Miracle-dz/UniFAR-FTUs huggingface dataset:
Proteomic Alteration in the Progression of Multiple Myeloma: A Comprehensive Review

Multiple myeloma (MM) is an incurable hematologic malignancy. Most MM patients are diagnosed at a late stage because the early symptoms of the disease can be uncertain and nonspecific, often resembling other, more common conditions. Additionally, MM patients are commonly associated with rapid relapse and an inevitable refractory phase. MM is characterized by the abnormal proliferation of monoclonal plasma cells in the bone marrow. During the progression of MM, massive genomic alterations occur that target multiple signaling pathways and are accompanied by a multistep process involving differentiation, proliferation, and invasion. Moreover, the transformation of healthy plasma cell biology into genetically heterogeneous MM clones is driven by a variety of post-translational protein modifications (PTMs), which has complicated the discovery of effective treatments. PTMs have been identified as the most promising candidates for biomarker detection, and further research has been recommended to develop promising surrogate markers. Proteomics research has begun in MM, and a comprehensive literature review is available. However, proteomics applications in MM have yet to make significant progress. Exploration of proteomic alterations in MM is worthwhile to improve understanding of the pathophysiology of MM and to search for new treatment targets. Proteomics studies using mass spectrometry (MS) in conjunction with robust bioinformatics tools are an excellent way to learn more about protein changes and modifications during disease progression MM. This article addresses in depth the proteomic changes associated with MM disease transformation.
Cross-Level Invariance in Multilevel Factor Models

When modeling latent variables at multiple levels, it is important to consider the meaning of the latent variables at the different levels. If a higher-level common factor represents the aggregated version of a lower-level factor, the associated factor loadings will be equal across levels. However, many researchers do not consider cross-level invariance constraints in their research. Not applying these constraints when in fact they are appropriate leads to overparameterized models, and associated convergence and estimation problems. This simulation study used a two-level mediation model on common factors to show that when factor loadings are equal in the population, not applying cross-level invariance constraints leads to more estimation problems and smaller true positive rates. Some directions for future research on cross-level invariance in MLSEM are discussed.
Neue Kriterien für die Irreduzibilität algebraischer Gleichungen.

JJie Frage, ob eine gegebene algebraische Gleichung mit rationalen Koeffizienten reduzibel oder irreduzibel ist im Bereich der rationalen Zahlen, kann theoretisch stets beantwortet werden. Denn es gibt mehrere allgemeine Methoden, die in jedem Fall nach einer endlichen Anzahl von Schritten zum Ziel führen müssen. Praktisch aber sind die erforderlichen Rechnungen wegen ihrer Länge meist unausführbar, und man muß sich daher nach anderen Mitteln umsehen. Da ist vor allem wichtig, daß vielfach die Irreduzibilität einer Gleichung schon von vornherein aus gewissen Eigenschaften ihrer Koeffizienten gefolgert werden kann; für die bis jetzt bekannten Kriterien dieser Art habe ich vor kurzem eine rationelle Beweismethode angegeben und einige weitere neu aufgestellt, die aus derselben Quelle fließen. *) Bei all diesen Sätzen bezogen sich die fraglichen Eigenschaften der Koeffizienten auf die Teilbarkeit, aber ebenso nützlich werden Kriterien sein, die aus Großenbeziehungen zwischen den Koeffizienten die Irreduzibilität erkennen lassen. Die Herleitung derartiger Theoreme auf Grund einfacher Prinzipien ist der Zweck der folgenden Zeilen. Im III. Abschnitt folgt dann kurz eine analoge Deduktion für solche Gleichungen, deren Koeffizienten selbst rationale Funktionen von einer oder mehr Variabein sind.
Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence

Purpose For patients receiving lung stereotactic ablative radiotherapy (SABR), evidence suggests that high peritumor density predicts an increased risk of microscopic disease (MDE) and local-regional failure, but only if there is low or heterogenous incidental dose surrounding the tumor (GTV). A data-mining method (Cox-per-radius) has been developed to investigate this dose-density interaction. We apply the method to predict local relapse (LR) and regional failure (RF) in patients with non-small cell lung cancer. Methods 199 patients treated in a routine setting were collated from a single institution for training, and 76 patients from an external institution for validation. Three density metrics (mean, 90th percentile, standard deviation (SD)) were studied in 1mm annuli between 0.5cm inside and 2cm outside the GTV boundary. Dose SD and fraction of volume receiving less than 30Gy were studied in annuli 0.5-2cm outside the GTV to describe incidental MDE dosage. Heat-maps were created that correlate with changes in LR and RF rates due to the interaction between dose heterogeneity and density at each distance combination. Regions of significant improvement were studied in Cox proportional hazards models, and explored with and without re-fitting in external data. Correlations between the dose component of the interaction and common dose metrics were reported. Results Local relapse occurred at a rate of 6.5% in the training cohort, and 18% in the validation cohort, which included larger and more centrally located tumors. High peritumor density in combination with high dose variability (0.5 - 1.6cm) predicts LR. No interactions predicted RF. The LR interaction improved the predictive ability compared to using clinical variables alone (optimism-adjusted C-index; 0.82 vs 0.76). Re-fitting model coefficients in external data confirmed the importance of this interaction (C-index; 0.86 vs 0.76). Dose variability in the 0.5-1.6 cm annular region strongly correlates with heterogeneity inside the target volume (SD; ρ = 0.53 training, ρ = 0.65 validation). Conclusion In these real-world cohorts, the combination of relatively high peritumor density and high dose variability predicts increase in LR, but not RF, following lung SABR. This external validation justifies potential use of the model to increase low-dose CTV margins for high-risk patients.
Strategic Partnerships – Best Practice Across Norway and Denmark

