Miracle-dz/UniFAR-FTUs huggingface dataset:
The End of the Binary Era: Revisiting the Spectrum of Tuberculosis

Human Mycobacterium tuberculosis infection was thought to result in either active symptomatic tuberculosis (TB) or latent asymptomatic infection. It is now clear that this binary classification is insufficient to describe the myriad of infection outcomes. In active TB, symptomatic disease can be mild to severe, with a range of lung and thoracic lymph node involvement or extrapulmonary manifestations. Most humans control the infection and develop latent TB infection, with differential risks of reactivation to active TB. However, some frequently exposed persons appear to be resistant to infection, whereas others may initially become infected yet subsequently eliminate all bacilli. The immunologic factors influencing these varied outcomes are still not clear, but likely involve a range of different responses. In this article, we review the data supporting the spectrum of M. tuberculosis infection in humans as well as data in nonhuman primates that allow dissection of the immune responses leading to the varied outcomes of infection.
Regional diastolic dysfunction in post-infarction heart failure: role of local mechanical load and SERCA expression

Abstract Aims Regional heterogeneities in contraction contribute to heart failure with reduced ejection fraction (HFrEF). We aimed to determine whether regional changes in myocardial relaxation similarly contribute to diastolic dysfunction in post-infarction HFrEF, and to elucidate the underlying mechanisms. Methods and results Using the magnetic resonance imaging phase-contrast technique, we examined local diastolic function in a rat model of post-infarction HFrEF. In comparison with sham-operated animals, post-infarction HFrEF rats exhibited reduced diastolic strain rate adjacent to the scar, but not in remote regions of the myocardium. Removal of Ca2+ within cardiomyocytes governs relaxation, and we indeed found that Ca2+ transients declined more slowly in cells isolated from the adjacent region. Resting Ca2+ levels in adjacent zone myocytes were also markedly elevated at high pacing rates. Impaired Ca2+ removal was attributed to a reduced rate of Ca2+ sequestration into the sarcoplasmic reticulum (SR), due to decreased local expression of the SR Ca2+ ATPase (SERCA). Wall stress was elevated in the adjacent region. Using ex vivo experiments with loaded papillary muscles, we demonstrated that high mechanical stress is directly linked to SERCA down-regulation and slowing of relaxation. Finally, we confirmed that regional diastolic dysfunction is also present in human HFrEF patients. Using echocardiographic speckle-tracking of patients enrolled in the LEAF trial, we found that in comparison with controls, post-infarction HFrEF subjects exhibited reduced diastolic train rate adjacent to the scar, but not in remote regions of the myocardium. Conclusion Our data indicate that relaxation varies across the heart in post-infarction HFrEF. Regional diastolic dysfunction in this condition is linked to elevated wall stress adjacent to the infarction, resulting in down-regulation of SERCA, disrupted diastolic Ca2+ handling, and local slowing of relaxation.
A Neural Compositional Paradigm for Image Captioning

Mainstream captioning models often follow a sequential structure to generate captions, leading to issues such as introduction of irrelevant semantics, lack of diversity in the generated captions, and inadequate generalization performance. In this paper, we present an alternative paradigm for image captioning, which factorizes the captioning procedure into two stages: (1) extracting an explicit semantic representation from the given image; and (2) constructing the caption based on a recursive compositional procedure in a bottom-up manner. Compared to conventional ones, our paradigm better preserves the semantic content through an explicit factorization of semantics and syntax. By using the compositional generation procedure, caption construction follows a recursive structure, which naturally fits the properties of human language. Moreover, the proposed compositional procedure requires less data to train, generalizes better, and yields more diverse captions.
Web Table Understanding by Collective Inference

