Miracle-dz/UniFAR-FTUs huggingface dataset:
The severity of addiction mediates loneliness and cortical volume in internet gaming disorder

Internet gaming disorder (IGD) subjects reported higher loneliness scores than healthy controls. However, the neural correlates underlying the association between loneliness and IGD remain unclear. Thus, the aim of this study was to explore the relationship between loneliness, online gaming addiction and brain structure. In the current study, structural MRI data were acquired from 84 IGD subjects and 103 matched recreational game users (RGUs). We assessed and compared their addiction severity, loneliness scores, and cortical volumes and analyzed the correlations among these values. Significant correlations were found between loneliness scores and brain volumes in the postcentral cortex, the medial orbitofrontal cortex, the rostral anterior cingulate cortex, and the temporal cortex. In addition, the addiction severity scores partly mediated the relationship between loneliness score and cortical volume in IGD. The results showed that participants with extreme loneliness had significant correlations with brain regions responsible for executive control, social threat surveillance and avoidance. More importantly, the severity of addiction mediates loneliness and cortical volume. The findings shed new insight into the neural mechanisms of loneliness and IGD and have implications for potential treatment.
Value-based decision-making predicts alcohol use and related problems in young men

Background: Alcohol consumption is a leading cause of morbidity and mortality worldwide, disproportionately affecting young men. Heavy episodic drinking is particularly prevalent among men, with this behavior peaking between the ages of 20 and 24. Aims: We sought to identify dimensions of decision-making in men that would predict the development of hazardous alcohol use through emerging adulthood. Methods: This prospective observational study profiled value-based decision-making in 198 healthy men at age 18 and assessed their alcohol involvement annually until age 24. Latent growth curve modeling estimated individual variability in trajectories of alcohol involvement and regressed this variability on five choice dimensions. Results: Low loss aversion predicted sustained heavy episodic drinking from age 18 to 24. Both high delay discounting and risk-seeking for gains independently predicted a considerably higher cumulative alcohol use during these 6 years, with high delay discounting indicating escalating consumption from age 21. Risk-seeking for gains additionally predicted meeting more criteria for Alcohol Use Disorder in these 6 years. Risk-seeking for losses was not significantly related to alcohol outcomes. Choice preferences were largely independent of each other but were correlated with choice consistency, with low consistency predicting heavy episodic drinking from age 18 to 24 beyond these associations. Conclusions: The predictive effects collectively suggest that overvaluing immediate and probabilistic incentives, rather than underestimating harm, drives hazardous drinking in young men. The differential relations of choice preferences and consistency to alcohol involvement through emerging adulthood provide distinct cognitive-behavioral patterns that warrant consideration in the development of harm reduction interventions.
Analysis on changes of stress strain porosity and permeability in multiphase reservoir with fluid－solid coupled and geomechanical mathematic simulation

 Hydrolic fracturing will change the stress in petroleum reservoir and induce deformation in rock so it will influence the fluid percolation． In this paper a fluid－solid coupled and geomechanical math model was set up for fractured reservoir． In this model the following factors were considered two phases of oil and water hydrolic fracture deformation of reservoir changes of stress porosity and permeability． There were eleven variables in the governing equations which comprised matrix pore pressure fracture pressure fluid saturation displacements． The system of the nonlinear governing partial differential equations was discretized using the finite difference method． The finite difference equations were arranged as seven－point stencils． A fully implicit procedure was adopted here for maximal numerical stability． By analysis it is explicit that this model can be used to solve many problems such as simulating deformation of reservoir calculating changes of stress and strain and analyzing changes of porosity and permeability in reservoir．
Unified measurement system with suction control for measuring hysteresis in soil‐gas transport parameters

A unified measurement system with suction control (UMS_SC) was developed for measuring soil water characteristics curves (SWCC) and gas transport parameters under alternating drying and wetting cycles. The new system consists of a diffusion chamber, sample ring, porous plate, tensiometer, moisture sensor, oxygen electrodes, and air pressure gauges. The SWCC and gas transport parameters [gas diffusion coefficient (Dp) and air permeability (ka)] for two different porous materials, Toyoura sand and granulated slag, were simultaneously measured under drying and wetting cycles. The SWCC and gas transport parameters measured by UMS_SC were consistent with recent models and independently measured data on exactly the same materials using standard experimental setups from literature. For an applied water suction head of less than 50 cm and corresponding water saturation of around 0.3–0.5, the UMS_SC data documented hysteretic (nonsingular) behavior in both measured Dp and ka under repeated drying and wetting cycles. The hysteretic behavior was insignificant for water and air contents but large for both gas transport parameters when applying suction, and hysteretic effects were larger for air permeability than for gas diffusivity. Additionally, hysteresis in the percolation threshold (soil‐air content where gas transport ceases due to interconnected water‐filled pores) for both gas diffusion and air permeability was insignificant for both materials. These findings should be taken into account when developing models for diffusive and convective gas transport and their parameters in variably saturated porous media.
Sustainable appraisal of lac (Kerria Lacca) based anthraquinone natural dye for chemical and bio-mordanted viscose and silk dyeing

