Individual Candidates Research Articles

Hybridization of Social Group Optimization and Differential Evolution Algorithm for Solving Speed Reducer Design Problem

Objectives: The objective of this study is to present a hybrid approach named SGO-DE, which combines the Social Group Optimization (SGO) algorithm and differential evolution (DE), aiming to balance exploration and exploitation capacities to improve the accuracy of the optimization algorithm in finding optimal solution for speed reducer design problem. This hybrid approach is simulated for a speed reducer mechanical engineering design problem and the results are compared to several other state-of-the-art optimization algorithms. Method: To improve the exploration and exploitation of SGO, in its acquiring phase Differential Evolution (DE) is introduced. The individual candidate solutions derived from the Improving phase of SGO tries to acquire better values using DE. This helps in striking a better balance between exploration and exploitation, there by achieving improved optimal values and not getting trapped in local optima. The performance of the SGO-DE method is then evaluated and compared to other optimization algorithms through experimentation on the speed reducer design challenge. Findings: The findings of this study indicate that the SGO-DE hybrid approach outperforms other state-of-the-art algorithms by a significant margin in terms of optimization results. The numbers of function evaluations (FEs) significantly go low as less as 6000 compared to other state-of-the algorithms. The comparison demonstrates the efficacy of the SGO-DE method in enhancing solution quality and speeding up execution. Novelty: The novelty of this study lies in the development a hybrid approach of SGO and DE which is efficient in achieving competitive performance in less numbers of function evaluation in speed reducer design problem. This hybridization can strike a better balance between exploration and exploitations. Keywords: SGO, DE, Hybridization, Nature-inspired, Optimization algorithm

Cerebrovascular miRNAs Track Early Development of Alzheimer's Disease and Target Molecular Markers of Angiogenesis and Blood Flow Regulation.

Alzheimer's disease (AD) is associated with impaired cerebral circulation which underscores diminished delivery of blood oxygen and nutrients to and throughout the brain. In the 3xTg-AD mouse model, we have recently found that > 10 cerebrovascular miRNAs pertaining to vascular permeability, angiogenesis, and inflammation (e.g., let-7d, miR-99a, miR-132, miR-133a, miR-151-5p, and miR-181a) track early development of AD. Further, endothelial-specific miRNAs (miR-126-3p, miR-23a/b, miR-27a) alter with onset of overall AD pathology relative to stability of smooth muscle/pericyte-specific miRNAs (miR-143, miR-145). We tested the hypothesis that cerebrovascular miRNAs indicating AD pathology share mRNA targets that regulate key endothelial cell functions such as angiogenesis, vascular permeability, and blood flow regulation. As detected by NanoString nCounter miRNA Expression panel for 3xTg-AD mice, 61 cerebrovascular miRNAs and respective mRNA targets were examined using Ingenuity Pathway Analysis for canonical Cardiovascular (Cardio) and Nervous System (Neuro) Signaling. The number of targets regulated per miRNA were 21±2 and 33±3 for the Cardio and Neuro pathways respectively, whereby 14±2 targets overlap among pathways. Endothelial miRNAs primarily target members of the PDE, PDGF, SMAD, and VEGF families. Individual candidates regulated by≥4 miRNAs that best mark AD pathology presence in 3xTg-AD mice include CFL2, GRIN2B, PDGFB, SLC6A1, SMAD3, SYT3, and TNFRSF11B. miRNAs selective for regulation of endothelial function and respective downstream mRNA targets support a molecular basis for dysregulated cerebral blood flow regulation coupled with enhanced cell growth, proliferation, and inflammation.

