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A substantial change towards more pro-environmental behavior (PEB) is essential to reach the required reduction in greenhouse gas emissions and mitigate climate change. These behavior changes will have consequences on people’s daily lives and thus might affect their well-being. Previous research generally finds positive correlations between PEB and well-being. This meta-analysis explores whether the relationship between PEB and well-being depends on the environmental impact of the performed PEB. Overall, the paper finds a small but significant positive relation between PEB and well-being. When accounting for the environmental impact of the PEB, however, the positive relationship only remains for low-impact PEB. The meta-analysis does not provide any evidence that engaging in high-impact PEB relates to well-being. Consequently, these findings demonstrate that there is more ambiguity in the relationship between PEB and well-being than previously described in the literature and that the environmental impact of PEB matters when evaluating its relationship with well-being. These findings have important implications for policy-making trying to facilitate mitigation efforts that ultimately aim to balance the well-being of the current and future generations.

Hereditary spastic paraplegia (HSP) is a diverse group of motor neuron disorders that is characterized by lower-limb weakness and spasticity due to a length-dependent axonopathy of the corticospinal tract. HSP type 11 (SPG11-HSP) is the most frequent form of autosomal recessive HSP and is caused by pathogenic variants in the SPG11gene, encoding the protein spatacsin. In this complicated form, motor neuron symptoms are accompanied by a thin corpus callosum, white matter abnormalities, and progressive cognitive decline. Currently, there are no effective treatments or reliable biomarkers available. Although inflammation is pivotal in several neurological diseases, SPG11-HSP research has mainly focussed on the neurodegenerative hallmarks. For this reason, we hypothesized that neuroinflammation is a significant disease mechanism in SPG11-HSP patients which can contribute to neurodegeneration. Both aspects of the disease can therefore provide potential biomarkers for monitoring disease progression and validating treatment strategies.We performed a detailed immunological characterization of SPG11-HSP patients by analyzing human postmortem brains, peripheral blood samples, and induced pluripotent stem cell-derived microglia-like cells (iMGL). Postmortem examination of three SPG11-HSP patient brains revealed profound microgliosis, signatures of disease-associated microglia, and lipid accumulations in myeloid cells. In a larger patient cohort, the ratio of proinflammatory monocytes in the blood was increased along with elevated serum levels of IL-6 that correlated with disease severity. Moreover, we delineated a novel interplay between SPG11 and IFNγ. In control iMGL, IFNγ triggered the upregulation of SPG11, whereas, in patient-specific SPG11 iMGL, IFNγ caused hyperactivation, which was characterized by increased secretion of inflammatory factors, such as CXCL10. Enhanced STAT1 phosphorylation was identified as a mechanism connecting IFNγ-mediated hyperactivation and SPG11 loss of function. Blocking STAT1 signaling by ruxolitinib prevented the upregulation of CXCL10 and rescued the neurotoxic effects of SPG11 iMGL. Examination of human postmortem brain tissue and an Spg11-/-mouse model confirmed increased numbers of STAT1+ cells. These findings highlight the impact of innate immunity in SPG11-HSP and indicate the potential of immunomodulators to slow down disease progression.To evaluate such therapeutic approaches, biomarkers are essential to monitor disease progression. For other neurodegenerative diseases, peripheral neurofilaments have emerged as promising indicators of neuronal damage. Therefore, we aimed to assess the potential of neurofilament light (NfL) and heavy (NfH) chains as biomarkers of neurodegeneration in SPG11-HSP. Both NfL and NfH were significantly increased in the plasma of SPG11-HSP patients with excellent discriminatory performance from controls and other HSP types. In a follow-up study, the NfL level in SPG11-HSP patients increased further within one year. These data emphasize the potential of neurofilaments as a fluidic biomarker for monitoring disease progression in this complicated subtype of HSP.Overall, this study demonstrates the role of innate immunity on SPG11-related neurodegeneration and highlights inflammatory factors and neurofilaments as potential biomarkers for SPG11-HSP.

Background Stroke-associated pneumonia (SAP) is a preventable determinant for poor outcome after stroke. Machine learning (ML) using large-scale clinical data warehouses may be able to predict SAP and identify patients for targeted interventions. The aim of this study was to develop a prediction model for identifying clinically apparent SAP using automated ML. Methods The ML model used clinical and laboratory parameters along with heart rate (HR), heart rate variability (HRV), and blood pressure (BP) values obtained during the first 48 h after stroke unit admission. A logistic regression classifier was developed and internally validated with a nested-cross-validation (nCV) approach. For every shuffle, the model was first trained and validated with a fixed threshold for 0.9 sensitivity, then finally tested on the out-of-sample data and benchmarked against a widely validated clinical score (A2DS2). Results We identified 2390 eligible patients admitted to two-stroke units at Charité between October 2020 and June 2023, of whom 1755 had all parameters available. SAP was diagnosed in 96/1755 (5.5%). Circadian profiles in HR, HRV, and BP metrics during the first 48 h after admission exhibited distinct differences between patients with SAP diagnosis vs. those without. CRP, mRS at admission, leukocyte count, high-frequency power in HRV, stroke severity at admission, sex, and diastolic BP were identified as the most informative ML features. We obtained an AUC of 0.91 (CI 0.88–0.95) for the ML model on the out-of-sample data in comparison to an AUC of 0.84 (CI 0.76–0.91) for the previously established A2DS2 score ( p  < 0.001). The ML model provided a sensitivity of 0.87 (CI 0.75–0.97) with a corresponding specificity of 0.82 (CI 0.78–0.85) which outperformed the A2DS2 score for multiple cutoffs. Conclusions Automated, data warehouse-based prediction of clinically apparent SAP in the stroke unit setting is feasible, benefits from the inclusion of vital signs, and could be useful for identifying high-risk patients or prophylactic pneumonia management in clinical routine.

