Miracle-dz/UniFAR-FTUs huggingface dataset:
The neurometabolic profiles of GABA and Glutamate as revealed by proton magnetic resonance spectroscopy in type 1 and type 2 diabetes

Glucose metabolism is pivotal for energy and neurotransmitter synthesis and homeostasis, particularly in Glutamate and GABA systems. In turn, the stringent control of inhibitory/excitatory tonus is known to be relevant in neuropsychiatric conditions. Glutamatergic neurotransmission dominates excitatory synaptic functions and is involved in plasticity and excitotoxicity. GABAergic neurochemistry underlies inhibition and predicts impaired psychophysical function in diabetes. It has also been associated with cognitive decline in people with diabetes. Still, the relation between metabolic homeostasis and neurotransmission remains elusive. Two 3T proton MR spectroscopy studies were independently conducted in the occipital cortex to provide insight into inhibitory/excitatory homeostasis (GABA/Glutamate) and to evaluate the impact of chronic metabolic control on the levels and regulation (as assessed by regression slopes) of the two main neurotransmitters of the CNS in type 2 diabetes (T2DM) and type 1 diabetes (T1DM). Compared to controls, participants with T2DM showed significantly lower Glutamate, and also GABA. Nevertheless, higher levels of GABA/Glx (Glutamate+Glutamine), and lower levels of Glutamate were associated with poor metabolic control in participants with T2DM. Importantly, the relationship between GABA/Glx and HbA1c found in T2DM supports a relationship between inhibitory/excitatory balance and metabolic control. Interestingly, this neurometabolic profile was undetected in T1DM. In this condition we found strong evidence for alterations in MRS surrogate measures of neuroinflammation (myo-Inositol), positively related to chronic metabolic control. Our results suggest a role for Glutamate as a global marker of T2DM and a sensitive marker of glycemic status. GABA/Glx may provide a signature of cortical metabolic state in poorly controlled patients as assessed by HbA1c levels, which indicate long-term blood Glucose control. These findings are consistent with an interplay between abnormal neurotransmission and metabolic control in particular in type 2 diabetes thereby revealing dissimilar contributions to the pathophysiology of neural dysfunction in both types of diabetes.
Treatment outcomes of Nigerian patients with tuberculosis: A retrospective 25-year review in a regional medical center

Introduction Tuberculosis (TB) remains a global health challenge and leading infectious killer worldwide. The need for continuous evaluation of TB treatment outcomes becomes more imperative in the midst of a global economic meltdown substantially impacting resource-limited-settings. Methods This study retrospectively reviewed 25-years of treatment outcomes in 3,384 patients who were managed for TB at a tertiary hospital in Nigeria. Confirmed TB cases were given directly observed therapy of a short-course treatment regimen and monitored for clinical response. Results Out of 1,146,560 patients screened, there were 24,330 (2.1%) presumptive and 3,384 (13.9%) confirmed TB cases. The patients’ mean age was 35.8 years (0.33–101 years). There were 1,902 (56.2%) male, 332(9.8%) pediatric, and 2,878 (85%) pulmonary TB cases. The annual mean measured treatment outcomes were as follows: adherence, 91.4(±5.8) %; successful outcome, 75.3(±8.8) % potentially unsatisfactory outcome, 14.8(±7.2) %; and mortality 10.0(±3.6) %. Female, extra-pulmonary TB (EPTB), newly diagnosed, and relapsed patients compliant with treatment had successful outcomes. Adulthood and HIV infection were mortality risk factors. Conclusion The mean annual successful treatment outcome is 75.3(±8.8) %. Female, pediatric, EPTB, new, and relapsed patients were predisposed to successful treatment outcomes. Lessons learned will guide future program modifications.
COMPARATIVE GROSS AND HISTOMORPHOLOGICAL