A modular simulation framework for organ allocation

BackgroundWe describe and validate a new simulation framework addressing important limitations of the Simulated Allocation Models (SAMs) long used to project population effects of transplant policy changes. MethodsWe developed the Computational Open-source Model for Evaluating Transplantation (COMET), an agent-based model simulating interactions of individual donors and candidates over time to project population outcomes. COMET functionality is organized into interacting modules. Donors and candidates are synthetically generated using data-driven probability models which are adaptable to account for ongoing or hypothetical donor/candidate population trends and evolving disease management. To validate the first implementation of COMET, COMET-Lung, we attempted to reproduce lung transplant outcomes for U.S. adults from 2018-2019 and in the six months following adoption of the Composite Allocation Score (CAS) for lung transplant. ResultsSimulated (median [Interquartile Range, IQR]) versus observed outcomes for 2018-2019 were: 0.162 [0.157, 0.167] versus 0.170 waitlist deaths per waitlist year; 1.25 [1.23, 1.28] versus 1.26 transplants per waitlist year; 0.115 [0.112, 0.118] versus 0.113 post-transplant deaths per patient year; 202 [102, 377] versus 165 nautical miles travel distance. The model accurately predicted the observed precipitous decrease in transplants received by type O lung candidates in the six months following CAS implementation. ConclusionsCOMET-Lung closely reproduced most observed outcomes. The use of synthetic populations in the COMET framework paves the way for examining possible transplant policy and clinical practice changes in populations reflecting realistic future states. Its flexible, modular nature can accelerate development of features to address specific research or policy questions across multiple organs.

Learning Dynamic Scene-Conditioned 3D Object Detectors.

In this paper, we propose a dynamic 3D object detector named HyperDet3D, which is adaptively adjusted based on the hyper scene-level knowledge on the fly. Existing methods strive for object-level representations of local elements and their relations without scene-level priors, which suffer from ambiguity between similarly-structured objects only based on the understanding of individual points and object candidates. Instead, we design scene-conditioned hypernetworks to simultaneously learn scene-agnostic embeddings to exploit sharable abstracts from various 3D scenes, and scene-specific knowledge which adapts the 3D detector to the given scene at test time. As a result, the lower-level ambiguity in object representations can be addressed by hierarchical context in scene priors. However, since the upstream hypernetwork in HyperDet3D takes raw scenes as input which contain noises and redundancy, it leads to sub-optimal parameters produced for the 3D detector simply under the constraint of downstream detection losses. Based on the fact that the downstream 3D detection task can be factorized into object-level semantic classification and bounding box regression, we furtherly propose HyperFormer3D by correspondingly designing their scene-level prior tasks in upstream hypernetworks, namely Semantic Occurrence and Objectness Localization. To this end, we design a transformer-based hypernetwork that translates the task-oriented scene priors into parameters of the downstream detector, which refrains from noises and redundancy of the scenes. Extensive experimental results on the ScanNet, SUN RGB-D and MatterPort3D datasets demonstrate the effectiveness of the proposed methods.

Serum Dehydroepiandrosterone sulfate (DHEA-S) level and its potential impact on immune responses and symptom severity after Oxford-AstraZeneca COVID-19 vaccination

BackgroundDehydroepiandrosterone sulfate (DHEA-S) has been associated with an immunomodulatory function. This study aims to explore the relationship between serum levels of DHEA-S and the immune responses triggered by the Oxford–AstraZeneca COVID-19 vaccine in individuals candidate for vaccination. MethodsSerum levels of DHEA-S, cytokine release, antibody production and virus neutralization potential were assessed in 50 male and 50 female subjects before and 2 weeks after vaccination with Oxford–AstraZeneca COVID-19 vaccine. ResultsLevel of DHEA-S before and 2 weeks after first and second dose of vaccination was not different significantly. Levels of Interleukin (IL)-2 and Interferon (IFN)-γ were significantly higher in the supernatant of peripheral blood mononuclear cells (PBMCs) obtained from subjects 2 weeks after both first and second dose of vaccination compared to before vaccination. Serum levels of IgM 2 weeks after first dose of vaccination was significantly higher compared to before first dose of vaccination. However, serum levels of IgG 2 weeks after first and second dose of vaccination were significantly higher compared to before first and second dose of vaccination. The 50 % focus reduction neutralization test (FRNT50) titer was significantly higher 2 weeks after both first and second dose of vaccination compared to before vaccination. Levels of DHEA-S did not have significant correlation with levels of IL-2, IFN-γ, IgM and IgG, and FRNT50 before and after first and second dose of vaccination. Vaccination did not result in intense unwanted clinical presentations. ConclusionDHEA-S is not involved in the quality of protective immune response during Oxford-AstraZeneca COVID-19 vaccination.

