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Abstract Background Animal systematic reviews are critical to inform translational research. Despite their growing popularity, there is a notable lack of information on their quality, scope, and geographical distribution over time. Addressing this gap is important to maintain their effectiveness in fostering medical advancements. Objective This study aimed to assess the quality and demographic trends of animal systematic reviews in neuroscience, including changes over time. Methods We performed an umbrella review of animal systematic reviews, searching Medline and Embase for reviews until January 27, 2023. A data mining method was developed and validated to automatically evaluate the quality of these reviews. Results From 18‘065 records identified, we included 1‘358 animal systematic reviews in our study. These reviews commonly focus on translational research but with notable topical gaps such as schizophrenia, other psychiatric disorders, and brain tumours. They originate from 64 countries, with the United States, China, the UK, Brazil, and Iran being the most prolific. The automated quality assessment indicated high reliability, with F1-scores over 80% for most criteria. Overall, the reviews were of high quality and the quality improved over time. However, many systematic reviews did not report a pre-registered study protocol. Reviews with a pre-registered protocol generally scored higher in quality. No significant differences in quality were observed between countries. Conclusion Animal systematic reviews in neuroscience are of overall of high quality. Our study highlights specific areas for enhancement such as the recommended pre-publication of study protocols. It also identifies under-represented topics that could benefit from further investigation to inform translational research. Such measures can contribute to the effective translation of animal research findings to clinical applications.

Asthma often remains uncontrolled, despite the fact that the pharmacological treatment has undergone large changes. We studied changes in the treatment of asthma over a 20-year period and identified factors associated with the regular use of inhaled corticosteroid (ICS) treatment. Changes in the use of medication were determined in 4617 randomly selected subjects, while changes in adults with persistent asthma were analysed in 369 participants. The study compares data from three surveys in 24 centres in 11 countries. The use of ICSs increased from 1.7% to 5.9% in the general population and the regular use of ICSs increased from 19% to 34% among persistent asthmatic subjects. The proportion of asthmatic subjects reporting asthma attacks in the last 12 months decreased, while the proportion that had seen a doctor in the last 12 months remained unchanged (42%). Subjects with asthma who had experienced attacks or had seen a doctor were more likely to use ICSs on a regular basis. Although ICS use has increased, only one-third of subjects with persistent asthma take ICSs on a regular basis. Less than half had seen a doctor during the last year. This indicates that underuse of ICSs and lack of regular healthcare contacts remains a problem in the management of asthma.

Summary: Background: Despite successes in multiple sclerosis (MS) drug development, the effectiveness of animal studies in predicting successful bench-to-bedside translation is uncertain. Our goal was to identify predictors of successful animal-to-human translation for MS by systematically comparing animal studies of approved disease-modifying therapies (DMTs) with those that failed in clinical trials due to efficacy or safety concerns. Methods: Systematic review of animal studies testing MS DMTs, identified from searches in PubMed and EMBASE. A random effect meta-analysis was fitted to the data to compare outcome effect sizes for approved versus failed DMTs. Effect sizes and testing under diverse experimental conditions were assessed as potential predictors for successful translation. Findings: We included 497 animal studies, covering 15 approved and 11 failed DMTs, tested in approximately 30′000 animals. DMTs were tested in a small repertoire of experimental parameters: about 86% of studies used experimental autoimmune encephalomyelitis (EAE), 80% used mice, and 76% used female animals. There was no association between animal study outcomes or testing DMTs under varied conditions (e.g., different laboratories or models) and successful approval. Surprisingly, 91% of animal studies were published after first-in-MS trial and 91% after official regulatory approval. Interpretation: Our findings emphasize the complexity in carrying drugs from animals to clinical practice. Specific challenges include limited experimental methods in animal research and a disconnect between preclinical and clinical research. We advocate for efforts to streamline drug development for MS to improve animal research's relevance for patients. Funding: NIH, Swiss National Science Foundation, Universities Federation for Animal Welfare.

Background and methodsSystematic reviews, i.e., research summaries that address focused questions in a structured and reproducible manner, are a cornerstone of evidence-based medicine and research. However, certain steps in systematic reviews, such as data extraction, are labour-intensive, which hampers their feasibility, especially with the rapidly expanding body of biomedical literature. To bridge this gap, we aimed to develop a data mining tool in the R programming environment to automate data extraction from neuroscience in vivo publications. The function was trained on a literature corpus (n = 45 publications) of animal motor neuron disease studies and tested in two validation corpora (motor neuron diseases, n = 31 publications; multiple sclerosis, n = 244 publications).ResultsOur data mining tool, STEED (STructured Extraction of Experimental Data), successfully extracted key experimental parameters such as animal models and species, as well as risk of bias items like randomization or blinding, from in vivo studies. Sensitivity and specificity were over 85% and 80%, respectively, for most items in both validation corpora. Accuracy and F1-score were above 90% and 0.9 for most items in the validation corpora, respectively. Time savings were above 99%.ConclusionsOur text mining tool, STEED, can extract key experimental parameters and risk of bias items from the neuroscience in vivo literature. This enables the tool's deployment for probing a field in a research improvement context or replacing one human reader during data extraction, resulting in substantial time savings and contributing towards the automation of systematic reviews.

