Head-to-Head Comparison of SSTR Antagonist [68Ga]Ga-DATA5m-LM4 with SSTR Agonist [68Ga]Ga-DOTANOC PET/CT in Patients with Well Differentiated Gastroenteropancreatic Neuroendocrine Tumors: A Prospective Imaging Study.

Neuroendocrine tumors (NETs) are slow-growing tumors that express high levels of somatostatin receptors (SSTRs). Recent studies have shown the superiority of radiolabeled SSTR antagonists in theranostics compared to agonists. In this prospective study, we compared the diagnostic efficacy between [68Ga]Ga-DOTANOC and [68Ga]Ga-DATA5m-LM4 in the detection of primary and metastatic lesions in patients with well differentiated gastroenteropancreatic (GEP) NETs. Histologically proven GEP-NET patients underwent [68Ga]Ga-DOTANOC & [68Ga]Ga-DATA5m-LM4 PET/CT scans, which were analyzed. The qualitative analysis involved the visual judgment of radiotracer uptake validated by the morphological findings using CT, which was considered as the reference standard. Quantitative comparisons were presented as the standardized uptake value (SUV) corrected for lean body mass: SULpeak, SULavg, and tumor-to-background ratios (TBR). In total, 490 lesions were confirmed via diagnostic CT. The lesion-based sensitivity of [68Ga]Ga-DATA5m-LM4 PET/CT was 94.28% (462/490) and 83.46% (409/490) for [68Ga]Ga-DOTANOC PET/CT (p < 0.0001). [68Ga]Ga-DATA5m-LM4 had statistical significance over [68Ga]Ga-DOTANOC in liver metastases [100% vs. 89.4%; p < 0.0001 (292 vs. 253 {283 lesions on CT})] and bone metastases [100% vs. 82.9%; p = 0.005 (45 vs. 34 {41 lesions on CT})]. Statistical significance was also noted for the TBR SULpeak of the primary and liver lesions. [68Ga]Ga-DATA5m-LM4 showed better sensitivity and a higher target-to-background ratio than [68Ga]Ga-DOTANOC PET/CT. [68Ga]Ga-DATA5m-LM4 PET/CT can be used to quantify the extent of skeletal and liver metastases for better planning of SSTR agonist- or antagonist-based therapy.

Genotyping SNPs in lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2) exhibits association with wood density in teak (Tectona grandis L.f.).

BACKGROUND: Teak (Tectona grandis L.f.), an important source of tropical timber with immense economic value, is a highly outcrossing forest tree species. 150 unrelated accessions of teak (Tectona grandis L.f.) plus trees assembled as clones at National Teak Germplasm Bank, Chandrapur, Maharashtra, India was investigated for association mapping of candidate lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2). METHODS AND RESULTS: The CAD1, MYB1 and MYB2 were amplified using specifically designed primers. The amplified sequences were then sequenced and genotyped for 112 SNPs/11 indels. We evaluated the association between SNPs and wood density in teak accessions using GLM and MLM statistical models, with Bonferroni correction applied. The teak accessions recorded an average wood density of 416.69 kg.m-3 (CV 4.97%) and comprised of three loosely structured admixed sub-populations (K = 3), containing 72.05% genetic variation within sub-populations with low intragenic LD (0-21% SNP pairs) at P < 0.05 and high LD decay (33-934 bp) at R2 = 0.1. GLM and MLM models discounting systematic biases (Q and K matrices) to avoid false discovery revealed five loci at rare variants (MAF 0.003) and three loci at common variants (MAF 0.05) to be significantly (P < 0.05) associated with the wood density. However, the stringent Bonferroni correction (4.06-7.04 × 10-4) yielded only a single associated locus (B1485C/A) from exon of MYB1 transcription factor, contributing to about 10.35% phenotypic variation in wood density trait. CONCLUSION: Scored SNP locus (B1485C/A) can be developed as a molecular probe for selection of improved planting stock with proven wood density trait for a large-scale teak plantation.

