Miracle-dz/UniFAR-FTUs huggingface dataset:
The Cycle Characteristics and Outcomes of Infertile Nonclassic 21-Hydroxylase Deficiency Patients Undergoing Ovarian Stimulation for In Vitro Fertilization

Abstract Background The objective of the work was to investigate the cycle characteristics and outcomes of infertile women with nonclassic 21-hydroxylase deficiency (21-OHD) undergoing in vitro fertilization (IVF). Methods Twenty-five infertile nonclassic 21-OHD patients were retrospectively observed. From cycle day 3, patients were given human menopausal gonadotropin (HMG) 150 IU/d or 225 IU/d daily. Dexamethasone was administered orally at 0.75 mg/d. Ovulation was co-triggered by human chorionic gonadotropin (hCG) and triptorelin. Binary logistic regression was performed to quantify the effect of IVF parameters on embryo transfer cycle outcomes. The receiver operating characteristic (ROC) curve was used to determine cutoff points of the selected confounders for predicting pregnant probabilities. Results In controlled ovarian hyperstimulation (COH) cycles, there was a trend that the viable embryos group consisted of more polycystic ovary (PCO) patients. In embryo transfer (ET) cycles, differences were detected in the usage rate of dexamethasone and the minimum progesterone (P4) and total testosterone (TT) values between the non-pregnant group and the biochemical pregnant group. Binary logistic regression analysis confirmed that decreasing minimum P4 and body mass index (BMI) value was respectively correlated with increasing pregnancy probability. ROC analysis proved that the cutoff values for minimum P4 and BMI were 0.45 ng/ml and 23.36 kg/m2. Conclusion In COH cycles, the ultrasonographic appearance of ovary helps to predict the number of viable embryos. In ET cycles, dexamethasone obviously improves the pregnancy rate. If the minimum P4 value before endometrial transformation cannot be kept below 0.45 ng/ml, we may consider cycle cancellation. Moreover, it is suggested that BMI of nonclassic 21-OHD women is regulated below 23.36 kg/m2.
Deconstructing NGC 7130

Observations of the Seyfert 2 and starburst galaxy NGC 7130 with the Chandra X-Ray Observatory illustrate that both of these phenomena contribute significantly to the galaxy's detectable X-ray emission. The active galactic nucleus (AGN) is strongly obscured, buried beneath column density NH > 1024 cm-2, and it is most evident in a prominent Fe Kα emission line with equivalent width greater than 1 keV. The AGN accounts for most (60%) of the observed X-rays at energy E > 2 keV, with the remainder due to spatially extended star formation. The soft X-ray emission is strong and predominantly thermal on both small and large scales. We attribute the thermal emission to stellar processes. In total, the AGN is responsible for only one-third of the observed 0.5-10 keV luminosity of 3 × 1041 ergs s-1 of this galaxy and less than half of its bolometric luminosity. Starburst/AGN composite galaxies like NGC 7130 are truly common, and similar examples may contribute significantly to the high-energy cosmic X-ray background while remaining hidden at lower energies, especially if they are distant.
The mechanism(s) of action of antioxidants: From scavenging reactive oxygen/nitrogen species to redox signaling and the generation of bioactive secondary metabolites

Small molecule, dietary antioxidants exert a remarkably broad range of bioactivities, and many of these can be explained by the influence of antioxidants on the redox homeostasis. Such compounds help to modulate the levels of harmful reactive oxygen/nitrogen species, and therefore participate in the regulation of various redox signaling pathways. However, upon ingestion, antioxidants usually undergo extensive metabolism that can generate a wide range of bioactive metabolites. This makes it difficult, but otherwise a need, to identify the ones responsible for the different activities of antioxidants. By better understanding their ways of action, the use of antioxidants in therapy can be improved.
Dose-adjusted EPOCH regimen as first-line treatment for non-Hodgkin lymphoma-associated hemophagocytic lymphohistiocytosis: a single-arm, open-label, phase II trial