BackgroundImproving health-related quality of life (HRQoL) is an important disease management goal in persons with Multiple Sclerosis (PwMS). HRQoL decreases with increasing age and prolonged disease duration; other factors remain less understood.ObjectiveTo identify associations of multiple sclerosis (MS) disease characteristics and symptom burden with low HRQoL.MethodsUsing the Swiss MS Registry, we applied quantile regression adjusted for age and MS disease duration to determine 25th (low HRQoL) and 75th (high HRQoL) percentiles of the EuroQol-5-Dimension (EQ-5D) distribution for PwMS. We compared PwMS across HRQoL groups by analyzing differences in sociodemographics, symptom burden, MS risk factors, gait impairment, and the MS Severity Score (MSSS), all measured at the same time as HRQoL. The analyses included descriptive methods, multivariable multinomial regression, and simultaneous quantile regression as a sensitivity analysis.ResultsWe included 1697 PwMS with median age and time-to-diagnosis of 49 and 9 years. Multivariable regression revealed low HRQoL to be associated with receiving invalidity insurance benefits, reporting depression, muscle weakness, memory problems, pain, and severe gait impairment. The analysis for individuals with available MSSS (n = 937) showed an increasing probability of low HRQoL with higher MSSS.ConclusionOur segmentation method identified symptom burden and MS severity as factors associated with low HRQoL. Pharmacological and non-pharmacological MS symptom management, especially for depression, fatigue, pain, and muscle weakness, may warrant increased attention to preserve or improve HRQoL.

Deep Brain Stimulation (DBS) represents a key area of neuromodulation that has gained wide adoption for the treatment of neurological and experimental testing for psychiatric disorders. It is associated with specific therapeutic effects based on the precision of an evolving mechanistic neuroscientific understanding. At the same time, there are obstacles to achieving symptom relief because of the incompleteness of such an understanding. These obstacles are at least in part based on the complexity of neuropsychiatric disorders and the incompleteness of DBS devices to represent prosthetics that modulate the breadth of pathological processes implicated in these disorders. Neuroprostheses, such as an implanted DBS system, can have vast effects on subjects in addition to the specific neuropsychiatric changes they are intended to produce. These effects largely represent blind spots in the current debate on neuromodulation. Anthropological accounts can illustrate the broad existential dimensions of patients' illness and responses to neural implants. In combination with current neuroscientific understanding, neuropsychiatric anthropology may illuminate the possibilities and limits of neurodevices as technical "world enablers". [ABSTRACT FROM AUTHOR]

Lucid dreaming offers the chance to investigate dreams from within a dream and by real-time dialogue between experimenters and dreamers during REM sleep. This state of consciousness opens a new experimental venue for dream research. However, laboratory study in this field is limited due to the rarity of lucid dreamers. In a previous study, we were able to induce in 50% of the participants a lucid dream in a single sleep laboratory night by combining a wake-up-back-to-bed (WBTB) sleep routine and a mnemonic method (Mnemonic Induction of Lucid Dreams, MILD). In three experiments, we tried to replicate our earlier findings while we adapted our procedure in shortening (Exp1–3: 4.5 vs. 6 h of uninterrupted sleep in the first half of the night), simplifying (Exp2: time-based wakening vs. REM wakening in the second half of the night), and applying another induction technique (Exp3: reality testing vs. MILD). In the three conditions, four out of 15 (26%), zero out of 20 (0%), and three out of 15 (20%) participants reported a lucid dream. Compared to the original study, the earlier sleep interruption seems to reduce the lucid dream induction rate. Furthermore, without REM awakenings in the morning, lucid dream induction failed, whereas reality testing showed a lower success rate compared to MILD. Further systematic sleep laboratory studies are needed to develop reliable techniques for lucid dream research.

Introduction: Motor complications (MCs) compromise therapy in many patients suffering from Parkinson’s Disease. By achieving more physiologic stimulation of dopamine-receptors, the continuous dopamine stimulation hypothesis suggests that longer-acting levodopa formulations may improve outcome. The aim of this study was to compare the duration until onset of MCs and motor disease progression in patients during their treatment initiation with either an immediate (IR) or a combined rapid- and sustained-release (i.e. dual-release; DR) levodopa formulation. Methods: Using a sample of 69 patients, we applied time-varying survival regression analyses and linear mixed effect models to analyze the data. The latter involved preprocessing of the data to temporally align the response and predictors, including analyzing the extent of visit irregularity and potential predictors of visit intensity. Results: This retrospective study suggests that levodopa-benserazide DR is not superior to levodopa-benserazide IR in affecting duration until MCs and disease progression. Conversely, using DR levodopa-benserazide, similar disease progression was achieved with lower and more constant doses. Conclusions: The effects of DR levodopa-benserazide might not be strong enough to delay onset of MCs. The development of more powerful levodopa formulations remains a pressing clinical need.

