Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Alternative Splicing-Specific Knockdown of Tjp1 α+ by Rbm47 on Tight Junctions Assembly during Blastocyst Development

Tjp1 α+ is considered a crucial protein involved in the stepwise assembly of tight junctions (TJs) between compaction and blastocoel cavitation in early development. In this study, we investigated the specific role of Tjp1 α+ in TJ formation by employing an alternative splicing-specific knockdown of the Tjp1 α+ exon. To deplete Tjp1 α+ expression, we used siRNA targeting RNA-binding protein 47 (Rbm47), which induces the inclusion of the α+ exon in Tjp1 mRNA. The knockdown resulted in approximately 85% reduction in Rbm47 mRNA levels and 75% reduction in Tjp1 α+ mRNA levels in blastocysts. Surprisingly, despite this knockdown, blastocyst development and TJ permeability of trophectoderm were unaffected. Additionally, we observed an interaction between Tjp1 α- and Ocln in Rbm47 knockdown blastocysts, suggesting a compensatory role of Tjp1 α-. Overall, our findings indicate that Tjp1 α+ is not essential for the stepwise assembly of TJs and the completion of TJ biogenesis during blastocyst development in mice although a minimal amount of remaining Tjp1 α+ is sufficient for TJs assembly. Summary statement Selective loss of Tjp1 α+ mediated by Rbm47 knockdown did affect mouse blastocyst development, suggesting that Tjp1 α+ may not be crucial for stepwise TJs assembly during blastocyst development
Protective intravenous BCG vaccination induces enhanced immune signaling in the airways

Intradermal (ID) Bacillus Calmette–Guérin (BCG) is the most widely administered vaccine in the world. However, ID-BCG fails to achieve the level of protection needed in adults to alter the course of the tuberculosis epidemic. Recent studies in non-human primates have demonstrated high levels of protection against Mycobacterium tuberculosis (Mtb) following intravenous (IV) administration of BCG. However, the protective immune features that emerge following IV BCG vaccination remain incompletely defined. Here we used single-cell RNA-sequencing (scRNAseq) to transcriptionally profile 157,114 unstimulated and purified protein derivative (PPD)-stimulated bronchoalveolar lavage (BAL) cells from 29 rhesus macaques immunized with BCG across routes of administration and doses to uncover cell composition-, gene expression-, and biological network-level signatures associated with IV BCG-mediated protection. Our analyses revealed that high-dose IV BCG drove an influx of polyfunctional T cells and macrophages into the airways. These macrophages exhibited a basal activation phenotype even in the absence of PPD-stimulation, defined in part by IFN and TNF-α signaling up to 6 months following BCG immunization. Furthermore, intercellular immune signaling pathways between key myeloid and T cell subsets were enhanced following PPD-stimulation in high-dose IV BCG-vaccinated macaques. High-dose IV BCG also engendered quantitatively and qualitatively stronger transcriptional responses to PPD-stimulation, with a robust Th1-Th17 transcriptional phenotype in T cells, and augmented transcriptional signatures of reactive oxygen species production, hypoxia, and IFN-γ response within alveolar macrophages. Collectively, this work supports that IV BCG immunization creates a unique cellular ecosystem in the airways, which primes and enables local myeloid cells to effectively clear Mtb upon challenge.
Assessing generalizability of a dengue classifier across multiple datasets

Background Early diagnosis of dengue fever is important for individual treatment and monitoring disease prevalence in the population. To assist diagnosis, previous studies have proposed classification models to detect dengue from symptoms and clinical measurements. However, there has been little exploration of whether existing models can be used to make predictions for new populations. Methods We trained logistic regression models on five publicly available dengue datasets from previous studies, using three explanatory variables identified as important in prior work: age, white blood cell count, and platelet count. These five datasets were collected at different times in different locations, with a variety of disease rates and patient ages. A model was trained on each dataset, and predictive performance was evaluated on both the original (training) dataset, and the other (test) datasets from different studies. Results In-sample area under the receiver operating characteristic curve (AUC) values for the logistic regression models ranged from 0.74 to 0.89, while out-of-sample AUCs ranged from 0.55 to 0.89. Matching age ranges in training/test datasets increased AUC values and balanced the sensitivity and specificity. Adjusting the predicted probabilities to account for differences in dengue prevalence improved calibration in 20/28 training-test pairs. Conclusions The in-sample performance of the logistic regression model was consistent with previous dengue classifiers, suggesting the chosen model is a good choice in a variety of settings and has decent overall performance. However, adjustments are required to make predictions on new datasets. Practitioners can use existing dengue classifiers in new settings but should be careful with different patient ages and disease rates. Author summary Dengue fever is an acute mosquito-borne infection with a substantial and growing disease burden. Early diagnosis of dengue fever is important for treatment and disease monitoring, but gold-standard tests are not always readily available. To supplement diagnostic tests, previous studies have investigated the use of classifiers trained on common diagnostic measurements such as symptoms, blood work, and demographic variables. However, comparisons of existing methods are limited, and in particular there has been little exploration of whether existing models can be used to make predictions for new populations. Generalizability of existing models to new settings could save the substantial time and effort required to collect new data and fit a model, but this generalizability may be limited by differences between populations. In this study, we assess performance of logistic regression models on five publicly available dengue datasets from previous studies, using three explanatory variables identified as important in prior work: age, white blood cell count, and platelet count. Our results show that it can be possible for practitioners to use existing models in new settings, but care is needed to account for differences in patient demographics and dengue prevalence.
Chronic warming and dry soils limit carbon uptake and growth despite a longer growing season in beech and oak

