Amorphous MoS2 from a machine learning inter-atomic potential.

Amorphous molybdenum disulfide has shown potential as a hydrogen evolution catalyst, but the origin of its high activity is unclear, as is its atomic structure. Here, we have developed a classical inter-atomic potential using the charge equilibration neural network method, and we have employed it to generate atomic models of amorphous MoS2 by melting and quenching processes. The amorphous phase contains an abundance of molybdenum and sulfur atoms in low coordination. Besides the 6-coordinated molybdenum typical of the crystalline phases, a substantial fraction displays coordinations 4 and 5. The amorphous phase is also characterized by the appearance of direct S-S bonds. Density functional theory shows that the amorphous phase is metallic, with a considerable contribution of the 4-coordinated molybdenum to the density of states at the Fermi level. S-S bonds are related to the reduction of sulfur, with the excess electrons spread over several molybdenum atoms. Moreover, S-S bond formation is associated with a distinctive broadening of the 3s states, which could be exploited for experimental characterization of the amorphous phases. The large variety of local environments and the high density of electronic states at the Fermi level may play a positive role in increasing the electrocatalytic activity of this compound.

Optimizing Screening for Intrastriatal Interventions in Huntington's Disease Using Predictive Models.

BACKGROUND: Intrastriatal delivery of potential therapeutics in Huntington's disease (HD) requires sufficient caudate and putamen volumes. Currently, volumetric magnetic resonance imaging is rarely done in clinical practice, and these data are not available in large research cohorts such as Enroll-HD. OBJECTIVE: The objective of this study was to investigate whether predictive models can accurately classify HD patients who exceed caudate and putamen volume thresholds required for intrastriatal therapeutic interventions. METHODS: We obtained and merged data for 1374 individuals across three HD cohorts: IMAGE-HD, PREDICT-HD, and TRACK-HD/TRACK-ON. We imputed missing data for clinical variables with >72% non-missing values and used the model-building algorithm BORUTA to identify the 10 most important variables. A random forest algorithm was applied to build a predictive model for putamen volume >2500 mm3 and caudate volume >2000 mm3 bilaterally. Using the same 10 predictors, we constructed a logistic regression model with predictors significant at P < 0.05. RESULTS: The random forest model with 1000 trees and minimal terminal node size of 5 resulted in 83% area under the curve (AUC). The logistic regression model retaining age, CAG repeat size, and symbol digit modalities test-correct had 85.1% AUC. A probability cutoff of 0.8 resulted in 5.4% false positive and 66.7% false negative rates. CONCLUSIONS: Using easily obtainable clinical data and machine learning-identified initial predictor variables, random forest, and logistic regression models can successfully identify people with sufficient striatal volumes for inclusion cutoffs. Adopting these models in prescreening could accelerate clinical trial enrollment in HD and other neurodegenerative disorders when volume cutoffs are necessary enrollment criteria. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Use of venetoclax in t(11;14) positive relapsed/refractory multiple myeloma: A systematic review.

BACKGROUND: The plasma cell malignancy, multiple myeloma (MM), remains incurable despite advanced treatment protocols. Overexpression of Bcl-2 (an anti-apoptotic protein), in MM harboring the translocation (11;14), contributes to resistance to prior therapy. Venetoclax, a selective oral inhibitor of BCL-2 is a novel agent that shows promise as a therapeutic agent. AIMS: The objective of this systematic review is to address how the use of venetoclax, alone or as a combination regimen, contributed to the treatment of patients with t(11:14) positive relapsed/refractory multiple myeloma (RRMM). DATA SOURCES: This systematic review was conducted in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was done on 5th June 2022. A literature search was conducted on PubMed and Scopus, 145 articles were screened and 10 studies were included. Risk of bias assessment was performed using the Methodological Index for Non-Randomized Studies (MINORS) criteria. DATA SUMMARY: Across the studies reviewed, a total of 311 patients were identified with t(11;14) positive RRMM. The overall response rate achieved ranged between 33% and 95.5%. Furthermore, the use of venetoclax has exhibited a favorable adverse effect profile. Side effects included hematological side effects, nausea, vomiting, and diarrhea. CONCLUSION: Venetoclax demonstrates promising results. When given with drugs like dexamethasone, daratumumab and carfilzomib, a synergistic effect is seen in treating translocation (11:14) positive relapsed/refractory MM. The use of venetoclax in clinical practice can potentially improve outcomes and quality of life in RRMM patients, and future research should continue to explore this promising treatment option.

Low-Income Older Adults' Vulnerability to Anticholinergic Medication-Associated Frailty.