Стан вивчення поліморфізму окремих генів у виникненні бронхіальної астми

The study of the polymorphism of individual genes is the basis of both preventive medicine and is used in the selection of adequate therapy. Polymorphism of individual candidate genes in bronchial asthma (BA) is studied taking into account many personal characteristics and the influence of environmental factors. Aim - to analyze the status of the study of the role of polymorphism of β2-adrenoceptors (ADRβ2) in the pathogenesis of bronchial asthma in children and to compare them with our own findings. Materials and methods. The results of research on polymorphism of individual genes in children with BA, which includes the PubMed database, were analyzed. An in-depth study of the anamnesis data (disease, life, hereditary), a complex clinical and laboratory examination of children (n=101) of school age with BA was carried out (the average age was: for boys 11.15±0.48 years; for girls - 10.63±0.7 years). Patients were diagnosed with BA in accordance with the GINA recommendations of the current revision. Determination of the Arg16Gly polymorphism of the ADRβ2 gene (rs 1042713) was performed by the polymerase chain reaction method followed by restriction enzyme analysis. The obtained data were processed in the Statsoft STATISTICA software package. Mean values were given as (M±m), Student's test was used for comparison. Results. The assessment of the frequency of polymorphism of the Arg16Gly gene in BA established that two variants prevailed in boys: Arg16Gly and Gly16Gly; at that time, the Gly16Gly genotype prevailed among girls, which, according to individual studies, is associated with good effectiveness of the applied therapy (nebulization of salbutamol). Mutations in the ADRβ2 gene in patients with BA were twice as frequent in the Arg16Gly genotype and three times as frequent in the Gln27Glu genotype, in contrast to healthy children. Such a polymorphism affects the functional activity of ADRβ2, the occurrence and course of BA. Conclusions. The Arg16Gly polymorphism of the ADRβ2 gene in children with BA largely determines the sensitivity of ADRβ2 to the applied exacerbation therapy and the effectiveness of basic treatment. In patients with the Gly16Gly genotype, most researchers note the good clinical effectiveness of both fast broncholytic drugs (β2 short-acting agonists) and basic anti-inflammatory drugs. The diagnosed homozygous Arg16Arg genotype of the ADRβ2 gene mostly accompanies the uncontrolled (or partially controlled) course of asthma in children. The revealed features of the Arg16Gly polymorphism of the ADRβ2 gene will help the doctor to draw up an adequate treatment plan, which is based on the genetically determined sensitivity of ADRβ2 receptors to medical preparations. The research was carried out in accordance with the principles of the Helsinki Declaration. The study protocol was approved by the Local Ethics Committee of the participating institution. The informed consent of the patient was obtained for conducting the studies. No conflict of interests was declared by the author.

Abstract B008: Alternative PER2 (Period2) enhancer usage drives epithelial-mesenchymal transition (EMT) in epithelial ovarian cancer (OC)

Abstract B008: Alternative <i>PER2</i> (Period2) enhancer usage drives epithelial-mesenchymal transition (EMT) in epithelial ovarian cancer (OC)

Cytokines as fast indicator of infectious virus titer during process development

Measuring infectious titer is the most time-consuming method during the production and process development of live viruses. Conventionally, it is done by measuring the tissue culture infectious dose (TCID50) or plaque forming units (pfu) in cell-based assays. Such assays require a time span of more than a week to the readout and significantly slow down process development. In this study, we utilized the pro-inflammatory cytokine response of a Vero production cell line to a recombinant measles vaccine virus (MVV) as model system for rapidly determining infectious virus titer within several hours after infection instead of one week. Cytokines are immunostimulatory proteins contributing to the first line of defence against virus infection. The probed cytokines in this study were MCP-1 and RANTES, which are secreted in a virus dose as well as time dependent manner and correlate to TCID50 over a concentration range of several logarithmic levels with R2 = 0.86 and R2 = 0.83, respectively. Furthermore, the pro-inflammatory cytokine response of the cells was specific for infectious virus particles and not evoked with filtered virus seed. We also discovered that individual cytokine candidates may be more suitable for off- or at-line analysis, depending on the secretion profile as well as their sensitivity towards changing process conditions. Furthermore, the method can be applied to follow a purification procedure and is therefore suited for process development and control.

