Miracle-dz/UniFAR-FTUs huggingface dataset:
Thyroid Carcinoma Showing Thymus-like Differentiation (CASTLE): A Case Report

Background and Objectives: Carcinoma showing thymus-like differentiation (CASTLE) is a low-grade thyroid carcinoma, with an indolent clinical course and usually a favorable prognosis. The clinical and imagistic features are not specific for CASTLE but similar to other malignant lesions of the thyroid. Definite diagnosis is based on an immunohistochemical examination, as this carcinoma shows positive CD5 immunoreactivity when compared to other aggressive thyroid carcinomas. Case presentation: The main focus of this study is to outline a rare case of CASTLE compressing the trachea in a 50-year-old female patient who was initially diagnosed with undifferentiated thyroid carcinoma, for which she underwent unsuccessful surgery, as well as postoperative radiotherapy and chemotherapy. After receiving a second medical opinion, the patient underwent a challenging radical resection consisting in total thyroidectomy and central neck dissection, with no local recurrence after 6 months and 2 years of follow-up and negative metastatic follow-up. The correct diagnosis has been established based on pathological and immunohistochemical examinations. Conclusions: In summary, the diagnosis of CASTLE is difficult and requires an experienced histological analysis and CD5 immunoreactivity. Lack of metastasis, complete removal of the tumor, and a low degree of tumor infiltration into nearby structures are all associated with better long-term survival.
COMPARISON OF SARS-COV2 GENOME SEQUENCES FROM PAKISTAN WITH GENOME SEQUENCES FROM OTHER COUNTRIES

OBJECTIVE: To analyze SARS-CoV-2 whole genome reported of Pakistan and compare them with other viral strains collected from other world region to better understand the origin and genetic characterization of the virus. METHODS: All the available genomic information of SARS-CoV-2 including Pakistani strains were collected from various online sources. Phylogenetic analysis of 131 sequences from 11 countries (Brazil, China, India, Italy, Nepal, Pakistan, Spain, Sweden, Taiwan, USA and Viet-Nam) were performed and compared with other related coronaviruses to find the evolution of virus and its origin. Individual SARS-CoV-2 gene, spike (S) glycoprotein and the receptor binding domain (RBD) with closely related coronaviruses were compared to further explore genetic variations and the likely RBD properties of the virus. RESULTS: The analysis shows that genome of all analyzed 131 SARS-CoV-2 strains collected from different geographical area were extremely similar, exhibiting >99% sequence identity. Notably, genome of the SARS-CoV-2 has high similarity (89.1% sequence identity) with the two bat-derived severe acute respiratory syndrome (SARS) like betacoronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21 but was sufficiently divergent from SARS-CoV (82.3% similarity) and MERS-CoV (50% similarity). Phylogenetic analysis shows that the SARS-CoV-2 has relatively similar spike glycoprotein with bat-SL-CoVZC45, however, the RBD was more like that of SARS-CoVGZ02. CONCLUSION: Using different bioinformatics tools, we determined that SARS-CoV-2 has high similarities to bat-derived SARS like betacoronaviruses than SARS-CoV at the whole genome level, however, the RBD was more like that of SARS-CoVGZ02, which shows that they use similar ACE2 as a cell receptor.
A multifrequency radio continuum survey of M33. III, The magnetic field

The linear polarization and Faraday depolarization of M 33 between 21.1 and 2.8 cm are analysed. Uniformity, strength and orientation of the magnetic field, Alfven velocity and rotation measures are determined. The field structure is dicussed in terms of the currently existing axisymmetric and bisymmetric models.
3D-Printed Compact Waveguide Filters Based on Slanted Ridge Resonators

This paper presents the design of waveguide filters based on the slanted ridge resonators and their implementation by additive manufacturing. The slanted ridge resonator is a simple and compact structure that can be used to implement singlets in the rectangular waveguide technology. The adopted manufacturing process is based on the 3D printing by plastic material and the subsequent metallization. To this aim, the component is printed in two parts according to a novel splitting strategy. A set of prototypes were fabricated and measured to validate the proposed design and manufacturing.
Understanding the Flow Physics of Shock Boundary Layer Interactions Using CFD and Numerical Analyses