Progressively warmer and drier conditions impact tree phenology and carbon cycling with large consequences for forest carbon balance. However, it remains unclear how individual impacts of warming and drier soils differ from their combined one and how species interactions modulate tree responses. Using mesocosms, we assessed the multi-year impact of continuous air warming and lower soil moisture acting alone or combined on phenology, leaf-level photosynthesis, non-structural carbohydrate concentrations, and aboveground growth of young European beech and Downy oak trees. We further tested how species interactions (monocultures vs. mixtures) modulated these effects. Warming prolonged the growing season of both species but reduced growth for oak. In contrast, lower moisture did not impact phenology but reduced trees’ assimilation and growth for both species. Combined impacts of warming and drier soils did not differ from single ones. Performances of both species in the mixtures were enhanced compared to the monocultures under extreme conditions. Our work revealed that higher temperature and lower soil moisture have contrasting impacts on phenology vs. leaf-level assimilation and growth, with the former being driven by temperature and the latter by moisture. Furthermore, we show a compensation of the negative impacts of extreme events by tree species interactions.
Host-microbiota interactions contributing to the heterogeneous tumor microenvironment in colorectal cancer

Background Colorectal cancer (CRC) is a highly heterogeneous cancer with four consensus molecular subtypes (CMSs) characterized by distinct tumor microenvironment (TME). We aimed to depict the characteristics of host-microbiota interactions and their contributions to TME in each CMS. Methods Host transcriptome and intratumoral microbiome profiles of 594 CRC samples were derived from RNA-Seq data from TCGA. Differential host genes and microbes among CMSs were identified. Immune microenvironments were assessed by CIBERSORTx and ESTIMATE and microbial co-abundance analyses were performed by FastSpar. Host-microbiota associations were evaluated by LASSO penalized regression in each CMS. Results Along with distinct host gene signatures, including ferroptosis-related genes and immune microenvironments, 293, 153, 66 and 109 intratumoral differential microbial genera were identified within each of the four CMSs, respectively. Furthermore, the host-microbiota interactions contributed to distinct TME in each CMS, represented by 829, 1,270, 634 and 1,882 robust gene-microbe associations, respectively. The TME in CMS1 was featured with inflammation-related HSF1 activation and interactions between genes of endothelin pathway and Flammeovirga. Integrins-related genes positively correlated with Sutterella in CMS2 while CMS3 displayed microbial associations with biosynthetic and metabolic pathways. Genes in collagens biosynthesis positively correlated with Sutterella, contributing to homeostasis disturbance in CMS4. Besides, ferroptosis dysregulation was more remarkable in immune-high subtypes, which might partly result from the colonization of tissue microbes. Conclusions We systematically profiled the landscapes of TME, of each CMS in CRC, encompassing host genes, intratumoral microbiome and their interactions, which could illuminate novel mechanisms for the heterogeneity in CRC and potential therapeutic targets.
Dynamical properties of self-sustained and driven neural networks

In the awake brain, cerebral cortex displays asynchronous-irregular (AI) states, where neurons fire irregularly and with low correlation. Neural networks can display AI states that are self-sustained through recurrent connections, or in some cases, need an external input to sustain activity. In this paper, we aim at comparing these two dynamics and their consequences on responsiveness. We first show that the first Lyapunov exponent (FLE) can differ between self-sustained and driven networks, the former displaying a higher FLE than the late. Next, we show that this impact the dynamics of the system, leading to a tendency for self-sustained networks to be more responsive, both properties that can also be captured by mean-field models. We conclude that there is a dynamical and excitability difference between the two types of networks besides their apparent similar collective firing. The model predicts that calculating FLE from population activities in experimental data could provide a way to identify if real neural networks are self-sustained or driven.
Biologically meaningful regulatory logic enhances the convergence rate in Boolean networks and bushiness of their state transition graph