Web tables have become very popular and important in many real applications, such as search engines and knowledge base enrichment. Due to its benefit, it is very urgent to understand web tables. An important task in web table understanding is the column-type detection, which detects the most likely types (categories) to describe the columns in the web table. Some existing studies use knowledge bases to determine the column types. However, this problem has three challenges. (i) Web tables are too dirty to be understood. (ii) Knowledge bases are not comprehensive enough to cover all the columns. (iii) The size of both knowledge bases and web tables are extremely huge. Thus, traditional approaches encounter the limitations with low quality and poor scalability. Also, they cannot extract the best type from top-k types automatically. To address these limitations, we propose a collective inference approach (CIA) based on Topic Sensitive PageRank, which considers not only the types of detected columns, but also the collective information of web tables to automatically produce more accurate top-k types, especially the top-1 type, for both incorrectly detected columns and undetectable columns whose cells do not exist in the knowledge base. We also propose three methods to improve the inference performance and implemented techniques of CIA in MapReduce. Experimental results on real-world datasets show that our CIA achieves much higher quality in top-1 type detection as well as the entity enrichment, and outperforms state-of-the-art approaches significantly.
Exploring Neural Translation Models for Cross-Lingual Text Similarity

This paper explores a neural network-based approach to computing similarity of two texts written in different languages. Such similarity can be useful for a variety of applications including cross-lingual information retrieval and cross-lingual text classification. To compute similarity, we focus on neural machine translation models and examine the utility of their intermediate states. Through experiments on an English-Japanese translation corpus, it is demonstrated that the intermediate states of input texts are indeed beneficial for computing cross-lingual text similarity, outperforming other approaches including a strong machine translation-based baseline.
A Mobile Videoconference-Based Intervention on Stress Reduction and Resilience Enhancement in Employees: Randomized Controlled Trial

Background Videoconferencing-based treatments have shown great potential in increasing engagement and compliance by decreasing the barriers of time and distance. In general, employees tend to experience a lot of stress, but find it difficult to visit a clinic during office hours. Objective The purpose of this study was to investigate the effectiveness of a mobile videoconference-based intervention for stress reduction and resilience enhancement in employees. Methods In total, 81 participants were randomly allocated to one of the three conditions: mobile videoconferencing, in-person, and self-care; of these, 72 completed the study. All participants underwent assessment via self-reported questionnaires before, immediately after, and 1 month after the intervention. Intervention lasted for 4 weeks and consisted of elements of cognitive behavioral therapy, positive psychology, and meditation. Changes in clinical variables regarding stress and resilience across time were compared between treatment conditions. Results There were significant condition × time effects on variables measuring perceived stress, resilience, emotional labor, and sleep, demonstrating significantly differential effects across time according to treatment condition. Moreover, there were significant effects of condition on perceived stress and occupational stress. There were no significant differences in any variable between the mobile videoconferencing and in-person conditions at 1 month after the intervention. Conclusions Results indicate that both mobile videoconferencing and in-person interventions were comparably effective in decreasing stress and enhancing resilience. Further studies with a larger sample size and a longer follow-up period are warranted to investigate the long-term effect of mobile videoconferencing interventions. Trial Registration ClinicalTrials.gov identifier NCT03256682; https://clinicaltrials.gov/ct2/show/NCT03256682 (Archived by WebCite at http://www.webcitation.org/71W77bwnR)
Attentive Interactive Convolutional Matching for Community Question Answering in Social Multimedia

Nowadays, community-based question answering (CQA) services have accumulated millions of users to share valuable knowledge. An essential function in CQA tasks is the accurate matching of answers w.r. t given questions. Existing methods usually ignore the redundant, heterogeneous, and multi-modal properties of CQA systems. In this paper, we propose a multi-modal attentive interactive convolutional matching method (MMAICM) to model the multi-modal content and social context jointly for questions and answers in a unified framework for CQA retrieval, which explores the redundant, heterogeneous, and multi-modal properties of CQA systems jointly. A well-designed attention mechanism is proposed to focus on useful word-pair interactions and neglect meaningless and noisy word-pair interactions. Moreover, a multi-modal interaction matrix method and a novel meta-path based network representation approach are proposed to consider the multi-modal content and social context, respectively. The attentive interactive convolutional matching network is proposed to infer the relevance between questions and answers, which can capture both the lexical and the sequential information of the contents. Experiment results on two real-world datasets demonstrate the superior performance of MMAICM compared with other state-of-the-art algorithms.
Computational analysis and prediction of lysine malonylation sites by exploiting informative features in an integrative machine-learning framework

