Miracle-dz/UniFAR-FTUs huggingface dataset:
Chess and Mathematics Performance of College Players: An Exploratory Analysis

The purpose of this study is to explore the performance in Chess and in Mathematics of the college players in Cabanatuan City, Philippines. Specif-ically, it aimed to determine the respondents’ mathematics and chess per-formances, their playing styles and their beliefs regarding chess players and mathematicians. The descriptive correlational research design was utilized in this study and the data gathered by the researcher were tallied and tabulated using frequency, percentage, mean and Pearson’s r. Furthermore, open-ended questions were used to solicit remarks/comments from the respondents regarding the role of chess in enhancing their thinking skills. It was found out that the general weighted average (GWA) in Mathematics of the respondents was above average. Most of them are barangay/school level champions. Males are tactician type of players while females are positional players. A respondent who performed better in higher chess competition also performed better or obtained higher GWA in Mathematics. Furthermore, the respondents believed that a chess player can be a good mathematician especially if they start playing early in life and if chess was a part of the school curriculum since playing chess continuously has helped them in developing and improving their problem solving and critical thinking skills.
PD-L1 Mediates Dysfunction in Activated PD-1+ NK Cells in Head and Neck Cancer Patients

PD-1 expression and function were assessed in NK cells from patients with head and neck cancer. NK cell dysfunction was reversed by PD-1 blockade and improved responses to cetuximab therapy, thus, providing an approach to reverse tumor immune evasion. Inhibitory immune-checkpoint receptors (ICRs), including programmed death 1 (PD-1), have been characterized as exhaustion markers on T cells that infiltrate the tumor microenvironment (TME) of many cancer types, including head and neck cancer (HNC). However, expression and function of ICRs, including PD-1, on natural killer (NK) cells remains less defined. NK cells are innate immune effector cells that lyse epidermal growth factor receptor–overexpressing HNC cells via cetuximab-mediated antibody-dependent cytotoxicity. Cetuximab is clinically effective but only in 10% to 15% of patients. Therefore, it is necessary to investigate how immunomodulation with cetuximab or PD-1 blockade might enhance NK cell responses in the TME and improve monoclonal antibody therapeutic efficacy. We observed that expression of PD-1 on NK cells marks an activated phenotype, which was suppressed only after binding programmed death ligand-1 (PD-L1). HNC patients who exhibit higher circulating PD-1+ NK cells associate with better clinical outcome, and these cells are enriched in the TME. Cetuximab-mediated NK cell activation increased PD-1 expression on NK cells in vitro, which was confirmed in vivo in a prospective neoadjuvant cetuximab trial. In contrast, PD-L1 ligation of PD-1+ NK cells diminished their activation status, whereas PD-1 blockade increased cetuximab-mediated NK cell activation and cytotoxicity, but only against HNC targets with high PD-L1 expression. Therefore, blocking the PD-1–PD-L1 axis may be a useful strategy to reverse immune evasion of HNC tumors with high PD-L1 expression during cetuximab therapy by reversing NK cell dysfunction.
Bone mineral density and general health of long-term residential psychiatric inpatients

Abstract Objective: The aim of this study was to determine the rates of osteopenia and osteoporosis and other general health problems in a long-stay male psychiatric unit. Method: All 15 patients underwent a semi-structured clinical interview and a full physical examination including calculation of Body Mass Index, central obesity (abdominal circumference) and blood pressure measurement. All patients had blood sampling examining FBC, U&E, LFTs, TFTs, PSA, prolactin, lipid profile and glucose. The rates of metabolic syndrome were calculated according to the International Diabetes Federation consensus worldwide definition. Bone mineral density was determined in the lumbar vertebrae and left hip by DEXA scanning. Results: The prevalence of osteopenia or osteoporosis was 46%, and bone mineral density was inversely correlated with serum prolactin levels (r = -0.595, p = 0.041) and chlorpromazine equivalence (r = -0.645, p = 0.017). The prevalence of obesity was 53%, while central obesity was present in 87% of patients. Metabolic Syndrome was present in 27% of patients. Conclusions: More attention should be given to diagnosing and treating osteopenia and osteoporosis in patients on long-term antipsychotic agents and preventative measures should form part of any treatment regime in these individuals. Frequent input from dietitians should also be available for long-stay psychiatric inpatients to reduce the prevalence of obesity.
Cytokine Mixtures Mimicking Secretomes From Mesenchymal Stem Cells Improve Medication‐Related Osteonecrosis of the Jaw in a Rat Model