Hemophagocytic lymphohistiocytosis (HLH) is a lifethreatening disorder characterized by uncontrolled T/natural killer (NK) cells and macrophage activation and an excessive production of inflammatory cytokines. HLH can be divided into primary (genetic) and secondary (reactive) which is secondary to infection, autoimmune disease, malignant tumors, and other causes. Lymphoma accounted for 67% in adult patients with HLH in the context of malignant tumors. First-line treatments of lymphoma-associated HLH (LA-HLH) have not been prospectively studied until now. No clear conclusions have been drawn as to whether an HLH-directed, lymphoma-directed, or combined approach should initially be adopted. Therefore, we aimed to assess the efficacy, safety, and feasibility of the DA-EPOCH±R regimen which contains the drugs both for HLH and nonHodgkin lymphoma (NHL) as a first-line treatment for NHL-associated HLH. We did a single-arm, open-label, phase II clinical trial in previously untreated patients diagnosed as NHL with HLH (clinicaltrials.gov identifier: 01818908). The eligibility and exclusion criteria are summarized in Online Supplementary Table S1. The study protocol is available online. B-cell NHL (B-NHL) patients with HLH were programmed to receive six cycles of DA-EPOCH-R regimen while T/NK-NHL patients with HLH were programmed to receive six cycles of DA-EPOCH regimen. Also, after achieving ≥ partial response (PR) after six cycles of DA-EPOCH±R regimen, autologous stem cell transplantation (ASCT) for B-NHL or allogeneic stem cell transplantation (allo-SCT) for T/NK-NHL was followed as consolidation therapies. Details of the DA-EPOCH regimen have been published elsewhere. Courses were repeated every three weeks. Central nervous system (CNS) prophylaxis was considered with 4-8 doses of intrathecal methotrexate (15 mg), cytarabine (50 mg) and dexamethasone (5 mg) for all patients. Patients’ responses were assessed by investigator according to standard Cheson criteria or Deauville criteria [Deauville score 1-3 considered positron emission tomography (PET) negative] for PET/computed tomography (CT) after three cycles, at the end of treatment and/or after the ASCT/allo-SCT. Follow-up assessments were planned every three months for one year, every six months for two more years, and yearly thereafter, including physical examination, laboratory tests, and enhanced CT scans. The primary end point was the overall response rate (ORR). The secondary outcome measures were progression-free survival (PFS), overall survival (OS), and the number of participants with adverse events. PFS and OS were calculated up to the last followup date (November 1, 2018) of this report. Safety was defined as the incidence and severity of adverse events according to National Cancer Institute-Common Terminology Criteria for Adverse Events (NCI-CTCAE) version 4.0. Fisher exact test was applied to categorical variables and the Mann-Whitney U test to continuous variables. Survival curves were constructed by the
Effects of zinc-substituted nano-hydroxyapatite coatings on bone integration with implant surfaces

ObjectiveThe purpose of this study was to investigate the effects of a zinc-substituted nano-hydroxyapatite (Zn-HA) coating, applied by an electrochemical process, on implant osseointegraton in a rabbit model.MethodsA Zn-HA coating or an HA coating was deposited using an electrochemical process. Surface morphology was examined using field-emission scanning electron microscopy. The crystal structure and chemical composition of the coatings were examined using an X-ray diffractometer (XRD) and Fourier transform infrared spectroscopy (FTIR). A total of 78 implants were inserted into femurs and tibias of rabbits. After two, four, and eight weeks, femurs and tibias were retrieved and prepared for histomorphometric evaluation and removal torque (RTQ) tests.ResultsRod-like HA crystals appeared on both implant surfaces. The dimensions of the Zn-HA crystals seemed to be smaller than those of HA. XRD patterns showed that the peaks of both coatings matched well with standard HA patterns. FTIR spectra showed that both coatings consisted of HA crystals. The Zn-HA coating significantly improved the bone area within all threads after four and eight weeks (P<0.05), the bone to implant contact (BIC) at four weeks (P<0.05), and RTQ values after four and eight weeks (P<0.05). ConclusionsThe study showed that an electrochemically deposited Zn-HA coating has potential for improving bone integration with an implant surface.
Reverse engineering the process of small novice software teams

