Emerging therapies in hereditary ataxias.

Recent investigations have defined the pathophysiological basis of many hereditary ataxias (HAs), including loss-of-function as well as gain-of-function mechanisms at either the RNA or protein level. Preclinical studies have assessed gene editing, gene and protein replacement, gene enhancement, and gene knockdown strategies. Methodologies include viral vector delivery of genes, oligonucleotide therapies, cell-penetrating peptides, synthetic transcription factors, and technologies to deliver therapies to defined targets. In this review, we focus on Friedreich ataxia (FRDA) and the polyglutamine ataxias in which translational research is active. However, much remains to be done to identify safe and effective molecules, create ideal delivery methods, and perform innovative clinical trials to prove the safety and efficacy of treatments for these rare but devastating diseases.

Immunogenicity of COVID-19 vaccines in patients with follicular lymphoma receiving frontline chemoimmunotherapy.

Immune responses to primary COVID-19 vaccination were investigated in 58 patients with follicular lymphoma (FL) as part of the PETReA trial of frontline therapy (EudraCT 2016-004010-10). COVID-19 vaccines (BNT162b2 or ChAdOx1) were administered before, during or after cytoreductive treatment comprising rituximab (depletes B cells) and either bendamustine (depletes CD4+ T cells) or cyclophosphamide-based chemotherapy. Blood samples obtained after vaccine doses 1 and 2 (V1, V2) were analysed for antibodies and T cells reactive to the SARS-CoV-2 spike protein using the Abbott Architect and interferon-gamma ELISpot assays respectively. Compared to 149 healthy controls, patients with FL exhibited lower antibody but preserved T-cell responses. Within the FL cohort, multivariable analysis identified low pre-treatment serum IgA levels and V2 administration during induction or maintenance treatment as independent determinants of lower antibody and higher T-cell responses, and bendamustine and high/intermediate FLIPI-2 score as additional determinants of a lower antibody response. Several clinical scenarios were identified where dichotomous immune responses were estimated with >95% confidence based on combinations of predictive variables. In conclusion, the immunogenicity of COVID-19 vaccines in FL patients is influenced by multiple disease- and treatment-related factors, among which B-cell depletion showed differential effects on antibody and T-cell responses.

Developing simple indicators of nitrogen and phosphorus removal in constructed stormwater wetlands.

Quantifying pollutant removal by stormwater wetlands requires intensive sampling which is cost-prohibitive for authorities responsible for a large number of wetlands. Wetland managers require simple indicators that provide a practical means of estimating performance and prioritising maintenance works across their asset base. We therefore aimed to develop vegetation cover and metrics derived from monitoring water level, as simple indicators of likely nutrient pollutant removal from stormwater wetlands. Over a two-year period, we measured vegetation cover and water levels at 17 wetlands and used both to predict nitrogen (N) and phosphorus (P) removal. Vegetation cover explained 48 % of variation in total nitrogen (TN) removal; with a linear relationship suggesting an approximate 9 % loss in TN removal per 10 % decrease in vegetation cover. Vegetation cover is therefore a useful indicator of TN removal. Further development of remotely-sensed data on vegetation configuration, species and condition will likely improve the accuracy of TN removal estimates. Total phosphorus (TP) removal was not predicted by vegetation cover, but was weakly related to the median water level which explained 25 % of variation TP removal. Despite weak prediction of TP removal, metrics derived from water level sensors identified faults such as excessive inflow and inefficient outflow, which in combination explained 50 % of the variation in the median water level. Monitoring water levels therefore has the potential to detect faults prior to loss of vegetation cover and therefore TN removal, as well as inform the corrective action required.

Fatigue Impacts Quality of Life in People with Spinocerebellar Ataxias.

BACKGROUND: Fatigue is a prevalent and debilitating symptom in neurological disorders, including spinocerebellar ataxias (SCAs). However, the risk factors of fatigue in the SCAs as well as its impact have not been well investigated. OBJECTIVES: To study the prevalence of fatigue in SCAs, the factors contributing to fatigue, and the influence of fatigue on quality of life. METHODS: Fatigue was assessed in 418 participants with SCA1, SCA2, SCA3, and SCA6 from the Clinical Research Consortium for the Study of Cerebellar Ataxia using the Fatigue Severity Scale. We conducted multi-variable linear regression models to examine the factors contributing to fatigue as well as the association between fatigue and quality of life. RESULTS: Fatigue was most prevalent in SCA3 (52.6%), followed by SCA1 (36.7%), SCA6 (35.7%), and SCA2 (35.6%). SCA cases with fatigue had more severe ataxia and worse depressive symptoms. In SCA3, those with fatigue had a longer disease duration and longer pathological CAG repeat numbers. In multi-variable models, depressive symptoms, but not ataxia severity, were associated with more severe fatigue. Fatigue, independent of ataxia and depression, contributed to worse quality of life in SCA3 and SCA6 at baseline, and fatigue continued affecting quality of life throughout the disease course in all types of SCA. CONCLUSIONS: Fatigue is a common symptom in SCAs and is closely related to depression. Fatigue significantly impacts patients' quality of life. Therefore, screening for fatigue should be considered a part of standard clinical care for SCAs.

Augmenting an electronic Ising machine to effectively solve boolean satisfiability.

With the slowdown of improvement in conventional von Neumann systems, increasing attention is paid to novel paradigms such as Ising machines. They have very different approach to solving combinatorial optimization problems. Ising machines have shown great potential in solving binary optimization problems like MaxCut. In this paper, we present an analysis of these systems in boolean satisfiability (SAT) problems. We demonstrate that, in the case of 3-SAT, a basic architecture fails to produce meaningful acceleration, largely due to the relentless progress made in conventional SAT solvers. Nevertheless, careful analysis attributes part of the failure to the lack of two important components: cubic interactions and efficient randomization heuristics. To overcome these limitations, we add proper architectural support for cubic interaction on a state-of-the-art Ising machine. More importantly, we propose a novel semantic-aware annealing schedule that makes the search-space navigation much more efficient than existing annealing heuristics. Using numerical simulations, we show that such an "Augmented" Ising Machine for SAT is projected to outperform state-of-the-art software-based, GPU-based and conventional hardware SAT solvers by orders of magnitude.