Miracle-dz/UniFAR-FTUs huggingface dataset:
Genomic prediction of optimal cross combinations to accelerate genetic improvement of soybean (Glycine max)

Improving yield is a primary soybean breeding goal, as yield is the main determinant of soybean’s profitability. Within the breeding process, selection of cross combinations is one of most important elements. Cross prediction will assist soybean breeders in identifying the best cross combinations among parental genotypes prior to crossing, increasing genetic gain and breeding efficiency. In this study optimal cross selection methods were created and applied in soybean and validated using historical data from the University of Georgia soybean breeding program, under multiple training set compositions and marker densities utilizing multiple genomic selection models for marker evaluation. Plant materials consisted of 702 advanced breeding lines evaluated in multiple environments and genotyped using SoySNP6k BeadChips. An additional marker set, the SoySNP3k marker set, was tested in this study as well. Optimal cross selection methods were used to predict the yield of 42 previously made crosses and compared to the performance of the cross’s offspring in replicated field trials. The best prediction accuracy was obtained when using Extended Genomic BLUP with the SoySNP6k marker set, consisting of 3,762 polymorphic markers, with an accuracy of 0.56 with a training set maximally related to the crosses predicted and 0.4 in a training set with minimized relatedness to predicted crosses. Prediction accuracy was most significantly impacted by training set relatedness to the predicted crosses, marker density, and the genomic model used to predict marker effects. The usefulness criterion selected had an impact on prediction accuracy within training sets with low relatedness to the crosses predicted. Optimal cross prediction provides a useful method that assists plant breeders in selecting crosses in soybean breeding.
Mnemonic representations in human lateral geniculate nucleus

There is a growing appreciation for the role of the thalamus in high-level cognition. Motivated by findings that internal cognitive state drives activity in feedback layers of primary visual cortex (V1) that target the lateral geniculate nucleus (LGN), we investigated the role of LGN in working memory (WM). Specifically, we leveraged model-based neuroimaging approaches to test the hypothesis that human LGN encodes information about spatial locations temporarily encoded in WM. First, we localized and derived a detailed topographic organization in LGN that accords well with previous findings in humans and non-human primates. Next, we used models constructed on the spatial preferences of LGN populations in order to reconstruct spatial locations stored in WM as subjects performed modified memory-guided saccade tasks. We found that population LGN activity faithfully encoded the spatial locations held in memory in all subjects. Importantly, our tasks and models allowed us to dissociate the locations of retinal stimulation and the motor metrics of memory-guided saccades from the maintained spatial locations, thus confirming that human LGN represents true WM information. These findings add LGN to the growing list of subcortical regions involved in WM, and suggest a key pathway by which memories may influence incoming processing at the earliest levels of the visual hierarchy.
Skin aging from mechanisms to interventions: focusing on dermal aging

Skin aging is a multifaceted process that involves intrinsic and extrinsic mechanisms that lead to various structural and physiological changes in the skin. Intrinsic aging is associated with programmed aging and cellular senescence, which are caused by endogenous oxidative stress and cellular damage. Extrinsic aging is the result of environmental factors, such as ultraviolet (UV) radiation and pollution, and leads to the production of reactive oxygen species, ultimately causing DNA damage and cellular dysfunction. In aged skin, senescent cells accumulate and contribute to the degradation of the extracellular matrix, which further contributes to the aging process. To combat the symptoms of aging, various topical agents and clinical procedures such as chemical peels, injectables, and energy-based devices have been developed. These procedures address different symptoms of aging, but to devise an effective anti-aging treatment protocol, it is essential to thoroughly understand the mechanisms of skin aging. This review provides an overview of the mechanisms of skin aging and their significance in the development of anti-aging treatments.
A novel risk classifier to predict the in-hospital death risk of nosocomial infections in elderly cancer patients

Background Elderly cancer patients are more predisposed to developing nosocomial infections during anti-neoplastic treatment, and are associated with a bleaker prognosis. This study aimed to develop a novel risk classifier to predict the in-hospital death risk of nosocomial infections in this population. Methods Retrospective clinical data were collected from a National Cancer Regional Center in Northwest China. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was utilized to filter the optimal variables for model development and avoid model overfitting. Logistic regression analysis was performed to identify the independent predictors of the in-hospital death risk. A nomogram was then developed to predict the in-hospital death risk of each participant. The performance of the nomogram was evaluated using receiver operating characteristics (ROC) curve, calibration curve, and decision curve analysis (DCA). Results A total of 569 elderly cancer patients were included in this study, and the estimated in-hospital mortality rate was 13.9%. The results of multivariate logistic regression analysis showed that ECOG-PS (odds ratio [OR]: 4.41, 95% confidence interval [CI]: 1.95-9.99), surgery type (OR: 0.18, 95%CI: 0.04-0.85), septic shock (OR: 5.92, 95%CI: 2.43-14.44), length of antibiotics treatment (OR: 0.21, 95%CI: 0.09-0.50), and prognostic nutritional index (PNI) (OR: 0.14, 95%CI: 0.06-0.33) were independent predictors of the in-hospital death risk of nosocomial infections in elderly cancer patients. A nomogram was then constructed to achieve personalized in-hospital death risk prediction. ROC curves yield excellent discrimination ability in the training (area under the curve [AUC]=0.882) and validation (AUC=0.825) cohorts. Additionally, the nomogram showed good calibration ability and net clinical benefit in both cohorts. Conclusion Nosocomial infections are a common and potentially fatal complication in elderly cancer patients. Clinical characteristics and infection types can vary among different age groups. The risk classifier developed in this study could accurately predict the in-hospital death risk for these patients, providing an important tool for personalized risk assessment and clinical decision-making.
Modeling semiconducting silicene nanostrips: electronics and THz plasmons

