Green energy: identifying development trends in society using Twitter data mining to make strategic decisions

This study analyzes Twitter’s contribution to green energy. More than 200,000 global tweets sent during 2020 containing the terms “green energy” OR “greenenergy” were analyzed. The tweets were captured by web scraping and processed using algorithms and techniques for the analysis of massive datasets from social networks. In particular, relationships between users (through mentions) were determined according to the Louvain multilevel algorithm to identify communities and analyze global (density and centralization) and node-level (centrality) metrics. Subsequently, the content of the conversation was subject to semantic analysis (co-occurrence of the most relevant words), hashtag analysis (frequency analysis), and sentiment analysis (using the Vader model). The results reveal nine main communities and their leaders, as well as three main topics of conversation and the emotional state of the digital discussion. The main communities revolve around politics, socioeconomic issues, and environmental activism, while the conversations, which have developed mostly in positive terms, focus on green energy sources and storage, being aligned with the main communities identified, i.e., on political, socioeconomic, and climate change issues. Although most of the conversations have been about socioeconomic issues, the presence of leading company accounts was minor. The main aim of this work is to take the first steps toward an innovative competitive intelligence methodology to study and determine trends within different scientific fields or technologies in society that will enable strategic decisions to be made

Synthetic multistability in mammalian cells

In multicellular organisms, gene regulatory circuits generate thousands of molecularly distinct, mitotically heritable states, through the property of multistability. Designing synthetic multistable circuits would provide insight into natural cell fate control circuit architectures and allow engineering of multicellular programs that require interactions among cells in distinct states. Here we introduce MultiFate, a naturally-inspired, synthetic circuit that supports long-term, controllable, and expandable multistability in mammalian cells. MultiFate uses engineered zinc finger transcription factors that transcriptionally self-activate as homodimers and mutually inhibit one another through heterodimerization. Using model-based design, we engineered MultiFate circuits that generate up to seven states, each stable for at least 18 days. MultiFate permits controlled state-switching and modulation of state stability through external inputs, and can be easily expanded with additional transcription factors. Together, these results provide a foundation for engineering multicellular behaviors in mammalian cells

Immunotherapy for people with clinically isolated syndrome or relapsing-remitting multiple sclerosis: treatment response by demographic, clinical, and biomarker subgroups (PROMISE)—a systematic review protocol

Immunotherapy; Multiple sclerosis; Treatment responseInmunoterapia; Esclerosis múltiple; Respuesta al tratamientoImmunoteràpia; Esclerosi múltiple; Resposta al tractamentBackground Multiple sclerosis (MS) is an inflammatory and degenerative disease of the central nervous system with an increasing worldwide prevalence. Since 1993, more than 15 disease-modifying immunotherapies (DMTs) have been licenced and have shown moderate efficacy in clinical trials. Based on the heterogeneity of the disease and the partial effectiveness of therapies, a personalised medicine approach would be valuable taking individual prognosis and suitability of a chosen therapy into account to gain the best possible treatment effect. The primary objective of this review is to assess the differential treatment effects of all approved DMTs in subgroups of adults with clinically isolated syndrome or relapsing forms of MS. We will analyse possible treatment effect modifiers (TEM) defined by baseline demographic characteristics (gender, age), and diagnostic (i.e. MRI measures) and clinical (i.e. relapses, disability level) measures of MS disease activity. Methods We will include all published and accessible unpublished primary and secondary analyses of randomised controlled trials (RCTs) with a follow-up of at least 12 months investigating the efficacy of at least one approved DMT, with placebo or other approved DMTs as control intervention(s) in subgroups of trial participants. As the primary outcome, we will address disability as defined by the Expanded Disability Status Scale or multiple sclerosis functional composite scores followed by relapse frequency, quality of life measures, and side effects. MRI data will be analysed as secondary outcomes. MEDLINE, EMBASE, CINAHL, LILACS, CENTRAL and major trial registers will be searched for suitable studies. Titles and abstracts and full texts will be screened by two persons independently using Covidence. The risk of bias will be analysed based on the Cochrane “Risk of Bias 2” tool, and the certainty of evidence will be assessed using GRADE. Treatment effects will be reported as rate ratio or odds ratio. Primary analyses will follow the intention-to-treat principle. Meta-analyses will be carried out using random-effects models. Discussion Given that individual patient data from clinical studies are often not available, the review will allow to analyse the evidence on TEM in MS immunotherapy and thus support clinical decision making in individual cases.Open Access funding enabled and organized by Projekt DEAL. Federal Ministry of Education and Research (BMBF), Germany (grant 01KG1804). The funding body had no influence on the design of the protocol