Genome-Wide Association Study of Body Conformation Traits in a Three-Way Crossbred Commercial Pig Population.

Body conformation is the most direct production index, which can fully reflect pig growth status and is closely related to critical economic traits. In this study, we conducted a genome-wide association study (GWAS) on body conformation traits in a population of 1518 Duroc × (Landrace × Yorkshire) commercial pigs. These traits included body length (BL), body height (BH), chest circumference (CC), abdominal circumference (AC), and waist circumference (WC). Both the mixed linear model (MLM) and fixed and random model circulating probability unification (FarmCPU) approaches were employed for the analysis. Our findings revealed 60 significant single nucleotide polymorphisms (SNPs) associated with these body conformation traits in the crossbred pig population. Specifically, sixteen SNPs were significantly associated with BL, three SNPs with BH, thirteen SNPs with CC, twelve SNPs with AC, and sixteen SNPs with WC. Moreover, we identified several promising candidate genes located within the genomic regions associated with body conformation traits. These candidate genes include INTS10, KIRREL3, SOX21, BMP2, MAP4K3, SOD3, FAM160B1, ATL2, SPRED2, SEC16B, and RASAL2. Furthermore, our analysis revealed a novel significant quantitative trait locus (QTL) on SSC7 specifically associated with waist circumference, spanning an 84 kb interval. Overall, the identification of these significant SNPs and potential candidate genes in crossbred commercial pigs enhances our understanding of the genetic basis underlying body conformation traits. Additionally, these findings provide valuable genetic resources for pig breeding programs.

Validation of genes affecting rice mesocotyl length through candidate association analysis and identification of the superior haplotypes.

Mesocotyl is an essential organ of rice for pushing buds out of soil and plays a crucial role in seeding emergence and development in direct-seeding. Thus, identify the loci associated with mesocotyl length (ML) could accelerate breeding progresses for direct-seeding cultivation. Mesocotyl elongation was mainly regulated by plant hormones. Although several regions and candidate genes governing ML have been reported, the effects of them in diverse breeding populations were still indistinct. In this study, 281 genes related to plant hormones at the genomic regions associated with ML were selected and evaluated by single-locus mixed linear model (SL-MLM) and multi-locus random-SNP-effect mixed linear model (mr-MLM) in two breeding panels (Trop and Indx) originated from the 3K re-sequence project. Furthermore, superior haplotypes with longer mesocotyl were also identified for marker assisted selection (MAS) breeding. Totally, LOC_Os02g17680 (explained 7.1-8.9% phenotypic variations), LOC_Os04g56950 (8.0%), LOC_Os07g24190 (9.3%) and LOC_Os12g12720 (5.6-8.0%) were identified significantly associated with ML in Trop panel, whereas LOC_Os02g17680 (6.5-7.4%), LOC_Os04g56950 (5.5%), LOC_Os06g24850 (4.8%) and LOC_Os07g40240 (4.8-7.1%) were detected in Indx panel. Among these, LOC_Os02g17680 and LOC_Os04g56950 were identified in both panels. Haplotype analysis for the six significant genes indicated that haplotype distribution of the same gene varies at Trop and Indx panels. Totally, 8 (LOC_Os02g17680-Hap1 and Hap2, LOC_Os04g56950-Hap1, Hap2 and Hap8, LOC_Os07g24190-Hap3, LOC_Os12g12720-Hap3 and Hap6) and six superior haplotypes (LOC_Os02g17680-Hap2, Hap5 and Hap7, LOC_Os04g56950-Hap4, LOC_Os06g24850-Hap2 and LOC_Os07g40240-Hap3) with higher ML were identified in Trop and Indx panels, respectively. In addition, significant additive effects for ML with more superior haplotypes were identified in both panels. Overall, the 6 significantly associated genes and their superior haplotypes could be used to enhancing ML through MAS breeding and further promote direct-seedling cultivation.

