Tumors and associated stroma manifest mechanical properties that promote cancer. Mechanosensation of tissue stiffness activates the Rho/ROCK pathway to increase actomyosin-mediated cellular tension ...to re-establish force equilibrium. To determine how actomyosin tension affects tissue homeostasis and tumor development, we expressed conditionally active ROCK2 in mouse skin. ROCK activation elevated tissue stiffness via increased collagen. β-catenin, a key element of mechanotranscription pathways, was stabilized by ROCK activation leading to nuclear accumulation, transcriptional activation, and consequent hyperproliferation and skin thickening. Inhibiting actomyosin contractility by blocking LIMK or myosin ATPase attenuated these responses, as did FAK inhibition. Tumor number, growth, and progression were increased by ROCK activation, while ROCK blockade was inhibitory, implicating actomyosin-mediated cellular tension and consequent collagen deposition as significant tumor promoters.
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► Collagen deposition and tissue stiffness induced by cellular actomyosin contraction ► ROCK-induced actomyosin contractility stimulates β-catenin transcriptional activity ► ROCK-induced proliferation blocked by β-catenin deletion or actomyosin inhibition ► Actomyosin contraction-driven tissue stiffness fosters tumor growth and progression
To understand hospital policies and practices as the COVID-19 pandemic accelerated, the Society for Healthcare Epidemiology of America (SHEA) conducted a survey through the SHEA Research Network ...(SRN). The survey assessed policies and practices around the optimization of personal protection equipment (PPE), testing, healthcare personnel policies, visitors of COVID-19 patients in relation to procedures, and types of patients. Overall, 69 individual healthcare facilities responded in the United States and internationally, for a 73% response rate.
To describe the outcomes of hospitalized patients in a multicenter, international coronavirus disease 2019 registry.
Cross-sectional observational study including coronavirus disease 2019 patients ...hospitalized with laboratory-confirmed severe acute respiratory syndrome coronavirus-2 infection between February 15, 2020, and November 30, 2020, according to age and type of organ support therapies.
About 168 hospitals in 16 countries within the Society of Critical Care Medicine's Discovery Viral Infection and Respiratory Illness University Study coronavirus disease 2019 registry.
Adult hospitalized coronavirus disease 2019 patients who did and did not require various types and combinations of organ support (mechanical ventilation, renal replacement therapy, vasopressors, and extracorporeal membrane oxygenation).
None.
Primary outcome was hospital mortality. Secondary outcomes were discharge home with or without assistance and hospital length of stay. Risk-adjusted variation in hospital mortality for patients receiving invasive mechanical ventilation was assessed by using multilevel models with hospitals as a random effect, adjusted for age, race/ethnicity, sex, and comorbidities. Among 20,608 patients with coronavirus disease 2019, the mean (± sd) age was 60.5 (±17), 11,1887 (54.3%) were men, 8,745 (42.4%) were admitted to the ICU, and 3,906 (19%) died in the hospital. Hospital mortality was 8.2% for patients receiving no organ support (n = 15,001). The most common organ support therapy was invasive mechanical ventilation (n = 5,005; 24.3%), with a hospital mortality of 49.8%. Mortality ranged from 40.8% among patients receiving only invasive mechanical ventilation (n =1,749) to 71.6% for patients receiving invasive mechanical ventilation, vasoactive drugs, and new renal replacement therapy (n = 655). Mortality was 39% for patients receiving extracorporeal membrane oxygenation (n = 389). Rates of discharge home ranged from 73.5% for patients who did not require organ support therapies to 29.8% for patients who only received invasive mechanical ventilation, and 8.8% for invasive mechanical ventilation, vasoactive drugs, and renal replacement; 10.8% of patients older than 74 years who received invasive mechanical ventilation were discharged home. Median hospital length of stay for patients on mechanical ventilation was 17.1 days (9.7-28 d). Adjusted interhospital variation in mortality among patients receiving invasive mechanical ventilation was large (median odds ratio 1.69).