Consensus on early detection of disease progression in patients with multiple sclerosis

Consensus; Early detection; Secondary progressive multiple sclerosisConsenso; Detección precoz; Esclerosis múltiple progresiva secundariaConsens; Detecció precoç; Esclerosi múltiple progressiva secundàriaBackground: Early identification of the transition from relapsing-remitting multiple sclerosis (RRMS) to secondary progressive MS (SPMS) can be challenging for clinicians, as diagnostic criteria for SPMS are primarily based on physical disability and a holistic interpretation. Objective: To establish a consensus on patient monitoring to identify promptly disease progression and the most useful clinical and paraclinical variables for early identification of disease progression in MS. Methods: A RAND/UCLA Appropriateness Method was used to establish the level of agreement among a panel of 15 medical experts in MS. Eighty-three items were circulated to the experts for confidential rating of the grade of agreement and recommendation. Consensus was defined when ≥66% agreement or disagreement was achieved. Results: Consensus was reached in 72 out of 83 items (86.7%). The items addressed frequency of follow-up visits, definition of progression, identification of clinical, cognitive, and radiological assessments as variables of suspected or confirmed SPMS diagnosis, the need for more accurate assessment tools, and the use of promising molecular and imaging biomarkers to predict disease progression and/or diagnose SPMS. Conclusion: Consensus achieved on these topics could guide neurologists to identify earlier disease progression and to plan targeted clinical and therapeutic interventions during the earliest stages of SPMS.This work was supported by Novartis. Meetings, data analysis, and medical writing assistance were funded by Novartis. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Serum Neurofilament Levels and PML Risk in Patients With Multiple Sclerosis Treated With Natalizumab

Natalizumab; Neurofilamento séricoNatalizumab; Neurofilament sèricNatalizumab; Serum NeurofilamentObjectives The study aimed to assess the potential for serum neurofilament light chain (NFL) levels to predict the risk of progressive multifocal leukoencephalopathy (PML) in natalizumab (NTZ)-treated patients with multiple sclerosis (MS) and to discriminate PML from MS relapses. Methods NFL levels were measured with single molecule array (Simoa) in 4 cohorts: (1) a prospective cohort of patients with MS who developed PML under NTZ therapy (pre-PML) and non-PML NTZ-treated patients (NTZ-ctr); (2) a cohort of patients whose blood was collected during PML; (3) an independent cohort of non-PML NTZ-treated patients with serum NFL determinations at 2 years (replication cohort); and (4) a cohort of patients whose blood was collected during exacerbations. Results Serum NFL levels were significantly increased after 2 years of NTZ treatment in pre-PML patients compared with NTZ-ctr. The prognostic performance of serum NFL levels to predict PML development at 2 years was similar in the NTZ-ctr group and replication cohort. Serum NFL levels also distinguished PML from MS relapses and were 8-fold higher during PML compared with relapses. Conclusions These results support the use of serum NFL levels in clinical practice to identify patients with relapsing-remitting MS at higher PML risk and to differentiate PML from clinical relapses in NTZ-treated patients. Classification of Evidence This study provides Class I evidence that serum NFL levels can identify NTZ-treated patients with MS who will develop PML with a sensitivity of 67% and specificity of 80%

Association of magnetic resonance imaging phenotypes and serum biomarker levels with treatment response and long-term disease outcomes in multiple sclerosis patients