Genome-wide association analysis provides insights into the genetic basis of photosynthetic responses to low-temperature stress in spring barley.

Low-temperature stress (LTS) is among the major abiotic stresses affecting the geographical distribution and productivity of the most important crops. Understanding the genetic basis of photosynthetic variation under cold stress is necessary for developing more climate-resilient barley cultivars. To that end, we investigated the ability of chlorophyll fluorescence parameters (FVFM, and FVF0) to respond to changes in the maximum quantum yield of Photosystem II photochemistry as an indicator of photosynthetic energy. A panel of 96 barley spring cultivars from different breeding zones of Canada was evaluated for chlorophyll fluorescence-related traits under cold acclimation and freeze shock stresses at different times. Genome-wide association studies (GWAS) were performed using a mixed linear model (MLM). We identified three major and putative genomic regions harboring 52 significant quantitative trait nucleotides (QTNs) on chromosomes 1H, 3H, and 6H for low-temperature tolerance. Functional annotation indicated several QTNs were either within the known or close to genes that play important roles in the photosynthetic metabolites such as abscisic acid (ABA) signaling, hydrolase activity, protein kinase, and transduction of environmental signal transduction at the posttranslational modification levels. These outcomes revealed that barley plants modified their gene expression profile in response to decreasing temperatures resulting in physiological and biochemical modifications. Cold tolerance could influence a long-term adaption of barley in many parts of the world. Since the degree and frequency of LTS vary considerably among production sites. Hence, these results could shed light on potential approaches for improving barley productivity under low-temperature stress.

Genome-wide association analysis for emergence of deeply sown rice (Oryza sativa) reveals novel aus-specific phytohormone candidate genes for adaptation to dry-direct seeding in the field.

Dry direct-seeded rice (dry-DSR) is typically sown deeply to circumvent the need for irrigation, and thus seedling emergence is a crucial trait affecting plant stand and yield. To breed elite cultivars that use less water and are climate-resilient, an understanding of the genomic regions and underlying genes that confer emergence in deeply sown dry-DSR would be highly advantageous. A combined diversity panel of 470 rice accessions (RDP1 plus aus subset of 3K RGP) was evaluated with 2.9 million single nucleotide polymorphisms (SNPs) to identify associations with dry-DSR traits in the field and component traits in a controlled-environment experiment. Using genome-wide association study (GWAS) analyses, we identified 18 unique QTLs on chromosomes 1, 2, 4, 5, 6, 7, 9, 10, and 11, explaining phenotypic variance ranging from 2.6% to 17.8%. Three QTLs, namely, qSOE-1.1, qEMERG-AUS-1.2, and qEMERG-AUS-7.1, were co-located with previously reported QTLs for mesocotyl length. Among the identified QTLs, half were associated with the emergence of aus, and six were unique to the aus genetic group. Based on functional annotation, we identified eleven compelling candidate genes that primarily regulate phytohormone pathways such as cytokinin, auxin, gibberellic acid, and jasmonic acid. Prior studies indicated that these phytohormones play a critical role in mesocotyl length under deep sowing. This study provides new insight into the importance of aus and indica as desirable genetic resources to mine favorable alleles for deep-sowing tolerance in rice. The candidate genes and marker-tagged desirable alleles identified in this study should benefit rice breeding programs directly.

Experimental Study on Repairing the Mechanical Characteristics of Oil-Contaminated Silty Clay in Ancient Dike with Modified Lime Mortar.

