Deepvirusclassifier: a deep learning tool for classifying SARS-CoV-2 based on viral subtypes within the coronaviridae family.

PURPOSE: In this study, we present DeepVirusClassifier, a tool capable of accurately classifying Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) viral sequences among other subtypes of the coronaviridae family. This classification is achieved through a deep neural network model that relies on convolutional neural networks (CNNs). Since viruses within the same family share similar genetic and structural characteristics, the classification process becomes more challenging, necessitating more robust models. With the rapid evolution of viral genomes and the increasing need for timely classification, we aimed to provide a robust and efficient tool that could increase the accuracy of viral identification and classification processes. Contribute to advancing research in viral genomics and assist in surveilling emerging viral strains. METHODS: Based on a one-dimensional deep CNN, the proposed tool is capable of training and testing on the Coronaviridae family, including SARS-CoV-2. Our model's performance was assessed using various metrics, including F1-score and AUROC. Additionally, artificial mutation tests were conducted to evaluate the model's generalization ability across sequence variations. We also used the BLAST algorithm and conducted comprehensive processing time analyses for comparison. RESULTS: DeepVirusClassifier demonstrated exceptional performance across several evaluation metrics in the training and testing phases. Indicating its robust learning capacity. Notably, during testing on more than 10,000 viral sequences, the model exhibited a more than 99% sensitivity for sequences with fewer than 2000 mutations. The tool achieves superior accuracy and significantly reduced processing times compared to the Basic Local Alignment Search Tool algorithm. Furthermore, the results appear more reliable than the work discussed in the text, indicating that the tool has great potential to revolutionize viral genomic research. CONCLUSION: DeepVirusClassifier is a powerful tool for accurately classifying viral sequences, specifically focusing on SARS-CoV-2 and other subtypes within the Coronaviridae family. The superiority of our model becomes evident through rigorous evaluation and comparison with existing methods. Introducing artificial mutations into the sequences demonstrates the tool's ability to identify variations and significantly contributes to viral classification and genomic research. As viral surveillance becomes increasingly critical, our model holds promise in aiding rapid and accurate identification of emerging viral strains.

Compensatory strategy use in diverse older adults with subjective cognitive complaints.

OBJECTIVES: The current study aimed to evaluate the relationship between subjective cognitive complaints (SCC) and compensatory strategy (CS) use in a diverse sample of non-Latinx White (NLW), Black, and Latinx American older adults. METHOD: 807 older adults (Mage = 65.38, 62.7% female) were recruited through Amazon's Mechanical Turk (MTurk) and Qualtrics Panel to complete questionnaires on SCC and CS use. Kruskall-Wallis tests were used to evaluate differences in SCC across groups given non-normal distributions. Analysis of variance (ANOVA) was used to evaluate group differences in CS use. The PROCESS macro for SPSS was used to examine whether demographic factors moderated the relationship between SCC and CS use. RESULTS: NLWs reported higher levels of SCC and greater overall use of CS in comparison to Latinx and Black individuals. Several demographic and psychosocial factors including age, ethno-racial group, education, and anxiety level were found to be associated with CS use. Education was found to moderate the association between SCC and CS use. CONCLUSION: Inconsistent with prior studies, our study found that NLWs reported the highest levels of SCC. CS were used across all racial/ethnic groups, but the frequency of CS use may be impacted by education level. While all education groups increased their CS in response to higher levels of SCC, this increase was more substantial for those with lower levels of education. Future work should consider individuals' cultural and educational background when examining SCC and/or developing CS-based intervention for the aging population.

Modeling Lysosomal Storage Disorders in an Innovative Way: Establishment and Characterization of Stem Cell Lines from Human Exfoliated Deciduous Teeth of Mucopolysaccharidosis Type II Patients.

