Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of dietary Garlic extract on growth, feeding parameters, hematological indices and body composition of Litopenaeus vannamei

In this study, Effects of garlic (Allium sativum) extract on growth indices and hemolymph parameters of Litopenaeus vannamei with mean weight 18.21±0.29 g were studied for a period of 56 days. This study was conducted inside 300-liter polyethylene containers as four treatments each with four replicates and each replicate testing 5 shrimps. A basic diet supplemented by 0 (control), 40, 80 and 100 ppm of garlic extract was provided for shrimps. Shrimp biometry was performed at the end of experiment and hemolymph was collected by 2ml syringe. The results showed that garlic extract positively affected daily feed intake, feed conversion efficiency, protein efficiency ratio, molting rate (P<0.05), but no significant change in weight gain rate, specific growth rate, condition factor and hepatosomatic index (P>0.05). Also, treated showed significant changes in body protein (increased levels), fat and ash composition (decreased levels) compared with control group (P<0.05). Total hemocytes count was not affected but differential hemocytes count and total plasma protein was significantly changed treated shrimps compared with control shrimps (P<0.05). Based on the results obtained from this study, garlic extract may be applied as a food supplementation in shrimp aquaculture.
Supplementary material for Learning Across Tasks and Domains

We report here additional experiments to asses the contribution of the different components of AT/DT. In Sec. 1.1 we conduct a study on the performance achievable on the training domain A with G1→2. In Sec. 1.2 we show ablation studies to confirm the key role ofG1→2 in our formulation. In Sec. 1.3 we perform tests considering different approaches to build a shared feature representation forNA∪B 1 . In Sec. 1.4 we provide additional details and results on the integration of AT/DT with existing domain adaptation techniques. In Sec. 1.5 we report qualitative results using normal estimation as target task (T2). Finally, in Sec. 2 and Sec. 3 we provide additional details about the training and evaluation processes.
Segmentação do Hipocampo com Múltiplas Redes Neurais Convolucionais 2D Estendido

A segmentação do hipocampo desempenha um papel fundamental no diagnóstico de vários distúrbios cerebrais. Atualmente, a segmentação é uma tarefa manual, demorada e considerada o padrão-ouro na avaliação de métodos automatizados. Durante anos, os métodos automáticos com melhor desempenho foram baseados na abordagem multi-atlas, com DICE de 0.7 a 0.9 dependendo do conjunto de dados utilizado, porem com tempos de execução da ordem de horas por volume. Recentemente, métodos de aprendizado de máquina estão sendo propostos na literatura, com desempenho promissor de tempo de execução e acurácia. Neste trabalho, um novo método para a segmentação do hipocampo é apresentado, baseado no consenso de três Redes Neurais Convolucionais (CNN) inspiradas na U-Net, com algumas modificações baseadas em CNNs bem-sucedidas da literatura e uma técnica de extração de regiões que emprega dados vizinhos à área analisada. O principal conjunto de dados utilizado apresenta atrofias do hipocampo resultantes do tratamento da cirurgia de epilepsia. Nosso método (rotulado E2D Consensus) também foi comparado a outros métodos recentes no conjunto de dados públicos HARP. E2D Consensus alcança um desempenho entre 0,87 e 0,96 DICE, em comparação com anotações manuais.
Measuring the effectiveness of improved versions of sdhash similarity tool

The use of Approximate Matching (AM) functions on digital forensic investigations allow practitioners to find similar data in an efficient by the use of digests, compact representations of objects. By comparing the object digests, a score related to the level of similarity is produced. Many functions were developed over years, but one that stood out and have been target of constant research is sdhash. In this work, we show that the open source implementation of sdhash present some bugs and issues in the digest generation process. We fixed the bugs and evaluate the impact of them in the similarity assessment. Moreover, we show that standard evaluation metrics (such as recall and precision) were not enough to highlight the benefits of the fixes, and a new metric is necessary. We finish our paper by proposing a new way of assessing the score quality of AM tools and present future work.
Enhancing Interpretability in Factor Analysis by Means of Mathematical Optimization