The software-development project success dependson the technical competence of the development team,the quality of its tools and the project-managementdecisions it makes during the software lifecycle. Newrequirements, tight delivery schedules and team-memberturnaround present the team with challenges.Flexible decision making for effective adaptation tothese challenges is an extremely difficult skill toacquire, and even more challenging to teach.Instructors of software-engineering courses involvingcollaborative project development are oftenoverwhelmed by the task of monitoring the progress ofmultiple teams and problems in the team's process maygo unnoticed until it is too late to be fixed.In this paper we describe our work on analyzingthe CVS history of a team project repository to extractinformation about the nature of the collaborationbetween the members of a team. This analysis cansupport the instructor in noticing evidence of potentialproblems who can then use this information to alert theteam. It can also be shown to the team membersthemselves, so that they become more aware of theirprocess. We evaluate our CVS analysis process with acase study, based on an undergraduate software-engineeringcourse.
Traffic Grooming for IP Multicast over WDM Networks Using Light-Path and Light-Tree Schemes

In this paper, we consider one light-path based and two light-tree based traffic grooming schemes for supporting IP multicast services. We made performance comparisons for call blocking probability and bandwidth blocking probability on those schemes. Simulation results reveal that light-path scheme has lower blocking probability and less consumes bandwidth consumption as IP demand volumes are small (i.e., several Megabit/sec). On the other hand, Light-tree based schemes have better performance as the IP demands become high. We conclude that the selection of grooming strategies should take the volume of demands of the provided services into account and the results in this work can provide a basic guideline for grooming strategy selection.
Uterine Glands: Developmental Biology and Functional Roles in Pregnancy.

All mammalian uteri contain glands in the endometrium that develop only or primarily after birth. Gland development or adenogenesis in the postnatal uterus is intrinsically regulated by proliferation, cell-cell interactions, growth factors and their inhibitors as well as transcription factors including forkhead box A2 (FOXA2) and estrogen receptor alpha (ESR1). Extrinsic factors regulating adenogenesis originate from other organs including the ovary, pituitary, and mammary gland. The infertility and recurrent pregnancy loss observed in uterine gland knockout sheep and mouse models support a primary role for secretions and products of the glands in pregnancy success. Recent studies in mice revealed that uterine glandular epithelia govern post-implantation pregnancy establishment through effects on stromal cell decidualization and placental development. In humans, uterine glands and, by inference, their secretions and products are hypothesized to be critical for blastocyst survival and implantation as well as embryo and placental development during the first trimester before the onset of fetal-maternal circulation. A variety of hormones and other factors from the ovary, placenta, and stromal cells impact secretory function of the uterine glands during pregnancy. This review will summarize new information related to the developmental biology of uterine glands and discuss novel perspectives on their functional roles in pregnancy establishment and success.
Embedding standard distributed object-oriented middlewares in wireless sensor networks

This article provides an analysis of the design space available to middleware developers in the context of wireless sensor networks. We identify the weaknesses of current communication abstraction layers and propose alternative implementation techniques that preserve most of the useful features but minimizes the implementation cost in resource constrained wireless sensor nodes. Our proposal includes a whole WSN development framework based on standard distributed objects and a set of specific services designed to support highly dynamic and scalable WSN applications. distributed objects; sensor middleware; device interoperability
Real-Time Three-Dimensional Knee Moment Estimation in Knee Osteoarthritis: Toward Biodynamic Knee Osteoarthritis Evaluation and Training

