Category: Nevin Manimala

NPJ Parkinsons Dis. 2021 Oct 29;7(1):96. doi: 10.1038/s41531-021-00236-0.

ABSTRACT

Multiple system atrophy (MSA) is classified into two main types: parkinsonian and cerebellar ataxia with oligodendrogliopathy. We examined microstructural alterations in the white matter and the substantia nigra pars compacta (SNc) of patients with MSA of parkinsonian type (MSA-P) using multishell diffusion magnetic resonance imaging (dMRI) and myelin sensitive imaging techniques. Age- and sex-matched patients with MSA-P (n = 21, n = 10 first and second cohorts, respectively), Parkinson’s disease patients (n = 19, 17), and healthy controls (n = 20, 24) were enrolled. Magnetization transfer saturation imaging (MT-sat) and dMRI were obtained using 3-T MRI. Measurements obtained from diffusion tensor imaging (DTI), free-water elimination DTI, neurite orientation dispersion and density imaging (NODDI), and MT-sat were compared between groups. Tract-based spatial statistics analysis revealed differences in diffuse white matter alterations in the free-water fractional volume, myelin volume fraction, and intracellular volume fraction between the patients with MSA-P and healthy controls, whereas free-water and MT-sat differences were limited to the middle cerebellar peduncle in comparison with those with Parkinson’s disease. Region-of-interest analysis of white matter and SNc revealed significant differences in the middle and inferior cerebellar peduncle, pontine crossing tract, corticospinal tract, and SNc between the MSA-P and healthy controls and/or Parkinson’s disease patients. Our results shed light on alterations to brain microstructure in MSA.

PMID:34716335 | DOI:10.1038/s41531-021-00236-0

Thorax. 2021 Oct 29:thoraxjnl-2021-217142. doi: 10.1136/thoraxjnl-2021-217142. Online ahead of print.

ABSTRACT

Lung cancer screening is effective if offered to people at increased risk of the disease. Currently, direct contact with potential participants is required for evaluating risk. A way to reduce the number of ineligible people contacted might be to apply risk-prediction models directly to digital primary care data, but model performance in this setting is unknown.

METHOD: The Clinical Practice Research Datalink, a computerised, longitudinal primary care database, was used to evaluate the Liverpool Lung Project V.2 (LLP_v2) and Prostate Lung Colorectal and Ovarian (modified 2012) (PLCO_m2012) models. Lung cancer occurrence over 5-6 years was measured in ever-smokers aged 50-80 years and compared with 5-year (LLP_v2) and 6-year (PLCO_m2012) predicted risk.

RESULTS: Over 5 and 6 years, 7123 and 7876 lung cancers occurred, respectively, from a cohort of 842 109 ever-smokers. After recalibration, LLP_V2 produced a c-statistic of 0.700 (0.694-0.710), but mean predicted risk was over-estimated (predicted: 4.61%, actual: 0.9%). PLCO_m2012 showed similar performance (c-statistic: 0.679 (0.673-0.685), predicted risk: 3.76%. Applying risk-thresholds of 1% (LLP_v2) and 0.15% (PLCO_m2012), would avoid contacting 42.7% and 27.4% of ever-smokers who did not develop lung cancer for screening eligibility assessment, at the cost of missing 15.6% and 11.4% of lung cancers.

CONCLUSION: Risk-prediction models showed only moderate discrimination when applied to routinely collected primary care data, which may be explained by quality and completeness of data. However, they may substantially reduce the number of people for initial evaluation of screening eligibility, at the cost of missing some lung cancers. Further work is needed to establish whether newer models have improved performance in primary care data.

PMID:34716280 | DOI:10.1136/thoraxjnl-2021-217142

J Neurosci. 2021 Oct 28:JN-RM-2687-20. doi: 10.1523/JNEUROSCI.2687-20.2021. Online ahead of print.

