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.

Estimating the cost-effectiveness of intermittently scanned continuous glucose monitoring in adults with type 1 diabetes in England.

OBJECTIVE: We previously showed that intermittently scanned continuous glucose monitoring (isCGM) reduces HbA1c at 24 weeks compared with self-monitoring of blood glucose with finger pricking (SMBG) in adults with type 1 diabetes and high HbA1c levels (58-97 mmol/mol [7.5%-11%]). We aim to assess the economic impact of isCGM compared with SMBG. METHODS: Participant-level baseline and follow-up health status (EQ-5D-5L) and within-trial healthcare resource-use data were collected. Quality-adjusted life-years (QALYs) were derived at 24 weeks, adjusting for baseline EQ-5D-5L. Participant-level costs were generated. Using the IQVIA CORE Diabetes Model, economic analysis was performed from the National Health Service perspective over a lifetime horizon, discounted at 3.5%. RESULTS: Within-trial EQ-5D-5L showed non-significant adjusted incremental QALY gain of 0.006 (95% CI: -0.007 to 0.019) for isCGM compared with SMBG and an adjusted cost increase of £548 (95% CI: 381-714) per participant. The lifetime projected incremental cost (95% CI) of isCGM was £1954 (-5108 to 8904) with an incremental QALY (95% CI) gain of 0.436 (0.195-0.652) resulting in an incremental cost-per-QALY of £4477. In all subgroups, isCGM had an incremental cost-per-QALY better than £20,000 compared with SMBG; for people with baseline HbA1c >75 mmol/mol (9.0%), it was cost-saving. Sensitivity analysis suggested that isCGM remains cost-effective if its effectiveness lasts for at least 7 years. CONCLUSION: While isCGM is associated with increased short-term costs, compared with SMBG, its benefits in lowering HbA1c will lead to sufficient long-term health-gains and cost-savings to justify costs, so long as the effect lasts into the medium term.

Intermittently scanned continuous glucose monitoring in adults with type 1 diabetes: A subgroup analysis from the FLASH-UK study.

AIMS: The FLASH-UK trial showed lower HbA1c with intermittently scanned continuous glucose monitoring (isCGM), as compared with self monitoring of blood glucose (SMBG), in adults with type 1 diabetes and HbA1c ≥58 mmol/mol (≥7.5%). Here, we present results from the pre-specified subgroup analysis for the 24-week HbA1c (primary outcome) and selected sensor-based secondary outcomes. METHODS: This was a multi-centre, parallel-design, randomised controlled trial. The difference in treatment effect between subgroups (baseline HbA1c [≤75 vs. >75 mmol/mol] [≤9.0 vs >9.0%], treatment modality [pump vs injections], prior participation in structured education, age, educational level, impaired awareness of hypoglycaemia, deprivation index quintile sex, ethnic group and Patient Health Questionnaire-9 [PHQ-9] detected depression category) were evaluated. RESULTS: One hundred fifty-six participants (females 44%, mean [SD] baseline HbA1c 71 [9] mmol/mol 8.6 [0.8%], age 44 [15]) were randomly assigned, in a 1:1 ratio to isCGM (n = 78) or SMBG (n = 78). The mean (SD) baseline HbA1c (%) was 8.7 (0.9) in the isCGM group and 8.5 (0.8) in the SMBG group, lowering to 7.9 (0.8) versus 8.3 (0.9), respectively, at 24 weeks (adjusted mean difference -0.5, 95% confidence interval [CI] -0.7 to -0.3; p < 0.001]. For HbA1c, there was no impact of treatment modality, prior participation in structured education, deprivation index quintile, sex or baseline depression category. The between-group difference in HbA1c was larger for younger people (a reduction of 2.7 [95% CI 0.3-5.0; p = 0.028] mmol/mol for every additional 15 years of age). Those with HbA1c 76-97 mmol/mol (>9.0%-11.0%) had a marginally non-significant higher reduction in HbA1c of 8.4 mmol/mol (3.3-13.5) compared to 3.1 (0.3-6.0) in those with HbA1c 58-75 mmol/mol (p = 0.08). For 'Time in range' (% 3.9-10 mmol/L), the difference was larger for those with at least a bachelor's degree. For 'Time below range' (% <3.9 mmol/L), the difference was larger for those using injections, older people and those with less than bachelor's degree. CONCLUSIONS: Intermittently scanned continuous glucose monitoring is generally effective across a range of baseline characteristics.

