Miracle-dz/UniFAR-FTUs huggingface dataset:
ASB4 modulates central melanocortinergic neurons and calcitonin signaling to control satiety and glucose homeostasis

Variants in the gene encoding ankyrin repeat and SOCS box–containing 4 (ASB4) are linked to human obesity. Here, we characterized the pathways underlying the metabolic functions of ASB4. Hypothalamic Asb4 expression was suppressed by fasting in wild-type mice but not in mice deficient in AgRP, which encodes Agouti-related protein (AgRP), an appetite-stimulating hormone, suggesting that ASB4 is a negative target of AgRP. Many ASB4 neurons in the brain were adjacent to AgRP terminals, and feeding induced by AgRP neuronal activation was disrupted in Asb4-deficient mice. Acute knockdown of Asb4 in the brain caused marked hyperphagia due to increased meal size, and Asb4 deficiency led to increased meal size and food intake at the onset of refeeding, when very large meals were consumed. Asb4-deficient mice were resistant to the meal-terminating effects of exogenously administered calcitonin and showed decreased neuronal expression of Calcr, which encodes the calcitonin receptor. Pro-opiomelanocortin (POMC) neurons in the arcuate nucleus in mice are involved in glucose homeostasis, and Asb4 deficiency specifically in POMC neurons resulted in glucose intolerance that was independent of obesity. Furthermore, individuals with type 2 diabetes showed reduced ASB4 abundance in the infundibular nuclei, the human equivalent of the arcuate nucleus. Together, our results indicate that ASB4 acts in the brain to improve glucose homeostasis and to induce satiety after substantial meals, particularly those after food deprivation. Description The neural circuits by which ASB4 affects appetite and glucose homeostasis are revealed. The metabolic attributes of ASB4 Variants in the ASB4 gene are associated with obesity. Using mice with acute, global, or neuron-specific deficiency in Asb4, Vagena et al. characterized how ASB4-positive neurons participated in the neural circuits that drive food intake, mediate satiety, and affect glucose homeostasis. ASB4 was required for limiting excessive feeding after fasting and for the effects of the satiety signal calcitonin. Moreover, ASB4 was required for proper glucose handling mediated by a specific neuron subset in a mouse brain region called the arcuate nucleus, and diabetic individuals showed decreased ASB4 abundance in the human equivalent of the arcuate nucleus. Thus, ASB4-positive neurons control behaviors and physiological processes that are important for metabolic health.
Prevalence of specific micronutrient deficiencies in urban school going children and adolescence of India: A multicenter cross-sectional study

Introduction Childhood and adolescence require adequate amount of micronutrients for normal growth and development. The primary objective of study was to assess the prevalence of deficiencies of Vitamins (Vitamin A, 25 Hydroxy Vitamin D, Vitamin B12 and Folate) and minerals (Calcium, Zinc, Selenium and Iron), among urban school going children aged 6–11 and 12–16 years in ten cities of India. Secondary objective was to find the association between micronutrient deficiencies with sociodemographic and anthropometric indicators. Methods A multi-center cross-sectional study was conducted across India. Participants in the age groups of 6 to 11 years (group 1) and 12 to 16 years (group 2) were selected from randomly chosen schools from each center. Data on socio economic status, anthropometric measures was collected. Blood samples were collected for biochemical analysis of micronutrients. Point estimates and 95% confidence intervals was used to assess the prevalence of deficiencies. Associations were observed using chi square, student t test and ANOVA test. Results From April 2019 to February 2020, 2428 participants (1235 in group 1 and 1193 group 2) were recruited from 60 schools across ten cites. The prevalence of calcium and iron deficiency was 59.9% and 49.4% respectively. 25 Hydroxy Vitamin D deficiency was seen in 39.7% and vitamin B12 in 33.4% of subjects. Folate, Selenium and Zinc were deficient in 22.2%, 10.4% and 6.8% of subjects respectively. Vitamin A deficiency least (1.6%). Anemia was prevalent in 17.6% subjects and was more common among females. Conclusion One or more micronutrient deficiencies are found in almost one half of school going children in urban area. Hence efforts must be made to combat these on priority. Trial registration number CTRI/2019/02/017783.
Invasive chameleons released from predation display more conspicuous colors