In recent years, the concept of strategic partnerships has gained attention in the Norwegian and Danish construction industry. As a project delivery method, strategic partnerships share similarities with the Lean project delivery perspective and Integrated Project Delivery (IPD) as they all seek to achieve more collaborative projects. In this paper we will compare strategic partnerships, strategic partnering and IPD based on literature reviews and experiences from recent strategic partnerships and strategic partnering in Norway and Denmark. The paper explains strategic partnerships and partnering by structuring it according to three essential Lean Construction (LC) elements: Commercial, organizational, and operating system. A combination of literature review and document study was used for data collection. Also, online meetings with all authors participating were completed to discuss and analyse data. Experiences from a Norwegian case study and Denmark points to several success criteria that are crucial for the success of long-term collaboration, such as multi-project framework agreement, keeping the same people, and support from the management. Some of the success criteria stem from IPD and others might also be a positive application for IPD.
On the threshold of being a teacher: motivations and ideals of 116 Dutch student teachers

ABSTARCT This study focuses on student teachers who are on the threshold of entering the teaching profession. The aim of this study is to examine their motivations for becoming teachers, their educational ideals and the meaningful experiences inside and outside teacher education that influenced their educational ideals. To examine these, we conducted a survey of 116 student teachers at three Dutch teacher education institutes who were at the end of a four-year bachelor programme to become secondary school teachers (of history and English language). The results of the factors influencing teaching (FIT)-choice scale show that motivations representing social utility value were rated highest. Regarding social development, the highest-rated ideals were social commitment and autonomy, and of the ideals that focus on qualification, subject matter knowledge was rated highest. Comparing the influence of the several domains of teacher education, more student teachers considered their internships at schools to have an influence on the formation of their educational ideals than the courses at the teacher education institute.
Elevated Serum Concentration of Adipocyte Fatty Acid-Binding Protein Correlates with the Markers of Abdominal Obesity Independently of Thyroid Hormones in Non-Obese Women with Polycystic Ovary Syndrome

Adipocyte fatty acid-binding protein (A-FABP) is mainly expressed in adipocytes. The risk of abdominal obesity and autoimmune thyroid disease is increased in women with polycystic ovary syndrome (PCOS). The objective of this study was to explore the relationship of serum concentration of A-FABP with parameters of obesity, e.g., waist to hip ratio (WHR) and the amount of adipose tissue assessed by bioelectrical impedance analysis (BIA), and thyroid hormone homeostasis in women with PCOS. We examined 66 women with PCOS and 67 healthy women. Serum concentrations of A-FABP and thyroid hormones were measured; the FT3/FT4 ratio, thyroid-stimulating hormone index (TSHI), thyrotrope thyroxine resistance index (TT4RI) and thyroid feedback quantile-based index (TFQI) were calculated. In the PCOS group, serum concentrations of A-FABP, FT3 and the FT3/FT4 ratio were significantly higher in comparison to the control group (all p < 0.05). A correlation of A-FABP with WHR (r = 0.26, p = 0.04) and the percentage of adipose tissue (r = 0.33, p = 0.01) has been found only in women with PCOS. We observed no correlation between serum levels of A-FABP and TSHI, TT4RI or TFQI in women with PCOS (all p > 0.05). Our results indicate that A-FABP is an adipokine that may be connected with abdominal obesity independently of thyroid hormone homeostasis in PCOS patients.
A Novel Hematological Inflammation-Nutrition Score (HINS) and Its Related Nomogram Model to Predict Survival Outcome in Advanced Gastric Cancer Patients Receiving First-Line Palliative Chemotherapy