Recently, several studies have demonstrated that intravenous administration of mesenchymal stem cells (MSCs) improve medication‐related osteonecrosis of the jaw (MRONJ), and paracrine effects of secretomes from MSCs have been hypothesized as the primary contributors. These secretomes in conditioned media from human MSCs (MSC‐CM) were previously demonstrated to promote bone and tissue regeneration. Because MSC‐CM contain cytokines monocyte chemoattractant protein (MCP)‐1, insulin growth factor (IGF)‐1, and vascular endothelial growth factor (VEGF) at relatively higher concentrations than other factors, these cytokines were considered as relevant active factors for tissue regeneration. By mixing the recombinant proteins of MCP‐1, IGF‐1, and VEGF, included at the same concentrations in MSC‐CM, we prepared cytokine mixtures mimicking MSC‐CM and then evaluated its therapeutic effects in a rat MRONJ model. In vitro, cytokine mixtures promoted osteogenic differentiation, migration, and proliferation of rat MSCs. In addition, these maintained osteoclastic function. In vivo, we used a rat MRONJ model to examine therapeutic effects of the cytokine mixtures through intravenous administration. In MSC‐CM or cytokine mixture group, open alveolar sockets in 66% or 67% of the rats with MRONJ, respectively, healed with complete soft tissue coverage and socket bones, whereas in the other groups, the exposed necrotic bone with inflamed soft tissue remained. Histological analysis revealed new bone formation and the appearance of osteoclasts in MSC‐CM or cytokine mixture group; however, osteoclasts were significantly reduced in the other groups. Thus, we concluded that intravenous administration of cytokine mixtures might be an effective therapeutic modality for treating patients with MRONJ. © 2017 The Authors JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research
Community placement planning for a long stay in-hospital population

Physician awareness and knowledge of the effects of methadone dose on QT prolongation and development of Torsades de Pointes is of huge importance. Patients on methadone would benefit from screening for cardiac risk factors. An electrocardiogram is deemed important in patients on high doses of methadone, an increasing methadone dose and if commencing QT prolonging medications. Drug-drug interactions play a key role in the occurrence of QT interval drugs. Routine toxicology screening is invaluable to monitor for abusing cocaine and unreported methadone physicians need to enhance the monitoring of out at risk vulnerable population who lead a chaotic lifestyle and some without a general practitioner. Improved communication between drug treatment services, general practitioners, infectious disease clinics and cardiology department to ensure follow up and management of our at risk population. Deirdre Hussey, Catherine McCarthy, Eamon Keenan, National Drug Treatment Centre, Pearse Street, Dublin, Ireland.
A Three-Stage Deep Learning Model for Accurate Retinal Vessel Segmentation

Automatic retinal vessel segmentation is a fundamental step in the diagnosis of eye-related diseases, in which both thick vessels and thin vessels are important features for symptom detection. All existing deep learning models attempt to segment both types of vessels simultaneously by using a unified pixel-wise loss that treats all vessel pixels with equal importance. Due to the highly imbalanced ratio between thick vessels and thin vessels (namely the majority of vessel pixels belong to thick vessels), the pixel-wise loss would be dominantly guided by thick vessels and relatively little influence comes from thin vessels, often leading to low segmentation accuracy for thin vessels. To address the imbalance problem, in this paper, we explore to segment thick vessels and thin vessels separately by proposing a three-stage deep learning model. The vessel segmentation task is divided into three stages, namely thick vessel segmentation, thin vessel segmentation, and vessel fusion. As better discriminative features could be learned for separate segmentation of thick vessels and thin vessels, this process minimizes the negative influence caused by their highly imbalanced ratio. The final vessel fusion stage refines the results by further identifying nonvessel pixels and improving the overall vessel thickness consistency. The experiments on public datasets DRIVE, STARE, and CHASE_DB1 clearly demonstrate that the proposed three-stage deep learning model outperforms the current state-of-the-art vessel segmentation methods.
Combining SERS analysis of serum with PSA levels for improving the detection of prostate cancer.

