The annexins: spatial and temporal coordination of signaling events during cellular stress

Annexins are a family of structurally related, Ca2+-sensitive proteins that bind to negatively charged phospholipids and establish specific interactions with other lipids and lipid microdomains. They are present in all eukaryotic cells and share a common folding motif, the "annexin core”, which incorporates Ca2+- and membrane-binding sites. Annexins participate in a variety of intracellular processes, ranging from the regulation of membrane dynamics to cell migration, proliferation, and apoptosis. Here we focus on the role of annexins in cellular signaling during stress. A chronic stress response triggers the activation of different intracellular pathways, resulting in profound changes in Ca2+ and pH homeostasis and the production of lipid second messengers. We review the latest data on how these changes are sensed by the annexins, which have the ability to simultaneously interact with specific lipid and protein moieties at the plasma membrane, contributing to stress adaptation via regulation of various signaling pathway

Deciphering microRNA code in pain and inflammation: lessons from bladder pain syndrome

MicroRNAs (miRNAs), a novel class of molecules regulating gene expression, have been hailed as modulators of many biological processes and disease states. Recent studies demonstrated an important role of miRNAs in the processes of inflammation and cancer, however, there are little data implicating miRNAs in peripheral pain. Bladder pain syndrome/interstitial cystitis (BPS/IC) is a clinical syndrome of pelvic pain and urinary urgency/frequency in the absence of a specific cause. BPS is a chronic inflammatory condition that might share some of the pathogenetic mechanisms with its common co-morbidities inflammatory bowel disease (IBD), asthma and autoimmune diseases. Using miRNA profiling in BPS and the information about validated miRNA targets, we delineated the signaling pathways activated in this and other inflammatory pain disorders. This review projects the miRNA profiling and functional data originating from the research in bladder cancer and immune-mediated diseases on the BPS-specific miRNAs with the aim to gain new insight into the pathogenesis of this enigmatic disorder, and highlighting the common regulatory mechanisms of pain and inflammatio

Machine Learning Made Easy (MLme): A Comprehensive Toolkit for Machine Learning-Driven Data Analysis.

BACKGROUND Machine learning (ML) has emerged as a vital asset for researchers to analyze and extract valuable information from complex datasets. However, developing an effective and robust ML pipeline can present a real challenge, demanding considerable time and effort, thereby impeding research progress. Existing tools in this landscape require a profound understanding of ML principles and programming skills. Furthermore, users are required to engage in the comprehensive configuration of their ML pipeline to obtain optimal performance. RESULTS To address these challenges, we have developed a novel tool called Machine Learning Made Easy (MLme) that streamlines the use of ML in research, specifically focusing on classification problems at present. By integrating four essential functionalities, namely Data Exploration, AutoML, CustomML, and Visualization, MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. To demonstrate the applicability of MLme, we conducted rigorous testing on six distinct datasets, each presenting unique characteristics and challenges. Our results consistently showed promising performance across different datasets, reaffirming the versatility and effectiveness of the tool. Additionally, by utilizing MLme's feature selection functionality, we successfully identified significant markers for CD8+ naive (BACH2), CD16+ (CD16), and CD14+ (VCAN) cell populations. CONCLUSION MLme serves as a valuable resource for leveraging machine learning (ML) to facilitate insightful data analysis and enhance research outcomes, while alleviating concerns related to complex coding scripts. The source code and a detailed tutorial for MLme are available at https://github.com/FunctionalUrology/MLme

Urinary miRNA profiles discriminate between obstruction-induced bladder dysfunction and healthy controls.

Urgency, frequency and incomplete emptying are the troublesome symptoms often shared between benign prostatic obstruction-induced (BLUTD) and neurogenic (NLUTD) lower urinary tract dysfunction. Previously, using bladder biopsies, we suggested a panel of miRNA biomarkers for different functional phenotypes of the bladder. Urine is a good source of circulating miRNAs, but sex- and age-matched controls are important for urinary metabolite comparison. In two groups of healthy subjects (average age 32 and 57 years old, respectively) the total protein and RNA content was very similar between age groups, but the number of secreted extracellular vesicles (uEVs) and expression of several miRNAs were higher in the young healthy male volunteers. Timing of urine collection was not important for these parameters. We also evaluated the suitability of urinary miRNAs for non-invasive diagnosis of bladder outlet obstruction (BOO). A three urinary miRNA signature (miR-10a-5p, miR-301b-3p and miR-363-3p) could discriminate between controls and patients with LUTD (BLUTD and NLUTD). This panel of representative miRNAs can be further explored to develop a non-invasive diagnostic test for BOO. The age-related discrepancy in the urinary miRNA content observed in this study points to the importance of selecting appropriate, age-matched controls

SpheroScan: A User-Friendly Deep Learning Tool for Spheroid Image Analysis.