Computational fluid dynamic (CFD) analyses of the University of Michigan (UM) Shock/Boundary-Layer Interaction (SBLI) experiments were performed as an extension of the CFD SBLI Workshop held at the 48th AIAA Aerospace Sciences Meeting in 2010. In particular, the UM Mach 2.75 Glass Tunnel with a semi-spanning 7.75deg wedge was analyzed in attempts to explore key physics pertinent to SBLI's, including thermodynamic and viscous boundary conditions as well as turbulence modeling. Most of the analyses were 3D CFD simulations using the OVERFLOW flow solver, with additional quasi-1D simulations performed with an in house MATLAB code interfacing with the NIST REFPROP code to explore perfect verses non-ideal air. A fundamental exploration pertaining to the effects of particle image velocimetry (PIV) on post-processing data is also shown. Results from the CFD simulations showed an improvement in agreement with experimental data with key contributions including adding a laminar zone upstream of the wedge and the necessity of mimicking PIV particle lag for comparisons. Results from the quasi-1D simulation showed that there was little difference between perfect and non-ideal air for the configuration presented.
Colour image segmentation using boundary relaxation

Proposes a colour distance measure based on the new TekHVC colour space and demonstrates its application to the problem of colour image segmentation. Two segmentation algorithms are presented and compared-relaxation at the boundaries of a split and merge and an optimal region grower. The authors conclude that the output of the region grower is the most suitable for the purposes of subsequent region grouping and object recognition. <<ETX>>
Conditioned Medium of Glioblastoma Cells Decreases the Viability of Each Other by Modulating Apoptosis- and Proliferation-Related Gene Expression

Background: Grade IV neoplasm of the central nervous system, GBM, is associated with poor prognosis and short overall survival. Objectives: This study aimed to investigate the effects of conditioned mediums of GBM cell lines on each other. Methods: Conditioned mediums of GBM cell lines were harvested at the 6th, 12th, 24th, and 48th h time points. The cellular and molecular effects of conditioned mediums were evaluated using gold standard techniques such as MTT assay, colony formation assay, wound healing assay, EdU labeling-based flow cytometry, and qRT-PCR. Results: Our study demonstrated that conditioned medium harvested from U87 or LN229 cells at the 48th h time point exhibited an anti-growth activity on each other by altering the gene expression pattern. Furthermore, the conditioned medium of LN229 decreased the migration capacity of U87 cells, and the conditioned medium of U87 cells significantly suppressed the LN229 proliferation. Conclusions: Growth-limiting activity achieved by conditioned mediums collected at the 48th h time point positioned them as promising candidates to further investigate their content. It was argued that this initial work provided new insights to expand our current understanding of the roles of GBM cells' secretome.
A Validation Study of the Chinese Version of the Mini-Addenbrooke’s Cognitive Examination for Screening Mild Cognitive Impairment and Mild Dementia

Background/Aims: There are limited cognitive screening tests for the Chinese-speaking population. This study aimed to validate the Chinese version of the Mini-Addenbrooke’s Cognitive Examination (M-ACE) for detecting mild cognitive impairment (MCI) and mild dementia. Its diagnostic accuracy was compared with that of Mini-Mental State Examination (MMSE). The study also evaluated the influential factors of M-ACE scores and its convergent validity against Clinical Dementia Rating Scale (CDR) and MMSE. Method: One hundred sixty-nine participants were classified into 3 groups: mild dementia, MCI, and healthy control. Mini-Mental State Examination and M-ACE were administered by researchers who were blinded to the clinical grouping. Receiver operating characteristic curves were graphed to test the diagnostic accuracy. Results: Mini-Addenbrooke’s Cognitive Examination scores had good convergent validity against CDR and MMSE. Years of education (r = 0.4, P < .001) yielded significant impacts on M-ACE scores. The optimal cutoff score of M-ACE to detect MCI was 25/26 (sensitivity = 0.88; specificity = 0.72) with an area under curve (AUC) significantly higher than MMSE (0.86 vs 0.72). The optimal cutoff score of M-ACE to screen mild dementia (21/22) yielded satisfactory sensitivity (0.96) and specificity (0.87) with a comparable AUC to MMSE (0.96 vs 0.94). Conclusions: Mini-Addenbrooke’s Cognitive Examination was a brief and reliable tool to detect MCI and mild dementia in the Chinese-speaking population significantly superior to MMSE when detecting MCI.
The Relationship Between Authoritarian Parenting and Aggressive Behavior of Adolescents in Nagari Bungo Tanjung

