention-deficit/hyperactivity disorder (ADHD) symptoms most important for indicating impairment in various functional domains. Participants comprised a nationally representative sample of 1249 adults in the United States. Bridge symptoms were identified as those demonstrating unique relations with impairment domains that, in total, were stronger than those involving other symptoms. Results suggested three inattentive (i.e., difficulty organizing; does not follow through; makes careless mistakes) and one hyperactive (difficulty engaging in leisure activities) bridge symptoms. Random forest regression results supported bridge symptoms as most important (compared to other symptoms) for predicting global and specific impairment domains. Hyperactive/impulsive symptoms appeared more strongly related to impairment in women, whereas difficulty organizing and easily distracted appeared more related to impairment in men. Clarification of bridge symptoms may help identify core characteristics of ADHD in adulthood and specify screening and intervention targets to reduce risk for related impairment.
The Role of De Ritis Ratio as a Clinical Prognostic Parameter in COVID 19 Patients.

BACKGROUND The study aims to investigate whether the De Ritis ratio can also be used in patients diagnosed with COVID-19 as a follow-up parameter, such as NLR, which is used in the follow-up and treatment of many diseases. METHODS Ninety-nine patients admitted to our hospital with suspected COVID-19 were included in the study. Demographic data of the patients, their history characteristics, presenting symptoms, filiation status, duration of clinical stay, and length of stay in intensive care unit, intubation, dialysis, and plasmapheresis needs were examined. The patients were divided into two groups: PCR positive and PCR negative. The presenting, 5th day, and the clinical discharge values of AST, ALT, LDH, urea, creatine, eGFR, De Ritis ratio, procalcitonin, CRP, WBC, NLR, ferritin, lymphocyte, and D-dimer levels of the patients in both groups were studied. RESULTS The DM and CAD presence in the histories of PCR-positive patients was found to be statistically signifi-cantly higher (p = 0.05, p = 0.03, respectively). Presenting symptoms of headache, fatigue, gastrointestinal symptoms, and taste loss were significantly higher in the PCR-positive patients (p = 0.04, p = 0.02, p = 0.03, p = 0.02, respectively). In the PCR-positive patients, a statistically significant correlation was found between the presenting De Ritis ratios and the presenting NLR, 5th day NLR, and NLR at discharge (p = 0.007, p = 0.02, p = 0.015, respectively). In the PCR-positive group, the 1st and 5th day De Ritis ratios of females were statistically significantly higher than males (p = 0.000, p = 0.006, respectively). Albumin, procalcitonin, length of stay in intensive care unit were significantly higher in the PCR-positive patients, while the presenting D-dimer, presenting WBC, and presenting and 5th day lymphocyte values were significantly higher in the PCR-negative patients. CONCLUSIONS These findings show that the De Ritis ratios can be used in PCR-positive patients as a parameter, such as NLR, to follow-up and determine the prognosis of many diseases.
Intravenous thrombolysis for acute ischemic stroke with extended time window

Abstract Background: Intravenous thrombolysis (IVT) is an effective way for treating acute ischemic stroke (AIS). However, its effects have not been established among AIS patients with unclear stroke symptoms or with stroke onset for >4.5 h. Methods: We searched PubMed, Embase, Web of Science, Cochrane Central Register of Controlled Trials and Google Scholar databases for randomized controlled trials that compared IVT (IVT group) and placebo or usual care (control group [CG]) in AIS patients with disease onset for >4.5 h. The outcomes of interest included the favorable functional outcome (defined as modified Rankin Scale [mRS] scores 0–1) at 90 days, the functional independence (defined as mRS scores 0–2) at 90 days, proportion of patients with symptomatic intracerebral hemorrhage (sICH) and death at 90 days. We assessed the risk of bias using the Cochrane tool. Pre-specified subgroup analyses were performed by age (≤70 years or >70 years), National Institute of Health Stroke Scale (NIHSS, ≤10 or >10) and time window (4.5–9.0 h or >9.0 h). Results: Four trials involving 848 patients were eligible. The risk of bias of included trials was low. Patients in the IVT group were more likely to achieve favorable functional outcomes (45.8% vs. 36.7%; OR 1.48, 95% CI 1.12–1.96) and functional independence (63.8% vs. 55.7%; OR 1.43, 95% CI 1.08–1.90) at 90 days, but had higher risk of sICH (3.0% vs. 0.5%; OR 5.28, 95% CI 1.35–20.68) at 90 days than those in the CG. No significant difference in death at 90 days was found between the two groups (7.0% vs. 4.1%; OR 1.80; 95% CI 0.97–3.34). Conclusions: Use of IVT in patients with extended time window may improve their functional outcomes at 90 days, although IVT may induce increased risk of sICH. Care of these patients should well balance the potential benefits and harms of IVT.
Co-VAE: Drug-target binding affinity prediction by co-regularized variational autoencoders

