A Unified Single-stage Learning Model for Estimating Fiber Orientation Distribution Functions on Heterogeneous Multi-shell Diffusion-weighted MRI

Diffusion-weighted (DW) MRI measures the direction and scale of the local diffusion process in every voxel through its spectrum in q-space, typically acquired in one or more shells. Recent developments in micro-structure imaging and multi-tissue decomposition have sparked renewed attention to the radial b-value dependence of the signal. Applications in tissue classification and micro-architecture estimation, therefore, require a signal representation that extends over the radial as well as angular domain. Multiple approaches have been proposed that can model the non-linear relationship between the DW-MRI signal and biological microstructure. In the past few years, many deep learning-based methods have been developed towards faster inference speed and higher inter-scan consistency compared with traditional model-based methods (e.g., multi-shell multi-tissue constrained spherical deconvolution). However, a multi-stage learning strategy is typically required since the learning process relied on various middle representations, such as simple harmonic oscillator reconstruction (SHORE) representation. In this work, we present a unified dynamic network with a single-stage spherical convolutional neural network, which allows efficient fiber orientation distribution function (fODF) estimation through heterogeneous multi-shell diffusion MRI sequences. We study the Human Connectome Project (HCP) young adults with test-retest scans. From the experimental results, the proposed single-stage method outperforms prior multi-stage approaches in repeated fODF estimation with shell dropoff and single-shell DW-MRI sequences

Genetic dissection of marker trait associations for grain micro-nutrients and thousand grain weight under heat and drought stress conditions in wheat

IntroductionWheat is grown and consumed worldwide, making it an important staple food crop for both its calorific and nutritional content. In places where wheat is used as a staple food, suboptimal micronutrient content levels, especially of grain iron (Fe) and zinc (Zn), can lead to malnutrition. Grain nutrient content is influenced by abiotic stresses, such as drought and heat stress. The best method for addressing micronutrient deficiencies is the biofortification of food crops. The prerequisites for marker-assisted varietal development are the identification of the genomic region responsible for high grain iron and zinc contents and an understanding of their genetics.MethodsA total of 193 diverse wheat genotypes were evaluated under drought and heat stress conditions across the years at the Indian Agricultural Research Institute (IARI), New Delhi, under timely sown irrigated (IR), restricted irrigated (RI) and late sown (LS) conditions. Grain iron content (GFeC) and grain zinc content (GZnC) were estimated from both the control and treatment groups. Genotyping of all the lines under study was carried out with the single nucleotide polymorphisms (SNPs) from Breeder’s 35K Axiom Array.Result and DiscussionThree subgroups were observed in the association panel based on both principal component analysis (PCA) and dendrogram analysis. A large whole-genome linkage disequilibrium (LD) block size of 3.49 Mb was observed. A genome-wide association study identified 16 unique stringent marker trait associations for GFeC, GZnC, and 1000-grain weight (TGW). In silico analysis demonstrated the presence of 28 potential candidate genes in the flanking region of 16 linked SNPs, such as synaptotagmin-like mitochondrial-lipid-binding domain, HAUS augmin-like complex, di-copper center-containing domain, protein kinase, chaperonin Cpn60, zinc finger, NUDIX hydrolase, etc. Expression levels of these genes in vegetative tissues and grain were also found. Utilization of identified markers in marker-assisted breeding may lead to the rapid development of biofortified wheat genotypes to combat malnutrition