Abstract Exploratory Factor Analysis (EFA) is a widely used statistical technique to discover the structure of latent unobserved variables, called factors, from a set of observed variables. EFA exploits the property of rotation invariance of the factor model to enhance factors’ interpretability by building a sparse loading matrix. In this paper, we propose an optimization-based procedure to give meaning to the factors arising in EFA by means of an additional set of variables, called explanatory variables, which may include in particular the set of observed variables. A goodness-of-fit criterion is introduced which quantifies the quality of the interpretation given this way. Our methodology also exploits the rotational invariance of EFA to obtain the best orthogonal rotation of the factors, in terms of the goodness-of-fit, but making them match to some of the explanatory variables, thus going beyond traditional rotation methods. Therefore, our approach allows the analyst to interpret the factors not only in terms of the observed variables, but in terms of a broader set of variables. Our experimental results demonstrate how our approach enhances interpretability in EFA, first in an empirical dataset, concerning volumes of reservoirs in California, and second in a synthetic data example.
The food environment in Latin America: a systematic review with a focus on environments relevant to obesity and related chronic diseases

Abstract Objective: Food environments may be contributing to the rapid increase in obesity occurring in most Latin American (LA) countries. The present study reviews literature from LA that (i) describes the food environment and policies targeting the food environment (FEP); and (ii) analytic studies that investigate associations between the FEP and dietary behaviours, overweight/obesity and obesity related chronic diseases. We focus on six dimensions of the FEP: food retail, provision, labelling, marketing, price and composition. Design: Systematic literature review. Three databases (Web of Science, SciELO, LILACS) were searched, from 1 January 1999 up to July 2017. Two authors independently selected the studies. A narrative synthesis was used to summarize, integrate and interpret findings. Setting: Studies conducted in LA countries. Participants: The search yielded 2695 articles of which eighty-four met inclusion criteria. Results: Most studies were descriptive and came from Brazil (61 %), followed by Mexico (18 %) and Guatemala (6 %). Studies were focused primarily on retail/provision (n 27), marketing (n 16) and labelling (n 15). Consistent associations between availability of fruit and vegetable markets and higher consumption of fruits and vegetables were found in cross-sectional studies. Health claims in food packaging were prevalent and mostly misleading. There was widespread use of marketing strategies for unhealthy foods aimed at children. Food prices were lower for processed relative to fresh foods. Some studies documented high sodium in industrially processed foods. Conclusions: Gaps in knowledge remain regarding policy evaluations, longitudinal food retail studies, impacts of food price on diet and effects of digital marketing on diet/health.
Shared decision making in routine clinical care of patients with rheumatoid arthritis: an assessment of audio-recorded consultations

Objectives Although shared decision making (SDM) is advocated in rheumatoid arthritis (RA) treatment, it is largely unclear when, how and to what extent SDM is applied in routine clinical care of patients with RA. This study aimed to investigate the level of SDM in RA treatment from an observer perspective and to assess associations between the level of SDM and characteristics of the clinician, patient and consultation. Methods The level of SDM was investigated by scoring audio-recordings of 168 routine consultations with unique patients with the observer patient involvement (OPTION) scale (scale 0–100, higher OPTION scores indicating higher levels of SDM). Associations between the level of SDM and characteristics of the clinician, patient and consultation were assessed using multilevel modelling. Statistical significance was set at p<0.05. Results The mean OPTION score was 28.3 (SD=15.1). The multilevel model included four characteristics: clinician age, patient age, consultation duration and type of treatment decision. There were significant, positive associations between the level of SDM and the consultation duration (b=0.63, 95% CI 0.16 to 1.11), decision for stopping and/or starting medication (b=14.30, 95% CI 5.62 to 22.98), decision for adjusting medication doses (b=8.36, 95% CI 3.92 to 12.81) and decision for administering single dose glucocorticoids (b=15.03, 95% CI 9.12 to 20.93). Thus, a higher level of SDM was significantly associated with a longer consultation duration and the type of treatment decision. No other significant associations were found. Conclusions Overall, the level of SDM in RA treatment leaves room for improvement. To foster SDM in routine clinical care, training programmes on patient-centred communication skills may be helpful.
Changes in Energy Metabolism Trigger Pupal Diapause Transition of Bactrocera minax After 20-Hydroxyecdysone Application

