Miracle-dz/UniFAR-FTUs huggingface dataset:
Prognosis Prediction Using Therapeutic Agreement of Video Conference–Delivered Cognitive Behavioral Therapy: Retrospective Secondary Analysis of a Single-Arm Pilot Trial

Background The therapist-patient therapeutic alliance is known to be an important factor in cognitive behavioral therapy (CBT). However, findings by previous studies for obsessive-compulsive disorder (OCD), panic disorder (PD), and social anxiety disorder (SAD) have not been consistent regarding whether this alliance provides symptomatic improvements. Objective This study investigated predictors of symptom improvement in patients receiving CBT via video conferencing. Methods A total of 29 patients who participated in a previous clinical trial were recruited for the current study. Therapeutic alliance and clinical background in patients with OCD, PD, and SAD were measured at first session or the eighth session, which were calculated by multiple regression analyses to estimate the impact on therapeutic response percentage change. Results The multiple regression analyses showed that, among the independent variables, only patients’ agreement in the therapeutic alliance remained viable, as other variables were a best fit for the excluded model (P=.002). The results show that patients’ agreement on therapeutic goals and tasks explains the prognosis, as the normalization factor beta was 0.54 (SE 32.73; 95% CI 1.23-5.17; P=.002) and the adjusted R2 was . 266. Conclusions Patients' agreement on therapeutic goals and tasks predicts improvement after CBT via video conferencing. Trial Registration UMIN Clinical Trial Repository UMIN000026609; https://tinyurl.com/ye6dcbwt
EFFECT OF AN INCREMENTAL EXERCISE TO EXHAUSTION ON PLASMA CONCENTRATIONS OF IRON AND ZINC IN ATHLETES AND NONATHLETES

Background: Trace elements are mineral nutrients involved in a lot of physiological processes during exercise. Some of the trace elements, such as iron (Fe) and zinc (Zn) play a major function in maintaining and regulating many of these processes. The variations in plasma Fe and Zn concentrations are dependent which follow intensity as well as the duration of the activity. Endurance exercise until exhaustion causes various changes in the body. Deficiencies in Fe and Zn can harmfully influence endurance performance. Objective: The purpose of the current study was to determine the effects of an incremental exercise until exhaustion on the plasma levels of Fe and Zn in athletes and nonathletes. Methods: Ten elite basketball players (Age: 19.1±0.8 years old, Height: 185.0±6.3 cm, Weight: 71.0±9.8 kg, VO2max: 59.5±7.3 mL.kg-1.min-1) and ten college students (Age: 22.5±3.8 years old, Height: 176.1±7.6 cm, Weight: 67.8±11.4 kg, VO2max: 33.1±8.4 mL.kg-1.min-1) participated as athletes’ group and control group respectively. All trials were conducted at the beginning of a competing season in one week for each group in the Ahvaz city, Khouzestan State, Islamic Republic of Iran. All participants completed 3 separate trials which consisted of maximal oxygen uptake test, a familiarization trial, and an actual trial. They pedaled an incremental exercise to exhaustion in the familiarization (without blood sampling) and actual trials. After a warm–up, the pedaling began on the ergometer at 100 watts and at 60 rpm. Then, the workload was increased gradually to 50 watts every two minutes until exhaustion. The blood samples were drawn three times after the actual trials. Statistical analyses were performed using the IBM SPSS v.25 for Windows. Results: The results of the current study showed a significant decrease in Fe and Zn immediately and 24 hours after incremental exercise to exhaustion (p<0.05) in both groups. However, there were no significant differences between the two groups of athletes and nonathletes (p>0.05). Conclusion: The current study concluded that exhaustive exercise was able to decrease the Fe and Zn status after exercise which may reflect the potential consequences for the dietary requirement of trace elements for physically active inhabitants.
The Prevalence and Analysis of Fibro-osseous Lesions of the Jaws in a Turkish Population Fibro-Osseous Lesions of the Jaws