Silicene nanostrips (SiNSs) have garnered significant attention due to their remarkable physical properties, making them an ideal candidate for numerous electronics and plasmonics applications. Their compatibility with current semiconductor technology further enhances their potential. This study aims to investigate the electronic and plasmonic properties of SiNSs with a minimum width of 100 nm using a semi-analytical model that utilizes the carrier velocity of silicene. The carrier velocity was calculated using density functional computations and refined through the GW approximation. Our results reveal that SiNSs with widths ranging from 100 to 500 nm exhibit small bandgaps within the range of a few meV, specifically ranging from 30 to 6 meV, respectively. Furthermore, all the nanostrips analyzed in this study exhibit a q -like plasmon dispersion within the THz regime ( ≤ 35 THz). By varying the experimental setup or the geometric factors of the nanostrips, the associated plasmon THz frequency can be manipulated, resulting in an increase or decrease in frequency or a shift to larger momentum values. Our study serves as a fundamental starting point and a source of inspiration for future experiments, providing a foundation for confirming the results presented in this study.
Post deposition annealing effect on properties of CdS films and its impact on CdS/Sb2Se3 solar cells performance

Antimony selenide (Sb2Se3) is one of the emerging photovoltaic absorber materials possessing abundance and non-toxicity as the main attributes. Following CdTe technology, CdS is a widely used partner layer for Sb2Se3 solar cells. Related to CdS/Sb2Se3 device configuration, a number of studies reported findings and challenges regarding the intermixing phenomenon at the main interface and suitability of various annealing for CdS (and related interface) and still, significant room remains in developing strategies for interface optimization and understanding of the physiochemistry behind. In this perspective, this work provides a systematic investigation of the effect of vacuum and air annealing at temperatures between 200 and 400°C on the properties of CdS deposited by chemical bath deposition and combined with Sb2Se3 absorber obtained by close-spaced sublimation the direct impact of the CdS annealing on the device performance is illustrated. It is found that by varying the annealing temperature from 200 to 400°C in both, vacuum and air ambient, the morphology of CdS changes from highly dispersed small grain structure to sintered dense grains, the band gap decreases from 2.43 to 2.35 eV and the electron density drops from ∼1018 to ∼1011 cm−3. These changes were correlated with the changes in the CdS lattice and connected with the mobility of the OH group and the presence of secondary phases in CdS layers. 200°C air annealing of CdS was found as an optimal treatment resulting in 2.8% Sb2Se3/CdS cell efficiency - a 60% boost compared to the 1.8% performance of the device with as-deposited CdS. Material and device characterization analysis is performed, providing complementary insights on the interrelation between the physicochemical mechanism of the CdS annealing processes and device functionality.
Hyaluronan regulates sperm-induced inflammatory response by enhancing sperm attachment to bovine endometrial epithelial cells via CD44: in-silico and in-vitro approaches