AIM Previous studies regarding surface-enhanced Raman scattering (SERS) of serum have shown promising initial results in discriminating prostate cancer, a strategy which could complement standard tests such as the prostate-specific antigen (PSA). MATERIALS & METHODS SERS spectra of serum samples were combined with serum PSA levels to improve the discrimination accuracy between prostate cancer and nonmalignant pathologies in a cohort of 54 patients using principal component analysis-linear discriminant analysis (PCA-LDA). RESULTS & DISCUSSION Combining SERS spectra with serum PSA levels in a single PCA-LDA model could discriminate between the two groups with an overall accuracy of 94%, yielding better results than either method alone. CONCLUSION These results highlight that combining SERS-based cancer screening with serum PSA levels represents a promising strategy for improving the accuracy of prostate cancer diagnosis.
An Engagement Model Based on User Interest and QoS in Video Streaming Systems

With the surging demand on high-quality mobile video services and the unabated development of new network technology, including fog computing, there is a need for a generalized quality of user experience (QoE) model that could provide insight for various network optimization designs. A good QoE, especially when measured as engagement, is an important optimization goal for investors and advertisers. Therefore, many works have focused on understanding how the factors, especially quality of service (QoS) factors, impact user engagement. However, the divergence of user interest is usually ignored or deliberatively decoupled from QoS and/or other objective factors. With an increasing trend towards personalization applications, it is necessary as well as feasible to consider user interest to satisfy aesthetic and personal needs of users when optimizing user engagement. We first propose an Extraction-Inference (E-I) algorithm to estimate the user interest from easily obtained user behaviors. Based on our empirical analysis on a large-scale dataset, we then build a QoS and user Interest based Engagement (QI-E) regression model. Through experiments on our dataset, we demonstrate that the proposed model reaches an improvement in accuracy by 9.99% over the baseline model which only considers QoS factors. The proposed model has potential for designing QoE-oriented scheduling strategies in various network scenarios, especially in the fog computing context.
An improved method for utilizing high‐throughput amplicon sequencing to determine the diets of insectivorous animals

DNA analysis of predator faeces using high‐throughput amplicon sequencing (HTS) enhances our understanding of predator–prey interactions. However, conclusions drawn from this technique are constrained by biases that occur in multiple steps of the HTS workflow. To better characterize insectivorous animal diets, we used DNA from a diverse set of arthropods to assess PCR biases of commonly used and novel primer pairs for the mitochondrial gene, cytochrome oxidase C subunit 1 (COI). We compared diversity recovered from HTS of bat guano samples using a commonly used primer pair “ZBJ” to results using the novel primer pair “ANML. ” To parameterize our bioinformatics pipeline, we created an arthropod mock community consisting of single‐copy (cloned) COI sequences. To examine biases associated with both PCR and HTS, mock community members were combined in equimolar amounts both pre‐ and post‐PCR. We validated our system using guano from bats fed known diets and using composite samples of morphologically identified insects collected in pitfall traps. In PCR tests, the ANML primer pair amplified 58 of 59 arthropod taxa (98%), whereas ZBJ amplified 24–40 of 59 taxa (41%–68%). Furthermore, in an HTS comparison of field‐collected samples, the ANML primers detected nearly fourfold more arthropod taxa than the ZBJ primers. The additional arthropods detected include medically and economically relevant insect groups such as mosquitoes. Results revealed biases at both the PCR and sequencing levels, demonstrating the pitfalls associated with using HTS read numbers as proxies for abundance. The use of an arthropod mock community allowed for improved bioinformatics pipeline parameterization.
A Divide-and-Conquer-Based Ensemble Classifier Learning by Means of Many-Objective Optimization