Flood-controlled ancient dikes play a significant role in flood control and have received widespread attention as historical and cultural symbols. Flood-controlled ancient dikes often undergo disasters, and research on their repair is receiving increasing attention from experts and scholars. This article studies the control of seepage and bank slope instability in flood-controlled ancient dikes. Starting from the repair of ancient dike materials, three types of work are carried out: a test of soil's mechanical properties, finite element numerical simulation, and repair technology research. The research results show that the soil of the ancient dike site has hardened after being contaminated with waste oil from catering. The strength index of the ancient dike soil decreases and shows brittleness when the water content is 15% and the oil content exceeds 6%. The strength index and permeability coefficient of oil-contaminated soil improved using modified lime mortar (MLM), which was achieved using the method of MLM to repair oil contaminated soil. When the MLM content was 10% and the oil content was 6%, the friction angle of the soil sample reached its maximum value. When the MLM content was the same, the higher the density of the soil sample, the greater the friction angle and cohesion and the smaller the permeability coefficient. Establishing a finite element numerical model, through comparative analysis, it was found that after MLM remediation of oil-contaminated soil, the extreme hydraulic gradient of the ancient dike decreased by 31.3%, and the extreme safety factor of the bank slope stability increased by 31.2%. MLM pressure grouting technology was used to improve the soil during the remediation of contaminated soil at the ancient dike site. Through on-site drilling inspection, the effective diffusion radius of MLM grouting was obtained, and the plane layout and grouting depth of MLM pressure grouting were determined. The on-site water injection permeability test showed that using MLM pressure grouting technology can effectively repair oil-contaminated soil in the ancient dike while reducing the permeability coefficient by 8-15%.

An Observational Study on Chronic Pain Biomarkers in Fibromyalgia and Osteoarthritis Patients: Which Role for Mu Opioid Receptor's Expression on NK Cells?

The evaluation of chronic pain is challenging because of the lack of specific biomarkers. We identified the Mu opioid receptor-positive (Mu+) B cell percentage of expression, named Mu-Lympho-Marker (MLM), as a candidate marker for chronic pain in fibromyalgia (FM) and osteoarthritis (OA) patients. Here, we investigate the role of MLM on natural killer (NK) cells in the same patients. Twenty-nine FM and twelve OA patients were analyzed, and twenty-three pain-free subjects were considered as the control group. Blood samples were collected to perform immunophenotyping and Western blot analysis. Biological and clinical data were statistically analyzed. The final results showed that the percentage of NK cells expressing Mu was statistically lower in FM and OA patients than in pain-free subjects, as already demonstrated for B cells. A Western blot analysis was performed in order to detect NK cells' functional status. Moreover, the correlation analysis of MLM expression with pharmacological therapy did not show any significant results. In conclusion, here, we confirm the role of MLM as a suitable marker for chronic pain and underline NK cells as a new possible immune cell type involved in the "Mu opioid receptor reserve theory".

Presumed Post-COVID Infection Retinitis - Clinical and Tomographic Features of Retinitis as a Post-COVID Syndrome.

PURPOSE: To study clinical and imaging features of presumed post-COVID infection retinitis. METHOD: Retrospective case series of patients presenting with retinitis lesions with evidence of recent COVID infection. Retinal findings and optical coherence tomography (OCT) features were studied at baseline and follow-ups. RESULTS: Twenty-four eyes of 17 patients were included. Mean age was 36.57 ± 11.78 years. Baseline visual acuity (VA) was log MAR 0.97 ± 0.43. Fundus findings included retinitis patches (n = 24),hard exudates (n = 8), and superficial hemorrhages (n = 16). OCT features included neurosensory detachment (NSD, n = 20), hyperreflective inner layers (n = 24), acute macular neuroretinopathy (AMN, n = 8), hyperreflective foci (n = 20). At final follow-up, VA was logMAR 0.43 ± 0.27. Retinitis patches persisted in four eyes, AMN in three eyes, and NSD in five eyes. Conclusion- Post- COVID infection retinitis adds to existing literature on post COVID syndromes.

r2mlm: An R package calculating R-squared measures for multilevel models.

Multilevel models are used ubiquitously in the social and behavioral sciences and effect sizes are critical for contextualizing results. A general framework of R-squared effect size measures for multilevel models has only recently been developed. Rights and Sterba (2019) distinguished each source of explained variance for each possible kind of outcome variance. Though researchers have long desired a comprehensive and coherent approach to computing R-squared measures for multilevel models, the use of this framework has a steep learning curve. The purpose of this tutorial is to introduce and demonstrate using a new R package - r2mlm - that automates the intensive computations involved in implementing the framework and provides accompanying graphics to visualize all multilevel R-squared measures together. We use accessible illustrations with open data and code to demonstrate how to use and interpret the R package output.