Competency-based postgraduate training: Mentoring and monitoring using entrustable professional activities with descriptive rubrics for objectivity- A step beyond Dreyfus.

Background At Sri Balaji Vidyapeeth, a competency-based learning and training (CoBaLT©) model for postgraduate (PG) curriculum, within the regulatory norms, was implemented in 2016 after adequate faculty development programmes. This focused on well-defined outcomes. Methods A review of the outcomes was undertaken in 2018 as part of internal quality assurance receiving feedback from all stakeholders, viz. students, alumni and faculty. Recent publications were also reviewed. A major problem identified was lack of clarity in definition of levels leading to subjectivity in assessment while grading. It was also noted that the process needed to be aligned with the programme outcomes. Further refinements were, therefore, made to align and objectivize formative assessment using entrustable professional activities (EPA) with the aid of descriptive rubrics of sub-competencies and milestones. Addition of detailed rubrics for objectivity takes assessment a step beyond the Dreyfus model, aligning overall to the programme outcomes. Results Achievement of appropriate grades in EPAs by individual candidates ensures entrustability in professional activities by the time of completion of the PG programme. The modification was found more transparent and objective with reference to grading by the teachers and more conducive to reflections by the residents on their performance and how to improve it. Conclusions The use of descriptive rubrics along with EPAs brings transparency and plays a key role as an objective assessment tool, which can lend direction to individual resident learning and entrustability. This is an important component of outcome-based education.

Prospects and Dynamics of Special Autonomy Post Aceh Government Law No. 11 of 2006 in Aceh

After the birth of the Aceh Government Law a year ago, the prospect of Special Autonomy in implementing and implementing all government system tools in Nanggroe Aceh Darussalam requires high energy. On the other hand, we read that the Unitary State system is in accordance with scientific theory. This research uses qualitative methods to see how individual candidates can survive amidst the onslaught of local and national political parties in Aceh. From the research results, it was found that the existence of individual candidates had caused political tensions in Aceh after the formation of local political parties.The State is also usually called unitary, the form of government is a single structure. It is not composed of several countries like a federation. This means that as a unitary State, there is only one State. Thus, in a unitary state there is only one government, namely the central government which has the highest power or authority in all areas of government.

Individual drivers of toxicity in radical right-wing populist legislative campaigns

Most studies of political rhetoric examine only political leadership or treat parties as unified actors. However, what happens where electoral systems incentivise candidates to diverge from stated party messaging during campaigns? This article uses novel data on political experience and candidate backgrounds from the 2022 French parliamentary elections to explore the individual drivers of campaigning behaviour. The choice of France, with its multiple and prominent radical right-wing parties, allows for the consideration of both within- and between-party differences in individual campaigning. Using the salient example of toxic rhetoric, findings demonstrate that even when party leaders publicly urge moderation, individual candidates do not necessarily follow along. This implies the need for additional focus on the individual-level drivers of political semantics, especially where candidates are apt to campaign independently, using social media platforms to communicate directly with citizens.

Identification of pyroptosis-associated genes with diagnostic value in calcific aortic valve disease