COVID-19 Antibody Testing in Healthcare Workers in Arkansas.

Introduction Seroprevalence surveys can estimate the cumulative incidence of SARS-CoV-2 infection in a symptom-independent manner, offering valuable data, including herd immunity, that can inform national and local public health policies. To our knowledge, there have been no large studies reporting seroprevalence in healthcare workers (HCWs) in the state of Arkansas. The objective of this study is to measure SARS-CoV-2 seroprevalence in HCWs in a large tertiary-care healthcare system prior to vaccine availability. Methods The Central Arkansas Veterans Healthcare System offered SARS-CoV-2 antibody testing prior to the widespread availability of vaccines. After Central Arkansas Veterans Healthcare System institutional review board (IRB) approval had been obtained, a retrospective chart review was used to identify all Central Arkansas Veterans Healthcare System HCWs who had undergone SARS-CoV-2 antibody testing from July 1, 2020, to September 30, 2020. Descriptive analysis was performed using Microsoft Excel (Microsoft Corporation, Redmond, Washington, United States). Correlation and regression tests were performed using SAS 9.4 software (SAS Institute Inc., Cary, NC). Results Over the study interval, 170 healthcare personnel had undergone SARS-CoV-2 anti-spike IgG antibody testing. Thirty-seven (21.8%) had positive antibody results. The 37 individuals were mostly women (94.5%), and the average age of the group was 47 years (range 29-69 years). The median antibody titers for those testing positive for antibodies were 10.8 units (range 1.1-58.5). Of the 37 people, 32 had a history of COVID-19 infection proven by reverse transcriptase polymerase chain reaction (RT-PCR). Conclusion Serologic testing is feasible for healthcare workers to document an immune response to a prior infection. In this study of HCWs, the rate of positivity among those tested was 21.8%. Data that do not incorporate the cohort of patients with prior infections will underestimate the impact of prior infections on herd immunity statistics and may misinform public policy.

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.

The influence of stormwater infiltration on downslope groundwater chemistry.

Stormwater infiltration basins have been used extensively around the world to restore urban hydrology towards more natural flow and water quality regimes. There is, however, significant uncertainty in the fate of infiltrated water and accompanying contaminants that depends on multiple factors including media characteristics, interactions with downslope vegetation, legacy contaminants, and presence of underground infrastructure. Understanding the influence of such factors is thus central to the design and siting of infiltration basins. An extensive field program was established to collect monthly data on ground water quality, including nutrients and major ion concentrations, in a bore network downstream of a stormwater infiltration basin in Victoria, Australia. The groundwater samples were analysed for temperature, pH, EC, turbidity, major ions (Na+, Ca2+, K+, Mg2+, Cl-, SO42-, NO3-, CO32-, HCO3-), NOx and heavy metals. The collected data were used to understand the origin and fate of water and solutes in the subsurface and their interactions with the soil matrix. The results revealed that Ca-HCO3, Na-Cl water types predominate in the study area, grouped in 3 clusters; shallow fresh groundwater in the vicinity of the basin (near basin), deep saline groundwater further downstream of the basin (near-stream) and a mid-section where rock-water interaction (Na-HCO3 water) through cation exchange control the chemistry of groundwater. The results also suggest that as the water moves downstream of the basin, it experiences significant evapotranspiration and concentration due to the presence of deep-rooted vegetation. The results suggest that while infiltration basins can remove infiltrated contaminants, the infiltrated stormwater can mobilise legacy contaminants such as nitrate. Overall, the efficacy of infiltration basins in urban regions depends substantially on the downstream vegetation, urban underground infrastructure and the presence of legacy contaminants in the soils. These all need to be considered in the design of stormwater infiltration basins.