ABSTRACT

Brain-machine interfaces (BMIs) for reaching have enjoyed continued performance improvements, yet there remains significant need for BMIs that control other movement classes. Recent scientific findings suggest that the intrinsic covariance structure of neural activity depends strongly on movement class, potentially necessitating different decode algorithms across classes. To address this possibility, we developed a self-motion BMI based on cortical activity as monkeys cycled a hand-held pedal to progress along a virtual track. Unlike during reaching, we found no high-variance dimensions that directly correlated with to-be-decoded variables. This was due to no neurons having consistent correlations between their responses and kinematic variables. Yet we could decode a single variable – self-motion – by non-linearly leveraging structure that spanned multiple high-variance neural dimensions. Resulting online BMI-control success rates approached those during manual control. These findings make two broad points regarding how to build decode algorithms that harmonize with the empirical structure of neural activity in motor cortex. First, even when decoding from the same cortical region (e.g., arm-related motor cortex) different movement classes may need to employ very different strategies. Although correlations between neural activity and hand velocity are prominent during reaching tasks, they are not a fundamental property of motor cortex and cannot be counted on to be present in general. Second, although one generally desires a low-dimensional readout, it can be beneficial to leverage a multi-dimensional high-variance subspace. Fully embracing this approach requires highly non-linear approaches tailored to the task at hand, but can produce near-native levels of performance.SIGNIFICANCE STATEMENTMany BMI decoders have been constructed for controlling movements normally performed with the arm. Yet it is unclear how these will function beyond the reach-like scenarios where they were developed. Existing decoders implicitly assume that neural covariance structure, and correlations with to-be-decoded kinematic variables, will be largely preserved across tasks. We find that the correlation between neural activity and hand kinematics, a feature typically exploited when decoding reach-like movements, is essentially absent during another task performed with the arm: cycling through a virtual environment. Nevertheless, the use of a different strategy, one focused on leveraging the highest-variance neural signals, supported high performance real-time BMI control.

PMID:34716229 | DOI:10.1523/JNEUROSCI.2687-20.2021

Proc Natl Acad Sci U S A. 2021 Nov 2;118(44):e2100482118. doi: 10.1073/pnas.2100482118.

ABSTRACT

In this article, we advance divide-and-conquer strategies for solving the community detection problem in networks. We propose two algorithms that perform clustering on several small subgraphs and finally patch the results into a single clustering. The main advantage of these algorithms is that they significantly bring down the computational cost of traditional algorithms, including spectral clustering, semidefinite programs, modularity-based methods, likelihood-based methods, etc., without losing accuracy, and even improving accuracy at times. These algorithms are also, by nature, parallelizable. Since most traditional algorithms are accurate, and the corresponding optimization problems are much simpler in small problems, our divide-and-conquer methods provide an omnibus recipe for scaling traditional algorithms up to large networks. We prove the consistency of these algorithms under various subgraph selection procedures and perform extensive simulations and real-data analysis to understand the advantages of the divide-and-conquer approach in various settings.

PMID:34716259 | DOI:10.1073/pnas.2100482118

Cold Spring Harb Mol Case Stud. 2021 Oct 29:mcs.a006137. doi: 10.1101/mcs.a006137. Online ahead of print.

ABSTRACT

An SLC30A9 associated cerebro renal syndrome was first reported in consanguineous Bedouin kindred by Perez et al in 2017. While the function of the gene has not yet been fully elucidated, it may be implicated in Wnt signaling, nuclear regulation, as well as cell and mitochondrial zinc regulation. In this research report, we present a female proband with two distinct, inherited autosomal recessive loss of function SLC30A9 variants from unrelated parents. To our knowledge, this is the first reported case of a possible SLC30A9 associated cerebro renal syndrome in a nonconsanguineous family. Furthermore, a limited statistical analysis was conducted to identify possible allele frequency differences between populations. Our findings provide further support for an SLC30A9 associated cerebro renal syndrome and may help further clarify the function of this gene.

PMID:34716203 | DOI:10.1101/mcs.a006137

Diabetes Care. 2021 Oct 29:dc202806. doi: 10.2337/dc20-2806. Online ahead of print.

ABSTRACT

OBJECTIVE: Phenotypic heterogeneity among patients with type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD) is ill defined. We used cluster analysis machine-learning algorithms to identify phenotypes among trial participants with T2DM and ASCVD.

RESEARCH DESIGN AND METHODS: We used data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS) study (n = 14,671), a cardiovascular outcome safety trial comparing sitagliptin with placebo in patients with T2DM and ASCVD (median follow-up 3.0 years). Cluster analysis using 40 baseline variables was conducted, with associations between clusters and the primary composite outcome (cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for unstable angina) assessed by Cox proportional hazards models. We replicated the results using the Exenatide Study of Cardiovascular Event Lowering (EXSCEL) trial.

