Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Common Neural Circuit Disruptions in Emotional Processing Across Psychiatric Disorders.

OBJECTIVE Disrupted emotional processing is a common feature of many psychiatric disorders. The authors investigated functional disruptions in neural circuitry underlying emotional processing across a range of tasks and across psychiatric disorders through a transdiagnostic quantitative meta-analysis of published neuroimaging data. METHODS A PubMed search was conducted for whole-brain functional neuroimaging findings published through May 2018 that compared activation during emotional processing tasks in patients with psychiatric disorders (including schizophrenia, bipolar or unipolar depression, anxiety, and substance use) to matched healthy control participants. Activation likelihood estimation (ALE) meta-analyses were conducted on peak voxel coordinates to identify spatial convergence. RESULTS The 298 experiments submitted to meta-analysis included 5,427 patients and 5,491 control participants. ALE across diagnoses and patterns of patient hyper- and hyporeactivity demonstrated abnormal activation in the amygdala, the hippocampal/parahippocampal gyri, the dorsomedial/pulvinar nuclei of the thalamus, and the fusiform gyri, as well as the medial and lateral dorsal and ventral prefrontal regions. ALE across disorders but considering directionality demonstrated patient hyperactivation in the amygdala and the hippocampal/parahippocampal gyri. Hypoactivation was found in the medial and lateral prefrontal regions, most pronounced during processing of unpleasant stimuli. More refined disorder-specific analyses suggested that these overall patterns were shared to varying degrees, with notable differences in patterns of hyper- and hypoactivation. CONCLUSIONS These findings demonstrate a pattern of neurocircuit disruption across major psychiatric disorders in regions and networks key to adaptive emotional reactivity and regulation. More specifically, disruption corresponded prominently to the "salience" network, the ventral striatal/ventromedial prefrontal "reward" network, and the lateral orbitofrontal "nonreward" network. Consistent with the Research Domain Criteria initiative, these findings suggest that psychiatric illness may be productively formulated as dysfunction in transdiagnostic neurobehavioral phenotypes such as neurocircuit activation.
Understanding the Relevance of DNA Methylation Changes in Immune Differentiation and Disease

Immune cells are one of the most complex and diverse systems in the human organism. Such diversity implies an intricate network of different cell types and interactions that are dependently interconnected. The processes by which different cell types differentiate from progenitors, mature, and finally exert their function requires an orchestrated succession of molecular processes that determine cell phenotype and function. The acquisition of these phenotypes is highly dependent on the establishment of unique epigenetic profiles that confer identity and function on the various types of effector cells. These epigenetic mechanisms integrate microenvironmental cues into the genome to establish specific transcriptional programs. Epigenetic modifications bridge environment and genome regulation and play a role in human diseases by their ability to modulate physiological programs through external stimuli. DNA methylation is one of the most ubiquitous, stable, and widely studied epigenetic modifications. Recent technological advances have facilitated the generation of a vast amount of genome-wide DNA methylation data, providing profound insights into the roles of DNA methylation in health and disease. This review considers the relevance of DNA methylation to immune system cellular development and function, as well as the participation of DNA methylation defects in immune-mediated pathologies, illustrated by selected paradigmatic diseases.
Glial Cells—The Strategic Targets in Amyotrophic Lateral Sclerosis Treatment

