Miracle-dz/UniFAR-FTUs huggingface dataset:
Antibody Light Chains Dictate the Specificity of Contact Hypersensitivity Effector Cell Suppression Mediated by Exosomes

Antibody light chains (LCs), formerly considered a waste product of immunoglobulin synthesis, are currently recognized as important players in the activation of the immune response. However, very little is known about the possible immune regulatory functions of LCs. Recently, we reported that hapten-specific LCs coat miRNA-150-carrying exosomes produced by CD8+ suppressor T cells downregulating the contact hypersensitivity (CHS) reaction in an antigen-specific manner, in mice tolerized by intravenous administration of a high dose of hapten-coupled syngeneic erythrocytes. Thus, the current studies aimed at investigating the role of hapten-specific LCs in antigen-specific, exosome-mediated suppression of CHS effector cells. Suppressor T cell-derived exosomes from tolerized B-cell-deficient µMT−/−, NKT-cell-deficient Jα18−/−, and immunoglobulin-deficient JH−/− mice were nonsuppressive, unless supplemented with LCs of specificity strictly respective to the hapten used for sensitization and CHS elicitation in mice. Thus, these observations demonstrate that B1-cell-derived LCs, coating exosomes in vivo and in vitro, actually ensure the specificity of CHS suppression. Our research findings substantially expand current understanding of the newly discovered, suppressor T cell-dependent tolerance mechanism by uncovering the function of antigen-specific LCs in exosome-mediated, cell–cell communication. This express great translational potential in designing nanocarriers for specific targeting of desired cells.
Weighting of Coda Voicing Cues: Glottalisation and Vowel Duration

Recent research suggests that a trading relationship may exist in speech production between vowel duration and glottalisation as cues to coda stop voicing in Australian English. Younger speakers have been shown to use glottalisation to signal voicelessness more than older speakers who instead make greater use of vowel duration. This suggests a sound change in progress for the voicing cues. In addition, the vowel duration cue to voicing is greater in inherently long vowel contexts compared to inherently short vowel contexts. We report on a perceptual study designed to examine whether the weighting of these two cues found in production is replicated in perception. Older and younger listeners were presented with audio stimuli co-varying in vowel duration and glottalisation. In accord with findings from production, the vowel duration cue was weaker for contexts containing inherently short vowels than for those containing inherently long vowels. Complementarily, glottalisation had a stronger effect on the perception of coda voicelessness in inherently short vowel contexts. Older and younger listeners did not differ in their use of glottalisation as a perceptual cue to voicelessness despite previously identified age differences in production. This finding raises questions about the link between perception and production in sound change.
Effects of continuous theta-burst stimulation of the primary motor and secondary somatosensory areas on the central processing and the perception of trigeminal nociceptive input in healthy volunteers

Abstract Noninvasive modulation of the activity of pain-related brain regions by means of transcranial magnetic stimulation promises an innovative approach at analgesic treatments. However, heterogeneous successes in pain modulation by setting reversible “virtual lesions” at different brain areas point at unresolved problems including the optimum stimulation site. The secondary somatosensory cortex (S2) has been previously identified to be involved in the perception of pain-intensity differences. Therefore, impeding its activity should impede the coding of the sensory component of pain intensity, resulting in a flattening of the relationship between pain intensity and physical stimulus strength. This was assessed using inactivating spaced continuous theta-burst stimulation (cTBS) in 18 healthy volunteers. In addition, cTBS was applied on the primary motor cortex (M1) shown previously to yield moderate and variable analgesic effects, whereas sham stimulation at both sites served as placebo condition. Continuous theta-burst stimulation flattened the relationship between brain activation and stimulus strength, mainly at S2, the insular cortex, and the postcentral gyrus (16 subjects analyzed). However, these effects were observed after inactivation of M1 while this effect was not observed after inactivation of S2. Nevertheless, both the M1 and the S2-spaced cTBS treatment were not reflected in the ratings of the nociceptive stimuli of different strengths (17 subjects analyzed), contrasting with the clear coding of stimulus strength by these data. Hence, while modulating the central processing of nociceptive input, cTBS failed to produce subjectively relevant changes in pain perception, indicating that the method in the present implementation is still unsuitable for clinical application.
Training Utterance-level Embedding Networks for Speaker Identification and Verification

Encoding speaker-speciﬁc characteristics from speech signals into ﬁxed length vectors is a key component of speaker identiﬁ-cation and veriﬁcation systems. This paper presents a deep neural network architecture for speaker embedding models where similarity in embedded utterance vectors explicitly approximates the similarity in vocal patterns of speakers. The proposed architecture contains an additional speaker embedding lookup table to compute loss based on embedding similarities. Furthermore, we propose a new feature sampling method for data augmentation. Experimentation based on two databases demonstrates that our model is more effective at speaker identiﬁcation and veriﬁcation when compared to a fully connected classiﬁer and an end-to-end veriﬁcation model.
Effects of interleukin‐17A in nucleus pulposus cells and its small‐molecule inhibitors for intervertebral disc disease