As a newly discovered post-translational modification (PTM), lysine malonylation (Kmal) regulates a myriad of cellular processes from prokaryotes to eukaryotes and has important implications in human diseases. Despite its functional significance, computational methods to accurately identify malonylation sites are still lacking and urgently needed. In particular, there is currently no comprehensive analysis and assessment of different features and machine learning (ML) methods that are required for constructing the necessary prediction models. Here, we review, analyze and compare 11 different feature encoding methods, with the goal of extracting key patterns and characteristics from residue sequences of Kmal sites. We identify optimized feature sets, with which four commonly used ML methods (random forest, support vector machines, K-nearest neighbor and logistic regression) and one recently proposed [Light Gradient Boosting Machine (LightGBM)] are trained on data from three species, namely, Escherichia coli, Mus musculus and Homo sapiens, and compared using randomized 10-fold cross-validation tests. We show that integration of the single method-based models through ensemble learning further improves the prediction performance and model robustness on the independent test. When compared to the existing state-of-the-art predictor, MaloPred, the optimal ensemble models were more accurate for all three species (AUC: 0.930, 0.923 and 0.944 for E. coli, M. musculus and H. sapiens, respectively). Using the ensemble models, we developed an accessible online predictor, kmal-sp, available at http://kmalsp.erc. monash.edu/. We hope that this comprehensive survey and the proposed strategy for building more accurate models can serve as a useful guide for inspiring future developments of computational methods for PTM site prediction, expedite the discovery of new malonylation and other PTM types and facilitate hypothesis-driven experimental validation of novel malonylated substrates and malonylation sites.
Climatic Variation of Supercooling Point in the Linden Bug Pyrrhocoris apterus (Heteroptera: Pyrrhocoridae)

Cold tolerance is often one of the key components of insect fitness, but the association between climatic conditions and supercooling capacity is poorly understood. We tested 16 lines originating from geographically different populations of the linden bug Pyrrhocoris apterus for their cold tolerance, determined as the supercooling point (SCP). The supercooling point was generally well explained by the climatic conditions of the population’s origin, as the best predictor—winter minimum temperature—explained 85% of the average SCP variation between populations. The supercooling capacity of P. apterus is strongly correlated with climatic conditions, which support the usage of SCP as an appropriate metric of cold tolerance in this species.
Self-presentation in digital media among adolescent patients with obesity: Striving for integrity, risk-reduction, and social recognition

Background Emerging research suggests that social media has the potential in clinical settings to enhance interaction with and between pediatric patients with various conditions. However, appearance norms and weight stigmatization can make adolescents with obesity uncomfortable about using these visual-based media. It is therefore important to explore these adolescents’ perspectives to identify the implications and concerns regarding the use of social media in clinical settings. Objective To explore the experiences of adolescents in treatment for obesity in terms of how they present themselves on social media, their rationale behind their presentations, and their feelings related to self-presentation. Methods Interviews were conducted with 20 adolescents enrolled in a pediatric outpatient obesity clinic, then transcribed and categorized using qualitative content analysis and Goffman’s dramaturgical model. Participants used a screen-recorded laptop to demonstrate their online self-presentation practices. Findings: Adolescent girls and boys undergoing treatment for obesity used visual-based social media, but girls in particular experienced weight stigma online and undertook self-presentation strategies to conceal weight-related content such as avoiding showing close-up photos of their bodies and not posting images of unhealthy “fattening” foods. Participants perceived the potential use of social media in clinical settings as being too risky and private. Conclusions Given the complexity of general visual-based social media use by adolescents, and not wanting their patient status to be visible to peers, healthcare should primarily focus on working with more restricted instant messaging when engaging with adolescents with obesity.
Local Convolutional Neural Networks for Person Re-Identification