Amyotrophic lateral sclerosis (ALS) is a fatal neurological disease, which is characterized by the degeneration of motor neurons in the motor cortex and the spinal cord and subsequently by muscle atrophy. To date, numerous gene mutations have been linked to both sporadic and familial ALS, but the effort of many experimental groups to develop a suitable therapy has not, as of yet, proven successful. The original focus was on the degenerating motor neurons, when researchers tried to understand the pathological mechanisms that cause their slow death. However, it was soon discovered that ALS is a complicated and diverse pathology, where not only neurons, but also other cell types, play a crucial role via the so-called non-cell autonomous effect, which strongly deteriorates neuronal conditions. Subsequently, variable glia-based in vitro and in vivo models of ALS were established and used for brand-new experimental and clinical approaches. Such a shift towards glia soon bore its fruit in the form of several clinical studies, which more or less successfully tried to ward the unfavourable prognosis of ALS progression off. In this review, we aimed to summarize current knowledge regarding the involvement of each glial cell type in the progression of ALS, currently available treatments, and to provide an overview of diverse clinical trials covering pharmacological approaches, gene, and cell therapies.
Surface-Enhanced Raman Spectroscopy on Hybrid Graphene/Gold Substrates near the Percolation Threshold

Graphene is a promising platform for surface-enhanced Raman spectroscopy (SERS)-active substrates, primarily due to the possibility of quenching photoluminescence and fluorescence. Here we study ultrathin gold films near the percolation threshold fabricated by electron-beam deposition on monolayer CVD graphene. The advantages of such hybrid graphene/gold substrates for surface-enhanced Raman spectroscopy are discussed in comparison with conventional substrates without the graphene layer. The percolation threshold is determined by independent measurements of the sheet resistance and effective dielectric constant by spectroscopic ellipsometry. The surface morphology of the ultrathin gold films is analyzed by the use of scanning electron microscopy (SEM) and atomic force microscopy (AFM), and the thicknesses of the films in addition to the quartz-crystal mass-thickness sensor are also measured by AFM. We experimentally demonstrate that the maximum SERS signal is observed near and slightly below the percolation threshold. In this case, the region of maximum enhancement of the SERS signal can be determined using the figure of merit (FOM), which is the ratio of the real and imaginary parts of the effective dielectric permittivity of the films. SERS measurements on hybrid graphene/gold substrates with the dye Crystal Violet show an enhancement factor of ~105 and also demonstrate the ability of graphene to quench photoluminescence by an average of ~60%.
Biomedical Applications of Calixarenes: State-of-the-Art and Perspectives.

Calixarenes (CAs), representing the third generation of supramolecular hosts and one of the most widely studied macrocyclic scaffolds, offer (almost) unlimited possibilities due to their ease of modification, which allows one to establish a large molecular library as a material basis for diverse biomedical applications. Moreover, CAs and their derivatives engage in various non-covalent interactions for the facile recognition of guests including bioactive molecules and are also important building blocks for the fabrication of supramolecular architectures. In view of their molecular recognition and self-assembly properties, CAs are extensively applied in biosensing, bioimaging, and drug/gene delivery. Additionally, some CA derivatives exhibit biological activities and can therefore be used as new therapeutic agents. Herein, we summarize the diverse biomedical applications of CAs including in-vitro diagnosis (biosensing), in-vivo diagnosis (bioimaging), and therapy.
Hemodynamic effects of inotropic drugs in heart failure

Abstract Background: There is currently no consensus on the appropriate selection of inotropic therapy in ventricular dysfunction. The objective of the study was to detect the effects of different inotropes on the hemodynamics of patients who developed low cardiac output. Methods: PubMed, Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched (all updated December 31, 2017). The inclusion criteria were as follows: low cardiac index (CI < 2.5 L/min/m2) or New York Heart Association class II–IV, and at least 1 group receiving an inotropic drug compared to another group receiving a different inotropic/placebo treatment. The exclusion criteria were studies published as an abstract only, crossover studies, and studies with a lack of data on the cardiac index. Results: A total of 1402 patients from 37 trials were included in the study. Inotropic drugs were shown to increase the cardiac index (0.32, 95%CI:0.25, 0.38), heart rate (7.68, 95%CI:6.36, 9.01), and mean arterial pressure (3.17, 95%CI:1.96, 4.38) than the placebo. Overall, the pooled estimates showed no difference in terms of cardiac index, heart rate, mean arterial pressure, systemic vascular resistance, and mean pulmonary arterial pressure among the groups receiving different inotropes. Conclusions: Our systematic review found that inotrope therapy is not associated with the amelioration of hemodynamics. An accurate evaluation of the benefits and risks, and selection of the correct inotropic agent is required in all clinical settings.
The Menstrual Cycle and Risk of Breast Cancer: A Review