The subject in this thesis is the application of authoritarian parenting of parents so that adolescents have feelings of pressure and have high fear around parents, also causing adolescents to have aggressive behaviour in society and in peer environments. The purpose of this study was to find out how authoritarian parenting relationships with adolescent aggressive behaviour in Nagari Bungo Tanjung. The purpose of quantitative research is to the relationship between the two variables, developing and using mathematical models, theories and hypotheses related to natural phenomena.
The Basic algorithm of machine learning and its application in protein phosphorylation

Phosphorylated proteomics is a discipline that studies all phosphorylated proteins involved in the life process and plays an important role in proteomics. With the advancement of technology, there have been many experimental methods for protein phosphorylation and bioinformatics-based computing strategies. The application of data-driven machine learning methods in phosphate-catalyzed research has matured and has become the mainstream method in this field. This paper mainly summarizes the main methods and principles of machine learning, including Bayesian Decision Theory (BDT), Random Forests (RFs), AdaBoost, Support Vector Machines (SVMs)and etc. Finally, the application of these methods in the field of phosphorylation is reviewed in this article.
An Injection-Lockable InP-DHBT Source Operating at 421 GHz with −2.4 dBm Output Power and 1.7% DC-to-RF Efficiency

In this work, an injection-lockable push-push oscillator operating at 421 GHz is presented. The circuit is based on a 0.5 um transferred substrate InP DHBT MMIC process. A peak output power of −2.4 dBm is measured at 34.6 mW DC-power consumption, resulting in 1.7% DC-to-RF conversion efficiency. The oscillator can be injection-locked through a dedicated locking port which, along with the compact core measuring 0.53 × 0.49 mm2, makes this design suitable for efficient injection-locked oscillator arrays comprising a beam steering function by phase tuning.
Hamiltonian $S^1$ actions with Isolated Fixed Points on 6-Dimensional Symplectic Manifolds

The question of what conditions guarantee that a symplectic $S^1$ action is Hamiltonian has been studied for many years. In a 1998 paper, Sue Tolman and Jonathon Weitsman proved that if the action is semifree and has a non-empty set of isolated fixed points then the action is Hamiltonian. Furthermore, in a 2010 paper Cho, Hwang, and Suh proved in the 6-dimensional case that if we have $b_2^+=1$ at a reduced space at a regular level $\lambda$ of the circle valued moment map, then the action is Hamiltonian. In this paper, we will use this to prove that certain 6-dimensional symplectic actions which are not semifree and have a non-empty set of isolated fixed points are Hamiltonian. In this case, the reduced spaces are 4-dimensional symplectic orbifolds, and we will resolve the orbifold singularities and use J-holomorphic curve techniques on the resolutions.
Using Word Embedding Methods for Product Recommendation

Recommendation systems have become increasingly popular in recent years. In today’s world where the competition is extremely high, many service providers, from e-commerce to music industry, use recommendation systems. Considering the number of products and customers, it is crucial to deliver the right products to the right customers. Numerous methods are applied in recommendation systems. In our study, it is aimed to examine the purchasing association between products and to offer alternative products to the customers based on what they have already bought. For this purpose, Apriori, and Word2Vec and FastText, a natural language processing method, which extract the relationship space between words according to their frequency of occurrence, are used. Then, these models are compared. The results from word embedding methods are promising and will be used in future studies.
Taming Memory With Disaggregation

: With memory requirements growing to process increasing data for machine learning and other data-intensive applications, we need better ways to utilize installed memory. The CXL protocol enables creating pools of memory and accelerators, allowing memory disaggregation, and enabling composable virtual machines or containers which can be spun up or down on demand and make more efficient use of expensive memory. New software will make CXL memory pools even more useful by addressing needs such as enhanced security of data in disaggregated memory and state consistency preservation in the face of decoupled CPU and memory failures.
Aspects of $\kappa$--symmetry

