Miracle-dz/UniFAR-FTUs huggingface dataset:
Work and Social Adjustment Scale (WSAS): psychometric characteristics of a Spanish adaptation in a clinical population.

BACKGROUND The Work and Social Adjustment Scale (WSAS) is an instrument that can be easily applied for routine evaluation of the impact of mental disorders on patient functioning. In spite of the interest in its use, there is very little information available on its psychometric characteristics and even less in Spanish. AIMS The objective of this study was to analyse its psychometric characteristics. METHOD The sample consisted of 441 patients treated in a community mental health unit. They filled out the WSAS and two psychopathology measures, one for anxiety and the other for depression. Fifty-five of them, chosen at random, were asked to fill out the scale again a second time to explore its temporal reliability. RESULTS The scale showed high internal consistency, a single factor that explained 60.4% of the variance, and temporal reliability of . 78 for the total score. Significant correlations were found between the WSAS scores and the psychopathological measures, as well as significant differences between those working and those on leave. CONCLUSIONS The results confirm the validity and reliability of the scale and support its possible use for routine evaluation of the functional impact of mental disorders.
Facing the quality of life: physical illness, anxiety, and depression symptoms among people living with HIV in rural Zambia – a cross-sectional study

ABSTRACT Widespread access to ART has not improved the quality of life (QoL) for people living with HIV (PLHIV). We used the United Nations Disability project (UNPRPD) evaluation data to examine how physical illness, anxiety, and depression shape the QoL of PLHIV in households receiving the social cash transfers safety nets in Luapula, Zambia. We explored associations between each outcome – physical illness, anxiety, depression symptoms – and age, gender, poverty, hunger and disability, using univariable and multivariable regressions. We adjusted p-values for multiple hypothesis testing with sharpened Qs. The sample comprised 1925 respondents 16–55 years old, median age 31 (IQR 22–42 years), majority women (n = 1514, 78.6%). Two-thirds (1239, 64.4%) reported having a physical illness, a third (671, 34.9%) anxiety, and nine per cent (366) depression symptoms. More HIV positive people had a disability (34.6%, 53 versus 28.3%, 502; Q = 0.033), were physically ill (72.5%, 111 versus 63.7%, 1128; Q = 0.011), and two-fold (aOR 1.97 95% CI 1.31–2.94) more likely to report depression symptoms than HIV negative peers. Food insecurity and disability among PLHIV may worsen their physical illnesses, anxiety, depression symptoms, and other QoL domains. More research on the quality of life of PLHIV in poverty is required.
New Features of the Open Source Monte Carlo Software Brick-CFCMC: Thermodynamic Integration and Hybrid Trial Moves

We present several new major features added to the Monte Carlo (MC) simulation code Brick-CFCMC for phase- and reaction equilibria calculations (https://gitlab.com/ETh_TU_Delft/Brick-CFCMC). The first one is thermodynamic integration for the computation of excess chemical potentials (μex). For this purpose, we implemented the computation of the ensemble average of the derivative of the potential energy with respect to the scaling factor for intermolecular interactions (). Efficient bookkeeping is implemented so that the quantity is updated after every MC trial move with negligible computational cost. We demonstrate the accuracy and reliability of the calculation of μex for sodium chloride in water. Second, we implemented hybrid MC/MD translation and rotation trial moves to increase the efficiency of sampling of the configuration space. In these trial moves, short Molecular Dynamics (MD) trajectories are performed to collectively displace or rotate all molecules in the system. These trajectories are accepted or rejected based on the total energy drift. The efficiency of these trial moves can be tuned by changing the time step and the trajectory length. The new trial moves are demonstrated using MC simulations of a viscous fluid (deep eutectic solvent).
Dietary Nucleotides Alleviate Hepatic Lipid Deposition via Exogenous AMP-Mediated AMPK Activation in Zebrafish.