Are clean energy markets efficient? A multifractal scaling and herding behavior analysis of clean and renewable energy markets before and during the COVID19 pandemic.

The literature lacks thorough and adequate evidence of the efficiency and herding behavior of clean and renewable energy markets. Therefore, the key objective of this paper is to explore the multifractality and efficiency of six clean energy markets by applying a robust method of Multifractal detrended fluctuation analysis (MFDFA) on daily data over a lengthy period. In addition, to examine the inner dynamics of clean energy markets around the global pandemic (COVID19), the data are further divided into two sub-periods of before and during COVID19. Our sampled clean energy markets exhibit multifractal behavior with a significant impact on the efficiency and intensified presence of multifractality during the COVID19 period. Overall, TXCT and BSEGRNX were the most efficient clean energy markets, but the ranking of TXCT deteriorated significantly in the sub-periods. The presence of multifractality and herding behavior symmetry intensified during the crisis period, which gives a potential for advancing portfolio management techniques. Moreover, our study provides practical implications and new insights for various market participants for better management and understanding of risks.

Rectal gastrointestinal stromal tumor with metachronous liver metastasis demonstrated no relapse after multidisciplinary team discussion and comprehensive treatment: a case report.

Background: This study sought to explore the role and significance of multidisciplinary team (MDT) discussion and comprehensive treatment in the diagnosis and treatment of a gastrointestinal stromal tumor (GIST) with liver metastasis. For GIST patients with liver metastasis, MDT can evaluate whether the liver metastasis is resectable, so as to formulate accurate treatment goals and the best diagnosis and treatment plan. Case Description: A 53-year-old male patient with localized rectal GIST with metachronous liver metastasis (MLM) was admitted to Yunnan Cancer Hospital in October 2014. At the 1st visit, he was diagnosed with locally advanced rectal GIST, and a MDT discussion was held by departments of colorectal surgery, imaging, pathology and oncology. The tumor shrank after neoadjuvant targeted treatment with imatinib. A local resection of the rectal GIST was successfully performed via the anal approach. R0 resection was achieved and the function of the anal sphincter was preserved. Following the operation, oral imatinib treatment was discontinued after 2 years. The patient developed isolated liver metastasis 6 months later. After the MDT discussion by departments of colorectal surgery, hepatobiliary surgery, imaging, pathology, and oncology, R0 resection of the liver metastasis was achieved. After the operation, sunitinib was administered for 4.5 years. The patient's overall survival (OS) has reached 7.5 years. No tumor recurrence or metastasis was found in the re-examinations. The follow-up is ongoing. Conclusions: Targeted therapy combined with surgery is the most suitable way to cure GIST patients with liver metastasis. More importantly, the multi-disciplinary management and the standardized diagnosis and treatment of GIST patients with liver metastasis through MDT discussion can improve the quality of life and prolong the survival of patients.

Reduced P300 amplitude is consistently associated with trait anhedonia across repeated assessments.

Understanding how event-related potentials (ERPs) change following repeated assessments is critical to advance our understanding of neural mechanisms implicated in psychopathology. Specifically, it is unclear if associations between ERPs and individual differences can be reproduced when repeatedly measured within the same participants, or if clinical characteristics impact ERP trajectories over repeated assessments. The present study assessed P300 amplitude and latency from a flanker task at four time points over one month (M = 7.24 days between assessments [SD = 1.02]) in 79 female undergraduates to examine how P300 amplitude/latency changes across repeated assessments, the presence of associations between within- and between-subjects measures of current depressive symptoms and the P300, and if between-subjects depressive symptoms moderated change in P300 over repeated assessment. Results using multilevel modeling indicated a significant reduction in P300 amplitude and latency across assessments. Individuals with increased trait anhedonia (i.e., between-subjects) exhibited reduced P300 amplitudes across assessments; there were no associations of within-subjects fluctuations in anhedonia symptoms and P300 amplitude across assessments. There was also no interaction between number of assessments and between-subjects anhedonia in relation to P300 amplitude. Unlike anhedonia, between-subjects dysphoria was unrelated to P300. These results demonstrate a relatively specific and consistent association between an attenuated P300 amplitude and trait anhedonia across repeated assessments - data that may further suggest that flanker P300 amplitude reflects hedonic and motivational processes.