We review various aspects of a fermionic gauge symmetry, known as the $\kappa$--symmetry, which plays an important role in formulations of superstrings, supermembranes and higher dimensional extended objects. We also review some aspects of the connection between $\kappa$--symmetric theories and their twistor-like formulations.
Glutamate Signaling and Filopodiagenesis of Astrocytoma Cells in Brain Cancers: Survey and Questions

Astrocytes are non-excitable cells in the CNS that can cause life-threatening astrocytoma tumors when they transform to cancerous cells. Perturbed homeostasis of the neurotransmitter glutamate is associated with astrocytoma tumor onset and progression, but the factors that govern this phenomenon are less known. Herein, we review possible mechanisms by which glutamate may act in facilitating the growth of projections in astrocytic cells. This review discusses the similarities and differences between the morphology of astrocytes and astrocytoma cells, and the role that dysregulation in glutamate and calcium signaling plays in the aberrant morphology of astrocytoma cells. Converging reports suggest that ionotropic glutamate receptors and voltage-gated calcium channels expressed in astrocytes may be responsible for the abnormal filopodiagenesis or process extension leading to astrocytoma cells’ infiltration throughout the brain.
Reordonnancement de domaines dans les reseaux de contraintes

Dans le but d'accelerer la resolution d'un CSP, nous nous interessons au probleme consistant a modifier l'ordre sur les valeurs qui est induit par la definition de chaque domaine. Nous discutons de l'interet de cette technique de reformulation et definissons les problemes pertinents. Nous montrons qu'on peut trouver un ordre rendant un reseau de contraintes monotone (s'il en existe un) en temps polynomial, mais que le meme probleme est NP-difficile pour la classe des contraintes min-closes. Enfin, nous montrons en quoi nos resultats s'appliquent au maintien de diverses consistances aux bornes.
Effect of Dietary Intervention Designed with Behavior Change Wheel on Compliance with Dietary Control in Women with Gestational Diabetes Mellitus: Study Protocol for a Randomized Controlled Trial

Background and Purpose: Previous studies have shown that women with GDM can benefit from following dietary recommendations, which are based on food exchange serving (FES) and glycemic load (GL), but compliance with dietary recommendations in women with GDM is not ideal. Therefore, the aim of this paper is to design a dietary intervention program based on behavior change wheel (BCW) to affect GDM women’s compliance with FES based on GL, and to compare the effects of this dietary intervention program versus general dietary management on compliance with dietary recommendations, improving maternal glucose metabolism, and reducing adverse pregnancy outcomes in women with GDM. Methods: This paper is a methodological description of a two-arm randomized controlled trial. In this study, eligible women with GDM will be recruited and divided into the control group (n = 30) and the intervention group (n = 30). Women with GDM will respectively receive general dietary management (control group) and dietary intervention designed with BCW (intervention group) until after delivery. Information about pregnant women will be collected through questionnaires or prenatal and delivery records. Conclusion: This randomized controlled trial is designed specifically for women with GDM to achieve effective blood glucose control by strengthening GDM women’s compliance with dietary recommendations. If this dietary intervention designed with BCW proves to be effective, then BCW may deserve to be applied to more areas of self-management in women with GDM.
Clinical Utility of Comprehensive Cell-free DNA Analysis to Identify Genomic Biomarkers in Patients with Newly Diagnosed Metastatic Non–small Cell Lung Cancer