Cyclic hormonal stimulation of the breast tissue plays a significant role in breast carcinogenesis. Current risk factor models do not include direct measures of cycle characteristics although the effects of possible surrogates of cycle activity such as age at menarche and menopause, parity, and nursing time have been investigated. Future risk models should also include menstrual cycle length, regularity, number of cycles before first full-term pregnancy, and life-time number of cycles. New risk factor models for pre- and postmenopausal breast cancer are proposed here. Furthermore, there is a need for more long-term, prospective studies investigating menstrual cycle characteristics as data currently available are primarily retrospective and collected at one time-point only.
RSC-DGS: Fusion of RGB and NIR Images Using Robust Spectral Consistency and Dynamic Gradient Sparsity

Color (RGB) images captured under low light condition contain much noise with loss of textures. Since near-infrared (NIR) images are robust to noise with clear textures even in low light condition, they can be used to enhance low light RGB images by image fusion. In this paper, we propose fusion of RGB and NIR images using robust spectral consistency (RSC) and dynamic gradient sparsity (DGS), called RSC-DGS. We build the RSC model based on a robust error function to remove noise and preserve color/spectral consistency. We construct the DGS model based on vectorial total variation minimization that uses the NIR image as the reference image. The DGS model transfers clear textures of the NIR image to the fusion result and successfully preserves cross-channel interdependency of the RGB image. We use alternating direction method of multipliers (ADMM) for efficiency to solve the proposed RSC-DGS fusion. Experimental results confirm that the proposed method effectively preserves color/spectral consistency and textures in fusion results while successfully removing noise with high computational efficiency.
Where Are They Now?: Revisiting Energy Use Feedback a Decade After Deployment

In home displays (IHD's) of energy use offers potential to engage households with energy use and improve energy literacy. Yet explorations of use over longer time periods are lacking. Based on qualitative in-home interviews with 19 participants, this research provides accounts from owners of IHD's up to 10 years after their initial deployment. Findings indicate the near complete abandonment of the devices and participants' reflections exemplify the short-lived value provided by simple cent-a-meter IHD's. The paper reflects on IHD's as a component of broadscale energy literacy programs, closing with suggestions for how designers might re-frame energy engagement as a service.
Crowdsourcing versus the laboratory: Towards crowd-based linguistic text quality assessment of query-based extractive summarization

Curating text manually in order to improve the quality of automatic natural language processing tools can become very time consuming and expensive. Especially, in the case of query-based extractive online forum summarization, curating complex information spread along multiple posts from multiple forum members to create a short meta-summary that answers a given query is a very challenging task. To overcome this challenge, we explore the applicability of microtask crowdsourcing as a fast and cheap alternative for query-based extractive text summarization of online forum discussions. We measure the linguistic quality of crowd-based forum summarizations, which is usually conducted in a traditional laboratory environment with the help of experts, via comparative crowdsourcing and laboratory experiments. To our knowledge, no other study considered query-based extractive text summarization and summary quality evaluation as an application area of the microtask crowdsourcing. By conducting experiments both in crowdsourcing and laboratory environments, and comparing the results of linguistic quality judgments, we found out that microtask crowdsourcing shows high applicability for determining the factors overall quality, grammaticality, non-redundancy, referential clarity, focus, and structure & coherence . Further, our comparison of these ﬁndings with a preliminary and initial set of expert annotations suggest that the crowd assessments can reach comparable results to experts speciﬁcally when determining factors such as overall quality and structure & coherence mean values. Eventually, preliminary analyses reveal a high correlation between the crowd and expert ratings when assessing low-quality summaries.
Understanding and targeting the disease‐related RNA binding protein human antigen R (HuR)