BackgroundCalcific aortic valve disease (CAVD) is one of the most prevalent valvular diseases and is the second most common cause for cardiac surgery. However, the mechanism of CAVD remains unclear. This study aimed to investigate the role of pyroptosis-related genes in CAVD by performing comprehensive bioinformatics analysis.MethodsThree microarray datasets (GSE51472, GSE12644 and GSE83453) and one RNA sequencing dataset (GSE153555) were obtained from the Gene Expression Omnibus (GEO) database. Pyroptosis-related differentially expressed genes (DEGs) were identified between the calcified and the normal valve samples. LASSO regression and random forest (RF) machine learning analyses were performed to identify pyroptosis-related DEGs with diagnostic value. A diagnostic model was constructed with the diagnostic candidate pyroptosis-related DEGs. Receiver operating characteristic (ROC) curve analysis was performed to estimate the diagnostic performances of the diagnostic model and the individual diagnostic candidate genes in the training and validation cohorts. CIBERSORT analysis was performed to estimate the differences in the infiltration of the immune cell types. Pearson correlation analysis was used to investigate associations between the diagnostic biomarkers and the immune cell types. Immunohistochemistry was used to validate protein concentration.ResultsWe identified 805 DEGs, including 319 down-regulated genes and 486 up-regulated genes. These DEGs were mainly enriched in pathways related to the inflammatory responses. Subsequently, we identified 17 pyroptosis-related DEGs by comparing the 805 DEGs with the 223 pyroptosis-related genes. LASSO regression and RF algorithm analyses identified three CAVD diagnostic candidate genes (TREM1, TNFRSF11B, and PGF), which were significantly upregulated in the CAVD tissue samples. A diagnostic model was constructed with these 3 diagnostic candidate genes. The diagnostic model and the 3 diagnostic candidate genes showed good diagnostic performances with AUC values &amp;gt;0.75 in both the training and the validation cohorts based on the ROC curve analyses. CIBERSORT analyses demonstrated positive correlation between the proportion of M0 macrophages in the valve tissues and the expression levels of TREM1, TNFRSF11B, and PGF.ConclusionThree pyroptosis-related genes (TREM1, TNFRSF11B and PGF) were identified as diagnostic biomarkers for CAVD. These pyroptosis genes and the pro-inflammatory microenvironment in the calcified valve tissues are potential therapeutic targets for alleviating CAVD.

Translational PK/PD for the Development of Novel Antibiotics-A Drug Developer's Perspective.

Antibiotic development traditionally involved large Phase 3 programs, preceded by Phase 2 studies. Recognizing the high unmet medical need for new antibiotics and, in some cases, challenges to conducting large clinical trials, regulators created a streamlined clinical development pathway in which a lean clinical efficacy dataset is complemented by nonclinical data as supportive evidence of efficacy. In this context, translational Pharmacokinetic/Pharmacodynamic (PK/PD) plays a key role and is a major contributor to a "robust" nonclinical package. The classical PK/PD index approach, proven successful for established classes of antibiotics, is at the core of recent antibiotic approvals and the current antibacterial PK/PD guidelines by regulators. Nevertheless, in the case of novel antibiotics with a novel Mechanism of Action (MoA), there is no prior experience with the PK/PD index approach as the basis for translating nonclinical efficacy to clinical outcome, and additional nonclinical studies and PK/PD analyses might be considered to increase confidence. In this review, we discuss the value and limitations of the classical PK/PD approach and present potential risk mitigation activities, including the introduction of a semi-mechanism-based PK/PD modeling approach. We propose a general nonclinical PK/PD package from which drug developers might choose the studies most relevant for each individual candidate in order to build up a "robust" nonclinical PK/PD understanding.

Leptohadronic multi-messenger modeling of 324 gamma-ray blazars

Context. The origin of the diffuse astrophysical neutrino flux observed by the IceCube experiment is still under debate. Multiple associations have been reported between high-energy neutrino events and individual bla/ars, such as the source TXS 0506+056, which are active galaxies with relativistic jets pointing toward Earth. From a theoretical perspective, the properties of these sources as neutrino emitters are not yet well understood. Aims. By systematically modeling the effect of cosmic-ray protons on the multiwavelength data from the largest sample of bright gamma-ray bla/ars to date, we expect to learn about the multi-messenger nature of the active galaxy population as a whole, as well as the relationship between neutrino production and the multiwavelength spectrum of these sources. Methods. We predict the emitted multiwavelength and neutrino spectrum using a self-consistent numerical radiation model applied individually to each source in the sample. We then study the properties of the full population and identify empirical relations. We focus on public multiwavelength data from the radio to the gamma-ray bands from a sample of 324 bla/ars detected by the Fermi Large Area Telescope (LAT), most of which are flat-spectrum radio quasars (FSRQs). This amounts to 34% of all FSRQs in the latest Fermi catalog. Results. We demonstrate that the optical and gigaelectronvolt gamma-ray broadband features are generally well described by electron emission, which helps for the location of the emission region relative to the central black hole to be constrained. For 33% of the bla/ars in our sample, a description of the observed X-ray spectrum benefits from an additional component from proton interactions, in agreement with recent studies of individual IceCube candidate bla/ars. We show that, on average, bla/ars that are brighter in gigaelectronvolt gamma rays have a higher neutrino production efficiency but a lower best-fit baryonic loading. The predicted neutrino luminosity shows a positive correlation both with the observed flux of gigaelectronvolt gamma rays and with the predicted flux of megaelectronvolt gamma rays. We also estimate the diffuse neutrino flux from gamma-ray bla/ars by extrapolating the result to the Fermi population, and we show that it may be at the level of ~20% of the diffuse neutrino flux observed by IceCube, in agreement with current limits from stacking analyses. We discuss the implications of our results for future neutrino searches and suggest promising sources for potential detections.