Magnetic resonance imaging; Multiple sclerosis; Neurofilament light chainImagen de resonancia magnética; Esclerosis múltiple; Cadena ligera de neurofilamentoImatges per ressonància magnètica; Esclerosi múltiple; Cadena lleugera de neurofilamentBackground and purpose The aim was to evaluate whether magnetic resonance imaging (MRI) phenotypes defined by inflammation and neurodegeneration markers correlate with serum levels of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in relapsing–remitting multiple sclerosis (RRMS) patients; and to explore the role of radiological phenotypes and biomarker levels on treatment response and long-term prognostic outcomes. Methods Magnetic resonance imaging scans from 80 RRMS patients were classified at baseline of interferon-beta (IFNβ) treatment into radiological phenotypes defined by high and low inflammation and high and low neurodegeneration, based on the number of contrast-enhancing lesions, brain parenchymal fraction and the relative volume of non-enhancing black holes on T1-weighted images. Serum levels of NfL and GFAP were measured at baseline with single molecule array (Simoa) assays. MRI phenotypes and serum biomarker levels were investigated for their association with IFNβ response, and times to second-line therapies, secondary-progressive MS (SPMS) conversion and Expanded Disability Status Scale (EDSS) 6.0. Results Mean (SD) follow-up was 17 (2.9) years. Serum NfL levels and GFAP were higher in the high inflammation (p = 0.04) and high neurodegeneration phenotypes (p = 0.03), respectively. The high inflammation phenotype was associated with poor response to IFNβ treatment (p = 0.04) and with shorter time to second-line therapies (p = 0.04). In contrast, the high neurodegeneration phenotype was associated with shorter time to SPMS (p = 0.006) and a trend towards shorter time to EDSS 6.0 (p = 0.09). High serum NfL levels were associated with poor response to IFNβ treatment (p = 0.004). Conclusions Magnetic resonance imaging phenotypes defined by inflammation and neurodegeneration correlate with serum biomarker levels, and both have prognostic implications in treatment response and long-term disease outcomes

Wide-Field Survey of Emission-line Stars in IC 1396

We have made an extensive survey of emission-line stars in the IC 1396 HII region to investigate the low-mass population of pre-main sequence (PMS) stars. A total of 639 H-alpha emission-line stars were detected in an area of 4.2 deg^2 and their i'-photometry was measured. Their spatial distribution exhibits several aggregates near the elephant trunk globule (Rim A) and bright-rimmed clouds at the edge of the HII region (Rim B and SFO 37, 38, 39, 41), and near HD 206267, which is the main exciting star of the HII region. Based on the extinction estimated from the near-infrared (NIR) color-color diagram, we have selected pre-main sequence star candidates associated with IC 1396. The age and mass were derived from the extinction corrected color-magnitude diagram and theoretical pre-main sequence tracks. Most of our PMS candidates have ages of < 3 Myr and masses of 0.2-0.6 Mo. Although it appears that only a few stars were formed in the last 1 Myr in the east region of the exciting star, the age difference among subregions in our surveyed area is not clear from the statistical test. Our results may suggest that massive stars were born after the continuous formation of low-mass stars for 10 Myr. The birth of the exciting star could be the late stage of slow but contiguous star formation in the natal molecular cloud. It may have triggered to form many low-mass stars at the dense inhomogeneity in and around the HII region by a radiation-driven implosion.Comment: 48 pages, 12 figures, 5 tables, accepted for publication in A

Usefulness of sputum gram stain for etiologic diagnosis in community-acquired pneumonia: a systematic review and meta-analysis