BACKGROUND: A growing body of research supports the negative impact of anticholinergic drug burden on physical frailty. However, prior research has been limited to homogeneous white European populations, and few studies have evaluated how anticholinergic burden tools compare in their measurement function and reliability with minority community-dwelling adult populations. This study investigated the association between anticholinergic drug exposure and frailty by conducting a sensitivity analysis using multiple anticholinergic burden tools in a diverse cohort. METHODS: A comprehensive psychometric approach was used to assess the performance of five clinical Anticholinergic Burden Tools: Anticholinergic Cognitive Burden Scale (ACB), Anticholinergic Drug Scale (ADS), average daily dose, total standardized daily doses (TSDD), and Cumulative Anticholinergic Burden scale (CAB). Spearman correlation matrix and intraclass correlation coefficients (ICC) were used to determine the association among the variables. Ordinal logistic regression is used to evaluate the anticholinergic burden measured by each scale to determine the prediction of frailty. Model performance is determined by the area under the curve (AUC). RESULTS: The cohort included 80 individuals (mean age 69 years; 55.7% female, 71% African American). All anticholinergic burden tools were highly correlated (p < 0.001), ICC3 0.66 (p < 0.001, 95% confidence interval (CI) 0.53-0.73). Among individuals prescribed anticholinergics, 33% were robust, 44% were prefrail, and 23% were frail. All five tools predicted prefrail and frail status (p < 0.05) with low model misclassification rates for frail individuals (AUC range 0.78-0.85). CONCLUSION: Anticholinergic burden tools evaluated in this cohort of low-income African American older adults were highly correlated and predicted prefrail and frail status. Findings indicate that clinicians can select the appropriate instrument for the clinic setting and research question while maintaining confidence that all five tools will produce reliable results. Future anticholinergic research is needed to unravel the association between interventions such as deprescribing on incident frailty in longitudinal data.

Cholinergic Nucleus 4 Degeneration and Cognitive Impairment in Isolated Rapid Eye Movement Sleep Behavior Disorder.

BACKGROUND: Cholinergic nucleus 4 (Ch4) degeneration is associated with cognitive impairment in Parkinson's disease and dementia with Lewy bodies, but it is unknown if Ch4 degeneration is also present in isolated rapid eye movement sleep behavior disorder (iRBD). OBJECTIVE: The aim was to determine if there is evidence of Ch4 degeneration in patients with iRBD and if it is associated with cognitive impairment. METHODS: We analyzed the clinical and neuropsychological data of 35 iRBD patients and 35 age- and sex-matched healthy controls. Regional gray matter density (GMD) was calculated for Ch4 using probabilistic maps applied to brain magnetic resonance imaging (MRI). RESULTS: Ch4 GMD was significantly lower in the iRBD group compared to controls (0.417 vs. 0.441, P = 0.02). Ch4 GMD was also found to be a significant predictor of letter number sequencing (ß-coefficient = 58.31, P = 0.026, 95% confidence interval [7.47, 109.15]), a measure of working memory. CONCLUSIONS: iRBD is associated with Ch4 degeneration, and Ch4 degeneration in iRBD is associated with impairment in working memory. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

One Minute of EEG Data Provides Sufficient and Reliable Data for Identifying Lewy Body Dementia.

OBJECTIVE: To determine the minimum duration of electroencephalography (EEG) data necessary to differentiate EEG features of Lewy body dementia (LBD), that is, dementia with Lewy bodies and Parkinson disease dementia, from non-LBD patients, that is, Alzheimer disease and Parkinson disease. METHODS: We performed quantitative EEG analysis for 16 LBD and 14 non-LBD patients. After artifact removal, a fast Fourier transform was performed on 90, 60, and thirty 2-second epochs to derive dominant frequency; dominant frequency variability; and dominant frequency prevalence. RESULTS: In LBD patients, there were no significant differences in EEG features derived from 90, 60, and thirty 2-second epochs (all P >0.05). There were no significant differences in EEG features derived from 3 different groups of thirty 2-second epochs (all P >0.05). When analyzing EEG features derived from ninety 2-second epochs, we found that LBD had significantly reduced dominant frequency, reduced dominant frequency variability, and reduced dominant frequency prevalence alpha compared with the non-LBD group (all P <0.05). These same differences were observed between the LBD and non-LBD groups when analyzing thirty 2-second epochs. CONCLUSIONS: There were no differences in EEG features derived from 1 minute versus 3 minutes of EEG data, and both durations of EEG data equally differentiated LBD from non-LBD.

Anticholinergic Medication Burden in Parkinson's Disease Outpatients.