Among the many lysosomal storage disorders (LSDs) that would benefit from the establishment of novel cell models, either patient-derived or genetically engineered, is mucopolysaccharidosis type II (MPS II). Here, we present our results on the establishment and characterization of two MPS II patient-derived stem cell line(s) from deciduous baby teeth. To the best of our knowledge, this is the first time a stem cell population has been isolated from LSD patient samples obtained from the dental pulp. Taking into account our results on the molecular and biochemical characterization of those cells and the fact that they exhibit visible and measurable disease phenotypes, we consider these cells may qualify as a valuable disease model, which may be useful for both pathophysiological assessments and in vitro screenings. Ultimately, we believe that patient-derived dental pulp stem cells (DPSCs), particularly those isolated from human exfoliated deciduous teeth (SHEDs), may represent a feasible alternative to induced pluripotent stem cells (iPSCs) in many labs with standard cell culture conditions and limited (human and economic) resources.

Inaugural editorial for Journal of Counseling Psychology.

The Journal of Counseling Psychology serves as the premier journal for critical and rigorous research within the field and beyond. In their inaugural editorial for Journa, Liu is joined by their associated editors and inaugural JCP fellows who have agreed to share authorship and their positionalities. In considering the Journal of Counseling Psychology for research, the editors encourage authors to reflect on these positionalities and how they might integrate their own into their publications. The editorial provides direction and some suggestions on submitted articles and research directions for JCP in the following areas: positionality and critical reflexivity; theoretical and conceptual advancement and clarity; body ideas, frameworks, and conceptualization; data clarity; and cultural validity of research instruments. The editors look forward to working with their communities as they transform their scholarship. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Diagnostic and prognostic contribution of DPD scintigraphy in transthyretin V30M cardiac amyloidosis.

BACKGROUND: Early diagnosis and prognostic stratification of cardiac transthyretin amyloidosis are crucial. Although 99mTc 3,3-diphosphono-1,2-propanedicarboxylic acid (DPD) scintigraphy is the preferred method for the non-invasive diagnosis, its accuracy appears to be limited in transthyretin amyloidosis protein (ATTR) V30M mutation. Furthermore, its prognostic value in this mutation is unknown. This study investigated the diagnostic value of DPD scintigraphy to detect ATTR cardiomyopathy in V30M mutation and explored its prognostic value regarding mortality. METHODS: A total of 288 ATTR V30M mutation carriers (median age: 46 years; 49% males) without myocardial thickening (defined as septal thickness ≥13mm) attributable to other causes and who underwent DPD scintigraphy were enrolled. ATTR cardiomyopathy was defined by septal thickness ≥13mm and at least one of the criteria: late heart-to-mediastinum (H/M) 123I-metaiodobenzylguanidine (MIBG) uptake ratio <1.60; electrical heart disease or biopsy-documented amyloidosis. RESULTS: ATTR cardiomyopathy was identified in 41 (14.2%) patients and cardiac DPD uptake in 34 (11.8%). During a mean follow-up of 33.6 ± 1.2 months, 16 patients died (5.6%). Mortality was 14 times higher in patients with ATTR cardiomyopathy, 13 times higher in those with DPD uptake and 10 times higher in those with late H/M MIBG <1.60. The combined assessment of septal thickness and cardiac DPD uptake improved risk stratification: patients without septal thickening and without DPD retention had an excellent prognosis while those who presented either or both of them had a significantly worse prognosis, with 5-year mortality rates ranging from 39.9 to 53.3%. CONCLUSIONS: DPD scintigraphy is useful for prognostic stratification of ATTR V30M mutation carriers. Patients without septal thickening and no DPD uptake present the best prognosis compared to those with any signs of cardiac involvement.

O percurso pela atenção à crise em saúde mental na cidade do Rio de Janeiro / The journey through mental health crisis care in the city of Rio de Janeiro

Resumo O conceito de crise em saúde metal envolve uma complexa formulação multidimensional, forjada no contexto da Reforma Psiquiátrica Brasileira, que nem sempre é tomado de maneira unívoca pelos envolvidos. Contudo, há de se considerar uma rede capaz de dar respostas adequadas sobre como acolher essa situação, de maneira que o trabalho em rede é uma condição essencial dessa abordagem. Este artigo traz a discussão do manejo da crise em saúde mental nos Centros de Atenção Psicossocial III (CAPS III) do município do Rio de Janeiro, Brasil, a partir da perspectiva dos gestores de saúde de nível central e local, realizada por meio de entrevistas semiestruturadas e analisadas com base na Teoria da Estruturação de Giddens. Este trabalho identificou que o Rio de Janeiro apresenta um modelo de atenção à crise estruturado em rede de atenção centralizada e rede integrada, uma vez que apresenta grande integração da rede de urgência com a Rede de Atenção Psicossocial (RAPS), sobretudo com os CAPS III, e as situações de crises são atendidas preferencialmente em serviços específicos para seu atendimento. Ainda assim, pela perspectiva de Giddens, os CAPS III têm legitimidade para cumprir o papel de atenção à crise em saúde mental.