Intervertebral discs (IVD) degeneration, which is caused by ageing or mechanical stress, leads to IVD disease, including back pain and sciatica. The cytokine interleukin (IL)‐17A is elevated in NP cells during IVD disease. Here we explored the pharmacotherapeutic potential of IL‐17A for the treatment of IVD disease using small‐molecule inhibitors that block binding of IL‐17A to the IL‐17A receptor (IL‐17RA). Treatment of NP cells with IL‐17A increased expression of cyclooxygenase‐2 (COX‐2), IL‐6, matrix metalloproteinase (MMP)‐3 and MMP‐13. These increases were suppressed by an IL‐17A‐neutralizing antibody, and small molecules that were identified as inhibitors by binding to the IL‐17A‐binding region of IL‐17RA. IL‐17A signalling also altered sulphated glycosaminoglycan deposition and spheroid colony formation, while treatment with small‐molecule inhibitors of IL‐17A attenuated this response. Furthermore, mitogen‐activated protein kinase pathways were activated by IL‐17A stimulation and induced IL‐6 and COX‐2 expression, while small‐molecule inhibitors of IL‐17A suppressed their expression. Taken together, these results show that IL‐17A is a valid target for IVD disease therapy and that small‐molecule inhibitors that inhibit the IL‐17A–IL‐17RA interaction may be useful for pharmacotherapy of IVD disease.
Genotypic Characterization of Cryptosporidium Species in Humans and Peri-Domestic Animals in Ekiti and Oyo States, Nigeria

ABSTRACT Cryptosporidiosis is one of the leading causes of diarrhea in humans and several other vertebrate species. Because surveys of Cryptosporidium genotypes from animals and humans living in the same region are rare, our understanding of the importance of zoonotic transmission in the epidemiology of cryptosporidiosis remains superficial. PCR was used to amplify a portion of the Cryptosporidium 18S small subunit ribosomal RNA gene from fecal DNA from humans and livestock living in Ekiti and Oyo states, Nigeria. PCR-positive samples were further analyzed using PCR targeting the heat-shock protein HSP-70, the actin, and the sporozoite glycoprotein gene gp60. A questionnaire was used to collect demographic information. Sixteen of 187 samples collected were Cryptosporidium 18S PCR positive. Of these, 5 samples originating from HIV-positive patients, 5 from otherwise healthy children, 2 from chickens, 3 from goats, and 1 from a dog were positive for at least 1 marker. Sequencing of the 18S rRNA amplicons revealed the presence of Cryptosporidium parvum in 2 HIV positive patients and in a child; the actin sequence confirmed the presence of this species. Two samples of HIV-positive patients amplified Cryptosporidium hominis 18S rRNA, one of them confirmed by the HSP-70, actin, and gp60 sequences. Cryptosporidium meleagridis was found in another HIV patient, while C. hominis was detected in 3 children (of which 2 were confirmed by gp60). Cryptosporidium muris was found in 1 child. In birds, we found C. meleagridis and, significantly, C. parvum, whereas we detected C. parvum and C. muris in 1 goat each. The only dog sampled was positive for Cryptosporidium canis. We conclude that, in the environment we surveyed, humans and animals are a potential part of the same transmission cycle. Measures to prevent zoonotic transmission should therefore be considered to reduce the prevalence of cryptosporidiosis.
Gated Convolutional Neural Network for Sentence Matching

The recurrent neural networks (RNN) have shown promising results in sentence matching tasks, such as paraphrase identiﬁ-cation (PI), natural language inference (NLI) and answer selection (AS). However, the recurrent architecture prevents parallel computation within a sequence and is highly time-consuming. To overcome this limitation, we propose a gated convolutional neural network (GCNN) for sentence matching tasks. In this model, the stacked convolutions encode hierarchical context-aware representations of a sentence, where the gating mechanism optionally controls and stores the convolutional contextual information. Furthermore, the attention mechanism is utilized to obtain interactive matching information between sentences. We evaluate our model on PI and NLI tasks, and the experiments demonstrate the advantages of the proposed approach in terms of both speed and accuracy performance.
A Brief History of Persistence

Persistent homology is currently one of the more widely known tools from computational topology and topological data analysis. We present in this note a brief survey on the evolution of the subject. The goal is to highlight the main ideas, starting from the subject's computational inception more than 20 years ago, to the more modern categorical and representation-theoretic point of view.
Diarization is Hard: Some Experiences and Lessons Learned for the JHU Team in the Inaugural DIHARD Challenge