Identifying drug-target interactions has been a key step in drug discovery. Many computational methods have been proposed to directly determine whether drugs and targets can interact or not. Drug-target binding affinity is another type of data which could show the strength of the binding interaction between a drug and a target. However, it is more challenging to predict drug-target binding affinity, and thus a very few studies follow this line. In our work, we propose a novel co-regularized variational autoencoders (Co-VAE) to predict drug-target binding affinity based on drug structures and target sequences. The Co-VAE model consists of two VAEs for generating drug SMILES strings and target sequences, respectively, and a co-regularization part for generating the binding affinities. We theoretically prove that the Co-VAE model is to maximize the lower bound of the joint likelihood of drug, protein and their affinity. The Co-VAE could predict drug-target affinity and generate new drugs which share similar targets with the input drugs. The experimental results on two datasets show that the Co-VAE could predict drug-target affinity better than existing affinity prediction methods such as DeepDTA and DeepAffinity, and could generate more new valid drugs than existing methods such as GAN and VAE.
Homogenization of terrestrial mammals in fragmented rainforests: the loss of species turnover and its landscape drivers.

Understanding the factors and mechanisms shaping differences in species composition across space and time (β-diversity) in human-modified landscapes has key ecological and applied implications. This topic is, however, challenging because landscape disturbance can promote either decreases (biotic homogenization) or increases (biotic differentiation) in β-diversity. We assessed temporal differences in inter-site β-diversity of medium- and large-bodied mammals in the fragmented Lacandona rainforest, Mexico. We hypothesized that given the relatively short history of land-use changes in the region, and the gain and loss of some species caused by landscape spatial changes, β-diversity would increase through time, especially its nestedness component. We estimated β-diversity between 24 forest sites (22 forest patches and two continuous forest sites) in 2011 and 2017 to assess whether β-diversity is decreasing or increasing in the region, and calculated its turnover and nestedness components to understand the mechanisms responsible for changes in β-diversity, separately assessing mammal groups with different body mass, feeding guild, and habitat specialization. We then related such temporal changes in β-diversity to temporal changes in five landscape variables (forest cover, matrix openness, number of patches, edge density and inter-patch distance) to identify the landscape drivers of β-diversity. In contrast to our expectations, β-diversity decreased over time, suggesting an ongoing biotic homogenization process. This pattern was mostly driven by a decrease in species turnover in all mammal groups, especially in landscapes with decreasing forest cover and increasing forested matrices. Although the nestedness component showed a 3-fold increase through time, species turnover was 22 and 6 times higher than nestedness in 2011 and 2017, respectively. The decreased turnover appears to be driven by an increase in dispersal (i.e., spillover) of native species among patches. The prevalence of species turnover over nestedness indicates that different forest sites have a fairly distinct subset of species (i.e., high complementarity in species composition). Therefore, conserving all remaining forest patches and increasing forest cover is of utmost importance to effectively maintain β-diversity and conserve the total diversity (γ) of mammal assemblages in this Mesoamerican biodiversity hotspot.
Health, Wealth, and Voting Trajectories in Later Life