Abstract The concept of crisis in mental health involves a complex multidimensional formulation, forged in the context of the Brazilian Psychiatric Reform, which is not always taken unequivocally by those involved. However, it is necessary to consider a network capable of providing adequate answers on how to provide care in this situation; thus, networking is an essential condition of this approach. This article discusses the management of the mental health crisis in Psychosocial Care Centers III (CAPS III) in the municipality of Rio de Janeiro, Brazil, from the perspective of central and local health care managers, via semi-structured interviews and analysis based on Giddens' Theory of Structuring. This study found that the municipality of Rio de Janeiro adopts a crisis care model structured into a centralized care network and integrated network, with an emergency network highly integrated with the Psychosocial Attention Network (RAPS), especially with the CAPS III, and the crisis situations are cared for preferably in specific services. Still, from Giddens' perspective, CAPS III have the legitimacy to provide care toward mental health crisis.

Help Comes from Unexpected Places: How a Tiny Fairy and a Tropical Fish may help us Model Mucopolysaccharidoses.

INTRODUCTION: When it comes to disease modeling, countless models are available for Lysosomal Storage Diseases (LSD). Historically, two major approaches are well-established: in vitro assessments are performed in patient fibroblasts, while in vivo pre-clinical studies are performed in mouse models. Still, both platforms have a series of drawbacks. Thus, we implemented two alternative and innovative protocols to mimic a particular sub-group of LSDs, the Mucopolysaccharidoses both in vitro and in vivo. METHODS: The first one relies on a non-invasive approach using dental pulp stem cells from deciduous teeth (SHEDs). SHEDs are multipotent neuronal precursors that can easily be collected. The second uses a state-of-the-art gene editing technology (CRISPR/Cas9) to generate zebrafish disease models. RESULTS: Even though this is an ongoing project, we have already established and characterized two MPS II and one MPS VI SHED cell models. These cells self-maintain through several passages and can give rise to a variety of cells including neurons. Furthermore, all MPS-associated sub-cellular phenotypes we have assessed so far are easily observable in these cells. Regarding our zebrafish models, we have successfully knocked down both naglu and hgsnat and the first results we got from the behavioral analysis are promising ones, as we can observe altered activity and sleep patterns in the genetically modified fish. For this particular approach we chose MPS III forms as our target disorders, since their neurological features (hyperactivity, seizures and motor impairment) and lifespan decrease would be easily recognizable in zebrafish. CONCLUSION: Now that these methods are well-established in our lab, their potential is immense. On one hand, the newly developed models will be of ultimate value to understand the mechanisms underlying MPS sub-cellular pathology, which have to be further elucidated. On the other hand, they will constitute an optimal platform for drug testing in house. Also noteworthy, our models will be published as lab resources and made available for the whole LSD community.

Challenges in the Definitive Diagnosis of Niemann-Pick Type C-Leaky Variants and Alternative Transcripts.

Niemann-Pick type C (NPC, ORPHA: 646) is a neuro-visceral, psychiatric disease caused predominantly by pathogenic variants in the NPC1 gene or seldom in NPC2. The rarity of the disease, and its wide range of clinical phenotypes and ages of onset, turn the diagnosis into a significant challenge. Other than the detailed clinical history, the typical diagnostic work-up for NPC includes the quantification of pathognomonic metabolites. However, the molecular basis diagnosis is still of utmost importance to fully characterize the disorder. Here, the authors provide an overview of splicing variants in the NPC1 and NPC2 genes and propose a new workflow for NPC diagnosis. Splicing variants cover a significant part of the disease-causing variants in NPC. The authors used cDNA analysis to study the impact of such variants, including the collection of data to classify them as leaky or non-leaky pathogenic variants. However, the presence of naturally occurring spliced transcripts can misdiagnose or mask a pathogenic variant and make the analysis even more difficult. Analysis of the NPC1 cDNA in NPC patients in parallel with controls is vital to assess and detect alternatively spliced forms. Moreover, nonsense-mediated mRNA decay (NMD) analysis plays an essential role in evaluating the naturally occurring transcripts during cDNA analysis and distinguishing them from other pathogenic variants' associated transcripts.