RESULTS: Four distinct phenotypes were identified: cluster I included Caucasian men with a high prevalence of coronary artery disease; cluster II included Asian patients with a low BMI; cluster III included women with noncoronary ASCVD disease; and cluster IV included patients with heart failure and kidney dysfunction. The primary outcome occurred, respectively, in 11.6%, 8.6%, 10.3%, and 16.8% of patients in clusters I to IV. The crude difference in cardiovascular risk for the highest versus lowest risk cluster (cluster IV vs. II) was statistically significant (hazard ratio 2.74 [95% CI 2.29-3.29]). Similar phenotypes and outcomes were identified in EXSCEL.

CONCLUSIONS: In patients with T2DM and ASCVD, cluster analysis identified four clinically distinct groups. Further cardiovascular phenotyping is warranted to inform patient care and optimize clinical trial designs.

PMID:34716214 | DOI:10.2337/dc20-2806

Heart. 2021 Oct 29:heartjnl-2021-319846. doi: 10.1136/heartjnl-2021-319846. Online ahead of print.

ABSTRACT

BACKGROUND: Diagnosis of cardiac amyloidosis (CA) requires advanced imaging techniques. Typical surface ECG patterns have been described, but their diagnostic abilities are limited.

OBJECTIVE: The aim was to perform a thorough electrophysiological characterisation of patients with CA and derive an easy-to-use tool for diagnosis.

METHODS: We applied electrocardiographic imaging (ECGI) to acquire electroanatomical maps in patients with CA and controls. A machine learning approach was then used to decipher the complex data sets obtained and generate a surface ECG-based diagnostic tool.

FINDINGS: Areas of low voltage were localised in the basal inferior regions of both ventricles and the remaining right ventricular segments in CA. The earliest epicardial breakthrough of myocardial activation was visualised on the right ventricle. Potential maps revealed an accelerated and diffuse propagation pattern. We correlated the results from ECGI with 12-lead ECG recordings. Ventricular activation correlated best with R-peak timing in leads V1-V3. Epicardial voltage showed a strong positive correlation with R-peak amplitude in the inferior leads II, III and aVF. Respective surface ECG leads showed two characteristic patterns. Ten blinded cardiologists were asked to identify patients with CA by analysing 12-lead ECGs before and after training on the defined ECG patterns. Training led to significant improvements in the detection rate of CA, with an area under the curve of 0.69 before and 0.97 after training.

INTERPRETATION: Using a machine learning approach, an ECG-based tool was developed from detailed electroanatomical mapping of patients with CA. The ECG algorithm is simple and has proven helpful to suspect CA without the aid of advanced imaging modalities.

PMID:34716183 | DOI:10.1136/heartjnl-2021-319846

Clin Cancer Res. 2021 Oct 29:clincanres.2182.2021. doi: 10.1158/1078-0432.CCR-21-2182. Online ahead of print.

ABSTRACT

PURPOSE: Metaplastic breast cancer (MpBC) is a rare aggressive subtype that responds poorly to cytotoxics. Median survival is approximately eight months for metastatic disease. We report results for advanced MpBC treated with ipilimumab+nivolumab, a cohort of S1609 for rare cancers (DART: NCT02834013).

METHODS: Prospective, open-label, multicenter phase II (two-stage) trial of ipilimumab (1mg/kg IV q6weeks) plus nivolumab (240mg IV q2weeks) for advanced MpBC. Primary endpoint was objective response rate (ORR). Secondary endpoints included progression-free survival (PFS), overall survival (OS) and toxicity.

RESULTS: Overall, 17 evaluable patients enrolled. Median age was 60 years (26-85); median number of prior therapy lines, 2 (0-5). ORR was 18%; 3/17 patients achieved objective responses (1 complete, 2 partial responses) (2 spindle cell, 1 chondromyxoid histology), which are ongoing at 28+, 33+ and 34+ months, respectively. Median PFS and OS were 2 and 12 months, respectively. Altogether, 11 patients (65%) experienced adverse events (AEs), including one grade 5 AE. Eight patients (47%) developed an immune-related AE (irAE); with adrenal insufficiency observed in all three responders. Responses occurred in tumors with low tumor mutational burden, low PD-L1 and absent TILs.

