Miracle-dz/UniFAR-FTUs huggingface dataset:
α‐galactosylceramide generates lung regulatory T cells through the activated natural killer T cells in mice

Our previous study showed that intraperitoneal injection of α‐galactosylceramide (α‐GalCer) has the ability to activate lung iNKT cells, but α‐GalCer‐activated iNKT cells do not result in airway inflammation in wild‐type (WT) mice. Many studies showed that iNKT cells had the capacity to induce Treg cells, which gave rise to peripheral tolerance. Therefore, we examined the influence of intraperitoneal administration of α‐GalCer on the expansion and suppressive activity of lung Treg cells using iNKT cell‐knockout mice and co‐culture experiments in vitro. We also compared airway inflammation and airway hyperresponsiveness (AHR) after α‐GalCer administration in specific anti‐CD25 mAb‐treated mice. Our data showed that intraperitoneal injection of α‐GalCer could promote the expansion of lung Treg cells in WT mice, but not in iNKT cell‐knockout mice. However, α‐GalCer administration could not boost suppressive activity of Treg cells in WT mice and iNKT cell‐knockout mice. Interestingly, functional inactivation of Treg cells could induce airway inflammation and AHR in WT mice treated with α‐GalCer. Furthermore, α‐GalCer administration could enhance iNKT cells to secrete IL‐2, and neutralization of IL‐2 reduced the expansion of Treg cells in vivo and in vitro. Thus, intraperitoneal administration of α‐GalCer can induce the generation of lung Treg cells in mice through the release of IL‐2 by the activated iNKT cells.
Real-Time Pedestrian Detection Using Convolutional Neural Networks

Pedestrian detection provides manager of a smart city with a great opportunity to manage their city effectively and automatically. Specifically, pedestrian detection technology can improve our secure environment and make our traffic more efficient. In this paper, all of our work both modification and improvement are made based on YOLO, which is a real-time Convolutional Neural Network detector. In our work, we extend YOLO’s original network structure, and also give a new definition of loss function to boost the performance for pedestrian detection, especially when the targets are small, and that is exactly what YOLO is not good at. In our experiment, the proposed model is tested on INRIA, UCF YouTube Action Data Set and Caltech Pedestrian Detection Benchmark. Experimental results indicate that after our modification and improvement, the revised YOLO network outperforms the original version and also is better than other solutions.
CSF-S100B Is a Potential Candidate Biomarker for Neuromyelitis Optica Spectrum Disorders

Astrocytic impairment is a pathologic feature of neuromyelitis optica spectrum disorder (NMOSD). S100B and glial fibrillary acidic protein (GFAP) are the two most commonly used astrocytic markers. The aim of this study was to evaluate whether CSF-S100B could serve as a marker of NMOSD. We enrolled 49 NMOSD patients [25 aquaporin-4 antibody (AQP4-Ab)–positive, 8 myelin-oligodendrocyte glycoprotein antibody (MOG-Ab)-positive, and 16 seronegative patients], 12 multiple sclerosis (MS) patients, and 15 other noninflammatory neurological diseases (OND) patients. The CSF levels of S100B and GFAP were measured by ELISA. Both CSF-S100B and GFAP levels significantly discriminated NMOSD from MS [area under curve (AUC) = 0.839 and 0.850, respectively] and OND (AUC = 0.839 and 0.850, respectively). The CSF-S100B levels differentiated AQP4-Ab–positive NMOSD from MOG-Ab–positive NMOSD with higher accuracy than the CSF-GFAP levels (AUC=0.865 and 0.772, respectively). The CSF-S100B levels also significantly discriminated MOG-Ab–positive patients from seronegative patients (AUC = 0.848). Both CSF-S100B and GFAP levels were correlated with the Expanded Disability Status Scale (EDSS) during remission. Only the CSF-S100B levels were correlated with the CSF WBC count and the EDSS during attack. The levels of CSF-S100B seemed to have a longer lasting time than the levels of CSF-GFAP, which may benefit patients who present late. As a result, CSF-S100B might be a potential candidate biomarker for NMOSD in discriminating, evaluating severity, and predicting disability.
Clinical Features, Metastasis, and Survival in Patients Younger Than 21 Years With Posterior Uveal Melanoma

