Cognitive behavioural therapy for insomnia does not appear to have a substantial impact on early markers of cardiovascular disease: A preliminary randomized controlled trial

According to the World Health Organization, cardiovascular diseases are the leading cause of death in the world. Therefore, early prevention of these diseases is a public health priority. Epidemiological data suggest that insomnia may be a modifiable risk factor for cardiovascular diseases. A randomized controlled trial in a sample of insomnia patients without cardiovascular disease was conducted to investigate the effects of insomnia treatment on early markers of cardiovascular diseases assessed by 24‐hr ambulatory blood pressure, heart rate and heart rate variability monitoring, and morning fasting blood samples. Forty‐six patients with insomnia disorder were randomized to cognitive behavioural therapy for insomnia (CBT‐I; n = 23) or a waitlist control condition (n = 23). Contrary to the hypothesis, intention‐to‐treat analyses did not show any significant treatment effects on early markers of cardiovascular disease (d = 0.0–0.6) despite successful insomnia treatment (d = 1.3). Potential methodological and conceptual reasons for these negative findings are discussed. Future studies might include larger sample sizes that are at risk of cardiovascular diseases and focus on other cardiovascular markers

MIBiG 3.0 : a community-driven effort to annotate experimentally validated biosynthetic gene clusters

With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/

A Momentum for Change? Systemic effects and catalytic impacts of transnational climate action

Non-state and subnational climate actors increasingly commit to act across borders to reduce greenhouse gas emissions, to help communities adapt to climate change, and to push governments into more ambitious climate policies. The effectiveness of such transnational climate initiatives, however, is still largely unknown. Current studies often only seek to estimate the mitigation potential of such initiatives or to study the design elements that may be more or less conducive to their effectiveness. Little is known about the impacts of such initiatives on broader social and environmental goals and about their “catalytic” impacts, that is, whether such transnational initiatives can grow and possibly replicate. Here we develop an approach inspired by political systems theory to reach a fuller understanding of the effectiveness of transnational initiatives. We operationalize a generalized framework through a combination of methodologies, using a new dataset of climate actions under the Momentum for Change program of the United Nations Framework Convention on Climate Change, which we combine with surveys, database analysis, and contextualizing interviews. We conclude with a reflection on the applicability of the framework and a discussion on opportunities for the Momentum for Change program to strengthen its efforts

A Momentum for Change? Systemic effects and catalytic impacts of transnational climate action

Non-state and subnational climate actors increasingly commit to act across borders to reduce greenhouse gas emissions, to help communities adapt to climate change, and to push governments into more ambitious climate policies. The effectiveness of such transnational climate initiatives, however, is still largely unknown. Current studies often only seek to estimate the mitigation potential of such initiatives or to study the design elements that may be more or less conducive to their effectiveness. Little is known about the impacts of such initiatives on broader social and environmental goals and about their “catalytic” impacts, that is, whether such transnational initiatives can grow and possibly replicate. Here we develop an approach inspired by political systems theory to reach a fuller understanding of the effectiveness of transnational initiatives. We operationalize a generalized framework through a combination of methodologies, using a new dataset of climate actions under the Momentum for Change program of the United Nations Framework Convention on Climate Change, which we combine with surveys, database analysis, and contextualizing interviews. We conclude with a reflection on the applicability of the framework and a discussion on opportunities for the Momentum for Change program to strengthen its efforts

Single-Pulse TMS to the Temporo-Occipital and Dorsolateral Prefrontal Cortex Evokes Lateralized Long Latency EEG Responses at the Stimulation Site

Introduction Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) allow for probing cortical functions in health and pathology. However, there is uncertainty whether long-latency TMS-evoked potentials reflect functioning of the targeted cortical area. It has been suggested that components such as the TMS-evoked N100 are stereotypical and related to nonspecific sensory processes rather than transcranial effects of the changing magnetic field. In contrast, TEPs that vary according to the targeted brain region and are systematically lateralized toward the stimulated hemisphere can be considered to reflect activity in the stimulated brain region resulting from transcranial electromagnetic induction. Methods TMS with concurrent 64-channel electroencephalography (EEG) was sequentially performed in homologous areas of both hemispheres. One sample of healthy adults received TMS to the dorsolateral prefrontal cortex; another sample received TMS to the temporo-occipital cortex. We analyzed late negative TEP deflections corresponding to the N100 component in motor cortex stimulation. Results TEP topography varied according to the stimulation target site. Long-latency negative TEP deflections were systematically lateralized (higher in ipsilateral compared to contralateral electrodes) in electrodes over the stimulated brain region. A calculation that removes evoked components that are not systematically lateralized relative to the stimulated hemisphere revealed negative maxima located around the respective target sites. Conclusion TEPs contain long-latency negative components that are lateralized toward the stimulated hemisphere and have their topographic maxima at the respective stimulation sites. They can be differentiated from co-occurring components that are invariable across different stimulation sites (probably reflecting coactivation of peripheral sensory afferences) according to their spatiotemporal patterns. Lateralized long-latency TEP components located at the stimulation site likely reflect activity evoked in the targeted cortex region by direct transcranial effects and are therefore suitable for assessing cortical functions

antiSMASH 7.0:new and improved predictions for detection, regulation, chemical structures and visualisation