The study was conducted on the histology and micrometry of the spleen of sheep and goat of Jammu region. The spleen of goat was quadrangular whereas that of sheep was triangular. The biometrical measurements of the spleens of sheep and goat revealed that the weight of spleen of sheep was 81.39 ± 12.79 gm while that of goat was 64.48 ± 7.82 gm. The length of the spleen was 12.70 ± 0.81 cm and 11.48 ± 0.73 cm in sheep and goat, respectively. The width of spleen of sheep was recorded to be 9.26 ± 0.38 cm and that of goat was measured as 9.37 ± 0.79 cm and the thickness of spleen was found to be 2.69 ± 0.2 cm and 2.37 ± 0.21 cm in sheep and goat, respectively. Histologically, spleen was covered by thick capsule with thickness 282.27 ± 14.88 μ in goat and 150.13 ± 8.14 μ in sheep. The thickness of trabeculae in goat was 224.67 ± 67 μ and in sheep was 104.35 ± 8.92 μ. Average diameter of white pulp was 478.20 ± 26.88 μ in sheep and 412.22 ± 47.85 μ in goat. Number of white pulps per field at 100 X magnification was 1.30 ± 0.21 in sheep and 1.60 ± 023 in goat. Similarly, number of white pulps per mm was 1.32 ± 0.22 in sheep and 1.62 ± 023 in goat. Red pulp consisted of spleenic cords and sinusoids. Sinusoids were lined by endothelial cells with large nuclei bulging into the sinusoidal lumen.
Contracts of Inattention

The standard paradigm of contracting assumes that parties will revise subsequent contracts if a court interpretation of a clause does not reflect their intent. This assumption, however, often does not match behavior—particularly, in boilerplate contracts. We examine the aftermath of an (in)famous 2016 case, Wilmington Savings Fund v. Cash America, to unpack possible reasons for this mismatch between theory and practice. We find evidence of a phenomenon in contracts that involves sophisticated parties who are nevertheless not represented by their own lawyers, lack full awareness of the fine print of the contractual terms, and, having devoted little attention to them, may be eclectic as to their meaning when they enter into these contracts. In these contracts, which we call contracts of inattention, a gap between lawyers’ understanding of a provision and the understanding of market participants is prone to emerge. The potential for such gaps has implications for how courts should interpret contracts of inattention and for how market participants will react to court rulings.
Speaker Attribution with Voice Profiles by Graph-Based Semi-Supervised Learning

Speaker attribution is required in many real-world applications, such as meeting transcription, where speaker identity is assigned to each utterance according to speaker voice profiles. In this paper, we propose to solve the speaker attribution problem by using graph-based semi-supervised learning methods. A graph of speech segments is built for each session, on which segments from voice profiles are represented by labeled nodes while segments from test utterances are unlabeled nodes. The weight of edges between nodes is evaluated by the similarities between the pretrained speaker embeddings of speech segments. Speaker attribution then becomes a semi-supervised learning problem on graphs, on which two graph-based methods are applied: label propagation (LP) and graph neural networks (GNNs). The proposed approaches are able to utilize the structural information of the graph to improve speaker attribution performance. Experimental results on real meeting data show that the graph based approaches reduce speaker attribution error by up to 68% compared to a baseline speaker identification approach that processes each utterance independently.
Analyzing Breath Signals for the Interspeech 2020 ComParE Challenge

This paper presents our contribution to the INTERSPEECH 2020 Breathing Sub-challenge. Besides fulﬁlling the main goal of the challenge, which involves the automatic prediction from conversational speech of the breath signals obtained from respiratory belts, we also analyse both original and predicted signals in an attempt to overcome the main pitfalls of the proposed systems. In particular, we identify the subsets of most irregular belt signals which yield the worst performance, measured by the Pearson correlation coefﬁcient, and show how they affect the re-sults that were obtained by both the baseline end-to-end system and variants such as a Bidirectional LSTM. The performance of this type of architecture indicates that future information is also relevant when predicting breathing patterns. We also study the information retained from the AM-FM decomposition of the speech signal for this purpose, showing how the AM component signiﬁcantly outperforms the FM component on all experiments, but fails to surpass the prediction results obtained using the original speech signal. Finally, we validate the system’s performance in video-conferencing conditions by using data augmentation and compare clinically relevant parameters, such as breathing rate, from both the original belt signals and the ones predicted from the simulated video-conferencing signals.
Optimized Architectures for Elliptic Curve Cryptography over Curve448