Altered gene expression is a characteristic feature of many disease states such as tumorigenesis, and in most cancers, it facilitates cancer cell survival and adaptation. Alterations in global gene expression are strongly impacted by post‐transcriptional gene regulation. The RNA binding protein (RBP) HuR (ELAVL1) is an established regulator of post‐transcriptional gene regulation and is overexpressed in most human cancers. In many cancerous settings, HuR is not only overexpressed, but it is “overactive” as denoted by increased subcellular localization within the cytoplasm. This dysregulation of HuR expression and cytoplasmic localization allows HuR to stabilize and increase the translation of various prosurvival messenger RNA (mRNAs) involved in the pathogenesis of numerous cancers and various diseases. Based on almost 20 years of work, HuR is now recognized as a therapeutic target. Herein, we will review the role HuR plays in the pathophysiology of different diseases and ongoing therapeutic strategies to target HuR. We will focus on three ongoing‐targeted strategies: (1) inhibiting HuR's translocation from the nucleus to the cytoplasm; (2) inhibiting the ability of HuR to bind target RNA; and (3) silencing HuR expression levels. In an oncologic setting, HuR has been demonstrated to be critical for a cancer cell's ability to survive a variety of cancer relevant stressors (including drugs and elements of the tumor microenvironment) and targeting this protein has been shown to sensitize cancer cells further to insult. We strongly believe that targeting HuR could be a powerful therapeutic target to treat different diseases, particularly cancer, in the near future.
Panax notoginseng preparations as adjuvant therapy for diabetic kidney disease: a systematic review and meta-analysis

Abstract Context Panax notoginseng (Burk.) F.H. Chen (Araliaceae) preparations (PNP) are traditional Chinese medicines used as adjuvant therapeutics for diabetic kidney disease (DKD). Objective To systematically review the efficacy of PNP as adjunct DKD therapy, including their effects on kidney function, serum lipid levels and fasting blood glucose levels. Methods The databases PubMed, Embase, Medline, Cochrane Library, CINAHL, China Biology Medicine disc, Wanfang, VIP and China National Knowledge Infrastructure were systematically searched from the date of their inception until May 2019. Panax notoginseng, Panax notoginseng saponins, Lulutong, Xueshuantong and Xuesaitong were the key terms searched. Randomized controlled trials (RCTs) comparing the combined use of PNP and conventional medicines (CM) versus CM for DKD were included. Data were pooled using random or fixed effect models depending on heterogeneity. Results In total, 24 RCTs involving 1918 participants were analysed. Adjunct PNP with CM was associated with reduction of albuminuria (MD –26.89 mg, 95% CI: –33.35 to –20.42), proteinuria (MD –0.32 g/24 h, 95% CI: –0.36 to –0.27), serum creatinine (MD –4.52 μmol/L, 95% CI: –8.71 to –0.32), total cholesterol (MD –1.56 mmol/L, 95% CI: –2.33 to –0.78), triglycerides (TG) (MD –0.56 mmol/L, 95% CI: –0.80 to –0.31) and low-density lipoprotein cholesterol (MD –0.94 mmol/L, 95% CI: –1.49 to –0.40) compared with CM. Conclusions This is the first meta-analysis investigating adjuvant PNP therapy for DKD. PNP apparently exerted beneficial effects on kidney function and improved the metabolism of serum lipids by CM. Further, well-conducted, high-quality trials on DKD patients are needed to provide high-quality evidence.
3D Printing On-Water Sports Boards with Bio-Inspired Core Designs