BACKGROUND In recent years, three-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional two-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays. RESULTS To address these issues, we have developed a fully automated, web-based tool called SpheroScan, which uses the deep learning framework called Mask Regions with Convolutional Neural Networks (R-CNN) for image detection and segmentation. To develop a deep learning model that could be applied to spheroid images from a range of experimental conditions, we trained the model using spheroid images captured using IncuCyte Live-Cell Analysis System and a conventional microscope. Performance evaluation of the trained model using validation and test datasets shows promising results. CONCLUSION SpheroScan allows for easy analysis of large numbers of images and provides interactive visualization features for a more in-depth understanding of the data. Our tool represents a significant advancement in the analysis of spheroid images and will facilitate the widespread adoption of 3D spheroid models in scientific research. The source code and a detailed tutorial for SpheroScan are available at https://github.com/FunctionalUrology/SpheroScan

SpheroScan: a user-friendly deep learning tool for spheroid image analysis.

BACKGROUND In recent years, 3-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional 2-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays. RESULTS To address these issues, we have developed a fully automated, web-based tool called SpheroScan, which uses the deep learning framework called Mask Regions with Convolutional Neural Networks (R-CNN) for image detection and segmentation. To develop a deep learning model that could be applied to spheroid images from a range of experimental conditions, we trained the model using spheroid images captured using IncuCyte Live-Cell Analysis System and a conventional microscope. Performance evaluation of the trained model using validation and test datasets shows promising results. CONCLUSION SpheroScan allows for easy analysis of large numbers of images and provides interactive visualization features for a more in-depth understanding of the data. Our tool represents a significant advancement in the analysis of spheroid images and will facilitate the widespread adoption of 3D spheroid models in scientific research. The source code and a detailed tutorial for SpheroScan are available at https://github.com/FunctionalUrology/SpheroScan

Buffel Grass (Cenchrus ciliaris) for livestock feed on small-scale farms

Information leaflet on livestock feeds and feeding technologies for small-scale farmers developed through collaboration between ILRI and its partner

The Targeting of Plasmalemmal Ceramide to Mitochondria during Apoptosis

Ceramide is a key lipid mediator of cellular processes such as differentiation, proliferation, growth arrest and apoptosis. During apoptosis, ceramide is produced within the plasma membrane. Although recent data suggest that the generation of intracellular ceramide increases mitochondrial permeability, the source of mitochondrial ceramide remains unknown. Here, we determine whether a stress-mediated plasmalemmal pool of ceramide might become available to the mitochondria of apoptotic cells. We have previously established annexin A1—a member of a family of Ca2+ and membrane-binding proteins—to be a marker of ceramide platforms. Using fluorescently tagged annexin A1, we show that, upon its generation within the plasma membrane, ceramide self-associates into platforms that subsequently invaginate and fuse with mitochondria. An accumulation of ceramide within the mitochondria of apoptotic cells was also confirmed using a ceramide-specific antibody. Electron microscopic tomography confirmed that upon the formation of ceramide platforms, the invaginated regions of the plasma membrane extend deep into the cytoplasm forming direct physical contacts with mitochondrial outer membranes. Ceramide might thus be directly transferred from the plasma membrane to the mitochondrial outer membrane. It is conceivable that this “kiss-of-death” increases the permeability of the mitochondrial outer membrane thereby triggering apoptosis

Functional Association between Regulatory RNAs and the Annexins.

Cells respond to pathophysiological states by activation of stress-induced signalling. Regulatory non-coding microRNAs (miRNAs) often form stable feed-forward loops which ensure prolongation of the signal, contributing to sustained activation. Members of the annexin protein family act as sensors for Ca, pH, and lipid second messengers, and regulate various signalling pathways. Recently, annexins were reported to participate in feedback loops, suppressing miRNA synthesis and attenuating stress-induced dysregulation of gene expression. They can directly or indirectly associate with RNAs, and are transferred between the cells in exosomes and shed microvesicles. The ability of annexins to recruit other proteins and miRNAs into exosomes implicates them in control of cell-cell interactions, affecting the adaptive responses and remodelling processes during disease. The studies summarized in this Review point to an emerging role of annexins in influencing the synthesis, localisation, and transfer of regulatory RNAs

Functional Association between Regulatory RNAs and the Annexins

Cells respond to pathophysiological states by activation of stress-induced signalling. Regulatory non-coding microRNAs (miRNAs) often form stable feed-forward loops which ensure prolongation of the signal, contributing to sustained activation. Members of the annexin protein family act as sensors for Ca2+, pH, and lipid second messengers, and regulate various signalling pathways. Recently, annexins were reported to participate in feedback loops, suppressing miRNA synthesis and attenuating stress-induced dysregulation of gene expression. They can directly or indirectly associate with RNAs, and are transferred between the cells in exosomes and shed microvesicles. The ability of annexins to recruit other proteins and miRNAs into exosomes implicates them in control of cell–cell interactions, affecting the adaptive responses and remodelling processes during disease. The studies summarized in this Review point to an emerging role of annexins in influencing the synthesis, localisation, and transfer of regulatory RNAs