Parameterizing Practice in a Longitudinal Measurement Burst Design to Dissociate Retest Effects From Developmental Change: Implications for Aging Neuroscience.

Background: In longitudinal designs, the extraneous influence of retest effects can confound and obscure estimates of developmental change. The current study provides a novel approach to independently parameterize short-term retest effects and long-term developmental change estimates by leveraging a measurement burst design and three-level multilevel modeling. We further employ these short- and long-term slopes as predictors of cognitive status at long-term follow-up assessments. Methods: Participants included 304 older adults from Project MIND: a longitudinal measurement burst study assessing cognitive performance across both biweekly sessions and annual retests. Participants were classified as either Healthy controls (HC) or Cognitively Impaired, not Demented (CIND) at baseline, the final burst assessment (Year 4), and at an additional four-year follow-up (Year 8). Response time inconsistencies (RTI) were computed at each burst occasion for a simple choice response time (CRT) task and a one-back response time (BRT) task. Three-level multilevel models were employed to simultaneously examine change in RTI for both CRT and BRT across weeks within years, as well as across years, in order to dissociate within-individual retest effects (short-term) from developmental (long-term) change slopes. Individual slopes were then extracted and utilized in a series of multinomial logistic regression equations to contrast short- vs. long-term RTI change as predictors of cognitive status. Results: Separately parameterizing short- and long-term change estimates yielded distinct patterns of variation. CRT RTI remained stable across short-term weekly assessments, while significantly increasing across years. In contrast, BRT RTI decreased significantly across short-term assessments but showed no change across long-term assessments. After dissociating change estimates, short-term BRT as well as long-term CRT and BRT estimates predicted cognitive status at long-term follow-ups; increases in RTI, suggesting either an inability to benefit from retest or process-based developmental decline, were associated with an increased likelihood of being classified as CIND. Conclusions: We showcase an innovative approach to dissociate retest effects from developmental change across and within individuals. Accurately parameterizing these distinct change estimates can both reduce systematic bias in longitudinal trend estimates as well as provide a clinically useful tool by utilizing retest effects to predict cognitive health and impairment.

Machine-Learning-Based Genome-Wide Association Studies for Uncovering QTL Underlying Soybean Yield and Its Components.

A genome-wide association study (GWAS) is currently one of the most recommended approaches for discovering marker-trait associations (MTAs) for complex traits in plant species. Insufficient statistical power is a limiting factor, especially in narrow genetic basis species, that conventional GWAS methods are suffering from. Using sophisticated mathematical methods such as machine learning (ML) algorithms may address this issue and advance the implication of this valuable genetic method in applied plant-breeding programs. In this study, we evaluated the potential use of two ML algorithms, support-vector machine (SVR) and random forest (RF), in a GWAS and compared them with two conventional methods of mixed linear models (MLM) and fixed and random model circulating probability unification (FarmCPU), for identifying MTAs for soybean-yield components. In this study, important soybean-yield component traits, including the number of reproductive nodes (RNP), non-reproductive nodes (NRNP), total nodes (NP), and total pods (PP) per plant along with yield and maturity, were assessed using a panel of 227 soybean genotypes evaluated at two locations over two years (four environments). Using the SVR-mediated GWAS method, we were able to discover MTAs colocalized with previously reported quantitative trait loci (QTL) with potential causal effects on the target traits, supported by the functional annotation of candidate gene analyses. This study demonstrated the potential benefit of using sophisticated mathematical approaches, such as SVR, in a GWAS to complement conventional GWAS methods for identifying MTAs that can improve the efficiency of genomic-based soybean-breeding programs.

