In a living cell, the movement of biomolecules is highly regulated by the cellular organization into subcompartments that impose barriers to diffusion, can locally break the spatial isotropy, and ultimately guide these molecules to their targets. Despite the pivotal role of these processes, experimental tools to fully probe the complex connectivity (and accessibility) of the cell interior with adequate spatiotemporal resolution are still lacking. Here, we show how the heterogeneity of molecular dynamics and the location of barriers to molecular motion can be mapped in live cells by exploiting a two-dimensional (2D) extension of the pair correlation function (pCF) analysis. Starting from a time series of images collected for the same field of view, the resulting 2D pCF is calculated in the proximity of each point for each time delay and allows us to probe the spatial distribution of the molecules that started from a given pixel. This 2D pCF yields an accurate description of the preferential diffusive routes. Furthermore, we combine this analysis with the image-derived mean-square displacement approach and gain information on the average nanoscopic molecular displacements in different directions. Through these quantities, we build a fluorescence-fluctuation-based diffusion tensor that contains information on speed and directionality of the local dynamical processes. Contrary to classical fluorescence correlation spectroscopy and related methods, this combined approach can distinguish between isotropic and anisotropic local diffusion. We argue that the measurement of this iMSD tensor will contribute to advance our understanding of the role played by the intracellular environment in the regulation of molecular diffusion at the nanoscale.

Background and objectives

Representation of persons from marginalized racial and ethnic groups in Parkinson disease (PD) trials has been low, limiting the generalizability of therapeutic options for individuals with PD. Two large phase 3 randomized clinical trials sponsored by the National Institute of Neurological Disorders and Stroke (NINDS), STEADY-PD III and SURE-PD3, screened participants from overlapping Parkinson Study Group clinical sites under similar eligibility criteria but differed in participation by underrepresented minorities. The goal of this research is to compare recruitment strategies of PD participants belonging to marginalized racial and ethnic groups.

Methods

A total of 998 participants with identified race and ethnicity consented to STEADY-PD III and SURE-PD3 from 86 clinical sites. Demographics, clinical trial characteristics, and recruitment strategies were compared. NINDS imposed a minority recruitment mandate on STEADY-PD III but not SURE-PD3.

Results

Ten percent of participants who consented to STEADY-PD III self-identified as belonging to marginalized racial and ethnic groups compared to 6.5% in SURE-PD3 (difference = 3.9%, 95% confidence interval [CI] 0.4%-7.5%, p value = 0.034). This difference persisted after screening (10.1% of patients in STEADY-PD III vs 5.4% in SURE-PD 3, difference = 4.7%, 95% CI 0.6%-8.8%, p value = 0.038).

Discussion

Although both trials targeted similar participants, STEADY-PD III was able to consent and recruit a higher percentage of patients from racial and ethnic marginalized groups. Possible reasons include differential incentives for achieving minority recruitment goals.

Trial registration information

This study used data from The Safety, Tolerability, and Efficacy Assessment of Isradipine for Parkinson Disease (STEADY-PD III; NCT02168842) and the Study of Urate Elevation in Parkinson's Disease (SURE-PD3; NCT02642393).

Background

Coronavirus disease 2019 (COVID-19)-related short-term mortality is high in dialysis patients, but longer-term outcomes are largely unknown. We therefore assessed patient recovery in a large cohort of dialysis patients 3 months after their COVID-19 diagnosis.

Methods

We analyzed data on dialysis patients diagnosed with COVID-19 from 1 February 2020 to 31 March 2021 from the European Renal Association COVID-19 Database (ERACODA). The outcomes studied were patient survival, residence and functional and mental health status (estimated by their treating physician) 3 months after COVID-19 diagnosis. Complete follow-up data were available for 854 surviving patients. Patient characteristics associated with recovery were analyzed using logistic regression.

Results

In 2449 hemodialysis patients (mean ± SD age 67.5 ± 14.4 years, 62% male), survival probabilities at 3 months after COVID-19 diagnosis were 90% for nonhospitalized patients (n = 1087), 73% for patients admitted to the hospital but not to an intensive care unit (ICU) (n = 1165) and 40% for those admitted to an ICU (n = 197). Patient survival hardly decreased between 28 days and 3 months after COVID-19 diagnosis. At 3 months, 87% functioned at their pre-existent functional and 94% at their pre-existent mental level. Only few of the surviving patients were still admitted to the hospital (0.8-6.3%) or a nursing home (∼5%). A higher age and frailty score at presentation and ICU admission were associated with worse functional outcome.

Conclusions

Mortality between 28 days and 3 months after COVID-19 diagnosis was low and the majority of patients who survived COVID-19 recovered to their pre-existent functional and mental health level at 3 months after diagnosis.

Background

Patients on kidney replacement therapy (KRT) are at very high risk of coronavirus disease 2019 (COVID-19). The triage pathway for KRT patients presenting to hospitals with varying severity of COVID-19 illness remains ill-defined. We studied the clinical characteristics of patients at initial and subsequent hospital presentations and the impact on patient outcomes.

Methods

The European Renal Association COVID-19 Database (ERACODA) was analysed for clinical and laboratory features of 1423 KRT patients with COVID-19 either hospitalized or non-hospitalized at initial triage and those re-presenting a second time. Predictors of outcomes (hospitalization, 28-day mortality) were then determined for all those not hospitalized at initial triage.

Results

Among 1423 KRT patients with COVID-19 [haemodialysis (HD), n = 1017; transplant, n = 406), 25% (n = 355) were not hospitalized at first presentation due to mild illness (30% HD, 13% transplant). Of the non-hospitalized patients, only 10% (n = 36) re-presented a second time, with a 5-day median interval between the two presentations (interquartile range 2-7 days). Patients who re-presented had worsening respiratory symptoms, a decrease in oxygen saturation (97% versus 90%) and an increase in C-reactive protein (26 versus 73 mg/L) and were older (72 vs 63 years) compared with those who did not return a second time. The 28-day mortality between early admission (at first presentation) and deferred admission (at second presentation) was not significantly different (29% versus 25%; P = 0.6). Older age, prior smoking history, higher clinical frailty score and self-reported shortness of breath at first presentation were identified as risk predictors of mortality when re-presenting after discharge at initial triage.

Conclusions

This study provides evidence that KRT patients with COVID-19 and mild illness can be managed effectively with supported outpatient care and with vigilance of respiratory symptoms, especially in those with risk factors for poor outcomes. Our findings support a risk-stratified clinical approach to admissions and discharges of KRT patients presenting with COVID-19 to aid clinical triage and optimize resource utilization during the ongoing pandemic.

A search for a long-lived, heavy neutral lepton (N) in 139  fb^{-1} of sqrt[s]=13  TeV pp collision data collected by the ATLAS detector at the Large Hadron Collider is reported. The N is produced via W→Nμ or W→Ne and decays into two charged leptons and a neutrino, forming a displaced vertex. The N mass is used to discriminate between signal and background. No signal is observed, and limits are set on the squared mixing parameters of the N with the left-handed neutrino states for the N mass range 3  GeV