We describe in this paper the experiences of the Johns Hopkins University team during the inaugural DIHARD diarization evaluation. This new task provided microphone recordings in a variety of difﬁcult conditions and challenged researchers to fully consider all speaker activity, without the currently typi-cal practices of unscored collars or ignored overlapping speaker segments. This paper explores several key aspects of currently state-of-the-art diarization methods, such as training data se-lection, signal bandwidth for feature extraction, representations of speech segments (i-vector versus x-vector), and domain-adaptive processing. In the end, our best system clustered x-vector embeddings trained on wideband microphone data followed by Variational-Bayesian reﬁnement, and a speech activity detector speciﬁcally trained for this task with in-domain data was found to be the best performing. After presenting these decisions and their ﬁnal result, we discuss lessons learned and remaining challenges within the lens of this new approach to diarization performance measurement.
Angiotensin‐converting enzyme 2 deficiency accelerates and angiotensin 1‐7 restores age‐related muscle weakness in mice

A pharmacologic strategy for age‐related muscle weakness is desired to improve mortality and disability in the elderly. Angiotensin‐converting enzyme 2 (ACE2) cleaves angiotensin II into angiotensin 1‐7, a peptide known to protect against acute and chronic skeletal muscle injury in rodents. Since physiological aging induces muscle weakness via mechanisms distinct from other muscle disorders, the role of ACE2‐angiotensin 1‐7 in age‐related muscle weakness remains undetermined. Here, we investigated whether deletion of ACE2 alters the development of muscle weakness by aging and whether angiotensin 1‐7 reverses muscle weakness in older mice.
Strategies for quantum races

We initiate the study of quantum races, games where two or more quantum computers compete to solve a computational problem. While the problem of dueling algorithms has been studied for classical deterministic algorithms, the quantum case presents additional sources of uncertainty for the players. The foremost among these is that players do not know if they have solved the problem until they measure their quantum state. This question of `when to measure? ' presents a very interesting strategic problem. We develop a game-theoretic model of a multiplayer quantum race, and find an approximate Nash equilibrium where all players play the same strategy. In the two-party case, we further show that this strategy is nearly optimal in terms of payoff among all symmetric Nash equilibria. A key role in our analysis of quantum races is played by a more tractable version of the game where there is no payout on a tie; for such races we completely characterize the Nash equilibria in the two-party case. One application of our results is to the stability of the Bitcoin protocol when mining is done by quantum computers. Bitcoin mining is a race to solve a computational search problem, with the winner gaining the right to create a new block. Our results inform the strategies that eventual quantum miners should use, and also indicate that the collision probability---the probability that two miners find a new block at the same time---would not be too high in the case of quantum miners. Such collisions are undesirable as they lead to forking of the Bitcoin blockchain.
Automatic Detection of Multi-speaker Fragments with High Time Resolution

Interruptions and simultaneous talking represent important patterns of speech behavior. However, there is a lack of approaches to their automatic detection in continuous audio data. We have developed a solution for automatic labeling of multi-speaker fragments using harmonic traces analysis. Since harmonic traces in multi-speaker intervals form an irregular pattern as opposed to the structured pattern typical for a single speaker, we resorted to computer vision methods to detect multi-speaker fragments. Aconvolutional neural network was trained on synthetic material to differentiate between single-speaker and multi-speaker fragments. For evaluation of the proposed method the SSPNet Conﬂict Corpus with provided manual diarization was used. We also examined factors affecting algorithm performance. The main advantages of the proposed method are calculation simplicity and high time resolution. With our approach it is possible to detect segments with minimum duration of 0.5 seconds. The proposed method demonstrates highly accurate results and may be used for speech segmentation, speaker tracking, content analysis such as conﬂict detection, and other practical purposes.
Multilingual Deep Neural Network Training Using Cyclical Learning Rate

Deep Neural Network (DNN) acoustic models are an essential component in automatic speech recognition (ASR). The main sources of accuracy improvements in ASR involve training DNN models that require large amounts of supervised data and computational resources. While the availability of sufﬁcient monolingual data is a challenge for low-resource languages, the computational requirements for resource rich languages increases signiﬁcantly with the availability of large data sets. In this work, we provide novel solutions for these two challenges in the context of training a feed-forward DNN acoustic model (AM) for mobile voice search. To address the data-sparsity challenge, we bootstrap our multilingual AM using data from languages in the same language family. To reduce training time, we use cyclical learning rate (CLR) which has demonstrated fast convergence with competitive or better performance when training neural networks on tasks related to text and images. We reduce training time for our Mandarin Chinese AM with 81.4% token accuracy from 40 to 21.3 hours and increase the word accuracy on three romance languages by 2-5% with multilingual AMs compared to monolingual DNN baselines.
Molecular Characterization of Near Full-Length Genomes of Hepatitis B Virus Isolated from Predominantly HIV Infected Individuals in Botswana