Performing Genome-Wide Association Studies Using rMVP.

Genome wide association study (GWAS), which is a powerful tool to detect the relationship between the traits of interest and high-density markers, has provided unprecedented insights into the genetic basis of quantitative variation for complex traits. Along with the development of high-throughput sequencing technology, both sample sizes and marker sizes are increasing rapidly, which make computations more challenging than ever. Therefore, to efficiently process big data with limited computing resources in a reasonable time and to use state-of-the-art statistical models to reduce false positive and false negative rates have always been hot topics in the domain of GWAS. In this chapter, we describe how to perform GWAS using an R package, rMVP, which includes data preparation, evaluation of population structure, association tests by different models, and high-quality visualization of GWAS results.

Identification of potential MTAs and candidate genes for juice quality- and yield-related traits in Saccharum clones: a genome-wide association and comparative genomic study.

Sugarcane is an economically important commercial crop which provides raw material for the production of sugar, jaggery, bioethanol, biomass and other by-products. Sugarcane breeding till today heavily relies on conventional breeding approaches which is time consuming, laborious and costly. Integration of marker-assisted selection (MAS) in sugarcane genetic improvement programs for difficult to select traits like sucrose content, resistance to pests and diseases and tolerance to abiotic stresses will accelerate varietal development. In the present study, association mapping approach was used to identify QTLs and genes associated with sucrose and other important yield-contributing traits. A mapping panel of 110 diverse sugarcane genotypes and 148 microsatellite primers were used for structured association mapping study. An optimal subpopulation number (ΔK) of 5 was identified by structure analysis. GWAS analysis using TASSEL identified a total of 110 MTAs which were localized into 27 QTLs by GLM and MLM (Q + K, PC + K) approaches. Among the 24 QTLs sequenced, 12 were able to identify potential candidate genes, viz., starch branching enzyme, starch synthase 4, sugar transporters and G3P-DH related to carbohydrate metabolism and hormone pathway-related genes ethylene insensitive 3-like 1, reversion to ethylene sensitive1-like, and auxin response factor associated to juice quality- and yield-related traits. Six markers, NKS 5_185, SCB 270_144, SCB 370_256, NKS 46_176 and UGSM 648_245, associated with juice quality traits and marker SMC31CUQ_304 associated with NMC were validated and identified as significantly associated to the traits by one-way ANOVA analysis. In conclusion, 24 potential QTLs identified in the present study could be used in sugarcane breeding programs after further validation in larger population. The candidate genes from carbohydrate and hormone response pathway presented in this study could be manipulated with genome editing approaches to further improve sugarcane crop.

Genetic diversity and population structure analysis for morphological traits in upland cotton (Gossypium hirsutum L.).

A total of 96 different genotypes of upland cotton (Gossypium hirsutum) were selected from the breeding material and germplasm available at CCS HAU, India, to find the novel marker-trait associations for morphological traits used for registration of variety in upland cotton. Twenty-three morphological traits of the selected genotypes were recorded in field trials conducted in two replication of randomized block design during Kharif 2018 and 2019. A total of 11 traits showed sufficient variations in the screened germplasm and the same were further used for association mapping. A total of 168 SSRs were used for genotyping, of which 97 SSRs showed polymorphism amplifying 293 different alleles with an average of 3.02 alleles per SSR. Clustering, principal component analysis, and population structure analysis advocated that the current germplasm panel has enough diversity to be considered for association mapping. A total of 20 significant marker-trait associations were identified by the mixed linear model (MLM) and compressed mixed linear model (CMLM), of which 15 were common to both models, hence considered as promising associations. To the best of our knowledge, it is a first attempt to identify the linked markers in relation to morphological traits for the cotton crop. Results of the present study will be highly useful in speeding up variety registration programmes of upland cotton complementing to Distinctiveness, Uniformity, and Stability (DUS) testing.