Correct timing of diapause entry and exit is critical for a species' survival. While many aspects of insect diapause are well-studied, the mechanisms underlying diapause termination remain largely unknown. The Chinese citrus fly, Bactrocera minax, is a univoltine insect with an obligatory pupal diapause. The application of 20-hydroxyecdysone (20E) is known to terminate diapause in B. minax, and we used this approach, along with isobaric tags for relative and absolute quantitation technology, to determine the proteins associated with diapause termination in this fly. Among 2,258 identified proteins, 1,169 proteins significantly differed at 1, 2, and 5 days post-injection of 20E, compared with the solvent-injected control group. Functional annotation revealed that the majority of differentially expressed proteins were enriched in the core energy metabolism of amino acids, proteins, lipids, and carbohydrates as well as in signal transduction pathways including PPAR signaling, Calcium signaling, Glucagon signaling, VEGF signaling, Ras signaling, cGMP-PKG signaling, and cAMP signaling. A combined transcriptomic and proteomic analysis suggested the involvement of energy metabolism in the response of diapause transition. RNA interference experiments disclosed that a 20E injection triggers diapause termination probably through non-genomic actions, rather than nuclear receptor mediated genomic actions. Our results provide extensive proteomic resources for insect diapause transition and offer a potential for pest control by incapacitating the regulation of diapause termination either by breaking diapause prematurely or by delaying diapause termination to render diapausing individuals at a high risk of mortality.
High glucose provokes microvesicles generation from glomerular podocytes via NOX4/ROS pathway

Abstract Microvesicles (MVs) were involved in the pathogenesis of many diseases, such as cardiovascular diseases and diabetes. Oxidative stress played a key role in the development and progression of diabetic nephropathy (DN). Our aim of the present study was to investigate whether high glucose (HG) could provoke MVs generation from podocytes and its potential mechanism. Mouse podocyte clone 5 (MPC-5) was stimulated by HG. The intracellular reactive oxygen species (ROS) of podocytes were measured by fluorescence microscopy with the probe of CM-H2DCFDA and MitoSOX™. Antioxidants N-Acetyl-l-cysteine (NAC) and α lipoic acid (α-LA) were used to treat podocytes after HG stimulation. The rate of podocyte apoptosis was evaluated with Annexin V-FITC by flow cytometry. NOX4 expression was examined and siRNA were performed to explore the mechanism of MVs generation. The quantities of MVs from MPC-5 cells was significantly increased (P<0.05) by 4.6-times after 30 mM glucose stimulation, accompanied with double increased apoptosis. Cellular ROS generation was increased by HG at the peak of 48 h stimulation. HG-induced MVs were significantly decreased by 52.9% after pretreatment by antioxidant NAC. Nevertheless, mitochondrial ROS in podocytes reached a peak at 4 h stimulation, but specific antioxidant α-LA had no effect on the production of MVs (P>0.05). Levels of NOX4 mRNA and protein expression were significantly up-regulated by HG (P<0.05). Podocyte-derived MVs by HG were eliminated by NOX4 siRNA. HG can provoke MVs generation from glomerular podocytes through ROS/NOX4 pathway, not from mitochondrial pathway.
Impact of Fabric Properties on Textile Pressure Sensors Performance