Abstract Objectives Much of what we know about voting behaviors is based on cross-sectional comparisons of voters at different ages. This study draws on a unique linkage between the Wisconsin Longitudinal Study and state voter files to characterize voting trajectories in later life and explore their determinants. Methods Using sequence analysis, we identify 5 voting typologies based on turnout and voting methods over 8 biennial elections. Using multinomial logistic and Poisson regressions, we examine the role of physical, cognitive, and mental health and wealth in shaping enfranchisement and civic participation at older ages. Results Health and wealth are both positively associated with voter turnout, but the negative impact of poor health on voting declines with increasing wealth. Voting at the polls and early voting are more common among healthier older adults, whereas absentee voting is more common among older voters who are more affluent, less healthy, or both. Among those less wealthy, absentee methods mitigate the impact of poor health for previously active voters, but do not compensate for a lower turnout rate. In addition to physical and cognitive limitations, emotional difficulties and depression reduce turnout, particularly among the least wealthy. Discussion In this sample of older, largely White, primarily Midwestern committed voters, civic participation at older ages is shaped by individual experiences with wealth and health across the life course as well as political structures that facilitate or restrict the ability of individuals to consistently participate in elections.
Exploring the neural correlates of (altered) moral cognition in psychopaths

Research into the neurofunctional mechanisms of psychopathy has gathered momentum over the last years. Previous neuroimaging studies have identified general changes in brain activity of psychopaths. In an exploratory meta-analysis, we here investigated the neural correlates of impaired moral cognition in psychopaths. Our analyses replicated general effects in the dorsomedial prefrontal cortex, lateral prefrontal cortex, fronto-insular cortex, and amygdala, which have been reported recently. In addition, we found aberrant brain activity in the midbrain and inferior parietal cortex. Our preliminary findings suggest that alterations in both regions may represent more specific functional brain changes related to (altered) moral cognition in psychopaths. Furthermore, future studies including a more comprehensive corpus of neuroimaging studies on moral cognition in psychopaths should re-examine this notion.
Understanding Private Car Aggregation Effect via Spatio-Temporal Analysis of Trajectory Data

Understanding the private car aggregation effect is conducive to a broad range of applications, from intelligent transportation management to urban planning. However, this work is challenging, especially on weekends, due to the inefficient representations of spatiotemporal features for such aggregation effect and the considerable randomness of private car mobility on weekends. In this article, we propose a deep learning framework for a spatiotemporal attention network (STANet) with a neural algorithm logic unit (NALU), the so-called STANet-NALU, to understand the dynamic aggregation effect of private cars on weekends. Specifically: 1) we design an improved kernel density estimator (KDE) by defining a log-cosh loss function to calculate the spatial distribution of the aggregation effect with guaranteed robustness and 2) we utilize the stay time of private cars as a temporal feature to represent the nonlinear temporal correlation of the aggregation effect. Next, we propose a spatiotemporal attention module that separately captures the dynamic spatial correlation and nonlinear temporal correlation of the private car aggregation effect, and then we design a gate control unit to fuse spatiotemporal features adaptively. Further, we establish the STANet-NALU structure, which provides the model with numerical extrapolation ability to generate promising prediction results of the private car aggregation effect on weekends. We conduct extensive experiments based on real-world private car trajectories data. The results reveal that the proposed STANet-NALU outperforms the well-known existing methods in terms of various metrics, including the mean absolute error (MAE), root mean square error (RMSE), Kullback–Leibler divergence (KL), and R2.
Quantitatively monitoring the resilience of patterned vegetation in the Sahel

Patterning of vegetation in drylands is a consequence of localized feedback mechanisms. Such feedbacks also determine ecosystem resilience—i.e. the ability to recover from perturbation. Hence, the patterning of vegetation has been hypothesized to be an indicator of resilience, that is, spots are less resilient than labyrinths. Previous studies have made this qualitative link and used models to quantitatively explore it, but few have quantitatively analysed available data to test the hypothesis. Here we provide methods for quantitatively monitoring the resilience of patterned vegetation, applied to 40 sites in the Sahel (a mix of previously identified and new ones). We show that an existing quantification of vegetation patterns in terms of a feature vector metric can effectively distinguish gaps, labyrinths, spots, and a novel category of spot–labyrinths at their maximum extent, whereas NDVI does not. The feature vector pattern metric correlates with mean precipitation. We then explored two approaches to measuring resilience. First we treated the rainy season as a perturbation and examined the subsequent rate of decay of patterns and NDVI as possible measures of resilience. This showed faster decay rates—conventionally interpreted as greater resilience—associated with wetter, more vegetated sites. Second we detrended the seasonal cycle and examined temporal autocorrelation and variance of the residuals as possible measures of resilience. Autocorrelation and variance of our pattern metric increase with declining mean precipitation, consistent with loss of resilience. Thus, drier sites appear less resilient, but we find no significant correlation between the mean or maximum value of the pattern metric (and associated morphological pattern types) and either of our measures of resilience.
Self-disgust and disgust sensitivity are increased in anorexia nervosa inpatients, but only self-disgust mediates between comorbid and core psychopathology.