Divide-and-conquer-based methods are quite successful across various problems from different disciplines. These methods divide a complex task into multiple simple tasks and solve them collectively. This paper presents a divide-and-conquer-based hierarchical optimization framework for ensemble classifier learning (ECL). The optimization framework includes a search space creation process [called data training environments (DTE)] that divides the data into multiple clusters, and then trains a set of heterogeneous base classifiers with the DTEs. The classifiers are then combined to form an optimal ensemble, by finding the fittest ones using many-objective optimization. The many-objective optimization algorithm considers each class accuracy as a separate objective and maximizes the class accuracies. An additional objective is also taken into account by maximizing the ensemble size. Since the partitioning of data creates diversity within the pool of classifiers, class accuracy tradeoff among the classifiers is observed. As a result, increasing the number of classifiers also increases the diversity within the ensemble. In order to tackle the optimization, a specialized many-objective optimization algorithm based on decomposition is proposed. Since ECL can be regarded as an NP-hard problem, the proposed optimization algorithm, instead identifies the optimal ensemble using a divide-and-conquer rule-based chromosome encoding. Moreover, with the involvement of individual class accuracy in the objectives, the performance does not get biased toward any majority class. The proposed framework is experimented with 24 benchmark datasets obtained from the UCI machine learning repository and compared with the existing approaches. The experimental results show better classification accuracy with the proposed framework in comparison with the recent ensemble classifiers.
Sleep and Wakefulness Are Controlled by Ventral Medial Midbrain/Pons GABAergic Neurons in Mice

Sleep–wake behavior is controlled by a wide range of neuronal populations in the mammalian brain. Although the ventral midbrain/pons (VMP) area is suggested to participate in sleep–wake regulation, the neuronal mechanisms have remained unclear. Here, we found that nonspecific cell ablation or selective ablation of GABAergic neurons by expressing diphtheria toxin fragment A in the VMP in male mice induced a large increase in wakefulness that lasted at least 4 weeks. In contrast, selective ablation of dopaminergic neurons in the VMP had little effect on wakefulness. Chemogenetic inhibition of VMP GABAergic neurons also markedly increased wakefulness. The wake-promoting effect of the VMP GABAergic neuron ablation or inhibition was attenuated to varying degrees by the administration of dopamine D1 or D2/3 receptor antagonists and abolished by the administration of both antagonists together. In contrast, chemogenetic activation of VMP GABAergic neurons very strongly increased slow-wave sleep and reduced wakefulness. These findings suggest that VMP GABAergic neurons regulate dopaminergic actions in the sleep–wake behavior of mice. SIGNIFICANCE STATEMENT Current understanding of the neuronal mechanisms and populations that regulate sleep–wake behavior is incomplete. Here, we identified a GABAergic ventral midbrain/pons area that is necessary for controlling the daily amount of sleep and wakefulness in mice. We also found that these inhibitory neurons control wakefulness by suppressing dopaminergic systems. Surprisingly, activation of these neurons strongly induced slow-wave sleep while suppressing wakefulness. Our study reveals a new brain mechanism critical for sleep–wake regulation.
N-acetylmannosamine (ManNAc) supports the growth of Borrelia burgdorferi in the absence of N-acetylglucosamine (GlcNAc)