In recent years, wearable technologies have attracted great attention in physical and chemical sensing applications. Wearable pressure sensors with high sensitivity in low pressure range (<10 kPa) allow touch detection for human-computer interaction and the development of artificial hands for handling objects. Conversely, pressure sensors that perform in a high pressure range (up to 100 kPa), can be used to monitor the foot pressure distribution, the hand stress during movements of heavy weights or to evaluate the cyclist’s pressure pattern on a bicycle saddle. Recently, we developed a fully textile pressure sensor based on a conductive polymer, with simple fabrication and scalable features. In this paper, we intend to provide an extensive description on how the mechanical properties of several fabrics and different piezoresistive ink formulation may have an impact in the sensor’s response during a dynamic operation mode. These results highlight the complexity of the system due to the presence of various parameters such as the fabric used, the conductive polymer solution, the operation mode and the desired pressure range. Furthermore, this work can lead to a protocol for new improvements and optimizations useful for adapting textile pressure sensors to a large variety of applications.
Mammalian transient receptor potential TRPA1 channels: from structure to disease.

The Transient Receptor Potential Ankyrin TRPA channels are Ca2+-permeable non-selective cation channels remarkably conserved through the animal kingdom. Mammals have only one member, TRPA1, which is widely expressed in sensory neurons and in non-neuronal cells (such as epithelial cells and hair cells). TRPA1 owes its name to the presence of 14 ankyrin repeats located in the N-terminus of the channel, an unusual structural feature that may be relevant to its interactions with intracellular components. TRPA1 is primarily involved in the detection of an extremely wide variety of exogenous stimuli that may produce cellular damage. This include a plethora of electrophilic compounds that interact with nucleophilic amino acid residues in the channel, and many other chemically-unrelated compounds whose only common feature seems to be their ability to partition in the plasma membrane. TRPA1 has been reported to be activated by cold, heat and mechanical stimuli, and its function is modulated by multiple factors, including Ca2+, trace metals, pH, and reactive oxygen, nitrogen and carbonyl species. TRPA1 is involved in acute and chronic pain, inflammation, plays a role in the pathophysiology of nearly all organ systems and is an attractive target for the treatment of related diseases. Here we review the current knowledge about the mammalian TRPA1 channel, linking its unique structure, widely tuned sensory properties and complex regulation to its roles in multiple pathophysiological conditions.
Detection of Participation and Training Task Difficulty Applied to the Multi-Sensor Systems of Rehabilitation Robots

In the process of rehabilitation training for stroke patients, the rehabilitation effect is positively affected by how much physical activity the patients take part in. Most of the signals used to measure the patients’ participation are EMG signals or oxygen consumption, which increase the cost and the complexity of the robotic device. In this work, we design a multi-sensor system robot with torque and six-dimensional force sensors to gauge the patients’ participation in training. By establishing the static equation of the mechanical leg, the man–machine interaction force of the patient can be accurately extracted. Using the impedance model, the auxiliary force training mode is established, and the difficulty of the target task is changed by adjusting the K value of auxiliary force. Participation models with three intensities were developed offline using support vector machines, for which the C and σ parameters are optimized by the hybrid quantum particle swarm optimization and support vector machines (Hybrid QPSO-SVM) algorithm. An experimental statistical analysis was conducted on ten volunteers’ motion representation in different training tasks, which are divided into three stages: over-challenge, challenge, less challenge, by choosing characteristic quantities with significant differences among the various difficulty task stages, as a training set for the support vector machines (SVM). Experimental results from 12 volunteers, with tasks conducted on the lower limb rehabilitation robot LLR-II show that the rehabilitation robot can accurately predict patient participation and training task difficulty. The prediction accuracy reflects the superiority of the Hybrid QPSO-SVM algorithm.
Adjustments of medication dosages in patients with renal impairment in Botswana; findings and implications to improve patient care