Conspicuous social and sexual signals are predicted to experience pronounced character release when natural selection via predation is relaxed. However, we have few good examples of this phenomenon in the wild and none in species with dynamic color change. Here, we show that Jackson’s chameleons inadvertently introduced from Kenya to Hawaii (Oahu), where there are no coevolved, native lizard predators, experienced pronounced character release of color signals. Hawaiian chameleons displayed more conspicuous social color signals than Kenyan chameleons during male contests and courtship, were less cryptic in response to bird and snake predators, and showed greater change between display and antipredator color states. Hawaiian chameleon display colors were also more conspicuous in their local than ancestral habitats, consistent with local adaptation of social signals. These results demonstrate that relaxed predation pressure can result in character release of dynamic social signals in introduced species experiencing strong sexual selection.
Cohort profile: the Swedish study of SUDden cardiac Death in the Young (SUDDY) 2000–2010: a complete nationwide cohort of SCDs

Purpose The rationale behind the SUDden cardiac Death in the Young (SUDDY) cohort was to provide a complete nationwide, high-quality platform with integrated multisource data, for clinical and genetic research on sudden cardiac death (SCD) in the young, with the ultimate goal to predict and prevent SCD. Participants The cohort contains all SCD victims <36 years, in Sweden during the period 2000–2010. We assigned five population-based controls per case, together with parents of cases and controls, in total 15 633 individuals. Data of all individuals were extracted from multiple mandatory registries; the National Patient Registry, the Medical Birth Registry, the Prescribed Drug registry, the Cause of Death registry, the Multigeneration Registry, combined with socioeconomic data from Statistics Sweden. From SCD victims, the autopsy report, medical records, ECGs, parental information and biological samples were gathered. Findings to date We identified 903 individuals diagnosed with SCD (67% men, 33% women). The cases comprised 236 infants <1 year of age (26%), 90 individuals aged 1–15 years (10%), 186 individuals aged 15–25 years (21%) and 391 aged 25–35 years (43%). Hospitalisations and outpatient clinic visits due to syncope were significantly more common among cases than controls. DNA obtained from dried blood spots tests (DBS) stored from birth was equally suitable as venous blood samples for high-throughput genetic analysis of SCD cases. Future plans We will explore the SUDDY cohort for symptoms and healthcare consumption, socioeconomic variables and family history of SCD. Furthermore, we will perform whole exome sequencing analysis on DNA of cases obtained from DBS or postmortem samples together with parental blood samples in search for gene variants associated with cardiac disease. The genetic analysis together with data compiled in the nationwide cohort is expected to improve current knowledge on the incidence, aetiology, clinical characteristics and family history of SCD.
Influence of different dietary fibre contents in the diet on feather pecking, locomotor activity and performance of laying hens

ABSTRACT 1. This study investigated the effects of three diets with increasing proportions of insoluble dietary fibre (3%, 6% and 9%) but with similar metabolisable energy on behaviour, plumage condition and laying performance of Lohmann Tradition hens. 2. At 21 weeks of age, four groups of 20 hens each (= four replicates/treatment) were randomly assigned to one of the three feeding treatments and exclusively fed with their assigned feed until the end of the laying period. 3. Severe feather pecking decreased with increasing fibre content (3%: 0.78 pecks/30 min/hen, 6%: 0.31, 9%: 0.12; P < 0.0001). In contrast, no effect of fibre was seen for gentle feather pecking (P = 0.19) and aggressive pecking (P = 0.84). The number of free feathers in the littered area increased with increasing fibre content (3%: 0.06 feathers/625cm2/hen, 6%: 0.09, 9%: 0.16; P = 0.0074). Over time, plumage quality worsened in all hens, but was consistently better with increasing fibre content (fibre content × sampling period; P < 0.0001). Locomotor activity was similar across all treatments, except for a slight decrease in hens fed the 3% fibre diet at the end of the experimental period. No effect of fibre content on hens’ weight (P = 0.75) was detectable. Similarly, performance did not differ between hens fed varying dietary fibre. 4. The results supported the assumption that increasing dietary fibre helps to reduce the risk for the occurrence of feather pecking in laying hens, i.e. improve well-being, while having no negative effects on performance.
Anti‐inflammatory activities of natural cyclopeptide RA‐XII in colitis‐associated colon cancer mouse model and its effect on gut microbiome