Purpose: Complete and timely tissue genotyping is challenging, leading to significant numbers of patients with newly diagnosed metastatic non–small cell lung cancer (mNSCLC) being undergenotyped for all eight genomic biomarkers recommended by professional guidelines. We aimed to demonstrate noninferiority of comprehensive cell-free DNA (cfDNA) relative to physician discretion standard-of-care (SOC) tissue genotyping to identify guideline-recommended biomarkers in patients with mNSCLC. Patients and Methods: Prospectively enrolled patients with previously untreated mNSCLC undergoing physician discretion SOC tissue genotyping submitted a pretreatment blood sample for comprehensive cfDNA analysis (Guardant360). Results: Among 282 patients, physician discretion SOC tissue genotyping identified a guideline-recommended biomarker in 60 patients versus 77 cfDNA identified patients (21.3% vs. 27.3%; P < 0.0001 for noninferiority). In tissue-positive patients, the biomarker was identified alone (12/60) or concordant with cfDNA (48/60), an 80% cfDNA clinical sensitivity for any guideline-recommended biomarker. For FDA-approved targets (EGFR, ALK, ROS1, BRAF) concordance was >98.2% with 100% positive predictive value for cfDNA versus tissue (34/34 EGFR-, ALK-, or BRAF-positive patients). Utilizing cfDNA, in addition to tissue, increased detection by 48%, from 60 to 89 patients, including those with negative, not assessed, or insufficient tissue results. cfDNA median turnaround time was significantly faster than tissue (9 vs. 15 days; P < 0.0001). Guideline-complete genotyping was significantly more likely (268 vs. 51; P < 0.0001). Conclusions: In the largest cfDNA study in previously untreated mNSCLC, a validated comprehensive cfDNA test identifies guideline-recommended biomarkers at a rate at least as high as SOC tissue genotyping, with high tissue concordance, more rapidly and completely than tissue-based genotyping. See related commentary by Meador and Oxnard, p. 4583
The role of Langerhans cells in pathologies of the skin

Langerhans cells (LCs) are epidermal immune cells of myeloid origin. Although these cells were primarily thought to play a defensive role in the skin, evidence now indicates a diverse range of LC‐mediated effects including the relay of viral antigens in herpes simplex infection, recruitment of eosinophils in atopic dermatitis and promotion of a Th17 response in Candida infection. LCs may have a protective or suppressive function in pathologies of the skin, with differing functions being driven by the skin milieu. Understanding LC function will help guide the development of interventions that modulate these cells for therapeutic benefit.
Application of Af4-Multidetection to Liraglutide in Its Formulation: Preserving and Representing Native Aggregation

Aggregation is among the most critical parameters affecting the pharmacological and safety profile of peptide Active Pharmaceutical Ingredients (APIs). For this reason, it is of utmost importance to define the exact aggregation state of peptide drugs, particularly when the API is marketed as a ready-to-use solution. Consequently, appropriate non-destructive techniques able to replicate the peptide environment must be employed. In our work, we exploited Asymmetrical Flow Field-Flow Fractionation (AF4), connected to UV, dRI, fluorescence, and MALS detectors, to fully characterize the aggregation state of Liraglutide, a peptide API used for the treatment of diabetes type 2 and chronic obesity. In previous studies, Liraglutide was hypothesized to assemble into hexa-octamers in phosphate buffer, but no information on its behavior in the formulation medium was provided up to now. The method used allowed researchers to work using formulation as the mobile phase with excellent recoveries and LoQ/LoD, discerning between stable and degraded samples, and detecting, when present, aggregates up to 108 Da. The native state of Liraglutide was assessed and found to be an association into pentamers, with a non-spherical conformation. Combined to benchmark analyses, the sameness study was complete and descriptive, also giving insight on the aggregation process and covalent/non-covalent aggregate types.
Improving the Performance of Batch-Constrained Reinforcement Learning in Continuous Action Domains via Generative Adversarial Networks

The Batch-Constrained Q-learning algorithm is shown to overcome the extrapolation error and enable deep reinforcement learning agents to learn from a previously collected fixed batch of transitions. However, due to conditional Variational Autoencoders (VAE) used in the data generation module, the BCQ algorithm optimizes a lower variational bound and hence, it is not generalizable to environments with large state and action spaces. In this paper, we show that the performance of the BCQ algorithm can be further improved with the employment of one of the recent advances in deep learning, Generative Adversarial Networks. Our extensive set of experiments shows that the introduced approach significantly improves BCQ in all of the control tasks tested. Moreover, the introduced approach demonstrates robust generalizability to environments with large state and action spaces in the OpenAI Gym control suite.