The coloring behavior of laccaic acid, a natural red dye derived from lac insects, has been investigated in this work for the dyeing of silk and viscose fabrics while being heated in MW radiation. The extract was made in an aqueous and acidic media and then used to color fabrics under microwave treatment for up to 10 min. For developing new shades, eco-friendly green bio-mordants and, in comparison, chemical mordants were employed at given conditions. The obtained results revealed that the aqueous extract after 4 min of radiation exposure produced a high color strength (K/S = 17.132) onto silk and the aqueous extract after 6 min of radiation exposure produced better color strength (K/S = 6.542) onto viscose at selected conditions. The fastness ratings evaluation as per ISO standards demonstrates that bio-anchors have provided good ratings under selected irradiation and dyeing conditions. It is concluded that this environmentally friendly technique has improved the natural coloration process of fabrics as well as addition of green mordants has furnished colorfast shades using lac-derived natural anthraquinone dye.
Pyroclastic density currents

Abstract High-speed, gravity-driven flows of hot particles and gas are a common and highly destructive product of explosive volcanism. They range widely in nature from expanded, turbulent suspension currents formed by lateral blasts or by the fountaining of vertical eruption columns, to highly concentrated granular avalanches formed by lava dome col-lapse or as dense underflows beneath suspension currents. The deposits from these flows, here called pyroclastic density currents, range in volume from much less than 1 km3 to thousands of cubic kilometres, and may extend over 100 km from their source. This chapter reviews the eruption, transport and deposition of pyroclastic density currents from both geological and physical perspectives, focussing on some recent advances.
The effect of different compost: soil rates on some parameters of the soil-plant system.

Composting is an alternative way for practicing site-specific and environmental friendly plant nutrient supply. Our aim was to study the effect of different composts on plant and soil system. Pot experiment with acidic sandy soil blended with three composts in five (0%, 5%, 10%, 25% and 50%) proportion was set up. Our experimental plant was perennial ryegrass (Lolium perenne L.). After the harvest of ryegrass we measured the fresh and dry weight of harvested plants, the P-, K-, Mg-contents, and the pH of soils. The three composts had different effect on dry weight production and on nutrient-supply of soil. We established that one of the compost had significantly larger effect on the dry weight of ryegrass compared to the others. In this study we proved that favorable compost/soil proportion is different in the case of different composts.
Structural analysis of PLD3 reveals insights into the mechanism of lysosomal 5′ exonuclease-mediated nucleic acid degradation

Abstract The phospholipase D (PLD) family is comprised of enzymes bearing phospholipase activity towards lipids or endo- and exonuclease activity towards nucleic acids. PLD3 is synthesized as a type II transmembrane protein and proteolytically cleaved in lysosomes, yielding a soluble active form. The deficiency of PLD3 leads to the slowed degradation of nucleic acids in lysosomes and chronic activation of nucleic acid-specific intracellular toll-like receptors. While the mechanism of PLD phospholipase activity has been extensively characterized, not much is known about how PLDs bind and hydrolyze nucleic acids. Here, we determined the high-resolution crystal structure of the luminal N-glycosylated domain of human PLD3 in its apo- and single-stranded DNA-bound forms. PLD3 has a typical phospholipase fold and forms homodimers with two independent catalytic centers via a newly identified dimerization interface. The structure of PLD3 in complex with an ssDNA-derived thymidine product in the catalytic center provides insights into the substrate binding mode of nucleic acids in the PLD family. Our structural data suggest a mechanism for substrate binding and nuclease activity in the PLD family and provide the structural basis to design immunomodulatory drugs targeting PLD3.
Sleep regularity and mortality: a prospective analysis in the UK Biobank

