Molecular retention mechanisms of the G1 cyclin/Cdk complex in budding yeast

Budding yeast (Saccharomyces cerevisiae) cells coordinate cell growth and cell cycle progression essentially during G1, where they must reach a critical cell size to traverse Start and enter the cell cycle. The most upstream activator of Start is Cln3, a G1 cyclin that together with the cyclin-dependent kinase Cdc28 triggers a transcriptional wave that drives cell cycle entry. The Cln3 cyclin is a low abundant and very unstable protein whose levels respond very rapidly to nutritional changes. However, Cln3 expression is not sharply regulated through the cell cycle and it is already present in early G1 cells. Notably, most Cln3 is retained bound to the ER in early G1 with the assistance of Whi3, an RNA-binding protein that binds the CLN3 mRNA, and it is released in late G1 by Ydj1, a J-chaperone that might transmit growth capacity information to the cell cycle machinery. However, little is known on the molecular mechanisms that retain the Cdc28-C1n3 complex in the cytoplasm and how do these mechanisms transmit information of cell size to coordinate cell proliferation with cell growth. As Cdc28 is important for proper retention of Cln3 at the ER, we hypothesized that mutations weakening interactions to unknown ER retention factors would cause premature release of the Cdc28-C1n3 complex and, hence, a smaller cell size. This thesis describes the isolation and characterization of a CDC28 quintuple mutant, which we refer to as CDC28wee, that causes premature entry into the cell cycle and a small cell size. Next we used isobaric tags for relative and absolute quantitation (iTRAQ) to identify direct interactors with lower affinities for mutant Cdc28wee, aiming at the identification of proteins with key regulatory roles in the retention mechanism. Among the identified proteins we found Sr13, a protein of unknown function, here renamed as Whi7. Here we show that Whi7 acts as an inhibitor of Start, associates to the ER and contributes to efficient retention of the Cln3 cyclin, thus preventing its unscheduled accumulation in the nucleus. Our results demonstrate that Whi7 acts in a positive feedback loop to release the G1 Cdk¬cyclin complex and trigger Start once a critical size has been reached, thus uncovering a key nonlinear mechanism at the earliest known events of cell cycle entry. In addition to Whi7 we also identified Whi8, renamed here as Whi8, which is an RNA-binding protein present in both stress granules (SGs) and P bodies (PBs) with unknown biological function. We have found that Whi8 interacts with Cdc28 in vivo, binds and colocalizes with the CLN3 mRNA, and interacts with Whi3 in an RNA-dependent manner. Whi8-deficient cells showed a smaller budding cell size while, on the other hand, overexpression of Whi8 increased the budding volume. Cells lacking Whi8 were not capable of accumulating the CLN3 mRNA in SGs under stress conditions, and Cln3 synthesis remained high under glucose and nitrogen starvation, two environmental stress conditions that dramatically decrease Cln3 levels in the cell. Whi8 accumulation in SGs depended on an intrinsically disordered domain (IDD) identified at C-terminus of Whi8 and specific PKA phophosites. Our results suggest that Whi8 acts under stress as a safeguard that limits the influx of newly synthesized Cln3 (and likely other proteins) into the cell cycle machinery, by trapping the CLN3 mRNA in mRNA granules. Thus, we have found a unique target for signaling pathways that directly links stress response and cell cycle entry

Brain tumor MRI medical images classification model based on CNN (BTMIC-CNN)

This research discusses a fully automatic brain tumour MRI medical images classification model that use Convolutional Neural Network (BTMIC-CNN). The proposed neural model adopted Design Science Research Methodology (DSRM) to classify MRI medical images from two datasets. One for binary classification task (contains tumorous and non-tumorous images). And the second for multiclass classification task (contains three types of brain tumor MRI medical images namely: Glioma, meningioma, and pituitary). The model's excellent performance was confirmed using the evaluation metrics and reported an overall accuracy of 99%. It outperforms existing methods in terms of classification accuracy and is expected to help radiologists and doctors accurately classify brain tumours’ images. This study contributes to goal three of the Sustainable Development Goals (SDGs), which involves excellent health and well-being

Brain tumor MRI medical images classification with data augmentation by transfer learning of VGG16

The ability to estimate conclusions without direct human input in healthcare systems via computer algorithms is known as Artificial intelligence (AI) in healthcare. Deep learning (DL) approaches are already being employed or exploited for healthcare purposes, and in the case of medical images analysis, DL paradigms opened a world of opportunities. This paper describes creating a DL model based on transfer learning of VGG16 that can correctly classify MRI images as either (tumorous) or (non-tumorous). In addition, the model employed data augmentation in order to balance the dataset and increase the number of images. The dataset comes from the brain tumour classification project, which contains publicly available tumorous and non-tumorous images. The result showed that the model performed better with the augmented dataset, with its validation accuracy reaching ~100 %