Colorectal cancer (CRC), the third most common cancer globally, is associated with intestinal inflammation that leads to poor prognosis. RA‐XII, a natural cyclopeptide, has previously been reported to possess anti‐tumor activities. Here, the anti‐inflammatory activities of RA‐XII were investigated in colitis‐associated colon cancer mice and a co‐culture in vitro model, in which colon cancer cells HCT116 and macrophages RAW264.7 were grown together to mimic the inflammatory microenvironment of CRC. Changes of inflammatory‐related molecules and protein expressions in cells were evaluated after RA‐XII incubation. Besides, azoxymethane and dextran sulfate sodium‐induced colitis‐associated colon cancer mice were treated with RA‐XII for 24 days, inflammatory parameters and gut microbiome alterations were studied. Our results showed that RA‐XII reversed the inflammatory responses of RAW264.7 cells induced by LPS and modulated the protein expressions of AKT, STAT3/p‐STAT3, P70S6K, NF‐κB and GSK3β and suppressed the expression of LC3A/B in HCT116 cells in co‐culture system. RA‐XII treatment restored the colitis damage in colon, reduced colon tumors numbers and decreased inflammatory factors (IL‐6, IL‐10 and TNF‐α). The role of RA‐XII on regulating gut microbiome was also demonstrated for the first time. In conclusion, our findings provided new scientific evidence for developing RA‐XII as a potent anti‐inflammatory agent for CRC.
Diabetic nephropathy ameliorated in patients with normal home blood pressure compared to those with isolated high home systolic blood pressure: A 5-year prospective cohort study among patients with type 2 diabetes mellitus

Background: Using normal home blood pressure (home BP) as a reference, isolated high home systolic blood pressure (IH-home SBP) increases the risk of diabetic nephropathy. However, whether diabetic nephropathy would improve among diabetic patients without IH-home SBP has not been previously assessed. Methods: This prospective 5-year cohort study of 264 patients with moderate or severe albuminuria investigated the effect of IH-home SBP or normal home BP on the risk of diabetic nephropathy in patients with type 2 diabetes mellitus. Improvement of diabetic nephropathy was defined as remission or regression from moderate or severe albuminuria to normal or mildly increased albuminuria. Results: Improvement of diabetic nephropathy was shown in 59 out of 264 patients during 5 years. The adjusted odds ratio (95% confidence interval) of normal home BP for improving diabetic nephropathy was 2.52 (1.01–5.99, p = 0.05). Conclusion: Normal home BP had relation to an improvement in diabetic nephropathy among type 2 diabetic patients with moderate and severe increased albuminuria in the observation period of 5 years. Good home BP control might be valuable to ameliorate diabetic nephropathy.
Machine Learning in Cardiac Surgery: Predicting Mortality and Readmission

Predicting outcomes in open-heart surgery can be challenging. Unexpected readmissions, long hospital stays, and mortality have economic implications. In this study, we investigated machine learning (ML) performance in data visualization and predicting patient outcomes associated with open-heart surgery. We evaluated 8,947 patients who underwent cardiac surgery from April 2006 to January 2018. Data visualization and classification were performed at cohort-level and patient-level using clustering, correlation matrix, and seven different predictive models for predicting three outcomes (“Discharged,” “Died,” and “Readmitted”) at binary level. Cross-validation was used to train and test each dataset with the application of hyperparameter optimization and data imputation techniques. Machine learning showed promising performance for predicting mortality (AUC 0.83 ± 0.03) and readmission (AUC 0.75 ± 0.035). The cohort-level analysis revealed that ML performance is comparable to the Society of Thoracic Surgeons (STS) risk model even with limited number of samples (e.g., less than 3,000 samples for ML versus more than 100,000 samples for the STS risk models). With all cases (8,947 samples, referred as patient-level analysis), ML showed comparable performance to what has been reported for the STS models. However, we acknowledge that it remains unknown at this stage as to how the model might perform outside the institution and does not in any way constitute a comparison of the performance of the internal model with the STS model. Our study demonstrates a systematic application of ML in analyzing and predicting outcomes after open-heart surgery. The predictive utility of ML in cardiac surgery and clinical implications of the results are highlighted.
Hippocampus mediates nocebo impairment of opioid analgesia through changes in functional connectivity