Development of Engineered-U1 snRNA Therapies: Current Status.

Splicing of pre-mRNA is a crucial regulatory stage in the pathway of gene expression. The majority of human genes that encode proteins undergo alternative pre-mRNA splicing and mutations that affect splicing are more prevalent than previously thought. Targeting aberrant RNA(s) may thus provide an opportunity to correct faulty splicing and potentially treat numerous genetic disorders. To that purpose, the use of engineered U1 snRNA (either modified U1 snRNAs or exon-specific U1s-ExSpeU1s) has been applied as a potentially therapeutic strategy to correct splicing mutations, particularly those affecting the 5' splice-site (5'ss). Here we review and summarize a vast panoply of studies that used either modified U1 snRNAs or ExSpeU1s to mediate gene therapeutic correction of splicing defects underlying a considerable number of genetic diseases. We also focus on the pre-clinical validation of these therapeutic approaches both in vitro and in vivo, and summarize the main obstacles that need to be overcome to allow for their successful translation to clinic practice in the future.

MicroRNA Profile, Putative Diagnostic Biomarkers and RNA-Based Therapies in the Inherited Lipid Storage Disease Niemann-Pick Type C.

Lipids are essential for cellular function and are tightly controlled at the transcriptional and post-transcriptional levels. Dysregulation of these pathways is associated with vascular diseases, diabetes, cancer, and several inherited metabolic disorders. MicroRNAs (miRNAs), in particular, are a family of post-transcriptional gene repressors associated with the regulation of many genes that encode proteins involved in multiple lipid metabolism pathways, thereby influencing their homeostasis. Thus, this class of non-coding RNAs (ncRNAs) has emerged as a promising therapeutic target for the treatment of lipid-related metabolic alterations. Most of these miRNAs act at an intracellular level, but in the past few years, a role for miRNAs as intercellular signaling molecules has also been uncovered since they can be transported in bodily fluids and used as potential biomarkers of lipid metabolic alterations. In this review, we point out the current knowledge on the miRNA signature in a lysosomal storage disorder associated with lipid dysfunction, Niemann-Pick type C, and discuss the potential use of miRNAs as biomarkers and therapeutic targets for RNA-based therapies.

Family asthma management and physical activity among urban children.

INTRODUCTION: Urban, low-income, and Black and Latino children with asthma experience higher morbidity and poorer outcomes compared to their suburban, higher-income, and non-Latino White counterparts. This risk is further compounded by higher rates of co-occurring overweight or obesity. Physical activity contributes to both asthma and overweight/obesity status, however, little is known about factors that may promote/limit physical activity among youth from low-income, urban, and racial/ethnic backgrounds. This study evaluates associations between asthma management behaviors and physical activity among a sample of racially/ethnically diverse youth with asthma of both healthy weight and overweight/obesity status. METHOD: 147 children with asthma (Mage = 8.3; 50% overweight/obese status, 58% Hispanic/Latino, and 26% Black) and their families completed the Family Asthma Management System Scale (FAMSS; McQuaid et al., 2005) between 2013 and 2015. Physical activity was measured with waist-worn accelerometers. Differences in FAMSS scores by physical activity levels and associations between FAMSS scores and physical activity for the total sample and by race/ethnicity and weight status were evaluated. RESULTS: Children who met recommended physical activity guidelines had higher FAMSS "medication adherence", t(89) = -2.04, p < .05, and "collaboration with health care provider", t(89) = -2.09, p < .05. More optimal "environmental control" related to lower levels of physical activity (ß = -.21, p < .05) while more optimal "medication adherence" was associated with higher levels of physical activity (ß = .21, p < .05). Differences in these associations were identified by race/ethnicity, though not weight status. CONCLUSIONS: Asthma management behaviors were associated with physical activity, with notable differences by race/ethnicity. Tailored interventions simultaneously addressing multiple health behaviors may be warranted. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Hypophosphatemia as a possible biomarker for epileptic seizures at the emergency department.