Purpose This study aims to construct a novel hematological inflammation-nutrition score (HINS) and investigate its prognostic value in patients with advanced gastric cancer (AGC). We investigated the risk stratification performance of HINS and developed a HINS-based nomogram model to predict overall survival by combining traditional predictors. Patients and Methods We conducted a retrospective study on 812 AGC patients who received first-line platinum- or fluoropyrimidine-containing chemotherapy at The First Affiliated Hospital of Zhengzhou University Hospital between 2014 and 2019. Patients were randomly divided into a training cohort (N=609) and a validation cohort (N=203). HINS (0–2) was constructed based on a pre-chemotherapy systemic immune-inflammation index (SII) and albumin (ALB). Prognostic factors were screened by univariate and multivariate COX proportional regression models. Significant factors were used to construct a nomogram model. Internal validation was performed by calibration curves, time-dependent receiver operating characteristics (ROC) curves, and decision curve analysis (DCA), evaluating its prediction consistency, discrimination ability, and clinical net benefit. Results HINS was constructed based on SII and ALB. HINS showed a better stratification ability than JCOG prognostic index, with significant differences between groups. Multivariate analysis showed that ECOG ≥1 (HR: 1.379; P=0.005), Stage IV (HR: 1.581; P <0.001), diffuse-type histology (HR: 1.586; P <0.001), number of metastases ≥2 (HR: 1.274; P=0.038), without prior gastrectomy (HR: 1.830; P <0.001), ALP ≥ULN (HR: 1.335; P=0.034), HINS (P <0.001) were independent factors of OS. We successfully established a HINS-based nomogram model that showed a strong discriminative ability, accuracy, and clinical utility in training and validation cohorts. Conclusion HINS shows a superior risk stratification ability, which might be a potential prognostic biomarker for AGC patients receiving palliative first-line palliative chemotherapy. The HINS-based nomogram model is a convenient and efficient tool for managing prognosis and follow-up treatments.
STATISTICAL GUIDANCE METHODS FOR PREDICTING SNOWFALL ACCUMULATION IN THE NORTHEAST UNITED STATES

The accuracy of snowfall accumulation forecasts has widespread economic and safety consequences. Due to the complex structure and dynamics of winter weather systems, snowfall accumulation forecasts tend to have a large degree of uncertainty associated with them. Numerical weather prediction (NWP) ensemble prediction systems were developed specifically to address the uncertainty in weather forecasts. An accurate deterministic forecast as well as an estimate of the uncertainty is of utmost importance to the public; therefore, the ensemble mean is often used as the deterministic forecast and the ensemble spread as the basis for a forecast uncertainty estimate. This approach works for weather parameters directly forecast by the model; however, snowfall accumulation is not directly forecast by the Global Ensemble Forecast System (GEFS). Therefore this study examines nine artificial intelligence methods for producing a 24-h snowfall accumulation prediction from the parameters directly output from the GEFS. These methods are then examined by their deterministic forecast skill using the mean absolute error of the ensemble mean forecast as well as the degree to which the ensemble spread corresponds to forecast uncertainty, which is examined by spread-skill relationships and quantile-quantile plots. Out of the nine methods—an artificial neural network, linear regression, least median squares regression, support vector regression, radial basis function network, conjunctive rule, k-nearest neighbor, regression tree, and an average of these methods— the k-nearest neighbor method produces significantly more accurate forecasts as well as the best calibrated ensemble spread. This postprocessing method would be appropriate for operational forecasting. STATISTICAL GUIDANCE METHODS FOR PREDICTING SNOWFALL ACCUMULATION IN THE NORTHEAST UNITED STATES
RELATIVE SLIP AMOUNT DEPENDENT ON THE INTERFACIAL SHEAR STRENGTH IN A NANO CHANNEL

The paper presents an analysis for the relative slip amount related to the fluid-wall interfacial shear strength in a nano channel formed by two parallel smooth solid planes sliding against one another. A closed-form equation formulation for the relative slip amount was obtained. It was shown that the relative slip amount is constant in the inlet zone of the channel, where the interfacial slippage occurs. This substantiates the assumption made in the analysis of this kind of channel as shown in the study by Zhang (2015). It was also shown that with the increases of the channel height or the fluidwall interfacial shear strength, the interfacial slippage is reduced. The strong fluid-stationary wall interaction in the outlet zone of the channel results in more severe interfacial slippage than the medium-level fluid-stationary wall interaction in the outlet zone.
Performance analysis of printed circuit heat exchanger for supercritical carbon dioxide and water

Printed circuit heat exchanger could be used as pre-cooler in the supercritical carbon dioxide (S-CO2) Brayton power cycle. Due to the drastic variations of S-CO2 properties in pre-cooler, segmental design method is used to investigate the thermal-hydraulic performance of PCHE. When the heat duty is given, the local heat transfer entropy generation number has extreme value, which appears near the intersection point of the heat capacity flow rates of both sides. In addition, the local and total entropy generation mainly depend on the local and total heat transfer entropy generation, and the flow imbalance increases entropy generation, especially under conditions of the higher local heat capacity flow rate of water.
Remarkably improved electrical insulating performances of lightweight polypropylene nanocomposites with fullerene