Coronavirus disease 2019 prognosis varies by age and level of organ support. Interhospital variation in mortality of mechanically ventilated patients was not explained by patient characteristics and requires further evaluation.
Objective
To determine the relation of gray matter (GM) and white matter (WM) brain volumes, and WM lesion load, with clinical outcomes 20 years after first presentation with clinically isolated ...syndrome suggestive of multiple sclerosis (MS).
Methods
Seventy‐three patients were studied a mean of 20 years from first presentation with a clinically isolated syndrome (33 of whom developed relapsing‐remitting MS and 11 secondary‐progressive MS, with the rest experiencing no further definite neurological events), together with 25 healthy control subjects. GM and WM volumetric measures were obtained from three‐dimensional T1‐weighted brain magnetic resonance images using Statistical Parametric Mapping 2.
Results
Significant GM (p < 0.001) and WM atrophy (p = 0.001) was seen in MS patients compared with control subjects. There was significantly more GM, but not WM atrophy, in secondary‐progressive MS versus relapsing‐remitting MS (p = 0.003), and relapsing‐remitting MS versus clinically isolated syndrome (p < 0.001). GM, but not WM, fraction correlated with expanded disability status scale (rs = −0.48; p < 0.001) and MS Functional Composite scores (rs = 0.59; p < 0.001). WM lesion load correlated with GM (rs = −0.63; p < 0.001), but not with WM fraction. Regression modeling indicated that the GM fraction explained more of the variability in clinical measures than did WM lesion load.
Interpretation
In MS patients with a relatively long and homogeneous disease duration, GM atrophy is more marked than WM atrophy, and reflects disease subtype and disability to a greater extent than WM atrophy or lesions. Ann Neurol 2008
Clinicians and laboratories routinely use urinalysis (UA) parameters to determine whether antimicrobial treatment and/or urine cultures are needed. Yet the performance of individual UA parameters and ...common thresholds for action are not well defined and may vary across different patient populations.
In this retrospective cohort study, we included all encounters with UAs ordered 24 hours prior to a urine culture between 2015 and 2020 at 3 North Carolina hospitals. We evaluated the performance of relevant UA parameters as potential outcome predictors, including sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). We also combined 18 different UA criteria and used receiver operating curves to identify the 5 best-performing models for predicting significant bacteriuria (≥100,000 colony-forming units of bacteria/mL).
In 221,933 encounters during the 6-year study period, no single UA parameter had both high sensitivity and high specificity in predicting bacteriuria. Absence of leukocyte esterase and pyuria had a high NPV for significant bacteriuria. Combined UA parameters did not perform better than pyuria alone with regard to NPV. The high NPV ≥0.90 of pyuria was maintained among most patient subgroups except females aged ≥65 years and patients with indwelling catheters.
When used as a part of a diagnostic workup, UA parameters should be leveraged for their NPV instead of sensitivity. Because many laboratories and hospitals use reflex urine culture algorithms, their workflow should include clinical decision support and or education to target symptomatic patients and focus on populations where absence of pyuria has high NPV.
Although specific interventions previously demonstrated benefit in patients with ARDS, use of these interventions is inconsistent, and patient mortality remains high. The impact of variability in ...center management practices on ARDS mortality rates remains unknown.
What is the impact of treatment variability on mortality in patients with moderate to severe ARDS in the United States?
We conducted a multicenter, observational cohort study of mechanically ventilated adults with ARDS and Pao
to Fio
ratio of ≤ 150 with positive end-expiratory pressure of ≥ 5 cm H
O, who were admitted to 29 US centers between October 1, 2016, and April 30, 2017. The primary outcome was 28-day in-hospital mortality. Center variation in ventilator management, adjunctive therapy use, and mortality also were assessed.
