Miracle-dz/UniFAR-FTUs huggingface dataset:
Post-Stroke Depression Modulation and in Vivo Antioxidant Activity of Gallic Acid and Its Synthetic Derivatives in a Murine Model System

Gallic acid (3,4,5-trihydroxybenzoic acid, GA) is a plant secondary metabolite, which shows antioxidant activity and is commonly found in many plant-based foods and beverages. Recent evidence suggests that oxidative stress contributes to the development of many human chronic diseases, including cardiovascular and neurodegenerative pathologies, metabolic syndrome, type 2 diabetes and cancer. GA and its derivative, methyl-3-O-methyl gallate (M3OMG), possess physiological and pharmacological activities closely related to their antioxidant properties. This paper describes the antidepressive-like effects of intraperitoneal administration of GA and two synthetic analogues, M3OMG and P3OMG (propyl-3-O-methylgallate), in balb/c mice with post-stroke depression, a secondary form of depression that could be due to oxidative stress occurring during cerebral ischemia and the following reperfusion. Moreover, this study determined the in vivo antioxidant activity of these compounds through the evaluation of superoxide dismutase (SOD) and catalase (Cat) activity, thiobarbituric acid-reactive substances (TBARS) and reduced glutathione (GSH) levels in mouse brain. GA and its synthetic analogues were found to be active (at doses of 25 and 50 mg/kg) in the modulation of depressive symptoms and the reduction of oxidative stress, restoring normal behavior and, at least in part, antioxidant endogenous defenses, with M3OMG being the most active of these compounds. SOD, TBARS, and GSH all showed strong correlation with behavioral parameters, suggesting that oxidative stress is tightly linked to the pathological processes involved in stroke and PSD. As a whole, the obtained results show that the administration of GA, M3OMG and P3OMG induce a reduction in depressive symptoms and oxidative stress.
Feedforward Inhibition Allows Input Summation to Vary in Recurrent Cortical Networks

Abstract Brain computations depend on how neurons transform inputs to spike outputs. Here, to understand input-output transformations in cortical networks, we recorded spiking responses from visual cortex (V1) of awake mice of either sex while pairing sensory stimuli with optogenetic perturbation of excitatory and parvalbumin-positive inhibitory neurons. We found that V1 neurons’ average responses were primarily additive (linear). We used a recurrent cortical network model to determine whether these data, as well as past observations of nonlinearity, could be described by a common circuit architecture. Simulations showed that cortical input-output transformations can be changed from linear to sublinear with moderate (∼20%) strengthening of connections between inhibitory neurons, but this change away from linear scaling depends on the presence of feedforward inhibition. Simulating a variety of recurrent connection strengths showed that, compared with when input arrives only to excitatory neurons, networks produce a wider range of output spiking responses in the presence of feedforward inhibition.
Targeting galectin-1 inhibits pancreatic cancer progression by modulating tumor–stroma crosstalk

Significance Pancreatic ductal adenocarcinoma (PDA) is the third leading of cause of cancer death in the United States and is predicted to be the second one by 2030. The tumor microenvironment is a major source of soluble mediators that influence tumor progression and hinder the success of therapeutic strategies. Using a genetically engineered mouse model and human cell-based systems, we identify galectin-1 (Gal1) as a critical soluble factor capable of regulating tumor–stroma crosstalk promoting proliferation, angiogenesis, and modulation of inflammatory responses, resulting in enhanced tumor development and metastasis. Our data provide an integrated view of the role of Gal1 in the PDA microenvironment and reinforce the high therapeutic value of Gal1 inhibition in PDA treatment. Pancreatic ductal adenocarcinoma (PDA) remains one of the most lethal tumor types, with extremely low survival rates due to late diagnosis and resistance to standard therapies. A more comprehensive understanding of the complexity of PDA pathobiology, and especially of the role of the tumor microenvironment in disease progression, should pave the way for therapies to improve patient response rates. In this study, we identify galectin-1 (Gal1), a glycan-binding protein that is highly overexpressed in PDA stroma, as a major driver of pancreatic cancer progression. Genetic deletion of Gal1 in a Kras-driven mouse model of PDA (Ela-KrasG12Vp53−/−) results in a significant increase in survival through mechanisms involving decreased stroma activation, attenuated vascularization, and enhanced T cell infiltration leading to diminished metastasis rates. In a human setting, human pancreatic stellate cells (HPSCs) promote cancer proliferation, migration, and invasion via Gal1-driven pathways. Moreover, in vivo orthotopic coinjection of pancreatic tumor cells with Gal1-depleted HPSCs leads to impaired tumor formation and metastasis in mice. Gene-expression analyses of pancreatic tumor cells exposed to Gal1 reveal modulation of multiple regulatory pathways involved in tumor progression. Thus, Gal1 hierarchically regulates different events implicated in PDA biology including tumor cell proliferation, invasion, angiogenesis, inflammation, and metastasis, highlighting the broad therapeutic potential of Gal1-specific inhibitors, either alone or in combination with other therapeutic modalities.
Bayesian Dose-Finding in Two Treatment Cycles Based on the Joint Utility of Efficacy and Toxicity