EEG-based emotion recognition while listening to Quran recitation compared with relaxing music using Valence-arousal model

Relaxation and calmness are two emotions that people always seek for. One popular method people used to do in order to reduce their level of tension and pressure is listening to some types of relaxing music. On the other hand, Quran is Allah’s words that are ultimately given to us human to benefit of. Although, Muslims are strongly believed that listening to Quran or reading it brings them to comfort, pleasure and confidence. Scientific evidence is still required to prove that scientifically. Human emotion can be recognized from voice, text, facial expression or body language. But those methods are susceptible to change and are not really accurate. Recently, electroencephalograms (EEG) allowed researchers to evoke the inner emotions. This paper aims to study human emotions while listening to Quran recitation compared with listening to relaxing music. To evoke emotions, some stimuli should be used; in this research we implemented International Affective Picture System (IAPS) database. And for the emotion classification technique we followed two-dimensional Arousal- Valence emotion model. Finally the emotion model was implemented to recognize four basic emotions Happy, Fear, Sad and Calm with an average accuracy of 76.81 %. The data collected while listening to Quran and music were tested and the result generally showed that both Quran and Music are classified more into positive valence

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

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Molecular retention mechanisms of the G1 cyclin/Cdk complex in budding yeast

Peer Reviewe

Cdc48/p97 segregase is modulated by cyclin‐dependent kinase to determine cyclin fate during G1 progression

Cells sense myriad signals during G1, and a rapid response to prevent cell cycle entry is of crucial importance for proper development and adaptation. Cln3, the most upstream G1 cyclin in budding yeast, is an extremely short‐lived protein subject to ubiquitination and proteasomal degradation. On the other hand, nuclear accumulation of Cln3 depends on chaperones that are also important for its degradation. However, how these processes are intertwined to control G1‐cyclin fate is not well understood. Here, we show that Cln3 undergoes a challenging ubiquitination step required for both degradation and full activation. Segregase Cdc48/p97 prevents degradation of ubiquitinated Cln3, and concurrently stimulates its ER release and nuclear accumulation to trigger Start. Cdc48/p97 phosphorylation at conserved Cdk‐target sites is important for recruitment of specific cofactors and, in both yeast and mammalian cells, to attain proper G1‐cyclin levels and activity. Cdk‐dependent modulation of Cdc48 would subjugate G1 cyclins to fast and reversible state switching, thus arresting cells promptly in G1 at developmental or environmental checkpoints, but also resuming G1 progression immediately after proliferative signals reappear.This work was funded by the Ministry of Economy and Competitiveness of Spain (BFU2013-47710-R), Consolider-Ingenio 2010 (CSD2007-15), and the European Union (FEDER).Peer reviewe

Competition in the chaperone-client network subordinates cell-cycle entry to growth and stress

© 2019 Moreno et al.The precise coordination of growth and proliferation has a universal prevalence in cell homeostasis. As a prominent property, cell size is modulated by the coordination between these processes in bacterial, yeast, and mammalian cells, but the underlying molecular mechanisms are largely unknown. Here, we show that multifunctional chaperone systems play a concerted and limiting role in cell-cycle entry, specifically driving nuclear accumulation of the G1 Cdk–cyclin complex. Based on these findings, we establish and test a molecular competition model that recapitulates cell-cycle-entry dependence on growth rate. As key predictions at a single-cell level, we show that availability of the Ydj1 chaperone and nuclear accumulation of the G1 cyclin Cln3 are inversely dependent on growth rate and readily respond to changes in protein synthesis and stress conditions that alter protein folding requirements. Thus, chaperone workload would subordinate Start to the biosynthetic machinery and dynamically adjust proliferation to the growth potential of the cell.This work was funded by the Spanish Ministry of Science, Consolider-Ingenio 2010, and the European Union (FEDER) to M Aldea. DF Moreno received an FI fellowship from Generalitat de Catalunya

Analyzing brainwaves while listening to Quranic recitation compared with listening to music based on EEG signals

The electroencephalogram (EEG) is an acquiring of the electrical fluctuations that occur in the brain, generated simply by positioning electrodes over the scalp with amplification of the electrical potential produced. The actual EEG indicates three primary types of wave, named alpha, beta and delta, which are distinct based on their rate of production. Data has been collected from twenty five subjects using BrainMarker EEG hardware and software. Brainwaves were measured, focusing on the Alpha and Beta bands to measure subjects’ calmness while listening to Quran recitation compared with relaxing music. The result showed that higher alpha magnitudes were generated during listening to Quran recitation