Recent works have shown that person re-identification can be substantially improved by introducing attention mechanisms, which allow learning both global and local representations. However, all these works learn global and local features in separate branches. As a consequence, the interaction/boosting of global and local information are not allowed, except in the final feature embedding layer. In this paper, we propose local operations as a generic family of building blocks for synthesizing global and local information in any layer. This building block can be inserted into any convolutional networks with only a small amount of prior knowledge about the approximate locations of local parts. For the task of person re-identification, even with only one local block inserted, our local convolutional neural networks (Local CNN) can outperform state-of-the-art methods consistently on three large-scale benchmarks, including Market-1501, CUHK03, and DukeMTMC-ReID.
Clinical outcomes of imatinib dose escalation versus sunitinib in first-line imatinib-failure gastrointestinal stromal tumour

Abstract Aim: The majority of available data on the clinical efficacy of sunitinib in patients with imatinib-resistant or -intolerant gastrointestinal stromal tumours (GISTs) are from studies of western populations. We investigated the clinical outcomes of imatinib dose escalation versus sunitinib in first-line imatinib-failure Asian GIST patients to further guide clinical treatment. Methods: Patients received imatinib dose escalation and a shift to sunitinib (Group A) or a direct shift to sunitinib (Group B). The objective tumour response was assessed according to Choi’s criteria. Progression-free survival (PFS) and overall survival (OS) were calculated. The relationship between genetic mutation and survival was analysed. Results: In total, 40 patients who fulfilled the inclusion criteria were recruited. The differences in survival between Group A and Group B were not significant for PFS (p = .776) or OS (p = .219). For patients with KIT exon 11 mutation, a trend towards a better PFS was found in Group B (p = .122), OS of Group B was better than Group A (p = .013). The median PFS and OS of sunitinib treatment were 8 and 24 months, respectively, and a clinical benefit was observed in 80%. Patients with KIT exon 11 mutations had better PFS compared to those with KIT exon 9 mutations or wild-type GISTs (p = .017, p = .040, respectively). Conclusions: Both imatinib dose escalation and sunitinib were optional in Asian patients after failure of first-line imatinib, and patients with KIT exon 11 mutation benefited more from a direct shift to sunitinib.
Targeting PIM Kinase with PD1 Inhibition Improves Immunotherapeutic Antitumor T-cell Response

Purpose: Adoptive T-cell therapy (ACT) of cancer, which involves the infusion of ex vivo–engineered tumor epitope reactive autologous T cells into the tumor-bearing host, is a potential treatment modality for cancer. However, the durable antitumor response following ACT is hampered either by loss of effector function or survival of the antitumor T cells. Therefore, strategies to improve the persistence and sustain the effector function of the antitumor T cells are of immense importance. Given the role of metabolism in determining the therapeutic efficacy of T cells, we hypothesize that inhibition of PIM kinases, a family of serine/threonine kinase that promote cell-cycle transition, cell growth, and regulate mTORC1 activity, can improve the potency of T cells in controlling tumor. Experimental Design: The role of PIM kinases in T cells was studied either by genetic ablation (PIM1−/−PIM2−/−PIM3−/−) or its pharmacologic inhibition (pan-PIM kinase inhibitor, PimKi). Murine melanoma B16 was established subcutaneously and treated by transferring tumor epitope gp100–reactive T cells along with treatment regimen that involved inhibiting PIM kinases, anti-PD1 or both. Results: With inhibition of PIM kinases, T cells had significant reduction in their uptake of glucose, and upregulated expression of memory-associated genes that inversely correlate with glycolysis. In addition, the expression of CD38, which negatively regulates the metabolic fitness of the T cells, was also reduced in PimKi-treated cells. Importantly, the efficacy of antitumor T-cell therapy was markedly improved by inhibiting PIM kinases in tumor-bearing mice receiving ACT, and further enhanced by adding anti-PD1 antibody to this combination. Conclusions: This study highlights the potential therapeutic significance of combinatorial strategies where ACT and inhibition of signaling kinase with checkpoint blockade could improve tumor control.
Pharmacological therapy and blood pressure control in primary health care sites in China: data from 254,848 hypertensive patients