This article proposes a phase I/II clinical trial design for adaptively and dynamically optimizing each patient’s dose in each of two cycles of therapy based on the joint binary efficacy and toxicity outcomes in each cycle. A dose-outcome model is assumed that includes a Bayesian hierarchical latent variable structure to induce association among the outcomes and also facilitate posterior computation. Doses are chosen in each cycle based on posteriors of a model-based objective function, similar to a reinforcement learning or Q-learning function, defined in terms of numerical utilities of the joint outcomes in each cycle. For each patient, the procedure outputs a sequence of two actions, one for each cycle, with each action being the decision to either treat the patient at a chosen dose or not to treat. The cycle 2 action depends on the individual patient’s cycle 1 dose and outcomes. In addition, decisions are based on posterior inference using other patients’ data, and therefore, the proposed method is adaptive both within and between patients. A simulation study of the method is presented, including comparison to two-cycle extensions of the conventional 3 + 3 algorithm, continual reassessment method, and a Bayesian model-based design, and evaluation of robustness. Supplementary materials for this article are available online.
Increased Dependence of Action Selection on Recent Motor History in Parkinson's Disease

It is well known that the basal ganglia are involved in switching between movement sequences. Here we test the hypothesis that this contribution is an instance of a more general role of the basal ganglia in selecting actions that deviate from the context defined by the recent motor history, even when there is no sequential structure to learn or implement. We investigated the effect of striatal dopamine depletion [in Parkinson's disease (PD)] on the ability to switch between independent action plans. PD patients with markedly lateralized signs performed a hand laterality judgment task that involved action selection of their most and least affected hand. Trials where patients selected the same (repeat) or the alternative (switch) hand as in a previous trial were compared, and this was done separately for the most and least affected hand. Behaviorally, PD patients showed switch-costs that were specific to the most affected hand and that increased with disease severity. Functional magnetic resonance imaging (fMRI) showed that this behavioral effect was related to the state of the frontostriatal system: as disease severity increased, contributions of the basal ganglia to the selection process and their effective connectivity with the medial frontal cortex (MFC) decreased, whereas involvement of the MFC increased. We conclude that the basal ganglia are important for rapidly switching toward novel motor plans even when there is no sequential structure to learn or implement. The enhanced MFC activity may result either from reduced focusing abilities of the basal ganglia or from compensatory processes.
Artificial skin for sweating guarded hotplates and manikins based on weft knitted fabrics

Measurement devices such as sweating manikins, cylinders or hotplates are used for testing thermal and moisture transfer properties of clothing or textiles. A critical feature of these measurement devices is the design of the outer covering fabric that tightly enfolds the device like a skin. The artificial skin principally has to match individual requirements because the different sweating devices have different sweating systems and surface compositions. In this study knitted fabrics with different fiber and yarn types are proposed to be used as an artificial skin. Thermal and moisture properties of the fabrics were measured to obtain skin-like characteristics and a mathematical model for the quantification of thermal and moisture-management properties based on geometrical characteristics was developed. The results show that the thermal and moisture-management properties of the fabrics do not only depend on the fiber properties but also relevantly on their geometrical properties such as thickness, diameter and number of stitch pores. For example, thermal resistance is significantly affected by the stitch pore diameter, and evaporative resistance by the fabric thickness. Furthermore, water content and drying speed are determined by the capillary structure, and therefore, are more influenced by yarn and fabric structure parameters, whereas contact angle and wettability are more influenced by the fiber type. In conclusion, the tested fabrics satisfy all the requirements to match the anatomical properties of the human skin; however, two fabric types, PES_19f30_SET and PES_28f48_GL, exhibited superior characteristics suitable for application as artificial skin on measurement devices.
Frequentist and Bayesian approaches for comparing interviewer variance components in two groups of survey interviewers

Survey methodologists have long studied the effects of interviewers on the variance of survey estimates. Statistical models including random interviewer effects are often fitted in such investigations, and research interest lies in the magnitude of the interviewer variance component. One question that might arise in a methodological investigation is whether or not different groups of interviewers (e.g., those with prior experience on a given survey vs. new hires, or CAPI interviewers vs. CATI interviewers) have significantly different variance components in these models. Significant differences may indicate a need for additional training in particular subgroups, or sub-optimal properties of different modes or interviewing styles for particular survey items (in terms of the overall mean squared error of survey estimates). Survey researchers seeking answers to these types of questions have different statistical tools available to them. This paper aims to provide an overview of alternative frequentist and Bayesian approaches to the comparison of variance components in different groups of survey interviewers, using a hierarchical generalized linear modeling framework that accommodates a variety of different types of survey variables. We first consider the benefits and limitations of each approach, contrasting the methods used for estimation and inference. We next present a simulation study, empirically evaluating the ability of each approach to efficiently estimate differences in variance components. We then apply the two approaches to an analysis of real survey data collected in the U.S. National Survey of Family Growth (NSFG). We conclude that the two approaches tend to result in very similar inferences, and we provide suggestions for practice given some of the subtle differences observed.
Application of DIC to Extract Full Field Thermo-Mechanical Data From an HTS Coil