Biallelic loss of SPG11 function constitutes the most frequent cause of complicated autosomal recessive hereditary spastic paraplegia (HSP) with thin corpus callosum, resulting in progressive multisystem neurodegeneration. While the impact of neuroinflammation is an emerging and potentially treatable aspect in neurodegenerative diseases and leukodystrophies, the role of immune cells in SPG11–HSP patients is unknown. Here, we performed a comprehensive immunological characterization of SPG11–HSP, including examination of three human postmortem brain donations, immunophenotyping of patients’ peripheral blood cells and patient-specific induced pluripotent stem cell-derived microglia-like cells (iMGL). We delineate a previously unknown role of innate immunity in SPG11–HSP. Neuropathological analysis of SPG11–HSP patient brain tissue revealed profound microgliosis in areas of neurodegeneration, downregulation of homeostatic microglial markers and cell-intrinsic accumulation of lipids and lipofuscin in IBA1 + cells. In a larger cohort of SPG11–HSP patients, the ratio of peripheral classical and intermediate monocytes was increased, along with increased serum levels of IL-6 that correlated with disease severity. Stimulation of patient-specific iMGLs with IFNγ led to increased phagocytic activity compared to control iMGL as well as increased upregulation and release of proinflammatory cytokines and chemokines, such as CXCL10. On a molecular basis, we identified increased STAT1 phosphorylation as mechanism connecting IFNγ-mediated immune hyperactivation and SPG11 loss of function. STAT1 expression was increased both in human postmortem brain tissue and in an Spg11 –/– mouse model. Application of an STAT1 inhibitor decreased CXCL10 production in SPG11 iMGL and rescued their toxic effect on SPG11 neurons. Our data establish neuroinflammation as a novel disease mechanism in SPG11–HSP patients and constitute the first description of myeloid cell/ microglia activation in human SPG11–HSP. IFNγ/ STAT1-mediated neurotoxic effects of hyperreactive microglia upon SPG11 loss of function indicate that immunomodulation strategies may slow down disease progression.

Current protocols converting human induced pluripotent stem cells (iPSCs) into induced microglia-like cells (iMGL) are either dependent on overexpression of transcription factors or require substantial experience in stem-cell technologies. Here, we developed an easy-to-use two-step protocol to convert iPSCs into functional iMGL via: (1) highly efficient differentiation of hematopoietic progenitor cells (HPCs) from iPSCs, and (2) optimized maturation of HPCs to iMGL. A sequential harvesting approach led to an increased HPC yield. The protocol implemented a freezing step, thus allowing HPC biobanking and flexible timing of differentiation into iMGL. Our iMGL responded adequately to the inflammatory stimuli LPS, and iMGL RNAseq analysis matched those of other frequently used protocols. Comparing three different coating modalities, we increased the iMGL yield by culturing on uncoated glass surfaces, thereby retaining differentiation efficiency and functional hallmarks of iMGL. In summary, we provide a high-quality, easy-to-use protocol, rendering generation and functional studies on iMGL an accessible lab resource.

Background: Pathogenic variants in SPG11 cause the most common autosomal recessive complicated hereditary spastic paraplegia. Besides the prototypical combination of spastic paraplegia with a thin corpus callosum, obesity has increasingly been reported in this multisystem neurodegenerative disease. However, a detailed analysis of the metabolic state is lacking. Methods: In order to characterize metabolic alterations, a cross-sectional analysis was performed comparing SPG11 patients (n = 16) and matched healthy controls (n = 16). We quantified anthropometric parameters, body composition as determined by bioimpedance spectroscopy, and serum metabolic biomarkers, and we measured hypothalamic volume by high-field MRI. Results: Compared to healthy controls, SPG11 patients exhibited profound changes in body composition, characterized by increased fat tissue index, decreased lean tissue index, and decreased muscle mass. The presence of lymphedema correlated with increased extracellular fluid. The serum levels of the adipokines leptin, resistin, and progranulin were significantly altered in SPG11 while adiponectin and C1q/TNF-related protein 3 (CTRP-3) were unchanged. MRI volumetry revealed a decreased hypothalamic volume in SPG11 patients. Conclusions: Body composition, adipokine levels, and hypothalamic volume are altered in SPG11. Our data indicate a link between obesity and hypothalamic neurodegeneration in SPG11 and imply that specific metabolic interventions may prevent obesity despite severely impaired mobility in SPG11.