Background: implementation of sputum Gram stain in the initial assessment of community-acquired pneumonia (CAP) patients is still controversial. We performed a systematic review and meta-analysis to investigate the usefulness of sputum Gram stain for defining the etiologic diagnosis of CAP in adult patients. Methods: we systematically searched the Medline, Embase, Science Direct, Scopus and LILACS databases for full-text articles. Relevant studies were reviewed by at least three investigators who extracted the data, pooled them using a random effects model, and carried out quality assessment. For each bacterium (Streptococcus pneumoniae, Haemophilus influenzae, Staphylococcus aureus, and Gram-negative bacilli), pooled sensitivity, specificity, positive and negative likelihood ratios were reported. Results: after a review of 3539 abstracts, 20 articles were included in the present meta-analysis. The studies included yielded 5619 patients with CAP. Pooled sensitivity and pooled specificity of sputum Gram stain were 0.59 (95% CI, 0.56-0.62) and 0.87 (95% CI, 0.86-0.89) respectively for S. pneumoniae, 0.78 (95% CI, 0.72-0.84) and 0.96 (95% CI, 0.94-0.97) for H. influenzae, 0.72 (95% CI, 0.53-0.87) and 0.97 (95% CI, 0.95-0.99) for S. aureus, and 0.64 (95% CI, 0.49-0.77) and 0.99 (95% CI, 0.97-0.99) for Gram-negative bacilli. Conclusion: Sputum Gram stain test is sensitive and highly specific for identifying the main causative pathogens in adult patients with CAP

Assessing the presence of oligoclonal IgM bands as a prognostic biomarker of cognitive decline in the early stages of multiple sclerosis

Bandes oligoclonals; Esclerosi múltiple; Disfunció cognitivaBandas oligoclonales; Esclerosis múltiple; Disfunción cognitivaOligoclonal bands; Multiple sclerosis; Cognitive dysfunctionBackground: An association has been found between the presence of lipid-specific oligoclonal IgM bands (LS-OCMB) in cerebrospinal fluid and a more severe clinical multiple sclerosis course. Objective: To investigate lipid-specific oligoclonal IgM bands as a prognostic biomarker of cognitive impairment in the early stages of multiple sclerosis. Methods: Forty-four patients underwent neuropsychological assessment at baseline and 4 years. Cognitive performance at follow-up was compared adjusting by age, education, anxiety-depression, and baseline performance. Results: LS-OCMB+ patients only performed worse for Long-Term Storage in the Selective Reminding Test (p = .018). Conclusion: There are no remarkable cognitive differences between LS-OCMB- and LS-OCMB+ patients in the early stages of MS

Age-dependent multisystem parkinsonian features in a novel neuromelanin-producing transgenic mouse model

Trabajo presentado en el 19th National Meeting of the Spanish Society of Neuroscience, celebrado en Lleida (España), del 3 al 5 de noviembre de 2021Parkinson’s disease (PD) is characterized by a preferential degeneration of neurons that accumulate with age the pigment neuromelanin, especially neurons from substantia nigra (SN) and locus coeruleus (LC). We aim to characterize the consequences of age-dependent intracellular neuromelanin accumulation in catecholaminergic neuronal populations to understand the relationship between this process and the vulnerability of these cells in PD, as well as its impact on healthy brain aging. We previously generated a rat model exhibiting progressive unilateral SN production of neuromelanin that showed parkinsonian-like neuropathology and motor deficits1. Here, we generated a new neuromelanin-producing rodent model, based on the tissue-specific constitutive expression of human tyrosinase (hTyr) under the tyrosine hydroxylase (TH) promoter (Tg-TH-hTyr), that mimics the bilateral distribution of pigmentation within the aging human brain (i.e. catecholaminergic groups A1-A142). In parallel to neuromelanin intracellular buildup, Tg-TH-hTyr mice exhibited major PD features, including motor and non-motor behavioral alterations, inclusion body formation and degeneration of specific catecholaminergic neuronal groups. Genome-wide transcriptomic analysis of neuromelanin-laden neurons revealed alterations in PD-related biological pathways that correlate with human PD postmortem studies. Our results show that modelling human neuromelanin accumulation in rodents leads to age-dependent catecholaminergic dysfunction and molecular alterations resulting in motor and non-motor deficits, which is relevant to PD pathology and brain aging.Peer reviewe