Importance Given the rarity of posterior uveal melanoma in patients younger than 21 years, reporting clinical experience in this area has relevance. Objective To describe the baseline clinical features, treatment, and clinical course of a group of patients younger than 21 years who have primary posterior uveal melanoma. Design, Setting, and Participants This retrospective descriptive case series of patients younger than 21 years who have a primary choroidal or ciliochoroidal melanoma was conducted at a single-center subspecialty referral practice. Patients in the relevant age group who were treated in a single practice between July 1980 and December 2013 were included; clinical data collected through December 2017 were captured to permit adequate follow-up time in all cases. Main Outcomes and Measures Conventional descriptive statistics of relevant clinical variables (eg, demographic, tumor, treatment, and outcome variables) of each patient were recorded. Actuarial metastasis-free and overall survival curves were computed and plotted, as was a postdetection survival curve of patients who developed metastasis during available follow-up. Results Of 2265 patients with posterior uveal melanoma encountered by the authors during the study interval, 18 (0.8%) were younger than 21 years when diagnosed and treated. Ten were female and 8 male, and the mean (SD) age was 16.6 (4.2) years. Through available follow-up, 8 of these patients had developed metastatic uveal melanoma (44%). All 8 died of metastasis. Actuarial survival analysis showed that the cumulative probability of metastatic death in this group exceeded 50%. The median overall survival time after treatment of the primary intraocular tumor was 11.9 (95% CI, 7.3-16.5) years. The median survival time after detection of metastasis in the 8 patients who developed metastasis was 2.3 months (95% CI, 0.0-5.2) months. Conclusions and Relevance Posterior uveal melanoma in patients younger than 21 years appears to have a similar if not worse prognosis than patients with PUM in the population overall. Owing to the later onset of metastasis observed, patients younger than 21 years should continue to have surveillance tests for more than 10 years after treatment.
Neuropsychological tests of the future: How do we get there from here?

Abstract Objective: This article reviews current approaches to neuropsychological assessment, identifies opportunities for development of new methods using modern psychometric theory and advances in technology, and suggests a transition path that promotes application of novel methods without sacrificing validity. Methods: Theoretical/state-of-the-art review.Conclusions: Clinical neuropsychological assessment today does not reflect advances in neuroscience, modern psychometrics, or technology. Major opportunities for improving practice include both psychometric and technological strategies. Modern psychometric approaches including item response theory (IRT) enable linking procedures that can place different measures on common scales; adaptive testing algorithms that can dramatically increase efficiency of assessment; examination of differential item functioning (DIF) to detect measures that behave differently in different groups; and person fit statistics to detect aberrant patterns of responding of high value for performance validity testing. Opportunities to introduce novel technologies include computerized adaptive testing, Web-based assessment, healthcare- and bio-informatics strategies, mobile platforms, wearables, and the ‘internet-of-things’. To overcome inertia in current practices, new methods must satisfy requirements for back-compatibility with legacy instrumentation, enabling us to leverage the wealth of validity data already accrued for classic procedures. A path to achieve these goals involves creation of a global network to aggregate item-level data into a shared repository that will enable modern psychometric analyses to refine existing methods, and serve as a platform to evolve novel assessment strategies, which over time can revolutionize neuropsychological assessment practices world-wide.
Changes in depressed patients’ self-statements