BACKGROUND Dietary nucleotides (NTs) have been reported to affect hepatic function and composition. However, the effects on hepatic lipid deposition are less studied. OBJECTIVES We aimed to identify the regulatory role of dietary NTs in hepatic lipid deposition of zebrafish and elucidate the underlying mechanisms. METHODS Zebrafish (60 ± 1.69 mg; 1 mo old) were fed control diet (16.2% energy as fat) or diet supplemented with 0.1% NTs or 0.02% AMP in feeding experiments 1 and 2. Experiment 3 was conducted with zebrafish larvae. In experiment 4, 1-mo-old zebrafish were fed a high-fat diet (HFD, 38.2% energy as fat) or an HFD supplemented with 0.1% NTs or 0.02% AMP. Hepatic lipid deposition was evaluated by triglyceride (TG) content and staining. Phosphorylation of AMP-activated protein kinase (AMPK) and acetyl-CoA carboxylase (ACC) was assayed by immunoblotting. Zebrafish liver (ZFL) cells were treated with exogenous adenosine. Small interfering RNA was used to knock down AMPK or nucleoside transporter SLC28a1 in ZFL cells. Vivo-morpholino was used to knock down AMPK in zebrafish larvae. RESULTS Dietary 0.1% NTs or 0.02% AMP reduced hepatic TGs by 62% and 32%, respectively, compared with control (P < 0.05). Dietary AMP enhanced hepatic AMPK and ACC phosphorylation. Consistently, exogenous adenosine enhanced AMPK and ACC phosphorylation by 111% and 53%, respectively, in ZFL cells (P < 0.01) and reduced TG content by 56% (P < 0.05). Knockdown of AMPK and SLC28a1 abolished the effect of adenosine on lipid deposition in ZFL cells, and AMPK morpholino blocked the hepatic lipid-lowering effect of dietary AMP in vivo. Finally, dietary NTs and AMP activated AMPK and attenuated hepatic lipid deposition (28% and 30%, P < 0.05) in fish fed an HFD. CONCLUSIONS Dietary NTs and AMP reduce hepatic lipid deposition in zebrafish, which involves exogenous AMP-mediated AMPK activation. Our results suggest that dietary NTs can contribute to alleviation of hepatic steatosis.
The Influence of Carbon Dioxide on Cerebral Autoregulation During Sevoflurane-based Anesthesia in Patients With Type 2 Diabetes

Background: Cerebral autoregulation (CA) continuously adjusts cerebrovascular resistance to maintain cerebral blood flow (CBF) constant despite changes in blood pressure. Also, CBF is proportional to changes in arterial carbon dioxide (CO2) (cerebrovascular CO2 reactivity). Hypercapnia elicits cerebral vasodilation that attenuates CA efficacy, while hypocapnia produces cerebral vasoconstriction that enhances CA efficacy. In this study, we quantified the influence of sevoflurane anesthesia on CO2 reactivity and the CA-CO2 relationship. Methods: We studied patients with type 2 diabetes mellitus (DM), prone to cerebrovascular disease, and compared them to control subjects. In 33 patients (19 DM, 14 control), end-tidal CO2, blood pressure, and CBF velocity were monitored awake and during sevoflurane-based anesthesia. CA, calculated with transfer function analysis assessing phase lead (degrees) between low-frequency oscillations in CBF velocity and mean arterial blood pressure, was quantified during hypocapnia, normocapnia, and hypercapnia. Results: In both control and DM patients, awake CO2 reactivity was smaller (2.8%/mm Hg CO2) than during sevoflurane anesthesia (3.9%/mm Hg; P<0.005). Hyperventilation increased CA efficacy more (3 deg./mm Hg CO2) in controls than in DM patients (1.8 deg./mm Hg CO2; P<0.001) in both awake and sevoflurane-anesthetized states. Conclusions: The CA-CO2 relationship is impaired in awake patients with type 2 DM. Sevoflurane-based anesthesia does not further impair this relationship. In patients with DM, hypocapnia induces cerebral vasoconstriction, but CA efficacy does not improve as observed in healthy subjects.
The attention schema theory in a neural network agent: Controlling visuospatial attention using a descriptive model of attention

Significance Attention, the deep processing of select items, is one of the most important cognitive operations in the brain. But how does the brain control its attention? One proposed part of the mechanism is that the brain builds a model, or attention schema, that helps monitor and predict the changing state of attention. Here, we show that an artificial neural network agent can be trained to control visual attention when it is given an attention schema, but its performance is greatly reduced when the schema is not available. We suggest that the brain may have evolved a model of attention because of the profound practical benefit for the control of attention. In the attention schema theory (AST), the brain constructs a model of attention, the attention schema, to aid in the endogenous control of attention. Growing behavioral evidence appears to support the presence of a model of attention. However, a central question remains: does a controller of attention actually benefit by having access to an attention schema? We constructed an artificial deep Q-learning neural network agent that was trained to control a simple form of visuospatial attention, tracking a stimulus with an attention spotlight in order to solve a catch task. The agent was tested with and without access to an attention schema. In both conditions, the agent received sufficient information such that it should, theoretically, be able to learn the task. We found that with an attention schema present, the agent learned to control its attention spotlight and learned the catch task. Once the agent learned, if the attention schema was then disabled, the agent’s performance was greatly reduced. If the attention schema was removed before learning began, the agent was impaired at learning. The results show how the presence of even a simple attention schema can provide a profound benefit to a controller of attention. We interpret these results as supporting the central argument of AST: the brain contains an attention schema because of its practical benefit in the endogenous control of attention.
A novel lncRNA derived from an ultraconserved region: lnc-uc.147, a potential biomarker in luminal A breast cancer