Background and methods: Systematic reviews, i.e., research summaries that address focused questions in a structured and reproducible manner, are a cornerstone of evidence-based medicine and research. However, certain steps in systematic reviews, such as data extraction, are labour-intensive, which hampers their feasibility, especially with the rapidly expanding body of biomedical literature. To bridge this gap, we aimed to develop a data mining tool in the R programming environment to automate data extraction from neuroscience in vivo publications. The function was trained on a literature corpus (n = 45 publications) of animal motor neuron disease studies and tested in two validation corpora (motor neuron diseases, n = 31 publications; multiple sclerosis, n = 244 publications). Results: Our data mining tool, STEED (STructured Extraction of Experimental Data), successfully extracted key experimental parameters such as animal models and species, as well as risk of bias items like randomization or blinding, from in vivo studies. Sensitivity and specificity were over 85% and 80%, respectively, for most items in both validation corpora. Accuracy and F1-score were above 90% and 0.9 for most items in the validation corpora, respectively. Time savings were above 99%. Conclusions: Our text mining tool, STEED, can extract key experimental parameters and risk of bias items from the neuroscience in vivo literature. This enables the tool's deployment for probing a field in a research improvement context or replacing one human reader during data extraction, resulting in substantial time savings and contributing towards the automation of systematic reviews. [ABSTRACT FROM AUTHOR]

Background: Improving health-related quality of life (HRQoL) is an important disease management goal in persons with Multiple Sclerosis (PwMS). HRQoL decreases with increasing age and prolonged disease duration; other factors remain less understood. Objective: To identify associations of multiple sclerosis (MS) disease characteristics and symptom burden with low HRQoL. Methods: Using the Swiss MS Registry, we applied quantile regression adjusted for age and MS disease duration to determine 25th (low HRQoL) and 75th (high HRQoL) percentiles of the EuroQol-5-Dimension (EQ-5D) distribution for PwMS. We compared PwMS across HRQoL groups by analyzing differences in sociodemographics, symptom burden, MS risk factors, gait impairment, and the MS Severity Score (MSSS), all measured at the same time as HRQoL. The analyses included descriptive methods, multivariable multinomial regression, and simultaneous quantile regression as a sensitivity analysis. Results: We included 1697 PwMS with median age and time-to-diagnosis of 49 and 9 years. Multivariable regression revealed low HRQoL to be associated with receiving invalidity insurance benefits, reporting depression, muscle weakness, memory problems, pain, and severe gait impairment. The analysis for individuals with available MSSS (n = 937) showed an increasing probability of low HRQoL with higher MSSS. Conclusion: Our segmentation method identified symptom burden and MS severity as factors associated with low HRQoL. Pharmacological and non-pharmacological MS symptom management, especially for depression, fatigue, pain, and muscle weakness, may warrant increased attention to preserve or improve HRQoL. [ABSTRACT FROM AUTHOR]

Background: Diagnostic errors in multiple sclerosis (MS) impact patients and healthcare systems. Objectives: This study aimed to determine the prevalence of MS misdiagnosis and underdiagnosis, time delay in reaching a correct diagnosis and potential impact of sex. Methods: Systematic review and meta-analysis on MS diagnostic errors. Results: Out of 3910 studies, we included 62 for a qualitative synthesis and 24 for meta-analyses. Frequency of misdiagnosis (incorrect assignment of an MS diagnosis) ranged from 5% to 41%, with a pooled proportion based on six studies of 15% (95% CI: 9%–26%, n = 1621). The delay to rectify a misdiagnosis ranged from 0.3 to 15.9 years. Conversely, underdiagnosis (unrecognized diagnosis of MS) ranged from 3% to 58%, with a pooled proportion in four studies of 36% (95% CI: 20%–55%, n = 728). Pooling seven studies comprising 2851 individuals suggested a diagnostic delay to establish a correct MS diagnosis of 17.3 months (95% CI: 11.9–22.7) in patients underdiagnosed. In a meta-analysis of five studies, women were 2.1 times more likely to be misdiagnosed with MS compared to men (odds ratio, 95% CI: 1.53–2.86). Conclusion: This study provides summary-level evidence for the high prevalence of MS misdiagnosis and underdiagnosis. Future studies are needed to understand the causes of these diagnostic challenges in MS care. [ABSTRACT FROM AUTHOR]