A digital imaging correlation (DIC) test setup was developed to accurately record the contraction of a Bi-2223 superconducting racetrack coil conduction cooled to 154 K. The coil was gripped at both ends to simultaneously measure the load and displacement induced by its own contraction. Postprocessing of the DIC data derived the displacement and strain fields from two areas of interest. The global deformation of the coil structure was influenced by how it was restrained, but the stress-strain curve in the y-direction of the HTS coil was established, and its stiffness when under thermally induced strain was found to closely match that of the epoxy resin. The coefficient of thermal expansion determined from the strain-temperature curve was in the same order of magnitude as dilatometer measurements performed upon a sample removed from a similar coil and the difference attributed to small variability in the temperatures across the coil and the mechanical restraint placed on the coil.
Cyclic nucleotide-gated ion channels.

Cyclic nucleotide-gated (CNG) channels are nonselective cation channels first identified in retinal photoreceptors and olfactory sensory neurons (OSNs). They are opened by the direct binding of cyclic nucleotides, cAMP and cGMP. Although their activity shows very little voltage dependence, CNG channels belong to the superfamily of voltage-gated ion channels. Like their cousins the voltage-gated K+ channels, CNG channels form heterotetrameric complexes consisting of two or three different types of subunits. Six different genes encoding CNG channels, four A subunits (A1 to A4) and two B subunits (B1 and B3), give rise to three different channels in rod and cone photoreceptors and in OSNs. Important functional features of these channels, i.e., ligand sensitivity and selectivity, ion permeation, and gating, are determined by the subunit composition of the respective channel complex. The function of CNG channels has been firmly established in retinal photoreceptors and in OSNs. Studies on their presence in other sensory and nonsensory cells have produced mixed results, and their purported roles in neuronal pathfinding or synaptic plasticity are not as well understood as their role in sensory neurons. Similarly, the function of invertebrate homologs found in Caenorhabditis elegans, Drosophila, and Limulus is largely unknown, except for two subunits of C. elegans that play a role in chemosensation. CNG channels are nonselective cation channels that do not discriminate well between alkali ions and even pass divalent cations, in particular Ca2+. Ca2+ entry through CNG channels is important for both excitation and adaptation of sensory cells. CNG channel activity is modulated by Ca2+/calmodulin and by phosphorylation. Other factors may also be involved in channel regulation. Mutations in CNG channel genes give rise to retinal degeneration and color blindness. In particular, mutations in the A and B subunits of the CNG channel expressed in human cones cause various forms of complete and incomplete achromatopsia.
Semi-Automated, Large-Scale Evaluation of Public Displays

ABSTRACT This article presents a scalable, semi-automated process for studying the usage of public displays. The process consists of gathering anonymous interaction and skeletal data of passersby during public display deployment and programmatically analyzing the data. This article demonstrates the use of the process with the analysis of the Information Wall, a gesture-controlled public information display. Information Wall was deployed in a university campus for one year and collected an extensive data set of more than 100 000 passersby. The main benefits of the process include (1) gathering of large data sets without considerable use of resources, (2) fast, semi-automated data analysis, and (3) applicability to studying the effects of long-term public display deployments. In analyzing the usage and passersby data of the Information Wall in our validation study, the main findings uncovered using the method were (i) most users were first-time users exploring the system, and not many returned to use the system again, and (ii) many users were accompanied by passive users who observed interaction from further away, which could suggest a case of multi-user interaction blindness. In the past, logged data has mainly been used as a supporting method for in situ observations and interviews, and its use has required a considerable amount of manual work. In this article, we argue that logged data analysis can be automated to complement other methods, particularly in the evaluation of long-term deployments.
Robust Downlink Beamforming for BDMA Massive MIMO System