Introduction Fibro-osseous lesions (FOL)of the jaws are a diverse group of lesions, which are characterized by substitution of normal bone with fibroblast-like cells, collagen bundles, and various mineralized materials (1). The term refers to different entities that present similar macroscopic and microscopic features, indicating they have similar clinical, radiological, and histopathological features but different biological behaviors. This difference in behavior may present a problem in diagnosis and clinical management (2, 3). FOLs of the maxillofacial region have been classified in different ways. The terms “cementifying ossifying fibroma” and “cementifying osseous dysplasias” have been changed to “ossifying fibroma” and “osseous dysplasias” by Reichhart et al (4). This step was taken to finalize the discussion as to whether cementum is produced in these lesions or not. The FOLs are classified into three groups: (1)fibrous dysplasia(FD); (2)ossifying fibroma(OF); and (3)osseous dysplasia(OD)(5). This was a practical classification based on the World Health Organization’s (WHO) criteria. OD has different subtypes. There is some evidence that florid osseous dysplasia(FLOD)is a progressive form of focal osseous dysplasia(FOD). FLOD may be one of its presentations or an early stage of the florid Correspondence to: Aysegul Apaydin E-mail:apaydin@istanbul.edu. tr Article History Abstract
PREVALENCE OF CARBAPENEM-RESISTANT ACINETOBACTER BAUMANNII (CRAB) IN MEDICAL AND SURGICAL INTENSIVE CARE UNITS (ICUS) OF JPMC, KARACHI

Background: Antimicrobial resistance is one of the research priorities of health organizations due to increased risk of morbidity and mortality. Outbreaks of nosocomial infections caused by carbapenem-resistant Acinetobacter Baumannii (CRAB) strains are at rise worldwide. Antimicrobial resistance to carbapenems reduces clinical therapeutic choices and frequently led to treatment failure. The aim of our study was to determine the prevalence of carbapenem resistance in A. baumannii isolated from patients in intensive care units (ICUs). Methods: This cross-sectional study was carried out in the Department of Microbiology, Basic Medical Sciences Institute (BMSI), Jinnah Postgraduate Medical Centre (JPMC), Karachi, from December 2016 to November 2017. Total 63 non-repetitive A. baumannii were collected from the patients’ specimens, admitted to medical and surgical ICUs and wards of JPMC, Karachi. The bacterial isolates were processed according to standard microbiological procedures to observe for carbapenem resistance. SPSS 21 was used for data analysis. Results: Out of the 63 patients, 40 (63.5%) were male. The age of the patient ranged from 15-85 year, with average of 43 year. 34.9% patients had been hospitalized for 3 days. Chronic obstructive pulmonary disease was present in highest number with average of 58.7% for morbidity. Number of patients on mechanical ventilation was highest (65.1%). All isolates were susceptible to colistin. The resistance to ampicillin-sulbactam, ceftazidime, ciprofloxacin, amikacin, piperacillin- tazobactam and meropenem was 82.5%, 81%, 100%, 87.3%, 82.5% and 82% respectively. Out of 82% CRAB, 77% were obtained from ICUs. Conclusion: This study has revealed the high rate of carbapenem resistance in A. baumannii isolates in ICUs thus leaving behind limited therapeutic options.
A study to assess the association of various factors of adherence to treatment on the tuberculosis treatment outcome among new sputum smear positive pulmonary tuberculosis patients under Revised National Tuberculosis Control Programme in Bengaluru area