INTRODUCTION: Hypophosphatemia seems to be temporally associated with seizures, despite not being considered a trigger. We aimed to evaluate hypophosphatemia as a biomarker for seizures. METHODS: Retrospective study, including all consecutive patients admitted at our central hospital's emergency department from 01/01-31/03/2021, screened as "altered consciousness/syncope" or "seizures", with available phosphate levels. RESULTS: 277 patients included, mostly male (61.7%), mean age 64.3 years. Final diagnosis was "seizure" in 34.7% and "other diagnosis" in 65.3%. Patients with seizures were younger (p<0.001), had more frequent epilepsy (p<0.001) and alcoholism (p=0.01). Patients with other diagnosis had more often renal failure (p<0.001) and statin (p=0.02) or diuretic (p=0.003) therapy. Time to blood collection (from the event and from admission) was similar between groups. Patients with seizures had lower mean phosphate levels and more frequent hypophosphatemia (<2.4mg/dL) (p<0.001). Mean CK levels were similar in both groups (p=0.25). HyperCK (>200U/L) was more frequent in the seizure group (p=0.04). Odds ratio (OR) of hypophosphatemia for seizures was 4.330 (CI 95% 2.170-8.640, p<0.001), persisting after correction for confounders. OR of hyperCK was 1.890 (CI 95% 1.060-3.371, p=0.03), losing significance when adjusted. Sensitivity was low for both. Hypophosphatemia was more specific (91.2% vs 79.9%). CONCLUSIONS: Our findings support hypophosphatemia as a seizure biomarker. More studies are needed.

Leukocyte Imbalances in Mucopolysaccharidoses Patients.

Mucopolysaccharidoses (MPSs) are rare inherited lysosomal storage diseases (LSDs) caused by deficient activity in one of the enzymes responsible for glycosaminoglycans lysosomal degradation. MPS II is caused by pathogenic mutations in the IDS gene, leading to deficient activity of the enzyme iduronate-2-sulfatase, which causes dermatan and heparan sulfate storage in the lysosomes. In MPS VI, there is dermatan sulfate lysosomal accumulation due to pathogenic mutations in the ARSB gene, leading to arylsulfatase B deficiency. Alterations in the immune system of MPS mouse models have already been described, but data concerning MPSs patients is still scarce. Herein, we study different leukocyte populations in MPS II and VI disease patients. MPS VI, but not MPS II patients, have a decrease percentage of natural killer (NK) cells and monocytes when compared with controls. No alterations were identified in the percentage of T, invariant NKT, and B cells in both groups of MPS disease patients. However, we discovered alterations in the naïve versus memory status of both helper and cytotoxic T cells in MPS VI disease patients compared to control group. Indeed, MPS VI disease patients have a higher frequency of naïve T cells and, consequently, lower memory T cell frequency than control subjects. Altogether, these results reveal MPS VI disease-specific alterations in some leukocyte populations, suggesting that the type of substrate accumulated and/or enzyme deficiency in the lysosome may have a particular effect on the normal cellular composition of the immune system.

Neurological Disease Modeling Using Pluripotent and Multipotent Stem Cells: A Key Step towards Understanding and Treating Mucopolysaccharidoses.

Despite extensive research, the links between the accumulation of glycosaminoglycans (GAGs) and the clinical features seen in patients suffering from various forms of mucopolysaccharidoses (MPSs) have yet to be further elucidated. This is particularly true for the neuropathology of these disorders; the neurological symptoms are currently incurable, even in the cases where a disease-specific therapeutic approach does exist. One of the best ways to get insights on the molecular mechanisms driving that pathogenesis is the analysis of patient-derived cells. Yet, not every patient-derived cell recapitulates relevant disease features. For the neuronopathic forms of MPSs, for example, this is particularly evident because of the obvious inability to access live neurons. This scenario changed significantly with the advent of induced pluripotent stem cell (iPSC) technologies. From then on, a series of differentiation protocols to generate neurons from iPSC was developed and extensively used for disease modeling. Currently, human iPSC and iPSC-derived cell models have been generated for several MPSs and numerous lessons were learnt from their analysis. Here we review most of those studies, not only listing the currently available MPS iPSC lines and their derived models, but also summarizing how they were generated and the major information different groups have gathered from their analyses. Finally, and taking into account that iPSC generation is a laborious/expensive protocol that holds significant limitations, we also hypothesize on a tempting alternative to establish MPS patient-derived neuronal cells in a much more expedite way, by taking advantage of the existence of a population of multipotent stem cells in human dental pulp to establish mixed neuronal and glial cultures.

