Harnessing rhizospheric core microbiomes from arid regions for enhancing date palm resilience to climate change effects

Date palm cultivation has thrived in the Gulf Cooperation Council region since ancient times, where it represents a vital sector in agricultural and socio-economic development. However, climate change conditions prevailing for decades in this area, next to rarefication of rain, hot temperatures, intense evapotranspiration, rise of sea level, salinization of groundwater, and intensification of cultivation, contributed to increase salinity in the soil as well as in irrigation water and to seriously threaten date palm cultivation sustainability. There are also growing concerns about soil erosion and its repercussions on date palm oases. While several reviews have reported on solutions to sustain date productivity, including genetic selection of suitable cultivars for the local harsh environmental conditions and the implementation of efficient management practices, no systematic review of the desertic plants’ below-ground microbial communities and their potential contributions to date palm adaptation to climate change has been reported yet. Indeed, desert microorganisms are expected to address critical agricultural challenges and economic issues. Therefore, the primary objectives of the present critical review are to (1) analyze and synthesize current knowledge and scientific advances on desert plant-associated microorganisms, (2) review and summarize the impacts of their application on date palm, and (3) identify possible gaps and suggest relevant guidance for desert plant microbes’ inoculation approach to sustain date palm cultivation within the Gulf Cooperation Council in general and in Qatar in particular

PTPA variants and impaired PP2A activity in early-onset parkinsonism with intellectual disability

The protein phosphatase 2A complex (PP2A), the major Ser/Thr phosphatase in the brain, is involved in a number of signalling pathways and functions, including the regulation of crucial proteins for neurodegeneration, such as alpha-synuclein, tau and LRRK2. Here, we report the identification of variants in the PTPA/PPP2R4 gene, encoding a major PP2A activator, in two families with early-onset parkinsonism and intellectual disability. We carried out clinical studies and genetic analyses, including genome-wide linkage analysis, whole-exome sequencing, and Sanger sequencing of candidate variants. We next performed functional studies on the disease-associated variants in cultured cells and knock-down of ptpa in Drosophila melanogaster. We first identified a homozygous PTPA variant, c.893T&gt;G (p.Met298Arg), in patients from a South African family with early-onset parkinsonism and intellectual disability. Screening of a large series of additional families yielded a second homozygous variant, c.512C&gt;A (p.Ala171Asp), in a Libyan family with a similar phenotype. Both variants co-segregate with disease in the respective families. The affected subjects display juvenile-onset parkinsonism and intellectual disability. The motor symptoms were responsive to treatment with levodopa and deep brain stimulation of the subthalamic nucleus. In overexpression studies, both the PTPA p.Ala171Asp and p.Met298Arg variants were associated with decreased PTPA RNA stability and decreased PTPA protein levels; the p.Ala171Asp variant additionally displayed decreased PTPA protein stability. Crucially, expression of both variants was associated with decreased PP2A complex levels and impaired PP2A phosphatase activation. PTPA orthologue knock-down in Drosophila neurons induced a significant impairment of locomotion in the climbing test. This defect was age-dependent and fully reversed by L-DOPA treatment. We conclude that bi-allelic missense PTPA variants associated with impaired activation of the PP2A phosphatase cause autosomal recessive early-onset parkinsonism with intellectual disability. Our findings might also provide new insights for understanding the role of the PP2A complex in the pathogenesis of more common forms of neurodegeneration.</p

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Optimization of a Redox-Flow Battery Simulation Model Based on a Deep Reinforcement Learning Approach

Vanadium redox-flow batteries (VRFBs) have played a significant role in hybrid energy storage systems (HESSs) over the last few decades owing to their unique characteristics and advantages. Hence, the accurate estimation of the VRFB model holds significant importance in large-scale storage applications, as they are indispensable for incorporating the distinctive features of energy storage systems and control algorithms within embedded energy architectures. In this work, we propose a novel approach that combines model-based and data-driven techniques to predict battery state variables, i.e., the state of charge (SoC), voltage, and current. Our proposal leverages enhanced deep reinforcement learning techniques, specifically deep q-learning (DQN), by combining q-learning with neural networks to optimize the VRFB-specific parameters, ensuring a robust fit between the real and simulated data. Our proposed method outperforms the existing approach in voltage prediction. Subsequently, we enhance the proposed approach by incorporating a second deep RL algorithm—dueling DQN—which is an improvement of DQN, resulting in a 10% improvement in the results, especially in terms of voltage prediction. The proposed approach results in an accurate VFRB model that can be generalized to several types of redox-flow batteries

Rank-Two NMF Clustering for Glioblastoma Characterization

This study investigates a novel classification method for 3D multimodal MRI glioblastomas tumor characterization. We formulate our segmentation problem as a linear mixture model (LMM). Thus, we provide a nonnegative matrix M from every MRI slice in every segmentation process’ step. This matrix will be used as an input for the first segmentation process to extract the edema region from T2 and FLAIR modalities. After that, in the rest of segmentation processes, we extract the edema region from T1c modality, generate the matrix M, and segment the necrosis, the enhanced tumor, and the nonenhanced tumor regions. In the segmentation process, we apply a rank-two NMF clustering. We have executed our tumor characterization method on BraTS 2015 challenge dataset. Quantitative and qualitative evaluations over the publicly training and testing dataset from the MICCAI 2015 multimodal brain segmentation challenge (BraTS 2015) attested that the proposed algorithm could yield a competitive performance for brain glioblastomas characterization (necrosis, tumor core, and edema) among several competing methods

Zoledronate Associated Seizure in Chronic Recurrent Multifocal Osteomyelitis

Chronic recurrent multifocal osteomyelitis (CRMO) is an auto-inflammatory disease characterized by sterile bone lesions. We report a case of a patient with CRMO who developed a seizure post bisphosphonate administration. Although, the treatment of CRMO is currently not codified, the most promising results have been observed in patients under treatment with bisphosphonates. Keywords: CRMO; Bisphosphonate; tonico-clonic seizure

Endosalpingiosis in a premenarchal girl: A case report

Introduction: The diagnosis of endosalpingiosis (ES) in the pediatric population is rare. ES is typically encountered between the third and the fifth decade of life. We present a case of ES in a premenarchal girl. Case report: A 11-year-old girl presented to the emergency room with recurrent, intermittent, abdominal pain over the previous three days, accompanied by nausea and non-bilious vomiting. She had no history of fever, weight loss, jaundice, abdominal distension, urinary problems or intestinal derangements. She had not attained menarche, and there was no family history of malignancies. On the physical exam she was hemodynamically stable, and her abdomen was tender in the right iliac fossa. Baseline blood investigations were normal. Abdominal ultrasound ruled out acute appendicitis and adnexal torsion. Due to the persistence of the abdominal pain, we did a laparoscopic exploration. We found bilateral small cystic blebs on the peritoneum attached to the fallopian tubes, and no other anomalies. We resected all the cysts/blebs. She had an uneventful recovery and was pain free without medication shortly after the operation. The final pathology revealed ES with clear margins. At 24-month follow-up, the patient has attained menarche, has regular menstrual cycles and remains symptom free. Conclusions: ES can be a source of abdominal pain in premenarchal females. Our case emphasizes the need for increased awareness among healthcare providers