Using data-driven analytics and ecological systems theory to identify risk and protective factors for school absenteeism among secondary students.

Chronic absenteeism is an administrative term defining extreme failure for students to be present at school, which can have devastating long-term impacts on students. Although numerous prior studies have investigated associated variables and interventions, there are few studies that utilize both theory-driven and data-informed approaches to investigate absenteeism. The current study applied data-driven machine learning techniques, grounded in "The Kids and Teens at School" (KiTeS) theoretical framework, to student-level data (N = 121,005) to identify risk and protective variables that are highly associated with school absences. A total of 18 risk and protective variables were identified; all 18 variables were characteristics of the microsystem or mesosystem, emphasizing school absences' proximity to variables within inner ecological systems rather than the exosystem or macrosystem. Implications for future studies and health infrastructure are discussed.

Evaluating components of the active view of reading as intervention targets: Implications for social justice.

Inequality in reading outcomes is perhaps the single greatest social justice issue faced by school psychologists, and school psychologists need a better understanding of reading theory and its application to intervention to better combat the important issue. The present study examined the active view of reading (AVR; Duke & Cartwright, 2021), by computing effect sizes from 333 studies that were reported in 26 meta-analyses. Interventions that targeted word recognition (effect size = 0.44) and language comprehension (effect size = 0.62) had statistically significant effects for striving readers, and interventions that targeted active self-regulation (effect size = 0.46) and bridging processes (effect size = 0.70) had medium-to-large median effects on reading. We found (a) large effects of interventions for striving readers focused on text structure, verbal reasoning, and vocabulary; (b) moderate effects for fluency, language structure, motivation, and phonics; and (c) limited research included in meta-analyses for several components of the AVR, including cultural and other content knowledge. The components unique to the AVR added significant variance in reading. Analyses suggest there are many intervention targets available to school psychologists as they work toward social justice in reading outcomes. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Deconstructive Functionalization of Unstrained Cycloalkanols via Electrochemically Generated Aromatic Radical Cations.

Herein we report an electrochemical approach for the deconstructive functionalization of cycloalkanols, where various alcohols, carboxylic acids, and N-heterocycles are employed as nucleophiles. The method has been demonstrated across a broad range of cycloalkanol substrates, including various ring sizes and substituents, to access useful remotely functionalized ketone products (36 examples). The method was demonstrated on a gram scale via single-pass continuous flow, which exhibited increased productivity in relation to the batch process.

Intermittently Scanned Continuous Glucose Monitoring for Type 1 Diabetes.

BACKGROUND: In persons with type 1 diabetes and high glycated hemoglobin levels, the benefits of intermittently scanned continuous glucose monitoring with optional alarms for high and low blood glucose levels are uncertain. METHODS: In a parallel-group, multicenter, randomized, controlled trial involving participants with type 1 diabetes and glycated hemoglobin levels between 7.5% and 11.0%, we investigated the efficacy of intermittently scanned continuous glucose monitoring as compared with participant monitoring of blood glucose levels with fingerstick testing. The primary outcome was the glycated hemoglobin level at 24 weeks, analyzed according to the intention-to-treat principle. Key secondary outcomes included sensor data, participant-reported outcome measures, and safety. RESULTS: A total of 156 participants were randomly assigned, in a 1:1 ratio, to undergo intermittently scanned continuous glucose monitoring (the intervention group, 78 participants) or to monitor their own blood glucose levels with fingerstick testing (the usual-care group, 78 participants). At baseline, the mean (±SD) age of the participants was 44±15 years, and the mean duration of diabetes was 21±13 years; 44% of the participants were women. The mean baseline glycated hemoglobin level was 8.7±0.9% in the intervention group and 8.5±0.8% in the usual-care group; these levels decreased to 7.9±0.8% and 8.3±0.9%, respectively, at 24 weeks (adjusted mean between-group difference, -0.5 percentage points; 95% confidence interval [CI], -0.7 to -0.3; P<0.001). The time per day that the glucose level was in the target range was 9.0 percentage points (95% CI, 4.7 to 13.3) higher or 130 minutes (95% CI, 68 to 192) longer in the intervention group than in the usual-care group, and the time spent in a hypoglycemic state (blood glucose level, <70 mg per deciliter [<3.9 mmol per liter]) was 3.0 percentage points (95% CI, 1.4 to 4.5) lower or 43 minutes (95% CI, 20 to 65) shorter in the intervention group. Two participants in the usual-care group had an episode of severe hypoglycemia, and 1 participant in the intervention group had a skin reaction to the sensor. CONCLUSIONS: Among participants with type 1 diabetes and high glycated hemoglobin levels, the use of intermittently scanned continuous glucose monitoring with optional alarms for high and low blood glucose levels resulted in significantly lower glycated hemoglobin levels than levels monitored by fingerstick testing. (Funded by Diabetes UK and others; FLASH-UK ClinicalTrials.gov number, NCT03815006.).