Boolean network (BN) models of gene regulatory networks (GRNs) have gained widespread traction as they can easily recapitulate cellular phenotypes via their attractor states. The overall dynamics of such models are embodied in the system’s state transition graph (STG) which is highly informative. Indeed, even if two BN models have the same network structure and recover the same attractors, their STGs can be drastically different depending on the type of regulatory logic rules or Boolean functions (BFs) employed. A key objective of the present work is to systematically delineate the effects of different classes of regulatory logic rules on the structural features of the STG of reconstructed Boolean GRNs, while keeping BN structure and biological attractors fixed. Furthermore, we ask how such global features might be driven by characteristics of the underlying BFs. For that, we draw from ideas and concepts proposed in cellular automata for both the structural features and their associated proxies. We use the network of 10 reconstructed Boolean GRNs to generate ensembles that differ in the type of logic used while keeping their structure fixed and recovering their biological attractors, and compute quantities associated with the structural features of the STG: ‘bushiness’ and ‘convergence’, that are based on the number of garden-of-Eden (GoE) states and transient times to reach attractor states when originating at them. We find that ensembles employing biologically meaningful BFs have higher ‘bushiness’ and ‘convergence’ than those employing random ones. Computing these ‘global’ measures gets expensive with larger network sizes, stressing the need for more feasible proxies. We thus adapt Wuensche’s Z-parameter to BFs in BNs and provide 4 natural variants, which along with the network sensitivity, comprise our descriptors of local dynamics. One variant of the network Z-parameter as well as the network sensitivity correlate particularly very well with the bushiness, serving as a good proxy for the same. Finally, we provide an excellent proxy for the ‘convergence’ based on computing transient lengths originating at random states rather than GoE states.
Ordinary differential equations of probability functions of convoluted distributions

Convolution is the sum of independent and identically distributed random variables. Derivatives of the probability density function (PDF) of probability distribution often lead to the construction of ordinary differential equation whose solution is the PDF of the given distribution. Little have been done to extend the construction of the ODE to the PDF, quantile function (QF), survival function (SF), hazard function (HF) and the reversed hazard function (RHF) of convoluted probability distributions. In this paper, three probability distributions were considered namely: Constant parameter convoluted exponential distribution (CPCED), convoluted uniform exponential distribution (CUED) and different parameter convoluted exponential distribution (DPCED). First order ordinary differential equations whose solutions were the PDF, SF, HF and RHF for the probability functions of CPCED by the use of differential calculus. The case of the QF was second order nonlinear differential equations obtained by the use of Quantile Mechanics. Similarly, the same was obtained for CUED for the two cases of the distribution. Some new relationships were obtained for the PDF, SF and HF, and also the RHF, PDF and CDF with their corresponding first derivatives. The difficulty of obtaining the ODE for the probability functions of the DPCED was due to the different parameters that characterize the distribution. The use of partial different equations is not an alternate because the distribution has only one independent variable.
Yukawa Unified GUTs in the era of the Large Hadron Collider

We analyze the consequences of gauge and third family Yukawa coupling unification for the Large Hadron Collider. We perform a global χ2 analysis including many experimental observables to determine model parameters that yield good fits to all the observables considered. We explore the consequences of the GUT scale supersymmetric boundary conditions, particularly of non-universal gaugino masses, on the low energy phenomenology. We analyze a complete three-family model with an additional family symmetry as well as a third-family model to focus on the consequences of the boundary conditions on the SUSY spectrum. We show that good fits suggest an upper bound on the gluino mass, . 2 TeV. This constraint comes predominantly from fitting the bottom-quark and Higgs masses. We therefore focus on the gluino phenomenology in these models. We determine the lower bound on the gluino mass in the models discussed here, using the most recent published data from the CMS and ATLAS collaborations of the LHC and compare this bound with similar bounds obtained using simplified models. We present the triangular visualization method and show that the (re)interpretation of the LHC data on triangles allows the extraction of accurate exclusion limits for a multitude of more realistic models with arbitrary decay branching ratios. We find that the lower bound on the gluino mass in Yukawa-unified SO(10) SUSY GUTs is generically about 1.2 TeV at the 1σ level, unless there is considerable degeneracy between the gluino and the lightest supersymmetric particle, in which case the bounds are much weaker.
Boundedness of classical solutions for a chemotaxis system with general sensitivity function

ABSTRACT This paper deals with the chemotaxis system with general sensitivity function: under homogeneous Neumann boundary conditions in a bounded domain with smooth boundary. Here, and the initial function and the sensitivity function satisfy: We prove that the classical solutions to the above system are uniformly in-time-bounded provided that there exists a smooth positive function such that for some and the following differential inequality holds where and is bounded from above. We also present our results for the special case with and These results coincide with the results obtained by Fujie et al. [Math Methods Appl Sci. 2015] in the case of and extend their results in the case of .
Identification and Characterization of Pseudomonas aeruginosa 16S rRNA Gene Isolated from Contaminated Soil With Oil Residues