Background: Tuberculosis (TB) is a top infectious disease killer worldwide. In India although Revised National Tuberculosis Control Programme (RNTCP) has seen significant success in TB treatment, patient non-adherence or lost to follow up continue to persist and are influenced by various factors. The present study aims to know the influence of adherence factors on TB treatment outcome among new sputum smear positive (NSSP) pulmonary TB patients under RNTCP. The objectives of the present study were to describe the distribution of socio-demographic factors, outcome patterns among NSSP patients and to assess the association of various adherence factors on TB-treatment outcome among NSSP patients.Methods: A prospective longitudinal study among 149 NSSP patients from selected TU’s of Bengaluru.Results: Among the 149 NSSP patients 107 (72%) were males and 42 (28%) were females. Treatment outcome is categorized as cured (120) and other treatment outcomes (defaulted-17 or treatment failure-3 or died-9). Among the various socio-demographic and adherence-factors: age >50years, illiteracy, male-gender, Hindu-religion, lower socioeconomic-status, poor-patient knowledge about TB, disbelief in TB-treatment, unwillingness to continue treatment with subsiding symptoms, smoking, alcohol intake, presence of diabetes or hypertension or COPD or HIV, patient’s un-satisfaction with treatment-availability or accessibility or contact-timings, no-encouragement from family members, other marital status and absence of stigma showed lower cure rates. Of these factors illiteracy, lower socioeconomic-status, poor patient’s knowledge on tuberculosis, smoking, alcohol intake, HIV positive status, un-satisfaction with TB-treatment availability and other marital-status showed statistical significance on the TB treatment outcome.Conclusions: With the observed associations of the above factors on TB-treatment outcome, Further measures like improving patient’s knowledge on tuberculosis, health-services and patient-provider relationship; appropriate TB-HIV care and encouragement to quit smoking or alcohol intake, could improve TB-treatment cure rates.
Meaningful outcome research to validate endoscopic treatment of common lumbar pain generators with durability analysis.

Endoscopic spine surgery may be questioned for its medical necessity and effectiveness when compared to other forms of spinal surgeries. The call for clinical evidence to justify the need for capital equipment purchases, disposables, and additional training often follows and is echoed by the repetitive question why endoscopy is better and more cost effective than traditional open or other types of translaminar minimally invasive spine surgery. What is evident though, is the pushback by payers purely against any advancement in spine care because of escalating costs. Lack of clinical evidence is the number one cited reason why coverage for proposed endoscopic spine care is denied by deeming it experimental and medically not necessary. Clinical coverage- and treatment guidelines written by payers and surgical societies are centered around available high-grade evidence published in the peer-reviewed literature.
Finite-Gain Repetitive Controller for Harmonic Sharing Improvement in a VSM Microgrid

Electronic power interfaces are commonly used in microgrids for renewable energy integration and a control method based on a virtual synchronous machine (VSM) represents an attractive alternative to conventional approaches. This control method has several advantages, however, a number of issues still need to be properly addressed, including those of power quality and harmonic current sharing. In this paper, a finite-gain repetitive controller (FGRC) is proposed to improve the current harmonic distribution in microgrids based on VSMs. Stability, transient performance, and performance under frequency variations are studied analytically. When compared to other control options, the method proposed here is capable of dealing with all harmonics simultaneously. A comparative analysis is provided to emphasize the contributions of this paper. The control system improvements were tested on a prototype microgrid consisting of two 15 kVA VSMs, distribution line impedances, and a non-linear load.
Learning dialogue POMDP model components from expert dialogues

Spoken dialogue systems should realize the user intentions and maintain a natural and efficient dialogue with users. This is however a difficult task as spoken language is naturally ambiguous and uncertain, and further the automatic speech recognition (ASR) output is noisy. In addition, the human user may change his intention during the interaction with the machine. To tackle this difficult task, the partially observable Markov decision process (POMDP) framework has been applied in dialogue systems as a formal framework to represent uncertainty explicitly while supporting automated policy solving. In this context, estimating the dialogue POMDP model components is a significant challenge as they have a direct impact on the optimized dialogue POMDP policy. This thesis proposes methods for learning dialogue POMDP model components using noisy and unannotated dialogues. Specifically, we introduce techniques to learn the set of possible user intentions from dialogues, use them as the dialogue POMDP states, and learn a maximum likelihood POMDP transition model from data. Since it is crucial to reduce the observation state size, we then propose two observation models: the keyword model and the intention model. Using these two models, the number of observations is reduced significantly while the POMDP performance remains high particularly in the intention POMDP. In addition to these model components, POMDPs also require a reward function. So, we propose new algorithms for learning the POMDP reward model from dialogues based on inverse reinforcement learning (IRL). In particular, we propose the POMDP-IRL-BT algorithm (BT for belief transition) that works on the belief states available in the dialogues. This algorithm learns the reward model by estimating a belief transition model, similar to MDP (Markov decision process) transition models. Ultimately, we apply the proposed methods on a healthcare domain and learn a dialogue POMDP essentially from real unannotated and noisy dialogues.
Distribution Network Reconfiguration for Loss Reduction and Voltage Stability With Random Fuzzy Uncertainties of Renewable Energy Generation and Load