SARS-CoV-2 virus classification based on stacked sparse autoencoder.

Since December 2019, the world has been intensely affected by the COVID-19 pandemic, caused by the SARS-CoV-2. In the case of a novel virus identification, the early elucidation of taxonomic classification and origin of the virus genomic sequence is essential for strategic planning, containment, and treatments. Deep learning techniques have been successfully used in many viral classification problems associated with viral infection diagnosis, metagenomics, phylogenetics, and analysis. Considering that motivation, the authors proposed an efficient viral genome classifier for the SARS-CoV-2 using the deep neural network based on the stacked sparse autoencoder (SSAE). For the best performance of the model, we explored the utilization of image representations of the complete genome sequences as the SSAE input to provide a classification of the SARS-CoV-2. For that, a dataset based on k-mers image representation was applied. We performed four experiments to provide different levels of taxonomic classification of the SARS-CoV-2. The SSAE technique provided great performance results in all experiments, achieving classification accuracy between 92% and 100% for the validation set and between 98.9% and 100% when the SARS-CoV-2 samples were applied for the test set. In this work, samples of the SARS-CoV-2 were not used during the training process, only during subsequent tests, in which the model was able to infer the correct classification of the samples in the vast majority of cases. This indicates that our model can be adapted to classify other emerging viruses. Finally, the results indicated the applicability of this deep learning technique in genome classification problems.

Inflammatory and Hemostatic Markers in COVID-19 Patients with Arterial Thrombosis Are Significantly Lower at Hospital Admission than in COVID-19 Patients without Thrombosis.

Patients with Coronavirus disease 2019 (COVID-19) are at increased risk of venous thromboembolism (VTE); however, data on arterial thromboembolism (ATE) is still limited. We report a case series of thromboembolic events (TE) in 290 COVID-19 patients admitted between October and December 2020 to a Portuguese hospital. Admission levels of various laboratory parameters were evaluated and compared between COVID-19 patients with (TE) and without thrombotic events (non-TE). The overall incidence of isolated ATE was 5.52%, isolated VTE was 2.41% and multiple mixed events was 0.7%. A total of 68% events were detected upon admission to the hospital with 76% corresponding to ATE. Admissions to the Intensive Care Unit were higher in patients with TE, when comparing with the non-TE group (44% vs. 27.2%; p = 0.003). Patients with ATE presented significantly lower levels of CRP (p = 0.007), ferritin (p = 0.045), LDH (p = 0.037), fibrinogen (p = 0.010) and higher monocyte counts (p = 0.033) comparatively to the non-TE patients. These results point to an early occurrence of TE and an increased incidence of ATE over VTE. The less prominent inflammation markers in patients with TE and the early presence of TE in patients with otherwise no reason for hospitalization, may suggest a direct role of SARS-CoV-2 in the thrombotic process.

Convolutional Neural Network Applied to SARS-CoV-2 Sequence Classification.