Exploring the genetic correlation between obesity-related traits and regional brain volumes: Evidence from UK Biobank cohort.

OBJECTIVE: To determine whether there is a correlation between obesity-related variants and regional brain volumes. METHODS: Based on a mixed linear model (MLM), we analyzed the association between 1,498 obesity-related SNPs in the GWAS Catalog and 164 regional brain volumes from 29,420 participants (discovery cohort N = 19,997, validation cohort N = 9,423) in UK Biobank. The statistically significant brain regions in association analysis were classified into 6 major neural networks (dopamine (DA) motive system, central autonomic network (CAN), cognitive emotion regulation, visual object recognition network, auditory object recognition network, and sensorimotor system). We summarized the association between obesity-related variants (metabolically healthy obesity variants, metabolically unhealthy obesity variants, and unclassified obesity-related variants) and neural networks. RESULTS: From association analysis, we determined that 17 obesity-related SNPs were associated with 51 regional brain volumes. Several single SNPs (e.g., rs13107325-T (SLC39A8), rs1876829-C (CRHR1), and rs1538170-T (CENPW)) were associated with multiple regional brain volumes. In addition, several single brain regions (e.g., the white matter, the grey matter in the putamen, subcallosal cortex, and insular cortex) were associated with multiple obesity-related variants. The metabolically healthy obesity variants were mainly associated with the regional brain volumes in the DA motive system, sensorimotor system and cognitive emotion regulation neural networks, while metabolically unhealthy obesity variants were mainly associated with regional brain volumes in the CAN and total tissue volumes. In addition, unclassified obesity-related variants were mainly associated with auditory object recognition network and total tissue volumes. The results of MeSH (medical subject headings) enrichment analysis showed that obesity genes associated with brain structure pointed to the functional relatedness with 5-Hydroxytryptamine receptor 4 (5-HT4), growth differentiation factor 5 (GDF5), and high mobility group protein AT-hook 2 (HMGA2 protein). CONCLUSION: In summary, we found that obesity-related variants were associated with different brain volume measures. On the basis of the multiple SNPs, we found that metabolically healthy and unhealthy obesity-related SNPs were associated with different brain neural networks. Based on our enrichment analysis, modifications of the 5-HT4 pathway might be a promising therapeutic strategy for obesity.

Key parameter optimization using multivariable linear model for the evaluation of the in vitro estrogenic activity assay in T47D cell lines (CXCL-test).

In comparison with analytical tools, bioassays provide higher sensitivity and more complex evaluation of environmental samples and are indispensable tools for monitoring increasing in anthropogenic pollution. Nevertheless, the disadvantage in cellular assays stems from the material variability used within the assays, and an interlaboratory adaptation does not usually lead to satisfactory test sensitivities. The aim of this study was to evaluate the influence of material variability on CXCL12 secretion by T47D cells, the outcome of the CXCL-test (estrogenic activity assay). For this purpose, the cell line sources, sera suppliers, experimental and seeding media, and the amount of cell/well were tested. The multivariable linear model (MLM), employed as an innovative approach in this field for parameter evaluation, identified that all the tested parameters had significant effects. Knowledge of the contributions of each parameter has permitted step-by-step optimization. The most beneficial approach was seeding 20,000 cells/well directly in treatment medium and using DMEM for the treatment. Great differences in both basal and maximal cytokine secretions among the three tested cell lines and different impacts of each serum were also observed. Altogether, both these biologically based and highly variable inputs were additionally assessed by MLM and a subsequent two-step evaluation, which revealed a lower variability and satisfactory reproducibility of the test. This analysis showed that not only parameter and procedure optimization but also the evaluation methodology must be considered from the perspective of interlaboratory method adaptation. This overall methodology could be applied to all bioanalytical methods for fast multiparameter and accurate analysis.