This paper presents a distribution reconfiguration framework to adapt to the distribution network considering the twofold random and fuzzy uncertainties of the wind, photovoltaic power generation, and load demand and considering the power loss reduction and voltage stability. First, the random fuzzy power output models of distributed generation and load are built based on the random fuzzy theory. Second, the corresponding objective functions are established, which are the random fuzzy expected value of active power loss and maximum probability of voltage limit. Third, the modified particle swarm optimization (MPSO) algorithm based on Kruskal algorithm is introduced for the first time to determine the optimal network topology. The Kruskal algorithm is employed to generate a radial network topology directly without checking the loops and islands. Lastly, the proposed method is applied to the IEEE33, PG&E 69-bus distribution systems, 25-bus unbalanced distribution system, as well as a real 109-bus distribution system. The results show that the proposed method has a good performance to solve distribution network reconfiguration problem.
Upregulation of sphingosine kinase 1 is associated with recurrence and poor prognosis in papillary thyroid carcinoma

Sphingosine kinase 1 (SPHK1), an ATP-dependent protein, has previously been demonstrated to be upregulated in several types of human cancer and to play an important role in tumor development and progression. However, the role of SPHK1 in predicting long-term prognosis in patients with papillary thyroid carcinoma (PTC) remains unclear. The purpose of the present study was to assess the significance of SPHK1 expression and its associations with clinicopathological characteristics and prognostic outcome in patients with PTC. Immunohistochemistry staining was retrospectively performed to investigate the expression levels of SPHK1 in 92 PTC tumors. Statistical analyses revealed that high levels of SPHK1 expression were associated with tumor size, lymph node metastasis and the Tumor-Node-Metastasis stage. The disease-free survival (DFS) time of patients that exhibited high levels of SPHK1 expression was shorter, whereas patients with lower levels of SPHK1 expression survived longer. Furthermore, multivariate analysis suggested that upregulated SPHK1 was an independent prognostic factor for predicting DFS of patients with PTC. The results of the Cell Counting Kit-8 and invasion assays demonstrated that SPHK1 overexpression significantly enhanced the proliferation and invasion of a PTC cell line, consistent with clinical findings. The results from the present study provide evidence that elevated expression levels of SPHK1 may be involved in the development and progression of PTC, indicating that this protein may act as a potential prognostic marker for patients with this disease.
Distributed and Robust Statistical Learning

Decentralized and corrupted data are nowadays ubiquitous, which impose fundamental challenges for modern statistical analysis. Illustrative examples are massive and decentralized data produced by distributed data collection systems of giant IT companies, corrupted measurement in genetic micro-array analysis, heavy-tailed returns of stocks and etc. These notorious features of modern data often contradict conventional theoretical assumptions in statistics research and invalidate standard statistical procedures. My dissertation addresses these problems by proposing new methodologies with strong statistical guarantees. When data are distributed over different places with limited communication budget, we propose to do local statistical analysis first and aggregate the local results rather than the data themselves to generate a final result. We applied this approach to low-dimensional regression, high-dimensional sparse regression and principal component analysis. When data are not over-scattered, our distributed approach is proved to achieve the same statistical performance as the full sample oracle, i.e., the standard procedure based on all the data. To handle heavy-tailed corruption, we propose a generic principle of data shrinkage for robust estimation and inference. To illustrate this principle, we apply it to estimate regression coefficients in the trace regression model and generalized linear model with heavy-tailed noise and design. The proposed method achieves nearly the same statistical error rate as the standard procedure while requiring only bounded moment conditions on data. This widens the scope of high-dimensional techniques, reducing the moment conditions from sub-exponential or sub-Gaussian distributions to merely bounded second or fourth moment.
METABOLITES PROFILE OF COLORECTAL CANCER CELLS AT DIFFERENT STAGES