Borrelia burgdorferi, the causative agent of Lyme disease, lacks the ability to biosynthesize many essential nutrients de novo, including N-acetylglucosamine (GlcNAc). This amino sugar is required for cell wall synthesis, and is a component of the complex growth medium used for in vitro propagation. When cultured without free GlcNAc, B. burgdorferi cells exhibit a unique biphasic growth pattern. We hypothesized that genes involved in the GlcNAc starvation response would be differentially expressed when compared to cells cultured in complete medium, and investigated this using transcriptomics. Twenty-one genes were differentially regulated in wild-type and starvation-adapted cells cultured without GlcNAc compared to wild-type cells cultured with GlcNAc. Of those, three genes involved in carbohydrate utilization were upregulated: bbb04 (chbC) encoding a subunit of the chitobiose transporter, bb0629 (fruA-2) encoding a putative carbohydrate transporter and bb0644 (nanE) encoding a putative GlcNAc-6-phosphate-2-epimerase predicted to catalyze the conversion of N-acetylmannosamine-6-phosphate (ManNAc-6-P) to GlcNAc-6-P. Quantitative RT-PCR was used to confirm differential expression of select genes, and substitution of free GlcNAc with free ManNAc resulted in growth to high cell density, suggesting B. burgdorferi cells can utilize free ManNAc for cell wall synthesis and energy production.
Etanercept in patients with inflammatory hand osteoarthritis (EHOA): a multicentre, randomised, double-blind, placebo-controlled trial

Objective Hand osteoarthritis is a prevalent disease with limited treatment options. Since joint inflammation is often present, we investigated tumour necrosis factor (TNF) as treatment target in patients with proven joint inflammation in a proof-of-concept study. Methods This 1-year, double-blind, randomised, multicentre trial (NTR1192) enrolled patients with symptomatic erosive inflammatory hand osteoarthritis. Patients flaring after non-steroidal anti-inflammatory drug washout were randomised to etanercept (24 weeks 50 mg/week, thereafter 25 mg/week) or placebo. The primary outcome was Visual Analogue Scale (VAS) pain at 24 weeks. Secondary outcomes included clinical and imaging outcomes (radiographs scored using Ghent University Scoring System (GUSS, n=54) and MRIs (n=20)). Results Of 90 patients randomised to etanercept (n=45) or placebo (n=45), respectively, 12 and 10 discontinued prematurely. More patients on placebo discontinued due to inefficacy (6 vs 3), but fewer due to adverse effects (1 vs 6). The mean between-group difference (MD) in VAS pain was not statistically significantly different (−5.7 (95% CI −15.9 to 4.5), p=0.27 at 24 weeks; − 8.5 (95% CI −18.6 to 1.6), p=0.10 at 1 year; favouring etanercept). In prespecified per-protocol analyses of completers with pain and inflammation at baseline (n=61), MD was −11.8 (95% CI −23.0 to −0.5) (p=0.04) at 1 year. Etanercept-treated joints showed more radiographic remodelling (delta GUSS: MD 2.9 (95% CI 0.5 to 5.4), p=0.02) and less MRI bone marrow lesions (MD −0.22 (95% CI −0.35 to −0.09), p = 0.001); this was more pronounced in joints with baseline inflammation. Conclusion Anti-TNF did not relieve pain effectively after 24 weeks in erosive osteoarthritis. Small subgroup analyses showed a signal for effects on subchondral bone in actively inflamed joints, but future studies to confirm this are warranted.
Novel Incentive Mechanism for End-Users Enrolled in DLC-Based Demand Response Programs Within Stochastic Planning Context

In this paper, a novel direct load control (DLC) planning based on providing free energy credits to residential end-users for their heating, ventilation, and air conditioning load during demand response (DR) events is proposed. The obtained credit can then be used by the end-users during relatively higher price periods free-of-cost to enable them lowering their energy procurement costs. Furthermore, the resulting reduction in the total household energy consumption considerably decreases the critical load demands in power systems, which is of vital importance for load-serving entities in maintaining the balance between supply and demand during peak load periods. In this regard, the aforementioned energy credits-based incentive mechanism is proposed for end-users enrolled in the DLC-based DR program, as a new contribution to the existing literature, testing it in a stochastic day-ahead planning context.