OBJECTIVE The possible role of abnormal disgust processing in the development and course of anorexia nervosa (AN) has been emphasized in theoretical models and research. However, disgust toward external stimuli and self-disgust have not yet been investigated together in a clinical sample of AN patients. Therefore, the purpose of the study was to measure these constructs and examine their role in shaping eating pathology in AN patients and healthy controls (HCs), considering comorbid depressive and anxiety psychopathology. The study also aimed at testing the possible mediational roles of both disgust types in the associations between comorbid psychopathology and eating disorders (EDs) characteristics. METHOD Altogether, 63 inpatients with AN and 57 HCs partook in the study. Participants completed the Eating Disorder Inventory-3, State-Trait Anxiety Inventory, Beck Depression Inventory-II, Disgust Scale-Revised and Self-Disgust Scale. RESULTS AN patients manifested higher self-disgust and disgust sensitivity than HCs. In addition, self-disgust predicted the severity of EDs characteristics and mediated the links of depressive symptoms and trait anxiety with EDs characteristics in both groups. DISCUSSION Our findings imply the putative role of self-disgust in the development of EDs psychopathology in HCs and in its maintenance in AN patients.
Glioblastoma–Astrocyte Connexin 43 Gap Junctions Promote Tumor Invasion

Glioblastoma multiforme (GBM), classified as World Health Organization grade IV astrocytoma, is the deadliest adult cancer of the central nervous system. An important contributing factor to poor survival rates in GBM is extensive invasion, which decreases the efficacy of resection and subsequent adjuvant therapies. These treatments could be markedly improved with increased resolution of the genetic and molecular initiators and effectors of invasion. Connexin 43 (Cx43) is the principal astrocytic gap junction (GJ) protein. Despite the heterogeneity of GBM, a subpopulation of cells in almost all GBM tumors express Cx43. Functional GJs between GBM cells and astrocytes at the tumor edge are of critical interest for understanding invasion. In this study, we find that both in vitro and in ex vivo slice cultures, GBM is substantially less invasive when placed in a Cx43-deficient astrocyte environment. Furthermore, when Cx43 is deleted in GBM, the invasive phenotype is recovered. These data strongly suggest that there are opposing roles for Cx43 in GBM migration. We find that Cx43 is localized to the tumor edge in our ex vivo model, suggesting that GBM–astrocyte GJ communication at the tumor border is a driving force for invasion. Finally, we find that by a Cx43-dependent mechanism, but likely not direct channel-mediated diffusion, miRNAs associated with cell–matrix adhesion are transferred from GBM to astrocytes and miR-19b promotes invasion, revealing a role for post-transcriptional manipulation of astrocytes in fostering an invasion-permissive peritumoral niche. Implications: Cx43-mediated communication, specifically miRNA transfer, profoundly impacts glioblastoma invasion and may enable further therapeutic insight.
Severe influenza virus infection in children admitted to the PICU: Comparison of influenza A and influenza B virus infection