The World Health Organization plans to eliminate hepatitis B and C Infections by 2030. Therefore, there is a need to study and understand hepatitis B virus (HBV) epidemiology and viral evolution further, including evaluating occult (HBsAg-negative) HBV infection (OBI), given that such infections are frequently undiagnosed and rarely treated. We aimed to molecularly characterize HBV genomes from 108 individuals co-infected with human immunodeficiency virus (HIV) and chronic hepatitis B (CHB) or OBI identified from previous HIV studies conducted in Botswana from 2009 to 2012. Full-length (3.2 kb) and nearly full-length (~3 kb) genomes were amplified by nested polymerase chain reaction (PCR). Sequences from OBI participants were compared to sequences from CHB participants and GenBank references to identify OBI-unique mutations. HBV genomes from 50 (25 CHB and 25 OBI) individuals were successfully genotyped. Among OBI participants, subgenotype A1 was identified in 12 (48%), D3 in 12 (48%), and E in 1 (4%). A similar genotype distribution was observed in CHB participants. Whole HBV genome sequences from Botswana, representing OBI and CHB, were compared for the first time. There were 43 OBI-unique mutations, of which 26 were novel. Future studies using larger sample sizes and functional analysis of OBI-unique mutations are warranted.
Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding

Learning long-term dependencies in extended temporal sequences requires credit assignment to events far back in the past. The most common method for training recurrent neural networks, back-propagation through time (BPTT), requires credit information to be propagated backwards through every single step of the forward computation, potentially over thousands or millions of time steps. This becomes computationally expensive or even infeasible when used with long sequences. Importantly, biological brains are unlikely to perform such detailed reverse replay over very long sequences of internal states (consider days, months, or years.) However, humans are often reminded of past memories or mental states which are associated with the current mental state. We consider the hypothesis that such memory associations between past and present could be used for credit assignment through arbitrarily long sequences, propagating the credit assigned to the current state to the associated past state. Based on this principle, we study a novel algorithm which only back-propagates through a few of these temporal skip connections, realized by a learned attention mechanism that associates current states with relevant past states. We demonstrate in experiments that our method matches or outperforms regular BPTT and truncated BPTT in tasks involving particularly long-term dependencies, but without requiring the biologically implausible backward replay through the whole history of states. Additionally, we demonstrate that the proposed method transfers to longer sequences significantly better than LSTMs trained with BPTT and LSTMs trained with full self-attention.
Experimentally Defined Convolutional Neural Network Architecture Variants for Non-Temporal Real-Time Fire Detection

In this work we investigate the automatic detection of fire pixel regions in video (or still) imagery within real-time bounds without reliance on temporal scene information. As an extension to prior work in the field, we consider the performance of experimentally defined, reduced complexity deep convolutional neural network architectures for this task. Contrary to contemporary trends in the field, our work illustrates maximal accuracy of 0.93 for whole image binary fire detection, with 0.89 accuracy within our superpixel localization framework can be achieved, via a network architecture of signficantly reduced complexity. These reduced architectures additionally offer a 3–4 fold increase in computational performance offering up to 17 fps processing on contemporary hardware independent of temporal information. We show the relative performance achieved against prior work using benchmark datasets to illustrate maximally robust real-time fire region detection.
Novel and classical renal biomarkers as evidence for the nephroprotective effect of Carica papaya leaf extract

The present study is aimed at utilization of novel and classical kidney function biomarkers to evaluate the nephroprotective potential of Carica papaya leaf extract (CPLE) in gentamicin nephrotoxicity model in albino rats. The used classical biomarkers were urea and creatinine; while the new biomarkers were Kidney injury molecule-1 (KIM-1) and Clusterin. Forty-five male albino rats were assigned into five groups and subjected to different treatments for nine consecutive days (vehicles; gentamicin, 100 mg/kg, subcutaneously; ascorbic acid, 200 mg/kg, orally; CPLE, 150 and 300 mg/kg b wt., orally). Three rats/group were killed on days 3, 6, and 9 for blood and tissue samples for renal and oxidation markers. Gentamicin resulted in significant increase in urea and creatinine only by the end of the experimental course; while the novel biomarkers were evident as early as 3 days upon gentamicin injection. When concurrently administered with gentamicin, CPLE significantly protected kidney tissues against gentamicin nephrotoxic effects indicated by decrement of both the novel and the classical standard biomarkers, in a dose-dependent manner. CPLE-mediated protection was attributed to its antioxidant potential indicated by significant inhibition of malondialdehyde (MDA) levels in both serum and kidney homogenates. The results were further supported by histopathological examination that revealed considerable amelioration of the pathological microscopic alterations induced by repeated gentamicin injection. Phytochemical analysis of CPLE indicated presence of tannins and flavonoids. These data may suggest CPLE, based on improvement of both classical and novel renal markers, as a highly potent nephroprotective and antioxidant from natural source that could be a good remedy in conditions associated with renal disorders.