ABSTRACT The human genome contains 481 ultraconserved regions (UCRs), which are genomic stretches of over 200 base pairs conserved among human, rat, and mouse. The majority of these regions are transcriptionally active (T-UCRs), and several have been found to be differentially expressed in tumours. Some T-UCRs have been functionally characterized, but of those few have been associated to breast cancer (BC). Using TCGA data, we found 302 T-UCRs related to clinical features in BC: 43% were associated with molecular subtypes, 36% with oestrogen-receptor positivity, 17% with HER2 expression, 12% with stage, and 10% with overall survival. The expression levels of 12 T-UCRs were further analysed in a cohort of 82 Brazilian BC patients using RT-qPCR. We found that uc.147 is high expressed in luminal A and B patients. For luminal A, a subtype usually associated with better prognosis, high uc.147 expression was associated with a poor prognosis and suggested as an independent prognostic factor. The lncRNA from uc.147 (lnc-uc.147) is located in the nucleus. Northern blotting results show that uc.147 is a 2,8 kb monoexonic trancript, and its sequence was confirmed by RACE. The silencing of uc.147 increases apoptosis, arrests cell cycle, and reduces cell viability and colony formation in BC cell lines. Additionally, we identifed 19 proteins that interact with lnc-uc.147 through mass spectrometry and demonstrated a high correlation of lnc-uc.147 with the neighbour gene expression and miR-18 and miR-190b. This is the first study to analyse the expression of all T-UCRs in BC and to functionally assess the lnc-uc.147.
Fluid–structure interaction analysis on motion control of a self-propelled flexible plate near a rigid body utilizing PD control

Inspired by a previous experimental study of fish swimming near a cylinder, we numerically investigate the swimming and station-holding behavior of a flexible plate ahead of a circular cylinder whose motion is controlled by a proportional–derivative (PD) controller. Specifically, the deformation of this two-dimensional plate is actuated by a periodically varying external force applied on the body surface, which mimics the fish muscle force to produce propulsive thrust. The actuation force amplitude is dynamically adjusted by a feedback controller to instruct the plate to swim the desired distance from an initial position to a target location and then hold the station there. Instead of directly using the instantaneous position signal, an average speed measured over one force actuation period is proposed with the inclusion of instantaneous position information to form the tracking error for the PD control. Our results show that the motion control of swimming and station holding has been achieved by this simple but effective feedback control without large overshoot when approaching the target at different flow conditions and actuation force formulas. Although the swimming distance remains the same, a plate whose initial position is closer to the cylinder requires less energy expenditure to swim to the target location and hold the station there. This is because the low-pressure zone near the trailing edge of the plate is reduced in size, which provides drag reduction, contributing to reduced swimming energy. A higher Reynolds number also leads to energy savings. Under the same control strategy, the swimming performance is more affected by the force-frequency while the phase shift of the actuation force has a less significant impact.
What sixty years of research says about the effectiveness of patient education on health: a second order meta-analysis

ABSTRACT Although meta-analyses have examined the association between patient education and health, the validity and quality of this evidence have not been comprehensively assessed. This second order meta-analysis combined previous meta-analyses that examined the effectiveness of patient education on health outcomes as an overall weighted grand mean . Further, measures of methodological quality, meaningful variability across first order meta-analyses, and evidence for publication bias were examined. Forty meta-analyses were identified, investigating 156 associations between patient education and health summarizing data from over 776 studies including more than 74.947 patients. Quantitative analyses showed that patient education positively affects health outcomes with = 0.316 (95% CI [0.304, 0.329]). Summarizing data exclusively from randomized controlled trials indicated a causal effect. Patient education was effective for patients with neoplasms, diabetes, mental and behavioral disorders, diseases of the circulatory system, the respiratory system, and the musculoskeletal system. Patient education was effective in the reduction of medication use, pain, and visits to medical facilities, and significantly improved physiological, physical, psychological outcomes, and patients’ general function. Overall, the findings reveal firm evidence for the effectiveness of patient education on health outcomes. However, theory-based interventions are lacking and need to be implemented to enable a successful transfer from theory to practice.
The impact of circadian timing on energy balance: an extension of the energy balance model

ABSTRACT A significant proportion of the population is classified as having overweight or obesity. One framework which has attempted to explain biobehavioral mechanisms influencing the development of overweight and obesity is the energy balance model. According to this model, the body continually attempts to balance energy intake with energy expenditure. When energy intake and energy expenditure become imbalanced, there is an increase in homeostatic and allostatic pressure, generally to either increase energy intake or decrease energy expenditure, so as to restore energy homeostasis.Recent research has indicated that circadian aspects of energy intake and energy expenditure may influence energy balance. This paper provides a narrative review of existing evidence of the role of circadian timing on components of energy balance. Research on the timing of food intake, physical activity, and sleep indicates that unhealthy timing is likely to increase risk of weight gain. Public health guidelines focus on how much individuals eat and sleep, what foods are consumed, and the type and frequency of exercise, but the field of circadian science has begun to demonstrate that when these behaviors occur may also influence overweight and obesity prevention and treatment efforts.
Phenomics Approach to Investigate Behavioral Toxicity of Environmental or Occupational Toxicants in Adult Zebrafish (Danio rerio)