Efficient deletion of microRNAs using CRISPR/Cas9 with dual guide RNAs

MicroRNAs (miRNAs) are short non-coding RNAs that play crucial roles in gene regulation, exerting post-transcriptional silencing, thereby influencing cellular function, development, and disease. Traditional loss-of-function methods for studying miRNA functions, such as miRNA inhibitors and sponges, present limitations in terms of specificity, transient effects, and off-target effects. Similarly, CRISPR/Cas9-based editing of miRNAs using single guide RNAs (sgRNAs) also has limitations in terms of design space for generating effective gRNAs. In this study, we introduce a novel approach that utilizes CRISPR/Cas9 with dual guide RNAs (dgRNAs) for the rapid and efficient generation of short deletions within miRNA genomic regions. Through the expression of dgRNAs through single-copy lentiviral integration, this approach achieves over a 90% downregulation of targeted miRNAs within a week. We conducted a comprehensive analysis of various parameters influencing efficient deletion formation. In addition, we employed doxycycline (Dox)-inducible expression of Cas9 from the AAVS1 locus, enabling homogeneous, temporal, and stage-specific editing during cellular differentiation. Compared to miRNA inhibitory methods, the dgRNA-based approach offers higher specificity, allowing for the deletion of individual miRNAs with similar seed sequences, without affecting other miRNAs. Due to the increased design space, the dgRNA-based approach provides greater flexibility in gRNA design compared to the sgRNA-based approach. We successfully applied this approach in two human cell lines, demonstrating its applicability for studying the mechanisms of human erythropoiesis and pluripotent stem cell (iPSC) biology and differentiation. Efficient deletion of miR-451 and miR-144 resulted in blockage of erythroid differentiation, and the deletion of miR-23a and miR-27a significantly affected iPSC survival. We have validated the highly efficient deletion of genomic regions by editing protein-coding genes, resulting in a significant impact on protein expression. This protocol has the potential to be extended to delete multiple miRNAs within miRNA clusters, allowing for future investigations into the cooperative effects of the cluster members on cellular functions. The protocol utilizing dgRNAs for miRNA deletion can be employed to generate efficient pooled libraries for high-throughput comprehensive analysis of miRNAs involved in different biological processes

Augmenting Autologous Stem Cell Transplantation to Improve Outcomes in Myeloma

Consolidation with high-dose chemotherapy and autologous stem cell transplantation (ASCT) is the standard of care for transplantation-eligible patients with multiple myeloma, based on randomized trials showing improved progression-free survival with autologous transplantation after combination chemotherapy induction. These trials were performed before novel agents were introduced; subsequently, combinations of immunomodulatory drugs and proteasome inhibitors as induction therapy have significantly improved rates and depth of response. Ongoing randomized trials are testing whether conventional autologous transplantation continues to improve responses after novel agent induction. Although these results are awaited, it is important to review strategies for improving outcomes after ASCT. Conditioning before ASCT with higher doses of melphalan and combinations of melphalan with other agents, including radiopharmaceuticals, has been explored. Tandem ASCT, consolidation, and maintenance therapy after ASCT have been investigated in phase III trials. Experimental cellular therapies using ex vivo–primed dendritic cells, ex vivo–expanded autologous lymphocytes, Killer Immunoglobulin Receptor (KIR)-mismatched allogeneic natural killer cells, and genetically modified T cells to augment ASCT are also in phase I trials. This review summarizes these strategies and highlights the importance of exploring strategies to augment ASCT, even in the era of novel agent induction

SBML Level 3: an extensible format for the exchange and reuse of biological models

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution

Immunomodulation in the Treatment of Refractory Catastrophic Antiphospholipid Syndrome

Catastrophic antiphospholipid syndrome is a rare condition with high morbidity and mortality. We present a refractory case of catastrophic antiphospholipid syndrome with a view to highlight the importance of early identification and aggressive treatment of this condition. A 36-year-old female presented with clinical manifestations of multiorgan vascular occlusion with a known history of primary antiphospholipid syndrome. The presentation was on a background of a recent change of her long-term anticoagulation from warfarin to therapeutic low-molecular-weight heparin. Given that multiorgan involvement with 3 organ systems occurred nearly simultaneously, a diagnosis of probable catastrophic antiphospholipid syndrome was made. Prompt therapeutic anticoagulation, antiplatelet, and glucocorticoid therapy was commenced. Despite this, the patient continued to demonstrate clinical features concerning for ongoing small vessel occlusion necessitating aggressive immunomodulatory therapy in the form of intravenous immunoglobulin, plasma exchange, and rituximab

Targeted Treatment of Follicular Lymphoma

Follicular lymphoma (FL) is the most common indolent B-cell lymphoma. Advanced stage disease is considered incurable and is characterized by a prolonged relapsing/remitting course. A significant minority have less favorable outcomes, particularly those with transformed or early progressive disease. Recent advances in our understanding of the unique genetic and immune biology of FL have led to increasingly potent and precise novel targeted agents, suggesting that a chemotherapy-future may one day be attainable. The current pipeline of new therapeutics is unprecedented. Particularly exciting is that many agents have non-overlapping modes of action, offering potential new combinatorial options and synergies. This review provides up-to-date clinical and mechanistic data on these new therapeutics. Ongoing dedicated attention to basic, translational and clinical research will provide further clarity as to when and how to best use these agents, to improve efficacy without eliciting unnecessary toxicity