We investigated differences in knee kinetic variables (external knee adduction, flexion, internal rotation moments, and impulses) between patients with knee osteoarthritis (KOA) and healthy controls during stepping on a custom elliptical trainer; and searched knee kinetic variable candidates for real-time biofeedback and for complementing diagnosis/evaluation on the elliptical trainer based on the knee kinetic variables’ associations with the knee injury and osteoarthritis outcome score (KOOS). Furthermore, we explored potential gait re-training strategies on the elliptical trainer by investigating the knee kinetic variables’ associations with 3-D ankle angles. The knee kinetic variables and ankle angles were determined in real-time in a patient group of 10 patients with KOA and an age-and sex-matched control group of 10 healthy subjects. The mean peak external knee adduction moment of the patient group was 47% higher than that of the control group. The KOOS-Sports and Recreational Activities and KOOS-Pain scores were found to be significantly associated with the knee kinetic variables. All the ankle angles were associated with the knee kinetic variables. The findings support the use of the knee kinetic variables on the elliptical trainer to complement KOA diagnosis quantitatively and provide potential real-time KOA gait re-training strategies/guides.
Aberrant gene expression by Sertoli cells in infertile men with Sertoli cell-only syndrome

Sertoli cell-only (SCO) syndrome is a severe form of human male infertility seemingly characterized by the lack all spermatogenic cells. However, tubules of some SCO testes contain small patches of active spermatogenesis and thus spermatogonial stem cells. We hypothesized that these stem cells cannot replicate and seed spermatogenesis in barren areas of tubule because as-of-yet unrecognized deficits in Sertoli cell gene expression disable most stem cell niches. Performing the first thorough comparison of the transcriptomes of human testes exhibiting complete spermatogenesis with the transcriptomes of testes with SCO syndrome, we defined transcripts that are both predominantly expressed by Sertoli cells and expressed at aberrant levels in SCO testes. Some of these transcripts encode proteins required for the proper assembly of adherent and gap junctions at sites of contact with other cells, including spermatogonial stem cells (SSCs). Other transcripts encode GDNF, FGF8 and BMP4, known regulators of mouse SSCs. Thus, most SCO Sertoli cells can neither organize junctions at normal sites of cell-cell contact nor stimulate SSCs with adequate levels of growth factors. We propose that the critical deficits in Sertoli cell gene expression we have identified contribute to the inability of spermatogonial stem cells within small patches of spermatogenesis in some SCO testes to seed spermatogenesis to adjacent areas of tubule that are barren of spermatogenesis. Furthermore, we predict that one or more of these deficits in gene expression are primary causes of human SCO syndrome.
Imitation in Location Choice

Under the assumption of perfect competition, it is difficult to avoid the conclusion that abandoned properties and long undeveloped neighborhoods remain that way because they are unprofitable. In contrast, this paper introduces a model in which firms systematically overlook neighborhoods with little commercial activity because of a positive informational externality motivating later movers to condition choice of location on earlier movers’ locations. When this occurs, firms sometimes find it profitable to imitate early movers’ locations even though privately acquired information suggests locating elsewhere. The model facilitates normative analysis of imitation in location choice by explicitly quantifying losses in aggregate efficiency following a shift from centralized to decentralized regimes. The model provides a tool for investigating the hypothesis of inefficient lock-in as it relates to neighborhoods in U.S. urban centers that remain underutilized despite the presence of profitable business prospects.
Recent progress and challenges in population genetics of polyploid organisms: an overview of current state‐of‐the‐art molecular and statistical tools

Despite the importance of polyploidy and the increasing availability of new genomic data, there remain important gaps in our knowledge of polyploid population genetics. These gaps arise from the complex nature of polyploid data (e.g. multiple alleles and loci, mixed inheritance patterns, association between ploidy and mating system variation). Furthermore, many of the standard tools for population genetics that have been developed for diploids are often not feasible for polyploids. This review aims to provide an overview of the state‐of‐the‐art in polyploid population genetics and to identify the main areas where further development of molecular techniques and statistical theory is required. We review commonly used molecular tools (amplified fragment length polymorphism, microsatellites, Sanger sequencing, next‐generation sequencing and derived technologies) and their challenges associated with their use in polyploid populations: that is, allele dosage determination, null alleles, difficulty of distinguishing orthologues from paralogues and copy number variation. In addition, we review the approaches that have been used for population genetic analysis in polyploids and their specific problems. These problems are in most cases directly associated with dosage uncertainty and the problem of inferring allele frequencies and assumptions regarding inheritance. This leads us to conclude that for advancing the field of polyploid population genetics, most priority should be given to development of new molecular approaches that allow efficient dosage determination, and to further development of analytical approaches to circumvent dosage uncertainty and to accommodate ‘flexible’ modes of inheritance. In addition, there is a need for more simulation‐based studies that test what kinds of biases could result from both existing and novel approaches.
A comparative study of various pressure relaxation closure models for one‐dimensional two‐material Lagrangian hydrodynamics