A polypropylene/fullerene nanocomposite was fabricated via solution processing with good dispersion of the fullerene nanoparticles. It was observed that a small amount of fullerene (~1 wt. ‰) can significantly improve the direct current (DC) electrical insulation performance (i.e. improved space charge distribution, greater DC dielectric breakdown strength, and larger DC volume resistivity) of polypropylene. Thermally stimulated depolarization current tests indicate that fullerene doping remarkably increases the deep trap density of pure polypropylene. The mechanisms by which the electrical properties of the polypropylene nanocomposites were improved are the introduction of deep traps and the high electron affinity of fullerene. The deep traps result from the interfaces between polypropylene and fullerene. This work provides a potential method to tailor lightweight nanodielectric materials with excellent electrical insulating performances.
Correlation between Neonatal Outcomes and Maternal Anemia among Attending Pregnant Women in Al-Elwiya Maternity Teaching Hospital

Background: Anemia in pregnancy can considerably elevate the maternal mortality risk and can negatively distress the development of fetus. Object of the Current Work: To assess the association between neonatal outcomes and maternal anemia (MA) among pregnant women (PW). Subjects and Methodology: The present work is a clinical prospective one performed at Al-Elwiya Maternity Teaching Hospital in Baghdad from January 1, 2022 to June 30, 2022. Current study selected 120 term PW with anemia admitted to hospital for caesarian section. Data were collected as a questionnaire. The data were directly taken from PW. The acquired data from anemic PW were distributed as followings: Age of anemic PW, which was classified into two groups; 25–29 years and 30–35 years. The gestational age of anemic PW, which was categorized into three groups; 37th week, 38th week, and 39th week of gestation. Anemia characteristics were studied, which included hemoglobin level (Hb) and packed cell volume test (PCV), which were done by taking 5 ml blood from each PW for s. ferritin, s.iron, Hb level, and blood film in laboratory of Al-Elwiya Maternity Teaching Hospital. The Hb helped in detecting anemic PW joined this study, as Hb was <10.5 g/dl at third trimester. Results: Mean gestational age (GA) of anemic PW was 37.5 ± 0.5 weeks; 58.3% of them were at 37th week, 39.2% of them were at 38th week, and 2.5% of them were at 39th week GA. So, the mean Hb of anemic PW was 8.6 ± 1.3 mg/dl, and the mean PCV was 28.6 ± 3.6%. Anemia was classified into mild (20%) and moderate (72.5%); also, mean ultrasound fetal head circumference (HC) among PW with mild anemia was 32.3 cm and for PW with moderate anemia was 32.1 cm, and mean ultrasound fetal abdominal circumference (AC) for PW with mild anemia was 31.3 cm and with moderate anemia was 31 cm, and validity results of MCA/UA-PI ratio regarding severe anemia of anemic were as follows: sensitivity (81.8%), specificity (79.8%), +ve predictive value (29%), −ve predictive value (97.8%), and accuracy (80%). Conclusion: The gestational mean age (GA) of anaemic PW was 37.50.5 weeks; 58.3% of them were in the 37th week and 39.2% were in the 38th week. Thus, the mean ultrasound foetal head circumference (HC) was 32.3 cm for PW with mild anemia and 32.1 cm for those with moderate anaemia. The mean ultrasound foetal abdominal circumference (AC) was 31.3 cm for those with mild anaemia and 31 cm for those with moderate anaemia, but 30 cm for those with severe anaemia, with no discernible difference. The following were the MCA/UA-PI ratio's validity findings for severe anaemia of anaemic: sensitivity (81.8%) and specificity (79.8%).
The Association between Internalizing Symptoms and Witnessing School Bullying and Defending Behavior: An Analysis of Gender Differences among Elementary and Middle School Students

Bullying is a significant public health concern that begins as early as elementary school and peaks in middle school. Although researchers have demonstrated the relationship between internalizing symptoms and being a target of bullying, there is limited research examining the association between internalizing symptoms and witnessing school bullying and defending targets or gender differences in these relationships. In this cross-sectional study, we examined gender as a moderator of the relationships between internalizing symptoms (e.g., depressive symptoms and social anxiety) and witnessing school bullying and defending behavior in a sample of elementary and middle school students (N = 126; 51.6% female; 3rd–8th grade). Results demonstrated that witnessing school bullying was a significant predictor of depressive symptoms. For social anxiety, the gender x witnessing school bullying interaction was significant for social avoidance and distress (SAD), such that among female students, SAD was positively related to witnessing school bullying. In contrast, the gender x defending behavior interaction was significant for fear of negative evaluation (FNE), such that among male students, FNE was positively related to defending behavior. Findings suggest bullying prevention should incorporate bystander training programs that include a focus on gender differences in social anxiety associated with being a bullying bystander.