ABSTRACT Background and aims: Medication dosage adjustments for renally impaired patients have not been studied in Botswana. This study was conducted to determine prescribing practices among patients with renal impairment in medical wards to improve future patient care. Methods: We conducted a retrospective study involving medical charts of patients admitted at a tertiary level hospital in Gaborone Botswana. Study participants included all patients admitted between August and October 2016 who were hospitalized for ≥24 h. ‘Drug prescribing in renal failure: dosing guidelines for adults and children'. was used to determine the extent of dosage adjustments. A logistic regression model was used to assess which patient factors were associated with inappropriate dosage adjustment. Results: Twenty-nine percent (233/804) of patients had renal impairment. Of these, 184 patients with renal impairment were included in the final analysis. There were 1143 prescription entries, of which 20.5% (n = 234) required dosage adjustment for renal function but only 45.7% (n = 107) were adjusted correctly. Of note, 112 patients were prescribed at least one drug that required dosage adjustment and only 30.4% (n = 34) patients had all of their medications appropriately adjusted. Patient factors associated with inappropriate dosage adjustment included a higher number of medicines being prescribed. Mortality among patients with renal impairment was independently associated with higher scores of the Charlson comorbidity index and hospital stay duration of 1–7 days. Conclusion: The renal function status of patients was not sufficiently taken into account when prescribing medicines especially in patients with severely impaired kidney function in Botswana. Continuous medical education needs to be encouraged to address this, which is being implemented. We will be following this up in future studies.
Subclinical leaflet thrombosis is associated with impaired reverse remodelling after transcatheter aortic valve implantation.

AIMS Cardiac CT is increasingly applied for planning and follow-up of transcatheter aortic valve implantation (TAVI). However, there are no data available on reverse remodelling after TAVI assessed by CT. Therefore, we aimed to evaluate the predictors and the prognostic value of left ventricular (LV) reverse remodelling following TAVI using CT angiography. METHODS AND RESULTS We investigated 117 patients with severe, symptomatic aortic stenosis (AS) who underwent CT scanning before and after TAVI procedure with a mean follow-up time of 2.6 years after TAVI. We found a significant reduction in LV mass (LVM) and LVM indexed to body surface area comparing pre- vs. post-TAVI images: 180.5 ± 53.0 vs. 137.1 ± 44.8 g and 99.7 ± 25.4 vs. 75.4 ± 19.9 g/m2, respectively, both P < 0.001. Subclinical leaflet thrombosis (SLT) was detected in 25.6% (30/117) patients. More than 20% reduction in LVM was defined as reverse remodelling and was detected in 62.4% (73/117) of the patients. SLT, change in mean pressure gradient on echocardiography and prior myocardial infarction was independently associated with LV reverse remodelling after adjusting for age, gender, and traditional risk factors (hypertension, body mass index, diabetes mellitus, and hyperlipidaemia): OR = 0.27, P = 0.022 for SLT and OR = 0.22, P = 0.006 for prior myocardial infarction, OR = 1.51, P = 0.004 for 10 mmHg change in mean pressure gradient. Reverse remodelling was independently associated with favourable outcomes (HR = 0.23; P = 0.019). CONCLUSION TAVI resulted in a significant LVM regression on CT. The presence of SLT showed an inverse association with LV reverse remodelling and thus it may hinder the beneficial LV structural changes. Reverse remodelling was associated with improved long-term prognosis.
Uncovering the In Vivo Proxisome Using Proximity‐Tagging Methods

The development of new approaches is critical to gain further insights into biological processes that cannot be obtained by existing methods or technologies. The detection of protein–protein interaction is often challenging, especially for weak and transient interactions or for membrane proteins. Over the last decade, several proximity‐tagging methodologies have been developed to explore protein interactions in living cells. Among those, the most efficient are based on protein partner modification, such as biotinylation or pupylation. Such technologies are based on engineered variants of enzymes like peroxidases or ligases that release reactive molecules, in the presence of specific substrates, that bind surrounding proteins. Fusing a protein of interest (POI) to these enzymes allows the definition of an unbiased “proxisome,” that is, all of the proteins in interaction or in close vicinity of the POI. Here, the different proximity‐labeling tools available are described and comprehensive comparison to discuss advantages and limitations is provided.