Over the last few years, environmental pollution, especially water pollution, has become a serious issue worldwide. Thus, methods that can help us understand the impact and effects of these pollutants, especially on aquatic animals, are needed. Behavioral assessment has emerged as a crucial tool in toxicology and pharmacology because many studies have shown, in multiple animal models, that various pharmacological compounds can alter behavior, with many of the findings being translatable to humans. Moreover, behavior study can also be used as a suitable indicator in the ecotoxicological risk assessment of pollutants. Several model organisms, especially rodent models, have been extensively employed for behavior studies. However, assessments using this model are generally time consuming, expensive, and require extensive facilities for housing experimental animals. Moreover, behavioral studies typically use different measurements and assessment tools, making comparisons difficult. In addition, even though behavioral phenomics has the potential to comprehensively illustrate the toxicities of chemicals, there is only a limited number of studies focusing on animal behavior using such a global approach. Here, we describe a phenomics approach that can be used to investigate the impact of pollutants using zebrafish. The approach consists of several behavioral tests, including response to a novel environment, mirror‐reflection image, predator fish, and conspecifics, after exposure to a test chemical. Phenotype fingerprinting, a method for summarizing individual phenotypes based on the results of the behavioral tests, is then conducted to reduce data complexity and display the pattern of each compound on behavioral phenotypes in zebrafish. This approach may be useful to researchers studying the potential adverse effects of different pollutants. © 2021 Wiley Periodicals LLC.
Entanglement transport and a nanophotonic interface for atoms in optical tweezers

Description Quantum trapping and shuffling Programmable arrays of atoms or ions trapped in optical potentials have recently emerged as a leading platform for quantum simulation. Being able to interface into these arrays to access the quantum information being processed and pass it along to another module remains a challenge. Ðorđević et al. developed a hybrid quantum system that combines atoms held in optical tweezers and a nanophotonic cavity to demonstrate full quantum control, efficient quantum nondestructive readout, and entanglement of atom pairs (see the Perspective by Kaufman). By combining atomic manipulation both inside and away from the cavity field and shuffling the atom qubits into and out of the cavity mode, the authors demonstrate a viable optical interface that could be scaled to larger systems. —ISO Optical tweezing of atom arrays combined with a photonic cavity leads to a viable interface for quantum information processing. The realization of an efficient quantum optical interface for multi-qubit systems is an outstanding challenge in science and engineering. Using two atoms in individually controlled optical tweezers coupled to a nanofabricated photonic crystal cavity, we demonstrate entanglement generation, fast nondestructive readout, and full quantum control of atomic qubits. The entangled state is verified in free space after being transported away from the cavity by encoding the qubits into long-lived states and using dynamical decoupling. Our approach bridges quantum operations at an optical link and in free space with a coherent one-way transport, potentially enabling an integrated optical interface for atomic quantum processors.
Distinguishable spatial-spectral feature learning neural network framework for motor imagery-based brain–computer interface

Objective. Spatial and spectral features extracted from electroencephalogram (EEG) are critical for the classification of motor imagery (MI) tasks. As prevalently used methods, the common spatial pattern (CSP) and filter bank CSP (FBCSP) can effectively extract spatial-spectral features from MI-related EEG. To further improve the separability of the CSP features, we proposed a distinguishable spatial-spectral feature learning neural network (DSSFLNN) framework for MI-based brain–computer interfaces (BCIs) in this study. Approach. The first step of the DSSFLNN framework was to extract FBCSP features from raw EEG signals. Then two squeeze-and-excitation modules were used to re-calibrate CSP features along the band-wise axis and the class-wise axis, respectively. Next, we used a parallel convolutional neural network module to learn distinguishable spatial-spectral features. Finally, the distinguishable spatial-spectral features were fed to a fully connected layer for classification. To verify the effectiveness of the proposed framework, we compared it with the state-of-the-art methods on BCI competition IV datasets 2a and 2b. Main results. The results showed that the DSSFLNN framework can achieve a mean Cohen’s kappa value of 0.7 on two datasets, which outperformed the state-of-the-art methods. Moreover, two additional experiments were conducted and they proved that the combination of band-wise feature learning and class-wise feature learning can achieve significantly better performance than only using either one of them. Significance. The proposed DSSFLNN can effectively improve the decoding performance of MI-based BCIs.