Background: Irregular sleep-wake timing may cause circadian disruption leading to several chronic age-related diseases. We examined the relationship between sleep regularity and risk of all-cause, cardiovascular disease (CVD), and cancer mortality in 88,975 participants from the prospective UK Biobank cohort. Methods: The sleep regularity index (SRI) was calculated as the probability of an individual being in the same state (asleep or awake) at any two time points 24 hr apart, averaged over 7 days of accelerometry (range 0–100, with 100 being perfectly regular). The SRI was related to the risk of mortality in time-to-event models. Results: The mean sample age was 62 years (standard deviation [SD], 8), 56% were women, and the median SRI was 60 (SD, 10). There were 3010 deaths during a mean follow-up of 7.1 years. Following adjustments for demographic and clinical variables, we identified a non-linear relationship between the SRI and all-cause mortality hazard (p [global test of spline term]<0.001). Hazard ratios, relative to the median SRI, were 1.53 (95% confidence interval [CI]: 1.41, 1.66) for participants with SRI at the 5th percentile (SRI = 41) and 0.90 (95% CI: 0.81, 1.00) for those with SRI at the 95th percentile (SRI = 75), respectively. Findings for CVD mortality and cancer mortality followed a similar pattern. Conclusions: Irregular sleep-wake patterns are associated with higher mortality risk. Funding: National Health and Medical Research Council of Australia (GTN2009264; GTN1158384), National Institute on Aging (AG062531), Alzheimer’s Association (2018-AARG-591358), and the Banting Fellowship Program (#454104).
BrAIST-Calc: Prediction of Individualized Benefit From Bracing for Adolescent Idiopathic Scoliosis

Study Design. Prospective multicenter study data were used for model derivation and externally validated using retrospective cohort data. Objective. Derive and validate a prognostic model of benefit from bracing for adolescent idiopathic scoliosis (AIS). Summary of Background Data. The Bracing in Adolescent Idiopathic Scoliosis Trial (BrAIST) demonstrated the superiority of bracing over observation to prevent curve progression to the surgical threshold; 42% of untreated subjects had a good outcome, and 28% progressed to the surgical threshold despite bracing, likely due to poor adherence. To avoid over-treatment and to promote patient goal setting and adherence, bracing decisions (who and how much) should be based on physician and patient discussions informed by individual-level data from high-quality predictive models. Materials and Methods. Logistic regression was used to predict curve progression to <45° at skeletal maturity (good prognosis) in 269 BrAIST subjects who were observed or braced. Predictors included age, sex, body mass index, Risser stage, Cobb angle, curve pattern, and treatment characteristics (hours of brace wear and in-brace correction). Internal and external validity were evaluated using jackknifed samples of the BrAIST data set and an independent cohort (n=299) through estimates of discrimination and calibration. Results. The final model included age, sex, body mass index, Risser stage, Cobb angle, and hours of brace wear per day. The model demonstrated strong discrimination (c-statistics 0.83–0.87) and calibration in all data sets. Classifying patients as low risk (high probability of a good prognosis) at the probability cut point of 70% resulted in a specificity of 92% and a positive predictive value of 89%. Conclusion. This externally validated model can be used by clinicians and families to make informed, individualized decisions about when and how much to brace to avoid progression to surgery. If widely adopted, this model could decrease overbracing of AIS, improve adherence, and, most importantly, decrease the likelihood of spinal fusion in this population.
Transition from Paediatric to adult health services: Aspirations and practices of human flourishing

ABSTRACT Background Transition from paediatric to adult care is challenging for youths with a chronic condition. Most transition programmes place high value in autonomy and independence. We undertook a qualitative study to: (1) identify the needs and aspirations of youths and (2) better understand the well-being and flourishing of youths. Methods Semi-structured interviews were conducted with youths, parents of youths and healthcare professionals recruited from four clinics. Thematic analysis focused on: (1) perceptions of transition; (2) key aspects of human flourishing during transition; and (3) salient concerns with respect to the transition and dimensions of human flourishing. Results 54 interviews were conducted. Perceptions of transition clustered around: (1) apprehension about adult care; (2) lack of clarity about the transition process; (3) emotional attachment to paediatric healthcare professionals; (4) the significance of the coinciding transition into adulthood. Fourteen salient concerns (e.g., Knowledge and information about the transition, Parental involvement in healthcare) were identified with corresponding recommendations. Salient concerns related to important dimensions of human flourishing (e.g., environmental mastery, autonomy). Discussion and conclusion The flourishing of youths is affected by suboptimal transition practices. We discuss the implications of our findings for environmental mastery, contextual autonomy, and the holistic and humanistic aspects of transition.
A multiscale model of the role of microenvironmental factors in cell segregation and heterogeneity in breast cancer development