Abstract Objective: Individuals’ use of self-statements reflecting self-criticism, a sense of inadequacy, and low self-worth has been linked to the incidence, severity, and recurrence of major depressive disorder [de Graaf, L. E. , Huibers, M. J. H. , Cuijpers, P., & Arntz, A. (2010). Minor and major depression in the general population: Does dysfunctional thinking play a role? Comprehensive Psychiatry, 51(3), 266–274. doi:10.1016/j.comppsych. 2009.08. 006; Riso, L. P., du Toit, P. L. , Blandino, J. A. , Penna, S. , Dacey, S. , Duin, J. S. , … Ulmer, C. S. (2003). Cognitive aspects of chronic depression. Journal of Abnormal Psychology, 112(1), 72–80. doi:10.1037/0021-843X.112. 1.72]. The present study used an observer-rated measure, the Structural Analysis of Social Behavior [Benjamin, L. S. (1974). Structural Analysis of Social Behavior. Psychological Review, 81(5), 392–425. doi:10.1037/h0037024], to examine patients’ self-directed communication over the course of psychotherapy. Method: Self-talk in early and late therapy sessions was examined using cases (N = 44) from the cognitive therapy arm of Jacobson and colleagues’ component study of cognitive therapy for depression [Jacobson, N. S. , Dobson, K. S. , Truax, P. A. , Addis, M. E. , Koerner, K. , Gollan, J. K. , … Prince, S. E. (1996). A component analysis of cognitive–behavioral treatment for depression. Journal of Consulting and Clinical Psychology, 64(2), 295–304. doi:10.1037/0022-006x.64. 2.295, Jacobson, N. S. , Dobson, K. S. , Truax, P. A. , Addis, M. E. , Koerner, K. , Gollan, J. K. , … Prince, S. E. (2000). A component analysis of cognitive–behavioral treatment for depression. Prevention & Treatment, 3(1). doi:10.1037/1522-3736.3. 1.323a]. We identified changes at treatment termination, and used hierarchical multiple regression to examine whether improvements in patient self-talk influenced treatment outcome up to 24 months post-termination. Results: Trends indicate that patients used friendlier and less critical self-statements at the end of treatment. Decreased self-critical behaviour was associated with fewer symptoms at the end of treatment and up to one year later; increased self-acceptance was linked to symptom improvement a year and a half after termination. Conclusion: Consistent with cognitive theory, reduced self-criticism was associated with better treatment outcomes. Longer-term improvement was linked to the development of friendlier and more accepting self-referential behaviour.
Characterization of Natural Killer Cells in HIV Patients Beginning Therapy with a High Burden of Cytomegalovirus

ABSTRACT Background: Active infections with cytomegalovirus (CMV) increase NK cell expression of the inhibitory receptor LIR-1 and the activating receptor NKG2C in transplant recipients. However, the effects of CMV on NK cells are different in HIV patients stable on antiretroviral therapy (ART) and have not been analyzed in young HIV patients beginning ART. Methodology: We followed a cohort of 78 Indonesian HIV patients beginning ART. CMV antibodies were measured in plasma before ART (baseline), and after 1, 3, 6, and 12 months. CMV DNA was sought in blood granulocytes at baseline by quantitative PCR assay and a deletion in the NKG2C gene was identified by PCR. NK cell profiles were monitored by flow cytometry in 19 patients stratified by the presence of CMV DNA. Healthy controls (n = 17) were assessed once. Results: All 78 patients were CMV seropositive and 41 had detectable CMV DNA. CMV DNA+ patients had higher proportions of total NK cells and CD16+ NK cells at baseline, but similar expression of LIR-1 and NKp30 on NK cells on ART. However, levels of CMV antibody were inversely related to median LIR-1 expression on NK cells. A dramatic elevation in cells expressing NKG2C was restricted to CMV DNA+ patients heterozygous for the NKG2C deletion. Patients with High NKG2C expression had lower levels of CMV antibodies. Conclusion: A subpopulation of NK cells expressing NKG2C was induced by CMV replication in HIV patients heterozygous for a deletion in this gene. Individuals with an abundant NKG2C+ and LIR-1+ NK cells displayed lower levels of CMV reactive antibody.
Low Level Laser Therapy for Healing of Aural Haematoma in Dogs

The study was conducted to evaluate the efficacy of low level laser therapy on healing of aural haematoma in twelve (12) dogs. These dogs were subjected to various clinical examinations viz. degree of inflammation, exudation, embedding of sutures and gross appearance of suture line and recorded on 1st, 3rd, 5th, 7th and 9th day post-operatively using visual score card method. Haemato-biochemical estimations were performed prior to surgery (day 0) and subsequently on 7th day postoperatively. Laser treated dogs revealed less inflammation, exudation, minimum embedding of sutures along with faster healing. The haematological and biochemical parameters remained within normal range by laser treatment, suggestive of no adverse effect on vital body functions, making it a safer therapeutic modality free from any side effects.
Design of the randomized, placebo‐controlled evolocumab for early reduction of LDL‐cholesterol levels in patients with acute coronary syndromes (EVOPACS) trial

