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Here, we introduced some classical models of IgAN with or without genetic manipulation and recent translational approaches with some promising models. This includes humanized mouse models expressing human IgA1 and human IgA Fc receptor (CD89) that develops spontaneously the disease. Pre-clinical studies targeting IgA1 are discussed. Together, animal models are very useful tools to study pathophysiology and to validate new therapeutic approaches for IgAN.

Fractures of the posterior wall (PW) of the acetabulum have a wide variety of patterns; treating them as a single entity using the standard ilio-ischial plate would be inappropriate. We are presenting our experience with a fragment-specific fixation technique in which each PW fragment is reduced and fixed with separate buttress/anti-glide plate(s) in a tailored fashion, abandoning the use of the ilio-ischial plate.

Fragment-specific fixation was applied to 46 patients with PW fractures (33 simple and 13 associated fracture types) with a mean follow-up of 34.9 ± 20.5months (range 12-72). Doxorubicin in vivo Kocher-Langenbeck approach was utilized for all patients with dissection limited to the fracture site (a limited form of the approach was used in three patients).

Anatomical reduction of the fracture was achieved in 41 (89.1%) patients, imperfect reduction in four (8.7%), and poor reduction in one (2.2%) patient. Excellent to good radiological and functional results were achieved in 91.3% of cases. A single case had recurrent subluxation which was related to avascular necrosis of the highly comminuted wall fragments. Four patients developed post-traumatic arthritis and required total hip arthroplasty. None of our cases developed clinically significant heterotopic bone formation.

With a versatile yet a strong-enough construct and limited soft tissue dissection, fragment-specific fixation yielded very good results with few complications.

With a versatile yet a strong-enough construct and limited soft tissue dissection, fragment-specific fixation yielded very good results with few complications.Uncovering the general principles that govern the structure of metabolic networks is key to understanding the emergence and evolution of living systems. Artificial chemistries can help illuminate this problem by enabling the exploration of chemical reaction universes that are constrained by general mathematical rules. Here, we focus on artificial chemistries in which strings of characters represent simplified molecules, and string concatenation and splitting represent possible chemical reactions. We developed a novel Python package, ARtificial CHemistry NEtwork Toolbox (ARCHNET), to study string chemistries using tools from the field of stoichiometric constraint-based modeling. In addition to exploring the topological characteristics of different string chemistry networks, we developed a network-pruning algorithm that can generate minimal metabolic networks capable of producing a specified set of biomass precursors from a given assortment of environmental nutrients. We found that the composition of these minimal metabolic networks was influenced more strongly by the metabolites in the biomass reaction than the identities of the environmental nutrients. This finding has important implications for the reconstruction of organismal metabolic networks and could help us better understand the rise and evolution of biochemical organization. More generally, our work provides a bridge between artificial chemistries and stoichiometric modeling, which can help address a broad range of open questions, from the spontaneous emergence of an organized metabolism to the structure of microbial communities.Diabetic retinopathy (DR) is the leading cause of vision loss in working adults in developed countries. The disease traditionally classified as a microvascular complication of diabetes is now widely recognized as a neurovascular disorder resulting from disruption of the retinal neurovascular unit (NVU). The NVU comprising retinal neurons, glia and vascular cells coordinately regulates blood flow, vascular density and permeability to maintain homeostasis. Disturbance of the NVU during DR can lead to vision-threatening clinical manifestations. A limited number of signaling pathways have been identified for intercellular communication within the NVU, including vascular endothelial growth factor (VEGF), the master switch for angiogenesis. VEGF inhibitors are now widely used to treat DR, but their limited efficacy implies that other signaling molecules are involved in the pathogenesis of DR. By applying a novel screening technology called comparative ligandomics, we recently discovered secretogranin III (Scg3) as a unique DR-selective angiogenic and vascular leakage factor with therapeutic potential for DR. This review proposes neuron-derived Scg3 as the first diabetes-selective neurovascular regulator and discusses important features of Scg3 inhibition for next-generation disease-targeted anti-angiogenic therapies of DR.Rapid industrialization and intensive agriculture activities have led to a rise in heavy metal contamination all over the world. Chhattisgarh (India) being an industrial state, the soil and water are thickly contaminated with heavy metals, especially from arsenic (As). In the present study, we isolated 108 arsenic-resistant bacteria (both from soil and water) from different arsenic-contaminated industrial and mining sites of Chhattisgarh to explore the bacterial gene pool. Further, we screened 24 potential isolates out of 108 for their ability to tolerate a high level of arsenic. The sequencing of the 16S rRNA gene of bacterial isolates revealed that all these samples belong to different diverse genera including Bacillus, Enterobacter, Klebsiella, Pantoea, Acinetobacter, Cronobacter, Pseudomonas and Agrobacterium. The metal tolerance ability was determined by amplification of arsB (arsenite efflux gene) and arsC (arsenate reductase gene) from chromosomal DNA of isolated RnASA11, which was identified as Klebsiella pneumoniae through in silico analysis. The bacterial strains RpSWA2 and RnASA11 were found to tolerate 600 mM As (V) and 30 mM As (III) but the growth of strain RpSWA2 was slower than RnASA11. Furthermore, atomic absorption spectroscopy (AAS) of the sample obtained from bioremediation assay revealed that Klebsiella pneumoniae RnASA11 was able to reduce the arsenic concentration significantly in the presence of arsenate (44%) and arsenite (38.8%) as compared to control.