CONCLUSION: The ipilimumab and nivolumab combination showed no new safety signals and met its primary endpoint with 18% ORR in advanced, chemotherapy-refractory MpBC. All responses are ongoing at >2 to almost 3 years later. The effect of ipilimumab and nivolumab was associated with exceptional responses in a subset of patients versus no activity. This combination warrants further investigation in MpBC, with special attention to understanding mechanism of action, and carefully designed to weigh against the significant risks of irAEs.

PMID:34716198 | DOI:10.1158/1078-0432.CCR-21-2182

Inj Prev. 2021 Oct 29:injuryprev-2021-044321. doi: 10.1136/injuryprev-2021-044321. Online ahead of print.

ABSTRACT

OBJECTIVE: Intersection conflict warning systems (ICWSs) have been implemented at high-risk two-way stop-controlled intersections to prevent right-angle crashes and associated injuries. This study involved investigation of the impacts of ICWSs on crash reductions.

METHODS: The study used a quasi-experimental design to analyse the potential causal relations between Minnesota’s ICWSs and various crash rate outcomes (including total, injury, non-injury, targeted right-angle and non-right-angle crashes) in pre-post analyses. A restricted randomisation method enabled identification of three controls to each ICWS treatment intersection, and included as many comparable intersection characteristics as possible. Annual crash rates (per year per intersection) were analysed over the same periods before and after system activation for treatment and control intersections in each matched group. Pre-crash data for 3 years and post-crash data for up to 5 years were included, ranging from 2010 to 2018. Negative binomial regression models with generalised estimating equations were applied to estimate the average, immediate and continuing treatment effects of ICWSs, through the difference-in-differences and difference-in-difference-in-difference approaches, respectively.

RESULTS: The ICWS treatment was significantly associated with a decreasing trend for targeted right-angle crash rates posttreatment. Although not statistically significant, most crash rate outcomes appeared to be elevated immediately after treatment (statistically significant for sideswipe crashes only). Pre-post differences in average crash rates (over entire periods), except for incapacitating injury-related crashes, were not statistically significant between treatment and control intersections.

CONCLUSIONS: The study provided important insight into potential causal associations between intersection safety countermeasures and crashes at high-risk rural two-way stop-controlled intersections.

PMID:34716178 | DOI:10.1136/injuryprev-2021-044321

BMJ Open. 2021 Oct 29;11(10):e047275. doi: 10.1136/bmjopen-2020-047275.

ABSTRACT

OBJECTIVE: Family caregivers play an essential role in end-of-life care but suffer considerable impact on their own health. A better understanding of main factors related to carers’ health is important to inform interventions. The purpose of the study was to test for the first time the potential impact of a comprehensive set of observable variables on carer health during end-of-life caregiving within a population-based carer sample.

DESIGN: National retrospective, cross-sectional, 4-month post-bereavement postal census survey of family carers of people who died from cancer.

SETTING AND PARTICIPANTS: Relatives who registered a death from cancer during a 2-week period in England were identified from death certificates by the Office of National Statistics; response rate was 1504/5271 (28.5%).

OUTCOME MEASURES: Carers’ mental health was measured through General Health Questionnaire (GHQ)-12; general health was measured through EuroQoL EQ-Visual Analogue Scale (EQ-5D VAS).

METHODS: Survey questions to measure potential variables associated with carer health were based on past research and covered patients’ symptoms and functioning; caregiving activities and hours; informal and formal help received; work hours, other caregiving, volunteering; changes to work, income and expenditure; sleep and relaxation; and demographic variables. Bivariate analyses and ordinary least square regression were performed to investigate these variables’ relationship with outcomes.

RESULTS: Patients’ psychological symptoms and functioning, caregiving hours, female gender and self-sought formal help related to worse mental health. General practitioner and social care input and relaxation related to better mental health. Patients’ psychological symptoms, caregiving hours and female gender were associated with worse general health, and older age, employment and relaxation were associated with better general health.

CONCLUSIONS: Improvements in carers’ health overall may be made by focusing on potential impacts of patients’ psychological symptoms on carers, facilitating respite and relaxation, and paying particular attention to factors affecting female carers.

PMID:34716156 | DOI:10.1136/bmjopen-2020-047275