BCR-ABL kinase domain mutations in CML patients, experience from a tertiary care center in North India

BackgroundChronic Myeloid Leukemia is characterized by the presence of the Philadelphia Chromosome (Ph) which contains the BCR::ABL1 fusion gene that occurs due to a reciprocal translocation between chromosomes 9 and 22. This accounts for up to 15 % of all adult leukemias [1]. Most patients treated with first line tyrosine kinase inhibitor (TKI) imatinib achieve durable response but may undergo relapse at some stage [2]. The most important mechanism that may confer imatinib resistance is point mutation within BCR::ABL kinase domain. Other generation ABL tyrosine kinase inhibitors such as dasatinib, nilotinib, bosutinib and ponatinib help to overcome imatinib resistance [3]. Sensitivity of the patient to each of the above TKIs depends upon the individual candidate mutation present. Thus, it is important to perform mutation analysis for effective therapeutic management of CML patients once they show imatinib resistance. We used direct sequencing to identify the different types of mutations responsible for resistance of imatinib treatment from north India. MethodsIn this study, the patient resistance for the imatinib were analyzed for BCR::ABL kinase domain mutation by direct sequencing and the detected mutations along with their percentage prevalence were reported. Results329 patients with CML-CP were analyzed for BCR::ABL kinase domain mutation. Total 66 (20.06 %) patients out of 329 had mutation in at least one of the domains of BCR::ABL conferring resistance to different generations of TKI. Mutations in BCR::ABL kinase domain was observed in different domain of BCR::ABL. ATP binding P-Loop (42.42 %), Direct binding site (36.36 %), C-Loop (10.60 %), A-Loop (6.06 %), SH2 contact (3.03 %), SH3 contact (1.51 %). ConclusionTotal 20.06 % patients (66/329) show mutation in at least one of the structural motifs of BCR-ABL kinase domain, which further confer the resistance to a particular generation of TKI.

Protein signaling and drug target activation signatures to guide therapy prioritization: Therapeutic resistance and sensitivity in the I-SPY 2 Trial

Molecular subtyping of breast cancer is based mostly on HR/HER2 and gene expression-based immune, DNA repair deficiency, and luminal signatures. We extend this description via functional protein pathway activation mapping using pre-treatment, quantitative expression data from 139 proteins/phosphoproteins from 736 patients across 8 treatment arms of the I-SPY 2 Trial (ClinicalTrials.gov: NCT01042379). We identify predictive fit-for-purpose, mechanism-of-action-based signatures and individual predictive protein biomarker candidates by evaluating associations with pathologic complete response. Elevated levels of cyclin D1, estrogen receptor alpha, and androgen receptor S650 associate with non-response and are biomarkers for global resistance. We uncover protein/phosphoprotein-based signatures that can be utilized both for molecularly rationalized therapeutic selection and for response prediction. We introduce a dichotomous HER2 activation response predictive signature for stratifying triple-negative breast cancer patients to either HER2 or immune checkpoint therapy response as a model for how protein activation signatures provide a different lens to view the molecular landscape of breast cancer and synergize with transcriptomic-defined signatures.