In this paper, we present diﬀerent implementations of point multiplication over Curve448. Curve448 has recently been recommended by NIST to provide 224-bit security over elliptic curve cryptography. Although implementing high-security cryptosystems should be considered due to recent improvements in cryptanalysis, hardware implementation of Curve488 has been investigated in a few studies. Hence, in this study, we propose three variable-base-point FPGA-based Curve448 implementations, i.e., lightweight, area-time eﬃcient, and high-performance architectures, which aim to be used for diﬀerent applications. Synthe-sized on a Xilinx Zynq 7020 FPGA, our proposed high-performance design increases 12% throughput with executing 1,219 point multiplication per second and increases 40% eﬃciency in terms of required clock cycles × utilized area compared to the best previous work. Furthermore, the proposed lightweight architecture works in 250 MHz and saves 96% of resources with the same performance. Additionally, our area-time ef-ﬁcient design considers a trade-oﬀ between time and required resources, which shows a 48% eﬃciency improvement with 52% fewer resources. Finally, eﬀective side-channel countermeasures are added to our proposed designs, which also outperform previous works.
Alignment in Multimodal Interaction: An Integrative Framework

Abstract When people are engaged in social interaction, they can repeat aspects of each other’s communicative behavior, such as words or gestures. This kind of behavioral alignment has been studied across a wide range of disciplines and has been accounted for by diverging theories. In this paper, we review various operationalizations of lexical and gestural alignment. We reveal that scholars have fundamentally different takes on when and how behavior is considered to be aligned, which makes it difficult to compare findings and draw uniform conclusions. Furthermore, we show that scholars tend to focus on one particular dimension of alignment (traditionally, whether two instances of behavior overlap in form), while other dimensions remain understudied. This hampers theory testing and building, which requires a well‐defined account of the factors that are central to or might enhance alignment. To capture the complex nature of alignment, we identify five key dimensions to formalize the relationship between any pair of behavior: time, sequence, meaning, form, and modality. We show how assumptions regarding the underlying mechanism of alignment (placed along the continuum of priming vs. grounding) pattern together with operationalizations in terms of the five dimensions. This integrative framework can help researchers in the field of alignment and related phenomena (including behavior matching, mimicry, entrainment, and accommodation) to formulate their hypotheses and operationalizations in a more transparent and systematic manner. The framework also enables us to discover unexplored research avenues and derive new hypotheses regarding alignment.
Low-Latency Single Channel Speech Dereverberation Using U-Net Convolutional Neural Networks

Speech signal reverberation due to reﬂections in a physical obstacle is one of the main difﬁculties in speech processing as well as the presence of non-stationary background noise. In this study we explore DNN-based single-channel speech dere-verberation with state-of-the-art performance comparisons. We propose a CNN auto-encoder architecture with skip connections focusing on real-time and low-latency applications. The proposed system is evaluated with the REVERB challenge dataset that includes simulated and real reverberated speech samples. Our experimental results show that the proposed system has superior results on the challenge evaluation dataset as opposed to a baseline system that uses deep neural network (DNN) based weighted prediction error (WPE) algorithm. We also extend the comparison with state of the art systems in terms of most commonly used objective metrics and our system achieves better results in the most of objective metrics. Moreover a latency analysis of the proposed system is performed and trade-off be-tween processing time and performance is examined.
Attention to Indexical Information Improves Voice Recall

In an exposure phase, two groups of listeners were exposed to a set of 10 voices. These groups differed in terms of the task assigned during exposure: one group was asked to make a decision about the regional affiliation of the voices (Indexical Condition), while the other group orthographically transcribed the words presented (Lexical Condition). Both groups were given an identical test phase where they were presented with 20 voices (10 old, 10 new) and asked to make old/new decisions on the voices. While both groups of listeners performed at above chance accuracy levels in recognizing voices at test as old/new, listeners in the Indexical Condition performed more accurately. These results suggest that the nature of attention during exposure has consequences for subsequent performance, suggesting encoding differences as a result of task demands.
Independent Echo Path Modeling for Stereophonic Acoustic Echo Cancellation

As stereophonic audio devices, such as smart speakers and cellphones, evolve to be daily essentials, stereophonic acoustic echo cancellation becomes more important for voice and audio applications. The cross-correlation between the far-end channels and the associated ambiguity in the estimated echo path transfer functions lead the misalignment and instability issues with conventional stereophonic acoustic echo cancellers (SAEC). In this paper, we propose a novel SAEC algorithm, which can better model the acoustic echo path between each loudspeaker and microphone. Specifically, filter adaptations are modeled independently by applying pre-whitening in solving the misalignment problem. Improvement in echo suppression capability is evaluated in terms of echo return loss enhancement(ERLE) and wakeup word detection accuracy.
Disfluencies and Fine-Tuning Pre-Trained Language Models for Detection of Alzheimer's Disease