Linking α-synuclein-induced synaptopathy and neural network dysfunction in early Parkinson's disease.

The prodromal phase of Parkinson's disease is characterized by aggregation of the misfolded pathogenic protein α-synuclein in select neural centres, co-occurring with non-motor symptoms including sensory and cognitive loss, and emotional disturbances. It is unclear whether neuronal loss is significant during the prodrome. Underlying these symptoms are synaptic impairments and aberrant neural network activity. However, the relationships between synaptic defects and network-level perturbations are not established. In experimental models, pathological α-synuclein not only impacts neurotransmission at the synaptic level, but also leads to changes in brain network-level oscillatory dynamics-both of which likely contribute to non-motor deficits observed in Parkinson's disease. Here we draw upon research from both human subjects and experimental models to propose a 'synapse to network prodrome cascade' wherein before overt cell death, pathological α-synuclein induces synaptic loss and contributes to aberrant network activity, which then gives rise to prodromal symptomology. As the disease progresses, abnormal patterns of neural activity ultimately lead to neuronal loss and clinical progression of disease. Finally, we outline goals and research needed to unravel the basis of functional impairments in Parkinson's disease and other α-synucleinopathies.

Evolving Concepts in Our Understanding and Treatment of Holmes Tremor, Over 100 Years in the Making.

Holmes Tremor (HT) is an irregular, slow-frequency (<4.5 Hz) tremor characterized by a combination of resting, postural, and action tremors mostly of the upper extremities. Symptoms of HT typically emerge 4 weeks to 2 years after a brain injury caused by a spectrum of etiologies. HT pathophysiology is thought to result from aberrant collateral axonal sprouting and synaptic dysfunction following neuronal damage. To date, the dopaminergic nigrostriatal system, cerebello-thalamo-cortical pathway, and dentate-rubro-olivary pathway have all been implicated in the clinical manifestations of HT. The diversity of HT etiologies usually requires a personalized treatment plan. Current treatment options include carbidopa-levodopa, levetiracetam, and trihexyphenidyl, and surgical management such as deep brain stimulation in selected medication-refractory patients. In this review we discuss the pathophysiology, etiology, neuroimaging, and the latest clinical guidelines for care and management of HT.

Electrochemical Deconstructive Functionalization of Cycloalkanols via Alkoxy Radicals Enabled by Proton-Coupled Electron Transfer.

Herein, we report a new electrochemical method for alkoxy radical generation from alcohols using a proton-coupled electron transfer (PCET) approach, showcased via the deconstructive functionalization of cycloalkanols. The electrochemical method is applicable across a diverse array of substituted cycloalkanols, accessing a broad range of synthetically useful distally functionalized ketones. The orthogonal derivatization of the products has been demonstrated through chemoselective transformations, and the electrochemical process has been performed on a gram scale in continuous single-pass flow.

Inherited Ataxias in Children.