Recently, we reported that sperm induce cluster of differentiation 44 (CD44) expression and Toll-like receptor 2 (TLR2)-mediated inflammatory response in bovine uterus. In the present study, we hypothesized that the interaction between CD44 of bovine endometrial epithelial cells (BEECs) and hyaluronan (HA) affects sperm attachment and thereby enhancing TLR2-mediated inflammation. To test our hypothesis, at first, in-silico approaches were employed to define the binding affinity of HA for CD44 and TLR2. Further, an in-vitro experiment using the sperm-BEECs co-culture model was applied to investigate the effect of HA on sperm attachment and inflammatory response. Here, low molecular weight (LMW) HA at different concentrations (0, 0.1, 1, or 10 µg/mL) was incubated with BEECs for 2 h followed by the co-culture without- or with non-capacitated washed sperm (106/ml) for additional 3 h was performed. The present in-silico model clarified that CD44 is a high-affinity receptor for HA. Moreover, TLR2 interactions with HA oligomer (4- and 8-mers) target a different subdomain (h-bonds) compared to TLR2-agonist (PAM3) which targets a central hydrophobic pocket. However, the interaction of LMW HA (32-mers) with TLR2 revealed no stability of HA at any pocket of TLR2. Notably, the immunofluorescence analysis revealed the HA localization in both endometrial stroma and epithelia of ex-vivo endometrial explant. Moreover, ELISA showed significant levels of HA in BEECs culture media. Importantly, BEECs pretreatment with HA prior to sperm exposure increased the number of attached sperm to BEECs, and upregulated the transcriptional levels of pro-inflammatory genes (TNFA, IL-1B, IL-8, and PGES) in BEECs in response to sperm. However, BEECs treated with HA only (no sperm exposure) did not show any significant effect on the transcript abundance of pro-inflammatory genes when compared to the non-treated BEECs. Altogether, our findings strongly suggest a possible cross-talk between sperm and endometrial epithelial cells via HA and HA binding receptors (CD44 and TLR2) to induce a pro-inflammatory response in bovine uterus.
Integration analysis of tumor metagenome and peripheral immunity data of diffuse large-B cell lymphoma

Background/purpose It has been demonstrated that gut microbes are closely associated with the pathogenesis of lymphoma, but the gut microbe landscape and its association with immune cells in diffuse large B-cell lymphoma (DLBCL) remain largely unknown. In this study, we explored the associations between gut microbiota, clinical features and peripheral blood immune cell subtypes in DLBCL. Method A total of 87 newly diagnosed DLBCL adults were enrolled in this study. The peripheral blood samples were collected from all patients and then submitted to immune cell subtyping using full-spectral flow cytometry. Metagenomic sequencing was applied to assess the microbiota landscape of 69 of 87 newly diagnosed DLBCL patients. The microbiotas and peripheral blood immune cell subsets with significant differences between different National Comprehensive Center Network-International Prognostic Indexes (NCCN-IPIs) (low-risk, low-intermediate-risk, intermediate-high-risk, high-risk) groups were screened. Results A total of 10 bacterial phyla, 31 orders and 455 bacteria species were identified in 69 patients with newly diagnosed DLBCL. The abundances of 6 bacteria, including Blautia sp.CAG 257, Actinomyces sp.S6 Spd3, Streptococcus parasanguinis, Bacteroides salyersiae, Enterococcus faecalls and Streptococcus salivarius were significantly different between the low-risk, low-intermediate-risk, intermediate-high-risk and high-risk groups, among which Streptococcus parasanguinis and Streptococcus salivarius were markedly accumulated in the high-risk group. The different bacteria species were mostly enriched in the Pyridoxal 5’-phosphate biosynthesis I pathway. In addition, we found that 2 of the 6 bacteria showed close associations with the different immune cell subtypes which were also identified from different NCCN-IPIs. In detail, the abundance of Bacteroides salyersiae was negatively correlated with Treg cells, CD38+ nonrescue exhausted T cells, nature killer 3 cells and CD38+CD8+ effector memory T cells, while the abundance of Streptococcus parasanguinis was negatively correlated with HLA-DR+ NK cells, CD4+ Treg cells, HLA-DR+ NKT cells and HLA-DR+CD94+CD159c+ NKT cells. Conclusion This study first reveals the gut microbiota landscape of patients with newly diagnosed DLBCL and highlights the association between the gut microbiota and immunity, which may provide a new idea for the prognosis assessment and treatment of DLBCL.
Evolutionary pathways for deep-sea adaptation in marine planktonic Actinobacteriota

The deep ocean, one of the largest ecosystems on earth, is dominated by microorganisms that are keystones in the regulation of biogeochemical cycles. However, the evolutionary pathways underlying the specific adaptations required (e.g., high pressure and low temperature) by this unique niche remain understudied. Here, we analyzed the first representatives belonging to the order Acidimicrobiales, a group of marine planktonic Actinobacteriota, that specifically inhabits the aphotic zone of the oceanic water column (>200 m). Compared with their epipelagic counterparts, deep-sea representatives showed the same evolution in genome architecture with higher GC content, longer intergenic spaces as well as higher nitrogen (N-ARSC) and lower carbon (C-ARSC) content in encoded amino acid residue side chains consistent with the higher nitrogen concentration and lower carbon concentration in deep waters compared to the photic zone. Metagenomic recruitment showed distribution patterns that allowed the description of different ecogenomic units within the three deep water-associated genera defined by our phylogenomic analyses (UBA3125, S20-B6 and UBA9410). The entire genus UBA3125 was found exclusively associated with oxygen minimum zones linked to the acquisition of genes involved in denitrification. Genomospecies of genus S20-B6 recruited in samples from both mesopelagic (200–1,000 m) and bathypelagic (1000–4,000 m) zones, including polar regions. Diversity in the genus UBA9410 was higher, with genomospecies widely distributed in temperate zones, others in polar regions, and the only genomospecies associated with abyssal zones (>4,000 m). At the functional level, groups beyond the epipelagic zone have a more complex transcriptional regulation including in their genomes a unique WhiB paralog. In addition, they showed higher metabolic potential for organic carbon and carbohydrate degradation as well as the ability to accumulate glycogen as a source of carbon and energy. This could compensate for energy metabolism in the absence of rhodopsins, which is only present in genomes associated with the photic zone. The abundance in deep samples of cytochrome P450 monooxygenases associated with the genomes of this order suggests an important role in remineralization of recalcitrant compounds throughout the water column.
Microwave-assisted biosynthesis of nano silver and its synergistic antifungal activity against Curvularia lunata