Disﬂuencies and language problems in Alzheimer’s Disease can be naturally modeled by ﬁne-tuning Transformer-based pre-trained language models such as BERT and ERNIE. Using this method, we achieved 89.6% accuracy on the test set of the ADReSS (Alzheimer’s Dementia Recognition through Spontaneous Speech) Challenge, a considerable improvement over the baseline of 75.0%, established by the organizers of the challenge. The best accuracy was obtained with ERNIE, plus an encoding of pauses. Robustness is a challenge for large models and small training sets. Ensemble over many runs of BERT/ERNIE ﬁne-tuning reduced variance and improved accuracy. We found that um was used much less frequently in Alzheimer’s speech, compared to uh . We discussed this interesting ﬁnding from linguistic and cognitive perspectives.
Critical Role for AMPK in Metabolic Disease-Induced Chronic Kidney Disease

Chronic kidney disease (CKD) is prevalent in 9.1% of the global population and is a significant public health problem associated with increased morbidity and mortality. CKD is associated with highly prevalent physiological and metabolic disturbances such as hypertension, obesity, insulin resistance, cardiovascular disease, and aging, which are also risk factors for CKD pathogenesis and progression. Podocytes and proximal tubular cells of the kidney strongly express AMP-activated protein kinase (AMPK). AMPK plays essential roles in glucose and lipid metabolism, cell survival, growth, and inflammation. Thus, metabolic disease-induced renal diseases like obesity-related and diabetic chronic kidney disease demonstrate dysregulated AMPK in the kidney. Activating AMPK ameliorates the pathological and phenotypical features of both diseases. As a metabolic sensor, AMPK regulates active tubular transport and helps renal cells to survive low energy states. AMPK also exerts a key role in mitochondrial homeostasis and is known to regulate autophagy in mammalian cells. While the nutrient-sensing role of AMPK is critical in determining the fate of renal cells, the role of AMPK in kidney autophagy and mitochondrial quality control leading to pathology in metabolic disease-related CKD is not very clear and needs further investigation. This review highlights the crucial role of AMPK in renal cell dysfunction associated with metabolic diseases and aims to expand therapeutic strategies by understanding the molecular and cellular processes underlying CKD.
Considerations for Antiplatelet Management of Carotid Stenting in the Setting of Mechanical Thrombectomy: A Delphi Consensus Statement

BACKGROUND AND PURPOSE: There are only few data and lack of consensus regarding antiplatelet management for carotid stent placement in the setting of endovascular stroke treatment. We aimed to develop a consensus-based algorithm for antiplatelet management in acute ischemic stroke patients undergoing endovascular treatment and simultaneous emergent carotid stent placement. MATERIALS AND METHODS: We performed a literature search and a modified Delphi approach used Web-based questionnaires that were sent in several iterations to an international multidisciplinary panel of 19 neurointerventionalists from 7 countries. The first round included open-ended questions and formed the basis for subsequent rounds, in which closed-ended questions were used. Participants continuously received feedback on the results from previous rounds. Consensus was defined as agreement of ≥70% for binary questions and agreement of ≥50% for questions with >2 answer options. The results of the Delphi process were then summarized in a draft manuscript that was circulated among the panel members for feedback. RESULTS: A total of 5 Delphi rounds were performed. Panel members preferred a single intravenous aspirin bolus or, in jurisdictions in which intravenous aspirin is not available, a glycoprotein IIb/IIIa receptor inhibitor as intraprocedural antiplatelet regimen and a combination therapy of oral aspirin and a P2Y12 inhibitor in the postprocedural period. There was no consensus on the role of platelet function testing in the postprocedural period. CONCLUSIONS: More and better data on antiplatelet management for carotid stent placement in the setting of endovascular treatment are urgently needed. Panel members preferred intravenous aspirin or, alternatively, a glycoprotein IIb/IIIa receptor inhibitor as an intraprocedural antiplatelet agent, followed by a dual oral regimen of aspirin and a P2Y12 inhibitor in the postprocedural period.
Associations between objective afternoon and evening physical activity and objective sleep in patients with fibromyalgia and insomnia