The conventional fed-batch process characterized by a low titer currently challenges pharmaceutical development. Process optimization by applying a perfusion process in the pre-stage and subsequent production phase at a high seeding density (HSD) can meet this challenge. In this study, we employed a simplified approach based on measured experiments, namely segmented modeling, to systematically analyze an HSD fed-batch process compared to a standard process. A comparison indicated that the metabolic phases of HSD processes are not only shifted in time, but metabolite trends show an altered metabolism. In an extended study, we integrated the intracellular fluxes determined by a metabolic flux analysis into the segmented modeling approach. Compared to using only extracellular rates, similar phases are identified, and this highlights the reliability of phase identification modeling using extracellular rates only. Furthermore, the segmented linear regression approach is used to create a model that describes cellular behavior and that can be used to predict potential improvements in the feeding strategy and in harvest viability. Here, overfeeding was eliminated and a significantly higher titer was achieved. This work provides insights into the overall metabolic changes in the HSD process and paves the way towards the optimization of the feeding regime.

RNA splicing modulators are a new class of small molecules with the potential to modify the expression levels of proteins. A recent clinical trial investigating the splicing modulator branaplam for Huntington’s disease to lower huntingtin levels was terminated due to the development of peripheral neuropathy. Here, we describe how branaplam leads to this adverse effect. On a cellular level, branaplam disrupts neurite integrity reflected by elevated neurofilament light chain levels in human induced pluripotent stem cell (iPSC)-derived motor neurons (iPSC-MN). Branaplam does not target neuropathy-associated genes. However, transcription factor binding site enrichment analysis indicates p53 activation. P53 activation upon branaplam treatment in iPSC-MN is linked to increased nucleolar stress, thereby enhanced expression of the neurotoxic p53-target gene BBC3. These findings illustrate that RNA splicing modulators may have clinically relevant off-target effects, implying the necessity of comprehensive pre-screening in human models prior to executing clinical trials. Predicting side effects of RNA splicing modulator branaplam leading to neurotoxicity via nucleolar stress, p53 activation, and axonal degeneration.

For all animals, undisturbed periods of rest are essential for undergoing recuperative processes. How neural interactions create brain states capable of dissociating an animal from its external world to promote quiescence remains a fundamental question. Here, we show how coherent network oscillations can create neural filters that favor a quiescent brain state over a state that promotes navigation. Circadian regulation and excitability of the Drosophila sleep homeostat (dFSB) generate nighttime specific slow-wave coherence between neural networks mediating sleep need (R5) and networks gating locomotion (helicon cells). Optogenetically mimicking coherent activity reveals that temporally fine-tuned R5 oscillations promote a quiescent state and reduce responsiveness to visual stimuli by hierarchically overruling locomotion-promoting helicon cells. We uncover that R5 and helicon bidirectionally regulate behavioral responsiveness by providing antagonistic inputs to head direction targets (EPG). Thus, coherent oscillations can form the mechanistic basis of neural filters by temporally associating antagonistic inputs and therefore reducing the functional connectivity between locomotion gating and navigational networks. Competing Interest Statement The authors have declared no competing interest. Footnotes * For all animals, undisturbed periods of rest are essential for undergoing recuperative processes. How neural interactions create brain states capable of dissociating an animal from its external world to promote quiescence remains a fundamental question. Here, we show how coherent network oscillations can create neural filters that favor a quiescent brain state over a state that promotes navigation. Circadian regulation and excitability of the Drosophila sleep homeostat (dFSB) generate nighttime specific slow-wave coherence between neural networks mediating sleep need (R5) and networks gating locomotion (helicon cells). Optogenetically mimicking coherent activity reveals that temporally fine-tuned R5 oscillations promote a quiescent state and reduce responsiveness to visual stimuli by hierarchically overruling locomotion-promoting helicon cells. We uncover that R5 and helicon bidirectionally regulate behavioral responsiveness by providing antagonistic inputs to head direction targets (EPG). Thus, coherent oscillations can form the mechanistic basis of neural filters by temporally associating antagonistic inputs and therefore reducing the functional connectivity between locomotion gating and navigational networks.

GEXA Gold Corp. (NASDAQ/SpE:GEXA) announced Wednesday that at the Annual Meeting of Shareholders held on June 22, both proposals put to the shareholders for vote, passed with an overwhelming majority. The company stated that the election of all eight directors and the approval of Coopers & Lybrand as the company's auditors both passed with at least 99.7 percent in favor of the shares voted at the meeting. The eight directors re-elected were David E.P. Lindh, Gary L. Rice, N. Peter Hamilton, Henry C.B. Lindh, Justin L. Rice, Peter E. Galli, James A. Fish and Robert McDougal. (excerpt)