Pseudomonas aeruginosa was isolated from fifty soil samples were collected from different sites of contaminated soil with oil residues in Ministry of science& technology. Morphological, biochemical tests and 16S rRNA genes sequencing was performed for bacterial isolates identification. Thirty (30) isolates of P. aeruginosa bacteria were confirmed according to morphological, biochemical tests. For molecular analysis, all isolates that tested positive for P. aeruginosa underwent amplification of the 16S rRNA gene using previously described primers that amplified a particular DNA fragment of 956 bp. PCR product was delivered to Macrogen Corporation - Korea for Sanger sequencing utilizing an automated DNA sequencer called the ABI3730XL. The results were emailed to us, and we used geneious software to analyze them. The investigation of phylogenetic relationships between different strains of Pseudomonas aeruginosa has frequently been conducted on the sequencing of the 16S rRNA gene region, which is a viable technique for species identification. To determine the degree of genetic similarity between the organisms, a distance tree was built. Consequently, gene sequencing of the 16S rRNA region was an appropriate method for isolating isolates at the molecular level. The a novel local strain of Ps. aeruginosa which isolated from contaminated soil with oil residues samples (MSZ. IRQ20) and we will registration of isolate in GenBank under accession number of MT832126.1. Distance Tree Using Blast Tool in the Geneious software.
Effect of Jelly and Planting Depths on the Traits of Two Barley Verities

A field experiment was conducted in two separated environments in Nineveh Governorate, northern Iraq: the first in Telkef district and the second in Mosul district. Each experiment featured the growing of two barley varieties (Var) [Local black (LB) and Local white (LW)] at different sowing depths (SD) (4 and 8 cm), as well as the addition of three levels of hydrogel (HL) (0, 100, and 200) kg.ha-1. Traits studies: plant height (PH), leaf area of the flag (LAF), spike length (SL), Spike No. m2 (NS.m2), Number of grains/spike (NG/S), 1000 weight grains (1000WG), Biological yield (BY), Straw yield (SY), Grain yield (GY), Harvest index (HI). The results indicated that the (LB) variety superiority the (LW) variety in characteristics of (SL), (NS/m2) and (GY), whereas the local white variety superiority it in characteristics of (LAF), (NG/S) and (GY) in both sites. The (SD) show that the depth (8 cm) was superior in the traits of (PH), (NS/m2), (BY), (SY) and (GY), while the depth (4 cm) was significantly superior in the trait of (1000WG) for the two experimental sites. For the two experimental sites, the treatment of adding (200 kg.ha-1) of hydrogel was superior in characteristics (LAF), (NS/m2), (NG/S), (1000WG), (BY), (SY), (GY) and (HI). The majority of the binary and triple interactions revealed substantial differences between them and for the majority of the attributes investigated, as well as for both locations.
Impact of Hydrogel and Its Relationship to Yield, some of Its Components and Grain Quality of Bread Wheat Genotypes (Triticum aestivum L.)

This study was conducted in two separate experiments, the first one was under conditions of irrigation water shortage and the second when irrigation water was sufficient to evaluate and determine the effect of Hydrogel on fifteen different genotypes of bread wheat and to identify the most superior varieties in terms of vegetative growth and yield of wheat, The grains of the genotypes were planted at the Sayada site - Agricultural Research and Experiment Station of the College of Agriculture - University of Kirkuk (longitude 44.42 0 east and latitude 35.16 0 north). For the season (2021-2022) using a randomized complete block design (R.C.B.D) with a split plot system, the two experiments included three sectors, and each sector included two main plots with addition of Hydrogel (A1) and without the addition of Hydrogel (A0), and each secondary plot contained (15) genotypes of different from soft bread wheat, the cultivars were planted in four lines with a length of (3) m, and the distance between one line and other was (0.25) m. The characteristics of the total number of tillers were studied. m-2, the height of the plant (cm), the area of the flag leaf (cm2), the number of days from sowing to 50% flowering (day), and the grain yield in a ton. and- The biological yield. A meta-analysis was carried out and the results were summarized by the superiority of irrigation water sufficiency over the lack of irrigation water, and all cultivars excelled when adding hydrogel over non adding hydrogel for all the studied characteristics. this explained that the effect of the hydrogel in storing and retaining water in a way that guarantees the actual need of the crop and achieves its sufficiency, As it was shown that the cultivar summer 2 was superior in terms of the number of spikes over all cultivars, with a rate of (431.4 spikes.m2-), and the cultivar Clar 1, according to the number of grains per spike, with a rate of (67.27) grains. spike-1, the Sulimany 2 variety excelled in terms of weight of 1000 grains, with an average of (57.43) g, and the Clar 1 variety excelled, with the highest average grain yield of (3.86) tons. h-1. And the lowest cultivar had the highest rate of the specific weight of the grain, which reached (80.35) kg. h-1 and Aras cultivar as a percentage of protein was (12.63) %.