The purpose of this review is to describe the current diagnostic approach to inherited ataxias during childhood. With the expanding use and availability of gene testing technologies including large sequencing panels, the ability to arrive at a precise genetic diagnosis in this group of disorders has been improving. We have reviewed all the gene sequencing studies of ataxias available by a comprehensive literature search and summarize their results. We provide a logical algorithm for a diagnostic approach in the context of this evolving information. We stress the fact that both autosomal recessive and autosomal dominant mutations can occur in children with ataxias and the need for keeping in mind nucleotide repeat expansions, which cannot be detected by sequencing technologies, as a possible cause of progressive ataxias in children. We discuss the traditional phenotype-based diagnostic approach in the context of gene testing technologies. Finally, we summarize those disorders in which a specific therapy may be indicated.

Language used in school psychological evaluation reports as predictors of SLD identification within a response to intervention model.

Despite decades of research, much is still unknown regarding how specific learning disability (SLD) identification decisions are made, particularly how language related to sociodemographic and psychosocial factors may impact decision-making. This study employed the Linguistic Inquiry and Word Count (LIWC) method to examine the language used in school psychological reports to better understand how sociodemographic (i.e., race, socioeconomic background, and gender) and psychosocial factors (e.g., positive and negative emotion, student effort, and student social processes) related to SLD identification within a Response to Intervention (RtI) identification method. The reports of students identified as SLD contained significantly more achievement-related language (e.g., hardworking, motivated, exerting effort) compared to students who were not identified as SLD, and achievement-related language was associated with SLD identification above and beyond RtI evaluation data (i.e., academic achievement and slope). Implications for research and practice are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Evaluation of the Abbott BinaxNOW COVID-19 Test Ag Card for rapid detection of SARS-CoV-2 infection by a local public health district with a rural population.

SARS-CoV-2 RT-PCR, the gold standard for diagnostic testing, may not be readily available or logistically applicable for routine COVID-19 testing in many rural communities in the United States. In this validation study, we compared the BinaxNOW™ COVID-19 Test Ag Card with SARS-CoV-2 RT-PCR in 214 participants who sought COVID-19 testing from a local public health district in Idaho, USA. The median age of participants was 35 and 82.7% were symptomatic. Thirty-seven participants (17.3%) had positive RT-PCR results. Results between the two tests were 94.4% concordant. The sensitivity of the BinaxNOW™ COVID-19 Test Ag Card was 67.6% (95% CI: 50.2-81.9%), and the specificity was 100.0% (95% CI: 97.9-100.0%). The positive predictive value (PPV) for the BinaxNOW™ COVID-19 Test Ag Card was 100.0% (95% CI: 86.2-100.0%), and the negative predictive value (NPV) was 93.6% (95% CI: 89.1-96.6%). Although the sensitivity of BinaxNOW™ COVID-19 Test Ag Card was lower than RT-PCR, rapid results and high specificity support its use for early detection of COVID-19, especially in settings where SARS-CoV-2 RT-PCR testing is not readily available. Rapid antigen tests, such as the BinaxNOW™ COVID-19 Test Ag Card, may be a more convenient tool in quickly identifying and preventing COVID-19 transmission, especially in rural settings.

Deep brain stimulation programming strategies: segmented leads, independent current sources, and future technology.

Introduction: Advances in neuromodulation and deep brain stimulation (DBS) technologies have facilitated opportunities for improved clinical benefit and side effect management. However, new technologies have added complexity to clinic-based DBS programming.Areas covered: In this article, we review basic basal ganglia physiology, proposed mechanisms of action and technical aspects of DBS. We discuss novel DBS technologies for movement disorders including the role of advanced imaging software, lead design, IPG design, novel programming techniques including directional stimulation and coordinated reset neuromodulation. Additional topics include the use of potential biomarkers, such as local field potentials, electrocorticography, and adaptive stimulation. We will also discuss future directions including optogenetically inspired DBS.Expert opinion: The introduction of DBS for the management of movement disorders has expanded treatment options. In parallel with our improved understanding of brain physiology and neuroanatomy, new technologies have emerged to address challenges associated with neuromodulation, including variable effectiveness, side-effects, and programming complexity. Advanced functional neuroanatomy, improved imaging, real-time neurophysiology, improved electrode designs, and novel programming techniques have collectively been driving improvements in DBS outcomes.