Between anger and love: A multi-level study on the impact of policy issues on user reactions in national election campaigns on Facebook in Germany, Hungary, and Norway

Eliciting user reactions is an important tactic for political actors using social media like Facebook to seek attention for campaign messages on policy issues. Still, little is known about policy issues’ effect on user reactions and how structural factors play into this relationship. Applying a standardized manual content analysis on Facebook posts from political parties and their top candidates during the German, Hungarian, and Norwegian national election campaigns in 2021/2022 ( N = 4988), we investigate the relationship between policy issues and two of Facebook’s “emotional reactions” (“angry” and “love”). We find that posts addressing the economy, energy policy, and foreign policy drive more “angry” reactions, while environmental posts drive more “love” reactions. While effects are largely uniform across different party types, there are more variations between countries. Our analyses suggest that differences between individual parties and candidates and situational factors are vital to understanding the relationship between policy issues and user reactions.

Hub Genes in Stable QTLs Orchestrate the Accumulation of Cottonseed Oil in Upland Cotton via Catalyzing Key Steps of Lipid-Related Pathways

Upland cotton is the fifth-largest oil crop in the world, with an average supply of nearly 20% of vegetable oil production. Cottonseed oil is also an ideal alternative raw material to be efficiently converted into biodiesel. However, the improvement in kernel oil content (KOC) of cottonseed has not received sufficient attention from researchers for a long time, due to the fact that the main product of cotton planting is fiber. Previous studies have tagged QTLs and identified individual candidate genes that regulate KOC of cottonseed. The regulatory mechanism of oil metabolism and accumulation of cottonseed are still elusive. In the current study, two high-density genetic maps (HDGMs), which were constructed based on a recombinant inbred line (RIL) population consisting of 231 individuals, were used to identify KOC QTLs. A total of forty-three stable QTLs were detected via these two HDGM strategies. Bioinformatic analysis of all the genes harbored in the marker intervals of the stable QTLs revealed that a total of fifty-one genes were involved in the pathways related to lipid biosynthesis. Functional analysis via coexpression network and RNA-seq revealed that the hub genes in the co-expression network that also catalyze the key steps of fatty acid synthesis, lipid metabolism and oil body formation pathways (ACX4, LACS4, KCR1, and SQD1) could jointly orchestrate oil accumulation in cottonseed. This study will strengthen our understanding of oil metabolism and accumulation in cottonseed and contribute to KOC improvement in cottonseed in the future, enhancing the security and stability of worldwide food supply.

Exploring Candidates' Initial Images of Similar Figures

This article investigates preservice candidates' knowledge of similar figures while engaged in teacher-related mathematical tasks (TRMT) with the primary goal of developing a lesson plan on similar figures. This investigation was part of a larger study investigating candidate knowledge of what and how to teach proportional reasoning concepts while engaged in TRMT. The data collection and TRMT cycle included individual discussions and reflections, group planning and discussions, and group presentations. Individual candidates also wrote their teaching philosophies and math autobiographies, which were reviewed. While candidates appeared to grasp many of the aspects of the concept of similar figures and similarity, there was a lack of precision and strength in their representations. The knowledge base of the candidates in both mathematics and teaching varied. As the study progressed, candidates relied heavily on their subject matter knowledge to justify their images and ideas.

Eating disorders among bariatric surgery patients: The chicken or the egg?

Postoperative eating behaviors and unhealthy weight control measures are leading causes of bariatric surgery complications. Candidates for bariatric surgery and individuals with eating disorders may share common risk factors, such as a history of dieting, and/or being bullied or teased for their weight. Binge-eating disorder, night eating syndrome, and bulimia nervosa are the most common eating disorders among candidates for bariatric surgery before the operation. Malnutrition, stress, and intense fear of weight gain can lead to the development of an eating disorder after surgery as well. Plugging, grazing, loss of control eating, dumping, and food avoidance are specific disordered behaviors that may present after bariatric surgery. To improve physical and psychological outcomes for individuals under their care, clinicians can screen for these disordered behaviors and distinguish them from a healthy diet and the expected postsurgical course.