Objective: The aim of this study is to characterize the metabolite profiles of colorectal cancer (CRC) cells of different stages of the disease to understandthe pathophysiological changes that may help to identify prevention strategies as well as the sites for potential therapeutic drug actions.Methods: Six CRC cell lines of different stages (classified using the Dukes classification) were used, and they are SW 1116 (stage A), HT 29 and SW480 (stage B), HCT 15 and DLD-1 (stage C), and HCT 116 (stage D). Metabolites were extracted using methanol and water, and metabolic profiling wasperformed using liquid chromatography-mass spectrometry. Mass profiler professional software was used for statistical analysis.Results: There were 111,096 compounds detected across the samples, and 24 metabolites were identified to be significantly different betweenthe CRC stages. Most notably, there were eight metabolites that were significantly upregulated in the more advanced stages (B, C, and D) comparedwith Stage A. These metabolites include flavin mononucleotide, l-methionine, muricatacin, amillaripin, 2-methylbutyroylcarnitine, lumichrome,hexadeconoic acid, and lysoPE (0:0/16:0). Conclusion: This study showed that the expressions of metabolites at different stages of CRC were different, which represent the metabolic changesoccurring as CRC advances. The knowledge may help identify biomarkers for the staging of CRC, which could improve its prognosis as well as providea basis for the development of therapeutic interventions.
Orotracheal treprostinil administration attenuates bleomycin-induced lung injury, vascular remodeling, and fibrosis in mice

Pulmonary fibrosis is a progressive disease characterized by disruption of lung architecture and deregulation of the pulmonary function. Prostacyclin, a metabolite of arachidonic acid, is a potential disease mediator since it exerts anti-inflammatory and anti-fibrotic actions. We investigated the effect of treprostinil, a prostacyclin analogue, in bleomycin-induced experimental pulmonary fibrosis. Bleomycin sulfate or saline was administrated intratracheally to mice (n = 9–10/group) at day 0. Orotracheal aspiration of treprostinil or vehicle was administered daily and started 24 h prior to bleomycin challenge. Evaluation of lung pathology was performed in tissue samples and bronchoalveolar lavage fluid collected 7, 14 and 21 days after bleomycin exposure. Lung injury was achieved due to bleomycin exposure at all time points as indicated by impaired lung mechanics, pathologic lung architecture (from day 14), and cellular and protein accumulation in the alveolar space accompanied by a minor decrease in lung tissue VE-cadherin at day 14. Treprostinil preserved lung mechanics, and reduced lung inflammation, fibrosis, and vascular remodeling (day 21); reduced cellularity and protein content of bronchoalveolar lavage fluid were additionally observed with no significant effect on VE-cadherin expression. Bleomycin-induced collagen deposition was attenuated by treprostinil from day 14, while treprostinil involvement in regulating inflammatory processes appears mediated by NF-κB signaling. Overall, prophylactic administration of treprostinil, a stable prostacyclin analogue, maintained lung function, and prevented bleomycin-induced lung injury, and fibrosis, as well as vascular remodeling, a hallmark of pulmonary hypertension. This suggests potential therapeutic efficacy of treprostinil in pulmonary fibrosis and possibly in pulmonary hypertension related to chronic lung diseases.
Exploring Genetic Biomarkers in a Sample of Depressed Patients in the UAE

This study focuses on exploring the expression of genes associated with depressive and anxiety disorders (AD) among depressed individuals. Anxiety and depression are well known to co-occur with each other. Growing research in the field of genetics has indicated moderate familial aggregation for these disorders. The aim of this study is to analyze gene expression among a depressed population residing in the UAE. The genes chosen to be studied (PPARGC1A, CAMKMT, HSD11B1, SLC6A4 and MAOA) have previously been linked to depression and anxiety in other populations. The study employed a case-control design, where gene expression in blood samples of the depressed group (29 participants) were compared with a control group (30 participants). Initial screening of depression levels for all participants was done using the Beck Depression Inventory (BDI) and Patient Health Questionnaire – 9 (PHQ9), and formal diagnosis for participants in the depression group was given by psychiatrists using ICD-10 criteria. Results indicate that the expression of PPARGC1A gene is significantly lower among the depressed group. These results indicate a novel association of PPARGC1A with depression and open several possibilities for further research to study its role as a protective factor against developing depression.