COVID-19, the illness caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus belonging to the Coronaviridade family, a single-strand positive-sense RNA genome, has been spreading around the world and has been declared a pandemic by the World Health Organization. On 17 January 2022, there were more than 329 million cases, with more than 5.5 million deaths. Although COVID-19 has a low mortality rate, its high capacities for contamination, spread, and mutation worry the authorities, especially after the emergence of the Omicron variant, which has a high transmission capacity and can more easily contaminate even vaccinated people. Such outbreaks require elucidation of the taxonomic classification and origin of the virus (SARS-CoV-2) from the genomic sequence for strategic planning, containment, and treatment of the disease. Thus, this work proposes a high-accuracy technique to classify viruses and other organisms from a genome sequence using a deep learning convolutional neural network (CNN). Unlike the other literature, the proposed approach does not limit the length of the genome sequence. The results show that the novel proposal accurately distinguishes SARS-CoV-2 from the sequences of other viruses. The results were obtained from 1557 instances of SARS-CoV-2 from the National Center for Biotechnology Information (NCBI) and 14,684 different viruses from the Virus-Host DB. As a CNN has several changeable parameters, the tests were performed with forty-eight different architectures; the best of these had an accuracy of 91.94 ± 2.62% in classifying viruses into their realms correctly, in addition to 100% accuracy in classifying SARS-CoV-2 into its respective realm, Riboviria. For the subsequent classifications (family, genera, and subgenus), this accuracy increased, which shows that the proposed architecture may be viable in the classification of the virus that causes COVID-19.

Outcomes in Guillain-Barré Syndrome following a second therapeutic cycle - A single-centre retrospective observational study.

INTRODUCTION: The treatment of Guillain-Barré Syndrome (GBS) with intravenous immunoglobulin (IVIg) or plasma exchange (PE) reduces time to clinical recovery. Although sometimes used in clinical practice, the benefit of a second treatment cycle is of unproven benefit. AIMS: Our aim was to compare GBS prognosis in patients treated with one or two cycles of IVIg or PE. METHODS: We selected patients with electrophysiological studies compatible with acute inflammatory demyelinating polyneuropathy or acute motor-sensory axonal neuropathy, from January 2018 to December 2020 in our hospital. Our primary outcome was any improvement in the Guillain-Barré Syndrome Disability Score (GBS-DS) at a mean of twelve weeks. We compared patients treated with one or two treatment cycles with a binary regression. RESULTS: We included twenty-six patients, 65.4% with the classical presentation and 30.8% were treated with two cycles. Patients treated with two cycles presented a higher basal GBS-DS (median 4; IQR 1-5) compared with the group of patients treated with one cycle (median 3; IQR 1-5), p = 0.01. The remaining basal characteristics were similar between groups. The two-cycle treatment regimen did not associate with an improvement in GBS-DS (OR 0.28, 95% CI 0.03-2.35, p = 0.24). Likewise there was no benefit in the need for intensive care unit (OR 2.0, 95% CI 0.37-10.92, p = 0.42) or mechanical invasive ventilation (OR 10.2, 95% CI 0.86-120.96, p = 0.66). DISCUSSION: Our analysis reinforces the recent literature data regarding the absence of benefit of two treatment cycles in patients with GBS.

Splicing Modulation as a Promising Therapeutic Strategy for Lysosomal Storage Disorders: The Mucopolysaccharidoses Example.

Over recent decades, the many functions of RNA have become more evident. This molecule has been recognized not only as a carrier of genetic information, but also as a specific and essential regulator of gene expression. Different RNA species have been identified and novel and exciting roles have been unveiled. Quite remarkably, this explosion of novel RNA classes has increased the possibility for new therapeutic strategies that tap into RNA biology. Most of these drugs use nucleic acid analogues and take advantage of complementary base pairing to either mimic or antagonize the function of RNAs. Among the most successful RNA-based drugs are those that act at the pre-mRNA level to modulate or correct aberrant splicing patterns, which are caused by specific pathogenic variants. This approach is particularly tempting for monogenic disorders with associated splicing defects, especially when they are highly frequent among affected patients worldwide or within a specific population. With more than 600 mutations that cause disease affecting the pre-mRNA splicing process, we consider lysosomal storage diseases (LSDs) to be perfect candidates for this type of approach. Here, we introduce the overall rationale and general mechanisms of splicing modulation approaches and highlight the currently marketed formulations, which have been developed for non-lysosomal genetic disorders. We also extensively reviewed the existing preclinical studies on the potential of this sort of therapeutic strategy to recover aberrant splicing and increase enzyme activity in our diseases of interest: the LSDs. Special attention was paid to a particular subgroup of LSDs: the mucopolysaccharidoses (MPSs). By doing this, we hoped to unveil the unique therapeutic potential of the use of this sort of approach for LSDs as a whole.