Microorganisms produce small bioactive compounds as part of their secondary or specialised metabolism. Often, such metabolites have antimicrobial, anticancer, antifungal, antiviral or other bio-activities and thus play an important role for applications in medicine and agriculture. In the past decade, genome mining has become a widely-used method to explore, access, and analyse the available biodiversity of these compounds. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' (https://antismash.secondarymetabolites.org/) has supported researchers in their microbial genome mining tasks, both as a free to use web server and as a standalone tool under an OSI-approved open source licence. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in archaea, bacteria, and fungi. Here, we present the updated version 7 of antiSMASH. antiSMASH 7 increases the number of supported cluster types from 71 to 81, as well as containing improvements in the areas of chemical structure prediction, enzymatic assembly-line visualisation and gene cluster regulation

Patient safety, cost-effectiveness, and quality of life: reduction of delirium risk and postoperative cognitive dysfunction after elective procedures in older adults—study protocol for a stepped-wedge cluster randomized trial (PAWEL Study)

Abstract Background Postoperative delirium is a common disorder in older adults that is associated with higher morbidity and mortality, prolonged cognitive impairment, development of dementia, higher institutionalization rates, and rising healthcare costs. The probability of delirium after surgery increases with patients’ age, with pre-existing cognitive impairment, and with comorbidities, and its diagnosis and treatment is dependent on the knowledge of diagnostic criteria, risk factors, and treatment options of the medical staff. In this study, we will investigate whether a cross-sectoral and multimodal intervention for preventing delirium can reduce the prevalence of delirium and postoperative cognitive decline (POCD) in patients older than 70 years undergoing elective surgery. Additionally, we will analyze whether the intervention is cost-effective. Methods The study will be conducted at five medical centers (with two or three surgical departments each) in the southwest of Germany. The study employs a stepped-wedge design with cluster randomization of the medical centers. Measurements are performed at six consecutive points: preadmission, preoperative, and postoperative with daily delirium screening up to day 7 and POCD evaluations at 2, 6, and 12 months after surgery. Recruitment goals are to enroll 1500 patients older than 70 years undergoing elective operative procedures (cardiac, thoracic, vascular, proximal big joints and spine, genitourinary, gastrointestinal, and general elective surgery procedures). Discussion Results of the trial should form the basis of future standards for preventing delirium and POCD in surgical wards. Key aims are the improvement of patient safety and quality of life, as well as the reduction of the long-term risk of conversion to dementia. Furthermore, from an economic perspective, we expect benefits and decreased costs for hospitals, patients, and healthcare insurances. Trial registration German Clinical Trials Register, DRKS00013311. Registered on 10 November 2017

Wada test results contribute to the prediction of change in verbal learning and verbal memory function after temporal lobe epilepsy surgery

In recent years, the clinical usefulness of the Wada test (WT) has been debated among researchers in the field. Therefore, we aimed to assess its contribution to the prediction of change in verbal learning and verbal memory function after epilepsy surgery. Data from 56 patients with temporal lobe epilepsy who underwent WT and subsequent surgery were analyzed retrospectively. Additionally, a standard neuropsychological assessment evaluating attentional, learning and memory, visuospatial, language, and executive function was performed both before and 12 months after surgery. Hierarchical linear regression analyses were used to determine the incremental value of WT results over socio-demographic, clinical, and neuropsychological characteristics in predicting postsurgical change in patients’ verbal learning and verbal memory function. The incorporation of WT results significantly improved the prediction models of postsurgical change in verbal learning (∆R2 = 0.233, p = .032) and verbal memory function (∆R2 = 0.386, p = .005). Presurgical performance and WT scores accounted for 41.8% of the variance in postsurgical change in verbal learning function, and 51.1% of the variance in postsurgical change in verbal memory function. Our findings confirm that WT results are of significant incremental value for the prediction of postsurgical change in verbal learning and verbal memory function. Thus, the WT contributes to determining the risks of epilepsy surgery and, therefore, remains an important part of the presurgical work-up of selected patients with clear clinical indications

Artificial intelligence for natural product drug discovery

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to exciting developments in the computational drug design field, facilitating biological activity prediction and de novo drug design for molecular targets of interest. Here, we describe current and future synergies between these developments to effectively identify drug candidates from the plethora of molecules produced by nature. We also discuss how to address key challenges in realizing the potential of these synergies, such as the need for high-quality datasets to train deep learning algorithms and appropriate strategies for algorithm validation. [Abstract copyright: © 2023. Springer Nature Limited.