Statins lower low‐density lipoprotein cholesterol (LDL‐C) and improve clinical outcomes in patients with atherosclerotic cardiovascular disease (CVD). Patients with acute coronary syndromes (ACS) often do not achieve LDL‐C targets despite potent statin treatment, and have a particularly high risk of early recurrent events. Evolocumab, a proprotein convertase subtilisin/kexin type (PCSK9)‐inhibitor resulting in rapid, marked LDL‐C reduction, has been studied in hypercholesterolemic subjects without CVD and stabilized patients with CVD; the feasibility, safety, and efficacy of this treatment initiated in the acute phase of ACS remain unknown. We report the design of evolocumab for early reduction of LDL‐cholesterol levels in patients with ACS (EVOPACS), a phase‐3, multicenter, randomized, double‐blind, placebo‐controlled trial to assess the feasibility, safety, and LDL‐C‐lowering efficacy of evolocumab on top of atorvastatin 40 mg in patients with ACS. The primary endpoint is percent change in LDL‐C from baseline to 8 weeks. Secondary endpoints are adverse events and serious adverse events. Against a background of beneficial cardiovascular effects of statins beyond LDL‐C lowering and in view of preclinical evidence of similar effects of PCSK9 inhibition, the study will also address a variety of exploratory endpoints including the change in C‐reactive protein and other inflammatory biomarkers; platelet reactivity; and occurrence of contrast‐induced acute kidney injury and myocardial injury in patients undergoing cardiac catheterization. An intracoronary imaging sub‐study will investigate the change from baseline in the lipid core burden index in non‐culprit lesions, as assessed by serial near‐infrared spectroscopy. Recruitment began in January 2018 and enrollment of 308 patients is planned.
An Overview of Cyber Security for Connected Vehicles

SUMMARY The demand for and the scope of connected services have rapidly grown and developed in many industries such as electronic appliances, robotics, and industry automation. In the automotive ﬁeld, including connected vehicles, di ﬀ erent types of connected services have become available and they provide convenience and comfort with users while yielding new business opportunities. With the advent of connected vehicles, the threat of cyber attacks has become a serious issue and protection meth-ods against these attacks are urgently needed to provide safe and secure connected services. From 2017, attack methods have become more sophisticated through di ﬀ erent attack surfaces attached to navigation systems and telematics modules, and security requirements to circumvent such attacks have begun to be established. Individual threats have been addressed previously; however, there are few reports that provide an overview of cyber security related to connected vehicles. This paper gives our perspective on cyber security for connected vehicles based on a survey of recent studies related to vehicle security. To introduce these studies, the environment surrounding connected vehicles is classiﬁed into three categories: inside the vehicle, communications between the back-end systems and vehicles, and the back-end systems. In each category, this paper introduces recent trends in cyber attacks and the protection requirements that should be developed for connected services. We show that the overall security covering the three categories must be considered because the security of the vehicle is jeopar-dized even if one item in the categories is not covered. We believe that this paper will further contribute to development of all service systems related to connected vehicles including autonomous vehicles and to the investigation into cyber security against these attacks.
Toward Supervised Reinforcement Learning with Partial States for Social HRI

Social interacting is a complex task for which machine learning holds particular promise. However, as no sufficiently accurate simulator of human interactions exists today, the learning of social interaction strategies has to happen online in the real world. Actions executed by the robot impact on humans, and as such have to be carefully selected, making it impossible to rely on random exploration. Additionally, no clear reward function exists for social interactions. This implies that traditional approaches used for Reinforcement Learning cannot be directly applied for learning how to interact with the social world. As such we argue that robots will profit from human expertise and guidance to learn social interactions. However, as the quantity of input a human can provide is limited, new methods have to be designed to use human input more efficiently. In this paper we describe a setup in which we combine a framework called Supervised Progressively Autonomous Robot Competencies (SPARC), which allows safer online learning with Reinforcement Learning, with the use of partial states rather than full states to accelerate generalisation and obtain a usable action policy more quickly.
Analysis of Structure and Dynamics in Three-Neuron Motifs