Modeling and analyzing the sports equipment for injury prevention, reduction in cost, and performance enhancement have gained considerable attention in the sports engineering community. In this regard, the structure study of on-water sports board (surfboard, kiteboard, and skimboard) is vital due to its close relation with environmental and human health as well as performance and safety of the board. The aim of this paper is to advance the on-water sports board through various bio-inspired core structure designs such as honeycomb, spiderweb, pinecone, and carbon atom configuration fabricated by three-dimensional (3D) printing technology. Fused deposition modeling was employed to fabricate complex structures from polylactic acid (PLA) materials. A 3D-printed sample board with a uniform honeycomb structure was designed, 3D printed, and tested under three-point bending conditions. A geometrically linear analytical method was developed for the honeycomb core structure using the energy method and considering the equivalent section for honeycombs. A geometrically non-linear finite element method based on the ABAQUS software was also employed to simulate the boards with various core designs. Experiments were conducted to verify the analytical and numerical results. After validation, various patterns were simulated, and it was found that bio-inspired functionally graded honeycomb structure had the best bending performance. Due to the absence of similar designs and results in the literature, this paper is expected to advance the state of the art of on-water sports boards and provide designers with structures that could enhance the performance of sports equipment.
Active Learning for Air Quality Station Location Recommendation

Motivation: Recent years have seen a decline in air quality across the planet, with studies suggesting that a significant proportion of global population has reduced life expectancy by up to 4 years [1, 2, 5]. To tackle this increasing growth in air pollution and its adverse effects, governments across the world have set up air quality monitoring stations that measure concentrations of various pollutants like NO2, SO2 and PM2.5, of which PM2.5 especially has significant health impact and is used for measuring air quality. One major issue with the deployment of these stations is the massive cost involved. Owing to the high installation and maintenance costs, the spatial resolution of air quality monitoring is generally poor. In this current work, we propose active learning methods to choose the next location to install an air quality monitor, motivated by sparse spatial air quality monitoring and expensive sensing equipment. Related Work: Previous work has predominantly focused on interpolation and forecasting of air quality [7, 8]. Work on air quality station location recommendation has largely been limited [4]. Previous work [4, 7, 8] has shown that installing air quality stations uniformly to maximize spatial coverage does not work well in practice, which acts as a major motivation for our work. Problem Statement: Given a set S of air quality monitoring stations, along with their corresponding values of PM2.5 over a period of time {d1,d2, . dn }, where di represents day i , we want to choose a new location s ′, such that installing a station at s ′ gives us the best estimate of air quality at unknown locations. Approach: We perform active learning using Query by Committee (QBC) [6]. Wemaintain three sets of stations the train set, the test set, and the pool set. The train set contains currently monitored locations, test set contains the locations where we wish to estimate the air quality and the pool set contains candidate stations for querying, i.e., we query from the pool set and observe how our estimation improves on the test set. To query from the pool set, we need a measure of uncertainty for the stations in the pool set. To obtain this uncertainty, we train an ensemble of learners, and take the standard deviation of their predictions for each station in the pool set. We add the station with maximum standard deviation to our train set, and remove the same station from the pool set. We repeat this process as time progresses. We use K Neighbors Regressor (KNN) as our main model inspired by the fact that nearby days will likely have similar air quality (temporal locality), and so will nearby stations (spatial
P/S sockets: supporting publish/subscribe communication through the standard socket API

While the address-oriented datagram and reliable stream services supported by the UDP and TCP protocols are the foundation of distributed computing, other forms of communication are increasingly being used to build contemporary systems and applications. A popular alternative to datagram- and stream-based communication is the Publish/Subscribe (P/S) paradigm, where message forwarding and reception is done based on a topic or content descriptions instead of an address. Several middleware systems have been built to support this form of communication, on top of the socket API. Taking a different approach, we discuss how P/S networking can be supported through the socket API, so that this can serve as a universal interface for supporting different communication abstractions. To this end we introduce a new address family and extend the semantics of selected socket primitives to support P/S functions. Also, we describe a proof-of-concept implementation of the proposed socket extension, which features two protocols for ad-hoc and infrastructure-based P/S communication, respectively.