In this paper, we design robust downlink beamforming against the imperfect channel state information (CSI) for beam division multiple access (BDMA) massive multiple-input multiple output (MIMO) systems. Following a worst-case deterministic model, the proposed design is formulated as minimizing the power consumption of base station (BS) under different signal-to-interference-plus-noise ratio (SINR) constraints. The S-Procedure and semi-definite relaxation (SDR) are used to convert the initial non-convex optimization to a convex semi-definite programming problem. Then the optimality of SDR is strictly proved by showing the rank-one property of the optimal beamforming thanks to the orthogonal channels under BDMA scheme. More importantly, we make one step further by deriving the optimal beamforming directions and optimal beamforming power allocation of the SDR in closed-form, which greatly reduces the optimization complexity and makes the proposed design practical for a real word massive MIMO system. Simulation results are then provided to verify the efficiency of the proposed robust beamforming algorithm.
Mechanisms of sampling interstitial fluid from skin using a microneedle patch

Significance Diagnosis and monitoring of disease is often done by measuring biomarkers found in blood, urine, saliva, and other bodily fluids. Another rich source of biomarkers is the interstitial fluid that surrounds cells and tissues in the body, but difficulty in accessing this fluid has limited its use in research and medicine. Here, we conducted experimental studies coupled with theoretical modeling to design a patch containing microscopic needles that puncture into superficial layers of skin and thereby enable withdrawal of interstitial fluid through micropores in a simple, minimally invasive manner. This patch can help researchers access interstitial fluid to advance discovery of novel biomarkers and enable doctors to use interstitial fluid for possible future diagnosis and monitoring of disease. Although interstitial fluid (ISF) contains biomarkers of physiological significance and medical interest, sampling of ISF for clinical applications has made limited impact due to a lack of simple, clinically useful techniques that collect more than nanoliter volumes of ISF. This study describes experimental and theoretical analysis of ISF transport from skin using microneedle (MN) patches and demonstrates collection of >1 µL of ISF within 20 min in pig cadaver skin and living human subjects using an optimized system. MN patches containing arrays of submillimeter solid, porous, or hollow needles were used to penetrate superficial skin layers and access ISF through micropores (µpores) formed upon insertion. Experimental studies in pig skin found that ISF collection depended on transport mechanism according to the rank order diffusion < capillary action < osmosis < pressure-driven convection, under the conditions studied. These findings were in agreement with independent theoretical modeling that considered transport within skin, across the interface between skin and µpores, and within µpores to the skin surface. This analysis indicated that the rate-limiting step for ISF sampling is transport through the dermis. Based on these studies and other considerations like safety and convenience for future clinical use, we designed an MN patch prototype to sample ISF using suction as the driving force. Using this approach, we collected ISF from human volunteers and identified the presence of biomarkers in the collected ISF. In this way, sampling ISF from skin using an MN patch could enable collection of ISF for use in research and medicine.
Estimating fugl-meyer clinical scores in stroke survivors using wearable sensors

Clinical assessment scales to evaluate motor abilities in stroke survivors could be used to individualize rehabilitation interventions thus maximizing motor gains. Unfortunately, these scales are not widely utilized in clinical practice because their administration is excessively time-consuming. Wearable sensors could be relied upon to address this issue. Sensor data could be unobtrusively gathered during the performance of motor tasks. Features extracted from the sensor data could provide the input to models designed to estimate the severity of motor impairments and functional limitations. In previous work, we showed that wearable sensor data collected during the performance of items of the Wolf Motor Function Test (a clinical scale designed to assess functional capability) can be used to estimate scores derived using the Functional Ability Scale, a clinical scale focused on quality of movement. The purpose of the study herein presented was to investigate whether the same dataset could be used to estimate clinical scores derived using the Fugl-Meyer Assessment scale (a clinical scale designed to assess motor impairments). Our results showed that Fugl-Meyer Assessment Test scores can be estimated by feeding a Random Forest with features derived from wearable sensor data recorded during the performance of as few as a single item of the Wolf Motor Function Test. Estimates achieved using the proposed method were marked by a root mean squared error as low as 4.7 points of the Fugl-Meyer Assessment Test scale.
Innovative Therapeutic Strategies for Cystic Fibrosis: Moving Forward to CRISPR Technique

One of the most revolutionary technologies in recent years in the field of molecular biology is CRISPR-Cas9. CRISPR technology is a promising tool for gene editing that provides researchers the opportunity to easily alter DNA sequences and modify gene function. Its many potential applications include correcting genetic defects, treating and preventing the spread of diseases. Cystic fibrosis (CF) is one of the most common lethal genetic diseases caused by mutations in the CF transmembrane conductance regulator (CFTR) gene. Although CF is an old acquaintance, there is still no effective/resolutive cure. Life expectancy has improved thanks to the combination of various treatments, but it is generally below average. Recently, a significant number of additional key medications have become licensed in Europe for the CF treatment including CFTR modulators. But innovative genomically-guided therapies have begun for CF and it is predictable that this will lead to rapid improvements in CF clinical disease and survival in the next decades. In this way, CRISPR-Cas9 approach may represent a valid tool to repair the CFTR mutation and hopeful results were obtained in tissue and animal models of CF disease.