We analyzed a quantitative multiscale model that describes the epigenetic dynamics during the growth and evolution of an avascular tumor. A gene regulatory network (GRN) formed by a set of ten genes that are believed to play an important role in breast cancer development was kinetically coupled to the microenvironmental agents: glucose, estrogens, and oxygen. The dynamics of spontaneous mutations was described by a Yule-Furry master equation whose solution represents the probability that a given cell in the tissue undergoes a certain number of mutations at a given time. We assumed that the mutation rate is modified by a spatial gradient of nutrients. The tumor mass was simulated by means of cellular automata supplemented with a set of reaction diffusion equations that described the transport of microenvironmental agents. By analyzing the epigenetic state space described by the GRN dynamics, we found three attractors that were identified with cellular epigenetic states: normal, precancer and cancer. For two-dimensional (2D) and three-dimensional (3D) tumors we calculated the spatial distribution of the following quantities: (i) number of mutations, (ii) mutation of each gene and, (iii) phenotypes. Using estrogen as the principal microenvironmental agent that regulates cell proliferation process, we obtained tumor shapes for different values of estrogen consumption and supply rates. It was found that he majority of mutations occurred in cells that were located close to the 2D tumor perimeter or close to the 3D tumor surface. Also, it was found that the occurrence of different phenotypes in the tumor are controlled by estrogen concentration levels since they can change the individual cell threshold and gene expression levels. All results were consistently observed for 2D and 3D tumors.
Monitoring reservoir storage in South Asia from multisatellite remote sensing

Reservoir storage information is essential for accurate flood monitoring and prediction. South Asia, however, is dominated by international river basins where communications among neighboring countries about reservoir storage and management are extremely limited. A suite of satellite observations were combined to achieve high‐quality estimation of reservoir storage and storage variations in South Asia from 2000 to 2012. The approach used water surface area estimations from the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices product and the area‐elevation relationship to estimate reservoir storage. The surface elevation measurements were from the Geoscience Laser Altimeter System (GLAS) on board the Ice, Cloud, and land Elevation Satellite (ICESat). In order to improve the accuracy of water surface area estimations for relatively small reservoirs, a novel classification algorithm was developed. In this study, storage information was retrieved for a total of 21 reservoirs, which represents 28% of the integrated reservoir capacity in South Asia. The satellite‐based reservoir elevation and storage were validated by gauge observations over five reservoirs. The storage estimates were highly correlated with observations (i.e., coefficients of determination larger than 0.9), with normalized root mean square error (NRMSE) ranging from 9.51% to 25.20%. Uncertainty analysis was also conducted for the remotely sensed storage estimations. For the parameterization uncertainty associated with surface area retrieval, the storage mean relative error was 3.90%. With regard to the uncertainty introduced by ICESat/GLAS elevation measurements, the storage mean relative error was 0.67%.
Machine learning‐derived identification of prognostic signature for improving prognosis and drug response in patients with ovarian cancer

Abstract Clinical assessments relying on pathology classification demonstrate limited effectiveness in predicting clinical outcomes and providing optimal treatment for patients with ovarian cancer (OV). Consequently, there is an urgent requirement for an ideal biomarker to facilitate precision medicine. To address this issue, we selected 15 multicentre cohorts, comprising 12 OV cohorts and 3 immunotherapy cohorts. Initially, we identified a set of robust prognostic risk genes using data from the 12 OV cohorts. Subsequently, we employed a consensus cluster analysis to identify distinct clusters based on the expression profiles of the risk genes. Finally, a machine learning‐derived prognostic signature (MLDPS) was developed based on differentially expressed genes and univariate Cox regression genes between the clusters by using 10 machine‐learning algorithms (101 combinations). Patients with high MLDPS had unfavourable survival rates and have good prediction performance in all cohorts and in‐house cohorts. The MLDPS exhibited robust and dramatically superior capability than 21 published signatures. Of note, low MLDIS have a positive prognostic impact on patients treated with anti‐PD‐1 immunotherapy by driving changes in the level of infiltration of immune cells. Additionally, patients suffering from OV with low MLDIS were more sensitive to immunotherapy. Meanwhile, patients with low MLDIS might benefit from chemotherapy, and 19 compounds that may be potential agents for patients with low MLDIS were identified. MLDIS presents an appealing instrument for the identification of patients at high/low risk. This could enhance the precision treatment, ultimately guiding the clinical management of OV.
Chemokine N‐terminal‐derived peptides differentially regulate signaling by the receptors CCR1 and CCR5

Inflammatory chemokines are often elevated in disease settings, where the largest group of CC‐chemokines are the macrophage inflammatory proteins (MIP), which are promiscuous for the receptors CCR1 and CCR5. MIP chemokines, such as CCL3 and CCL5 are processed at the N terminus, which influences signaling in a highly diverse manner. Here, we investigate the signaling capacity of peptides corresponding to truncated N termini. These 3–10‐residue peptides displayed weak potency but, surprisingly, retained their signaling on CCR1. In contrast, none of the peptides generated a signal on CCR5, but a CCL3‐derived tetrapeptide was a positive modulator boosting the signal of several chemokine variants on CCR5. In conclusion, chemokine N termini can be mimicked to produce small CCR1‐selective agonists, as well as CCR5‐selective modulators.