Patients with fibromyalgia (FM) suffer from chronic pain, which limits physical activity and is associated with disturbed sleep. However, the relationship between physical activity, pain and sleep is unclear in these patients. This study examined whether actigraphic (Actiwatch‐2, Philips Respironics) afternoon and evening activity and pain are associated with actigraphic sleep. Adults with FM and insomnia complaints (n = 160, mean age [Mage] = 52, SD = 12, 94% female) completed 14 days of actigraphy. Activity levels (i.e., activity counts per minute) were recorded, and average afternoon/evening activity for intervals 12:00–3:00 PM, 3:00–6:00 PM and 6:00–9:00 PM was computed. Multiple linear regressions examined whether afternoon/evening activity, pain (daily evening diaries from 0 [no pain sensation] to 100 [most intense pain imaginable]), or their interaction, predicted sleep onset latency (SOL), wake time after sleep onset (WASO), total sleep time (TST) and sleep efficiency (SE). Greater afternoon activity was independently associated with lower SE (B = −0.08, p < .001), lower TST (β = −0.36, standard error [SE] = 0.06, p < .001) and longer WASO (B = 0.34, p < .001). Greater early evening activity was independently associated with lower SE (B = −0.06, p < .001), lower TST (β = −0.26, SE = 0.06, p < .001) and longer WASO (B = 0.23, p < .001). Self‐reported pain intensity interacted with afternoon and early evening physical activity, such that associations between higher activity and lower SE were stronger for individuals reporting higher pain. Late evening activity was not associated with sleep outcomes. Results suggest that in FM, increased afternoon and early evening physical activity is associated with sleep disturbance, and this relationship is stronger in individuals with higher pain.
Dangerous Liaisons: Interactions of Cryptococcus neoformans with Host Phagocytes

Cryptococcus neoformans is an opportunistic fungal pathogen and a leading cause of death in immunocompromised individuals. The interactions of this yeast with host phagocytes are critical to disease outcome, and C. neoformans is equipped with an array of factors to modulate these processes. Cryptococcal infection begins with the deposition of infectious particles into the lungs, where the fungal cells deploy various antiphagocytic factors to resist internalization by host cells. If the cryptococci are still engulfed, they can survive and proliferate within host cells by modulating the phagolysosome environment in which they reside. Lastly, cryptococcal cells may escape from phagocytes by host cell lysis, nonlytic exocytosis, or lateral cell-to-cell transfer. The interactions between C. neoformans and host phagocytes also influence the dissemination of this pathogen to the brain, where it may cross the blood-brain barrier and cause an often-fatal meningoencephalitis. In this review, we highlight key cryptococcal factors involved in various stages of cryptococcal-host interaction and pathogenesis.
Female urine incontinence: vaginal erbium laser (VEL) effectiveness and safety

Abstract Urinary incontinence is a common health problem that impacts the quality of life of women at different ages. Its physiopathology is not unequivocal, and it is necessary to consider the stress urinary incontinence (SUI), the overactive bladder syndrome and the mixed incontinence (MUI). According to the type of incontinence, its impact on the quality of life and age of the patients, therapeutic strategies are currently summarized in physiotherapy, surgery and drug treatments. We already know the benefit/risk ratio of each of these strategies. Our objective is to evaluate the potential effectiveness and safety of the VEL, an innovative vaginal laser technique (VEL – Vaginal Erbium Laser, erbium yttrium-aluminum-garnet -Er: YAG) a non-invasive laser proposed as a treatment for SUI, overactive bladder syndrome and MUI. The mechanisms of action of lasers are discussed in general and those of VEL in particular with the description of the Smooth® mode. To do this, we have collected the 21 published studies including the first randomized vs. placebo and two pilot studies of intra-urethral VEL. In conclusion: VEL procedures already have their place between the rehabilitation of the perineal floor and surgery. Further properly sized, randomized studies are needed to evaluate the laser treatments in comparison with other therapies, as well as to assess the duration of the therapeutic effects and the safety of repeated applications.