Although the influenza virus usually causes a self‐limiting disease, deaths are reported even in children without risk factors. We aimed to identify the clinical features, mortality associated with severe influenza A and B virus infections of children admitted to the pediatric intensive care unit (PICU). We conducted a retrospective study of children with confirmed influenza infection between 2012 and 2019 who were admitted to the PICU. Demographic features, risk factors, clinical data, microbiological data, complications, and outcomes were collected. Over seven influenza seasons (2012–2011 to 2015–2016), 713 children diagnosed with laboratory‐confirmed influenza‐related LRTI, and PICU admission was needed in 6% (46/713) of the patients. Thirty‐one patients (67.4%) were diagnosed with influenza A and 15 patients were diagnosed with influenza B. Epidemiologic and clinical characteristics were similar in both influenza types, lactate dehydrogenase levels were significantly higher for influenza A than for influenza B infections. Although the influenza A to B ratio among the patients admitted to the PICU was 2.06, the percentage of cases requiring PICU admission was nearly two times higher in influenza B cases. There was no statistically significant difference in disease severity and complications in patients with influenza A and influenza B.
Characteristics of PM and PAHs emitted from a coal-fired boiler and the efficiencies of its air pollution control devices

ABSTRACT Sampling and analysis of filterable particulate matter (FPM), FPM2.5, condensable particulate matter (CPM), polycyclic aromatic hydrocarbons (PAHs), sulfur oxides (SOx), and nitrogen oxides (NOx) emitted from a coal-fired boiler equipped with selective catalytic reduction (SCR)+ electrostatic precipitator (ESP) + wet flue gas desulfurization (WFGD) + wet electrostatic precipitator (WESP) as air pollution control devices (APCDs) are conducted. The results show that NOx concentration emitted from the coal-fired boiler is 56 ± 2.17 ppm (with the NOx removal efficiency of 47.2%), which does not meet the best available control technology (BACT) emission standard (≤ 30 ppm). On the other hand, the WFGD adopted has a good removal efficiency for SOx and HCl. Both SOx and HCl emission concentrations are < 1 ppm, and removal efficiencies are > 99%. The FPM and FPM2.5 emitted from the coal-fired boiler are 0.9 ± 0.06 mg/Nm3 and < 0.09 ± 0.006 mg/Nm3, respectively. The overall removal efficiency of FPM achieved with ESP+WFGD+WESP+MGGH is 99.98%. However, high concentration of CPM (37.4 ± 6.3 mg/Nm3) is measured, which is significantly higher than FPM and FPM2.5. The concentrations of 27 PAHs at the WESP inlet and stack are measured as 667 ng/Nm3 and 547 ng/Nm3, respectively while the removal efficiencies of gas- and solid-phase PAHs are 9% and 58%, respectively. The results show that APCDs adopted are not effective in removing PAHs (only 18%), and gas-phase PAHs contribute the most in the total PAH emission. In addition, the benzo(a)pyrene equivalent (BaPeq) concentration emitted from the stack is 28.8 ng-BaPeq/Nm3, and most of it is contributed by 4–6 ring PAHs with high toxic equivalent factors (TEFs). Furthermore, the emission factors of air pollutant emitted from coal-fired boilers equipped with different combinations of APCDs are compiled and compared. The results show that except for CPM and NOx, the emission factors of air pollutant calculated for this coal-fired boiler are lower if compared with other studies. Implications: Primary particles discharged from coal-fired processes include filterable particulate matter (FPM) and condensable particulate matter (CPM). PM2.5 emissions would be greatly underestimated if CPM is ignored. Polycyclic aromatic hydrocarbons (PAHs) are semi-volatile organic compounds (SVOCs) formed by two or more fused benzene rings. PAHs have attracted much public attention because of toxicity and carcinogenicity. This study selects one coal-fired boiler with the best available control technology (BACT) to simultaneously measure the concentrations of PM, PAHs, and gaseous pollutants at the inlet and outlet of air pollution control devices (APCDs) to understand the efficacy of APCDs adopted and pollutant emission intensity.
Hearing test results of newborns born from the coronavirus disease 2019 (COVID‐19) infected mothers: A tertiary center experience in Turkey

Congenital infections can cause newborn hearing loss. Although vertical transmission of coronavirus disease 2019 (COVID‐19) infection is theoretically possible, this has not been proven yet. To our knowledge, there is no previous report on whether COVID‐19 infection during pregnancy can cause congenital hearing loss. This paper aimed to find an answer to this question.