The neural mechanisms underlying placebo analgesia have attracted considerable attention over the recent years. In contrast, little is known about the neural underpinnings of a nocebo‐induced increase in pain. We previously showed that nocebo‐induced hyperalgesia is accompanied by increased activity in the hippocampus that scaled with the perceived level of anxiety. As a key node of the neural circuitry of perceived threat and fear, the hippocampus has recently been proposed to coordinate defensive behaviour in a context‐dependent manner. Such a role requires close interactions with other regions involved in the detection of and responses to threat. Here, we investigated the functional connectivity of the hippocampus during nocebo‐induced hyperalgesia. Our results show an increase in functional connectivity between hippocampus and brain regions implicated in the processing of sensory‐discriminative aspects of pain (posterior insula and primary somatosensory/motor cortex) as well as the periaqueductal grey. This nocebo‐induced increase in connectivity scaled with an individual's increase in anxiety. Moreover, hippocampus connectivity with the amygdala was negatively correlated with the pain intensity reported during nocebo hyperalgesia relative to the placebo condition. Our findings suggest that the hippocampus links nocebo‐induced anxiety to a heightened responsiveness to nociceptive input through changes in its crosstalk with pain‐modulatory brain areas.
Subspace approach to performance modelling of range-sidelobe suppressed waveforms

An important concern in radar is understanding the consequence of waveform design constraints on the signal-to-interference-plus-noise ratio (SINR) performance. In this study, the authors develop performance models for the attendant drop in SINR as an integrated sidelobe (ISL) constraint is placed on the waveform. The performance models are developed using an eigenbasis subspace approach. The authors validate the performance models against measured data and conclude that the proposed approach provides reasonable performance modelling of the SINR as a function of the ISL constraint.
Planning and control of an autonomous hovering airborne dedicated for the monitoring of structures

Today, the inspection of structures is carried out through visual assessments effected by qualified inspectors. This procedure is very expensive and can put the personal in dangerous situations. Consequently, the development of an unmanned aerial vehicle equipped with on-board vision systems is privileged nowadays in order to facilitate the access to unreachable zones. In this context, the main focus in the thesis is developing original methods to deal with planning, reference trajectories generation and tracking issues by a hovering airborne platform. These methods should allow an automation of the flight in the presence of air disturbances and obstacles. Within this framework, we are interested in two kinds of aerial vehicles with hovering capacity: airship and quad-rotors.
Low-Cost Feature-Based Tolerance Optimization of Multi-Band Antennas

Manufacturing inaccuracies are detrimental to performance of engineering designs. Antenna structures are no exception here. The effects of parameter deviations are particularly noticeable for narrow- and multi-band antennas and manifest themselves through relocations of the operating frequencies or bandwidth degradation. The ability to reduce the system sensitivity to tolerances is therefore an important design consideration. Unfortunately, robust design is a challenging task, primarily because it has to be carried out at the level of full-wave electromagnetic (EM) simulation models, which generates considerable computational expenses. In this paper, we propose a novel approach to tolerance optimization of multi-band antennas. The objective is to enlarge the maximum levels of geometry parameter deviations that still ensure perfect (100-percent) fabrication yield. The presented approach involves feature-based regression surrogates as well as the trust-region framework to ensure low cost and convergence of the optimization process. Numerical validation of the method, conducted for a dual- and a triple-band microstrip antenna, corroborates its efficacy with the average robust design cost of only a few dozens of EM analyses of the respective structure.
Employing Intelligent Aerial Data Aggregators for the Internet of Things: Challenges and Solutions