Background Studies on pharmacological therapy and blood pressure (BP) control in primary health care sites of China are limited. We aimed to investigate drug use and compliance as well as compare BP control between pharmacological therapies for lowering BP in hypertensive population serviced by these sites. Methods This is a 1-year cohort study using electronic health care records from the National Primary Public Health Services of China. For patients with antihypertensive drugs at the first follow-up, we defined compliance with treatment as a continued treatment with the same specified class of agents at next three follow-ups. In those with compliance, BP control was defined as systolic BP <140 mmHg and diastolic BP <90 mmHg in four follow-ups within 1 year. Results Primary health care sites of four areas managed 254,848 hypertensive patients aged ≥35 years. At the first follow-up, 50.2% of the patients took medicines for lowering BP. In those, calcium channel antagonist monotherapy was the most common medicine in urban areas (57.1% vs 15.6% in rural areas, P<0.001); however, the most common one was single-pill combinations including diuretics and non-first-line drugs in rural areas (34.4% vs 10.7% in urban areas, P<0.001). Compliance was 79.9% and 53.2% for single- and multiple-pill combinations in first-line drugs; this rate was 69.5% and 45.0% in regimens combined with non-first-line drugs, respectively. Compared with calcium channel antagonists, diuretics monotherapy increased the overall BP control by 11% (risk ratio, 1.11; 95% confidence interval, 1.08 to 1.13), but it was used in few patients (3.3%); first-line multiple-pill combinations significantly decreased BP control by 20% to 28% in three less urbanized areas, but a similar BP control was achieved in the highly urbanized area. Conclusion Our study indicated that drug use such as diuretics could be strengthened in primary health care sites and combined therapy may be improved particularly in less urbanized areas.
Successful treatment of chronic knee pain following localization by a sigma-1 receptor radioligand and PET/MRI: a case report

Background The ability to accurately diagnose and objectively localize pain generators in chronic pain sufferers remains a major clinical challenge since assessment relies on subjective patient complaints and relatively non-specific diagnostic tools. Developments in clinical molecular imaging, including advances in imaging technology and radiotracer design, have afforded the opportunity to identify tissues involved in pain generation based on their pro-nociceptive condition. The sigma-1 receptor (S1R) is a pro-nociceptive receptor upregulated in painful, inflamed tissues, and it can be imaged using the highly specific radioligand 18F-FTC-146 with PET. Case presentation A 50-year-old woman with a 7-year history of refractory, left-knee pain of unknown origin was referred to our pain management team. Over the past several years, she had undergone multiple treatments, including a lateral retinacular release, radiofrequency ablation of a peripheral nerve, and physical therapy. While certain treatments provided partial relief, her pain would inevitably return to its original state. Using simultaneous positron emission tomography/magnetic resonance imaging (PET/MRI) with the novel radiotracer 18F-FTC-146, imaging showed increased focal uptake of 18F-FTC-146 in the intercondylar notch, corresponding to an irregular but equivocal lesion identified in the simultaneously acquired MRI. These imaging results prompted surgical removal of the lesion, which upon resection was identified as an inflamed, intraarticular synovial lipoma. Removal of the lesion relieved the patient’s pain, and to date the pain has not recurred. Conclusion We present a case of chronic, debilitating knee pain that resolved with surgery following identification of the pathology with a novel clinical molecular imaging approach that detects chronic pain generators at the molecular and cellular level. This approach has the potential to identify and localize pain-associated pathology in a variety of chronic pain syndromes.