BACKGROUND: Individuals with Parkinson's disease (PD) may be especially vulnerable to future cognitive decline from anticholinergic medications. OBJECTIVE: To characterize anticholinergic medication burden, determine the co-occurrence of anticholinergic and cholinesterase inhibitors, and to assess the correlations among anticholinergic burden scales in PD outpatients. METHODS: We studied 670 PD outpatients enrolled in a clinic registry between 2012 and 2020. Anticholinergic burden was measured with the Anticholinergic Cognitive Burden Scale (ACB), Anticholinergic Drug Scale (ADS), Anticholinergic Risk Scale (ARS), and Drug Burden Index-Anticholinergic component (DBI-Ach). Correlations between scales were assessed with weighted kappa coefficients. RESULTS: Between 31.5 to 46.3% of PD patients were taking medications with anticholinergic properties. Among the scales applied, the ACB produced the highest prevalence of medications with anticholinergic properties (46.3%). Considering only medications with definite anticholinergic activity (scores of 2 or 3 on ACB, ADS, or ARS), the most common anticholinergic drug classes were antiparkinsonian (8.2%), antipsychotic (6.4%), and urological (3.3%) medications. Cholinesterase inhibitors and medications with anticholinergic properties were co-prescribed to 5.4% of the total cohort. The most highly correlated scales were ACB and ADS (κ= 0.71), ACB and ARS (κ= 0.67), and ADS and ARS (κ= 0.55). CONCLUSION: A high proportion of PD patients (20%) were either taking antiparkinsonian, urological, or antipsychotic anticholinergic medications or were co-prescribed anticholinergic medications and cholinesterase inhibitors. By virtue of its detection of a high prevalence of anticholinergic medication usage and its high correlation with other scales, our data support use of the ACB scale to assess anticholinergic burden in PD patients.

Genotoxic and cytotoxic assessment of sitagliptin and simvastatin alone and in combination.

Type 2 Diabetes Mellitus (T2DM) patients are at high risk of Coronary Heart Disease (CHD) and need a global therapeutic intervention. A fixed-dose combination prescription medication containing anti-diabetic drug (Sitagliptin) and lipid lowering (Simvastatin) has recently been approved. Present study was designed to explore the potential synergistic toxic effects of sitagliptin and simvastatin at cellular level. MTT assay revealed the potential synergistic cytotoxic effect whereas Comet assay spotlighted the genotoxicity. MTT assay conducted on Vero cell lines revealed no significant change in proliferative activity upon treatment with simvastatin but cell survival percentage (CSP) decreased upon treatment with sitagliptin (51% at 1000µg/mL). However, combination of both drugs exhibited a better survival percentage except highest dose combination (1000:500µg/mL) which augmented antiproliferative effects rendering CSP 71.6%. The genotoxic assay spotted that Simvastatin produced less damage to DNA with the threshold of 500µg/ml whereas Sitagliptin significantly damage above the 250µg/mL, However, combination of drugs produced lesser damage than Sitagliptin alone. The findings concluded a non-genotoxic combination of sitagliptin and simvastatin which possess a least cytotoxic potential suggesting the safe use of the combination both in T2DM and CHD.

Antimuscarinic Anticholinergic Medications in Parkinson Disease: To Prescribe or Deprescribe?

The relative importance of antimuscarinic anticholinergic medications for Parkinson's disease (PD) declined after the introduction of levodopa, such that anticholinergic medications are now much more likely to be prescribed for clinical indications other than parkinsonism. Recent studies have found an association between anticholinergic medication exposure and future risk of dementia in older individuals and those with PD. These findings provide a further reason to avoid the use of anticholinergic medications to treat motor symptoms of PD. More importantly, they raise the question of whether one of the goals of PD treatment should be to deprescribe all medications with anticholinergic properties, regardless of their indication, to reduce dementia risk. In this review, we discuss the use of anticholinergic medications in PD, the evidence supporting the association between anticholinergic medications and future dementia risk, and the potential implications of these findings for clinical care in PD.

Olfaction, cholinergic basal forebrain degeneration, and cognition in early Parkinson disease.

INTRODUCTION: Impaired olfaction and reduced cholinergic nucleus 4 (Ch4) volume both predict greater cognitive decline in Parkinson's disease (PD). We examined the relationship between olfaction, longitudinal change in cholinergic basal forebrain nuclei and their target regions, and cognition in early PD. METHODS: We analyzed a cohort of 97 PD participants from the Parkinson's Progression Markers Initiative with brain MRIs at baseline, 1 year, 2 years, and 4 years. Using probabilistic maps, regional grey matter density (GMD) was calculated for Ch4, cholinergic nuclei 1, 2, and 3 (Ch123), and their target regions. RESULTS: Baseline University of Pennsylvania Smell Identification Test score correlated with change in GMD of all regions of interest (all p < 0.05). Rate of change of Ch4 GMD was correlated with rate of change of Ch123 (p = 0.034), cortex (p = 0.001), and amygdala GMD (p < 0.001), but not hippocampus GMD (p = 0.38). Rate of change of Ch123 GMD was correlated with rate of change of cortex (p = 0.001) and hippocampus (p < 0.001), but not amygdala GMD (p = 0.133). In a linear regression model including change in GMD of all regions of interest and age as predictors, change in cortex GMD (߈slope= 38.2; 95 % CI: [0.47, 75.9]) and change in hippocampus GMD (߈slope= 24.8; 95 % CI: [0.80, 48.8]) were significant predictors of Montreal Cognitive Assessment score change over time. CONCLUSION: Impaired olfaction is associated with degeneration of the cholinergic basal forebrain and bilateral cortex, amygdala, and hippocampus in PD. The relationship between impaired olfaction and cognitive decline may be mediated by greater atrophy of the cortex and hippocampus.