Internet-of-Things (IoT) devices equipped with temperature and humidity sensors and cameras are increasingly deployed to monitor remote and human-unfriendly areas (e.g., farmlands, forests, rural highways, and electricity infrastructures). Aerial data aggregators such as autonomous drones provide a promising solution for collecting sensory data of IoT devices in human-unfriendly environments, enhancing network scalability and connectivity. The flexibility of a drone and favorable line-of-sight connection between the drone and IoT devices can be exploited to improve data reception at the drone. This article first discusses challenges of the drone-assisted data aggregation in IoT networks, such as incomplete network knowledge at the drone, limited buffers of the IoT devices, and lossy wireless channels. Next, we investigate the feasibility of onboard deep-reinforcement-learning-based solutions to allow a drone to learn its cruise control and data collection schedule online. For deep reinforcement learning in a continuous operation domain, deep deterministic policy gradient (DDPG) is suitable to deliver effective joint cruise control and communication decision, using its outdated knowledge of the IoT devices and network states. A case study shows that the DDPG-based framework can take advantage of the continuous actions to substantially outperform existing non-learning-based alternatives.
Clustering Young Children’s Coding Project Scores with Machine Learning

Engaging children in making creative coding projects is a popular approach for young children to develop computational skills. Children learn to transform their ideas and knowledge into personally meaningful projects. However, the connection between children’s coding competencies and their created coding projects remains unclear. This study explored how ScratchJr coding projects created by first and second graders (n=75) differed and whether the project focuses varied by the children’s coding competencies. ScratchJr is a free downloadable tablet game for children ages 5-7 to create animated stories and games. Through unsupervised machine learning algorithms, this study grouped coding project concepts by Principal Component Analysis then classified students into four groups by K-means. The results showed that students across the four groups focused on creating different aspects of the ScratchJr projects. Moreover, the median coding competency score of each student group also differed significantly. This study implies that young children with varying levels of coding competency tend to focus on creating different aspects of ScratchJr projects. Findings from this study can help to inform curriculum designers and teachers on essential approaches for guiding children in creating their own coding projects.
Experimental Evaluation of Transmitted Signal Distortion Caused by Power Allocation in Inter-Cell Interference Coordination Techniques for LTE/LTE-A and 5G Systems

Error vector magnitude (EVM) and out-of-band emissions are key metrics for evaluating in-band and out-band distortions introduced by all potential non-idealities in the transmitters of wireless systems. As EVM is a measure of the quality of the modulated signal/symbols, LTE/LTE-A and 5G systems specify mandatory EVM requirements in transmission for each modulation scheme. This paper analyzes the influence of the mandatory satisfaction of EVM requirements on the design of radio resource management strategies (RRM) (link adaptation, inter-cell interference coordination), specifically in the downlink (DL). EVM depends on the non-idealities of the transmitter implementations, on the allocated power variations between the subcarriers and on the selected modulations. In the DL of LTE, link adaptation is usually executed by adaptive modulation and coding (AMC) instead of power control, but some flexibility in power allocation remains being used. LTE specifies some limits in the power dynamic ranges depending on the allocated modulation, which ensures the satisfaction of EVM requirements. However, the required recommendations concerning the allowed power dynamic range when inter-cell interference coordination (ICIC) and enhanced ICIC (eICIC) mechanisms (through power coordination) are out of specification, even though the EVM performance should be known to obtain the maximum benefit of these strategies. We perform an experimental characterization of the EVM in the DL under real and widely known ICIC implementation schemes. These studies demonstrate that an accurate analysis of EVM is required. It allows a better adjustment of the design parameters of these strategies, and also allows the redefinition of the main criteria to be considered in the implementation of the scheduler/link adaptation concerning the allocable modulation coding scheme (MCS) in each resource block.