It is necessary to explore eco-friendly antimicrobial agents to resolve problems such as pathogen resistance and pesticide residues. In this study, Mentha haplocalyx leaf extract was applied to biosynthesize nano silver using a microwave-assisted method. The detailed properties of the nano silver were systematically revealed by several analytical methods. The antifungal activity of nano silver and synergistic antifungal effects of nano silver conjugated with pesticides against Curvularia lunata were determined. Pathogen invasion was significantly inhibited (57.3%) on detached and intravital maize leaves when the concentration of nano silver was 200 μg mL−1, with an inhibition zone diameter of 12.5 ± 1.18 mm. In addition, a clear synergistic antifungal effect of nano silver conjugated with epoxiconazole was observed at volume ratios of 8:2 and 9:1, while the toxicity ratios were 1.18 and 1.11, respectively. These results not only provide a new avenue for pathogen management, but also enable reduced dosages of antibiotics and pesticides to mitigate or avoid emergence of drug-resistant pathogens.
Linking cortex and contraction—Integrating models along the corticomuscular pathway

Computational models of the neuromusculoskeletal system provide a deterministic approach to investigate input-output relationships in the human motor system. Neuromusculoskeletal models are typically used to estimate muscle activations and forces that are consistent with observed motion under healthy and pathological conditions. However, many movement pathologies originate in the brain, including stroke, cerebral palsy, and Parkinson’s disease, while most neuromusculoskeletal models deal exclusively with the peripheral nervous system and do not incorporate models of the motor cortex, cerebellum, or spinal cord. An integrated understanding of motor control is necessary to reveal underlying neural-input and motor-output relationships. To facilitate the development of integrated corticomuscular motor pathway models, we provide an overview of the neuromusculoskeletal modelling landscape with a focus on integrating computational models of the motor cortex, spinal cord circuitry, α-motoneurons and skeletal muscle in regard to their role in generating voluntary muscle contraction. Further, we highlight the challenges and opportunities associated with an integrated corticomuscular pathway model, such as challenges in defining neuron connectivities, modelling standardisation, and opportunities in applying models to study emergent behaviour. Integrated corticomuscular pathway models have applications in brain-machine-interaction, education, and our understanding of neurological disease.
T cell immunity following COVID-19 vaccination in adult patients with primary antibody deficiency – a 22-month follow-up

Primary antibody deficiencies, such as common variable immunodeficiency (CVID), are heterogenous disease entities consisting of primary hypogammaglobulinemia and impaired antibody responses to vaccination and natural infection. CVID is the most common primary immunodeficiency in adults, presenting with recurrent bacterial infections, enteropathy, autoimmune disorders, interstitial lung diseases and increased risk of malignancies. Patients with CVID are recommended to be vaccinated against SARS-CoV-2, but there are relatively few studies investigating humoral and cellular responses to immunization. We studied the dynamics of humoral and cell-mediated immunity responses up to 22 months in 28 patients with primary immunodeficiency and three patients with secondary immunodeficiency receiving ChAdOx1, BNT162b2 and mRNA-1273 COVID-19 vaccines. Despite inadequate humoral response to immunization, we demonstrate a robust T cell activation likely protecting from severe COVID-19.
The role of fibroblast growth factor 18 in cancers: functions and signaling pathways

Fibroblast growth factor 18(FGF18) is a member of the fibroblast growth factor family (FGFs). FGF18 is a class of bioactive substances that can conduct biological signals, regulate cell growth, participate in tissue repair and other functions, and can promote the occurrence and development of different types of malignant tumors through various mechanisms. In this review, we focus on recent studies of FGF18 in the diagnosis, treatment, and prognosis of tumors in digestive, reproductive, urinary, respiratory, motor, and pediatric systems. These findings suggest that FGF18 may play an increasingly important role in the clinical evaluation of these malignancies. Overall, FGF18 can function as an important oncogene at different gene and protein levels, and can be used as a potential new therapeutic target and prognostic biomarker for these tumors.