Recurrent neural networks can produce ongoing state-to-state transitions without any driving inputs, and the dynamical properties of these transitions are determined by the neuronal connection strengths. Due to non-linearity, it is not clear how strongly the system dynamics is affected by discrete local changes in the connection structure, such as the removal, addition, or sign-switching of individual connections. Moreover, there are no suitable metrics to quantify structural and dynamical differences between two given networks with arbitrarily indexed neurons. In this work, we present such permutation-invariant metrics and apply them to motifs of three binary neurons with discrete ternary connection strengths, an important class of building blocks in biological networks. Using multidimensional scaling, we then study the similarity relations between all 3,411 topologically distinct motifs with regard to structure and dynamics, revealing a strong clustering and various symmetries. As expected, the structural and dynamical distance between pairs of motifs show a significant positive correlation. Strikingly, however, the key parameter controlling motif dynamics turns out to be the ratio of excitatory to inhibitory connections.
The Boundedness Conditions for Model-Free HDP( $\lambda$ )

This paper provides the stability analysis for a model-free action-dependent heuristic dynamic programing (HDP) approach with an eligibility trace long-term prediction parameter (<inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>). HDP(<inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>) learns from more than one future reward. Eligibility traces have long been popular in Q-learning. This paper proves and demonstrates that they are worthwhile to use with HDP. In this paper, we prove its uniformly ultimately bounded (UUB) property under certain conditions. Previous works present a UUB proof for traditional HDP [HDP(<inline-formula> <tex-math notation="LaTeX">$\lambda =0$ </tex-math></inline-formula>)], but we extend the proof with the <inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> parameter. By using Lyapunov stability, we demonstrate the boundedness of the estimated error for the critic and actor neural networks as well as learning rate parameters. Three case studies demonstrate the effectiveness of HDP(<inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>). The trajectories of the internal reinforcement signal nonlinear system are considered as the first case. We compare the results with the performance of HDP and traditional temporal difference [TD(<inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>)] with different <inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> values. The second case study is a single-link inverted pendulum. We investigate the performance of the inverted pendulum by comparing HDP(<inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>) with regular HDP, with different levels of noise. The third case study is a 3-D maze navigation benchmark, which is compared with state action reward state action, Q(<inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>), HDP, and HDP(<inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>). All these simulation results illustrate that HDP(<inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>) has a competitive performance; thus this contribution is not only UUB but also useful in comparison with traditional HDP.
Analysis of The PPARD Gene Expression Level Changes in Football Players in Response To the Training Cycle

Abstract The PPARD gene codes protein that belongs to the peroxisome proliferator-activated receptor (PPAR) family engaged in a variety of biological processes, including lipid metabolism in muscle cells. In this study, we assess the relationship between PPARD gene expression lipid metabolism parameters and the variation of the PPARD gene expression before (T1) and after 12 hours of training (T2) sessions in a group of football players. Peripheral blood lymphocytes were obtained from 22 football players (17.5±0.7 years, 178±0.7 cm, 68.05±9.18 kg). The PPARD gene expression, analyzed by quantitative polymerase chain reaction (qPCR), was significantly higher after T2 (p = 0.0006). Moreover, at the end of the training cycle, there was a significant decrease in relative fat tissue (FAT) (%) (p = 0.01) and absolute FAT (kg) (p = 0.01). A negative correlation was observed between absolute FAT (kg) and PPARD gene expression level in T2 (p = 0.03). The levels of cholesterol and triglyceride (TG) fractions were not significantly different (p >0.05) before and after training. No significant relationship between PPARD expression and cholesterol or TG levels was found. We found that physical training affects PPARD expression. Moreover, the negative correlation between PPARD expression and absolute FAT (kg) level may be indicative of the contribution of PPARD in metabolic adaptation to increased lipid uptake that can be used to control the body composition of athletes.