Lagrangian hydrodynamics of strength‐free materials continues to present open issues, even in one dimension. We focus on the problem of closing a system of equations for a two‐material cell under the assumption of a single velocity model. There are several existing models and approaches, each possessing different levels of fidelity to the underlying physics and each exhibiting unique features in the computed solutions. We consider three models that take different approaches to breaking the assumption of instantaneous pressure equilibration in the mixed‐material cell. The first of these is the well‐known method of Tipton, in which a viscosity‐like pressure relaxation term is coupled with an otherwise isentropic pressure update to obtain closed‐form expressions for the materials' volume fractions and corresponding sub‐cell pressures. The second is the physics‐inspired, geometry‐based pressure relaxation model of Kamm and Shashkov, which is based on an optimization procedure that uses a local, exact Riemann problem. The third model is the unique aspect of this paper, inspired by the work of Delov and Sadchikov and Goncharov and Yanilkin. This sub‐scale dynamics approach is motivated by the linearized Riemann problem to initialize volume fraction changes, which are then modified, via the materials' SIEs, to drive the mixed cell toward pressure equilibrium. Each of these approaches is packaged in the framework of a two‐step time integration scheme. We compare these multi‐material pressure relaxation models, together with corresponding pure‐material calculations, on idealized, two‐material problems with either ideal‐gas or stiffened‐gas equations of state. Published in 2010 by John Wiley & Sons, Ltd.
An emerging role of interleukin-23 in rheumatoid arthritis

Abstract Rheumatoid arthritis (RA) is an autoimmune, chronic inflammatory disease and is characterized by destruction of the articular cartilage. A number of pro-inflammatory cytokines work sequentially and in concert with one another to induce the development of RA. IL-23, a member of IL-12 family, is composed of p19 and p40 subunits and it interacts with IL-23 receptor complex to trigger plethora of biochemical actions. A number of preclinical studies have shown the role of IL-23 in the development of RA in rodents. IL-23 receptor signaling is primarily linked to the activation of JAK-STAT, tyrosine kinase 2, NF-kB, and retinoic acid receptor-related orphan receptors. IL-23 produces its osteoclastogenic effects, mainly through IL-17 and Th17 cells suggesting the importance of IL-23/IL-17/Th17 in the joint inflammation and destruction in RA. Monoclonal antibodies targeted against IL-23, including tildrakizumab and guselkumab have been developed and evaluated in clinical trials. However, there are very limited clinical studies regarding the use of IL-23 modulators in RA patients. The present review discusses the different aspects of IL-23 including its structural features, signal transduction pathway, preclinical, and clinical role in RA.
Comparing deep belief networks with support vector machines for classifying gene expression data from complex disorders

Genomics data provide great opportunities for translational research and the clinical practice, for example, for predicting disease stages. However, the classification of such data is a challenging task due to their high dimensionality, noise, and heterogeneity. In recent years, deep learning classifiers generated much interest, but due to their complexity, so far, little is known about the utility of this method for genomics. In this paper, we address this problem by studying a computational diagnostics task by classification of breast cancer and inflammatory bowel disease patients based on high‐dimensional gene expression data. We provide a comprehensive analysis of the classification performance of deep belief networks (DBNs) in dependence on its multiple model parameters and in comparison with support vector machines (SVMs). Furthermore, we investigate combined classifiers that integrate DBNs with SVMs. Such a classifier utilizes a DBN as representation learner forming the input for a SVM. Overall, our results provide guidelines for the complex usage of DBN for classifying gene expression data from complex diseases.