A total of 2,466 patients were enrolled. Median baseline Pao
to Fio
ratio was 105 (interquartile range, 78.0-129.0). In-hospital 28-day mortality was 40.7%. Initial adherence to lung protective ventilation (LPV; tidal volume, ≤ 6.5 mL/kg predicted body weight; plateau pressure, or when unavailable, peak inspiratory pressure, ≤ 30 mm H
O) was 31.4% and varied between centers (0%-65%), as did rates of adjunctive therapy use (27.1%-96.4%), methods used (neuromuscular blockade, prone positioning, systemic steroids, pulmonary vasodilators, and extracorporeal support), and mortality (16.7%-73.3%). Center standardized mortality ratios (SMRs), calculated using baseline patient-level characteristics to derive expected mortality rate, ranged from 0.33 to 1.98. Of the treatment-level factors explored, only center adherence to early LPV was correlated with SMR.
Substantial center-to-center variability exists in ARDS management, suggesting that further opportunities for improving ARDS outcomes exist. Early adherence to LPV was associated with lower center mortality and may be a surrogate for overall quality of care processes. Future collaboration is needed to identify additional treatment-level factors influencing center-level outcomes.
ClinicalTrials.gov; No.: NCT03021824; URL: www.clinicaltrials.gov.
Background
Given the high risk of COVID‐19 mortality, patients with cancer may be vulnerable to fear of COVID‐19, adverse psychological outcomes, and health care delays.
Methods
This longitudinal ...study surveyed the pandemic's impact on patients with cancer (N= 1529) receiving Patient Advocate Foundation services during early and later pandemic. Generalized estimating equation with repeated measures was conducted to assess the effect of COVID‐19 on psychological distress. Logistic regression with repeated measures was used to assess the effect of COVID‐19 on any delays in accessing health care (e.g., specialty care doctors, laboratory, or diagnostic testing, etc.).
Results
Among 1199 respondents, 94% considered themselves high risk for COVID‐19. Respondents with more fear of COVID‐19 had a higher mean psychological distress score (10.21; 95% confidence intervals CI 9.38–11.03) compared to respondents with less fear (7.55; 95% CI 6.75–8.36). Additionally, 47% reported delaying care. Respondents with more fear of COVID‐19 had higher percentages of delayed care than those with less (56; 95% CI 39%–72% vs. 44%; 95% CI 28%–61%). These relationships persisted throughout the pandemic. For respondents with a COVID‐19 diagnosis in their household (n = 116), distress scores were similar despite higher delays in care (58% vs. 27%) than those without COVID‐19.
Conclusions
Fear of COVID‐19 is linked to psychological distress and delays in care among patients with cancer. Furthermore, those who are personally impacted see exacerbated cancer care delays. Timely psychosocial support and health care coordination are critical to meet increased care needs of patients with cancer during the COVID‐19 pandemic.
Fear of COVID‐19 is associated with psychological distress and delay in cancer care. Timely psychosocial support and health care coordination are needed to meet increased care needs of patient with cancer during the pandemic.
To study disease development, an inventory of an organ's cell types and understanding of physiologic function is paramount. Here, we performed single-cell RNA-sequencing to examine heterogeneity of ...murine pancreatic duct cells, pancreatobiliary cells, and intrapancreatic bile duct cells. We describe an epithelial-mesenchymal transitory axis in our three pancreatic duct subpopulations and identify osteopontin as a regulator of this fate decision as well as human duct cell dedifferentiation. Our results further identify functional heterogeneity within pancreatic duct subpopulations by elucidating a role for geminin in accumulation of DNA damage in the setting of chronic pancreatitis. Our findings implicate diverse functional roles for subpopulations of pancreatic duct cells in maintenance of duct cell identity and disease progression and establish a comprehensive road map of murine pancreatic duct cell, pancreatobiliary cell, and intrapancreatic bile duct cell homeostasis.
Schizophrenia may develop from disruptions in functional connectivity regulated by neurotransmitters such as dopamine and acetylcholine. The modulatory effects of these neurotransmitters might ...explain how antipsychotics attenuate symptoms of schizophrenia and account for the variable response to antipsychotics observed in clinical practice. Based on the putative mechanisms of antipsychotics and evidence of disrupted connectivity in schizophrenia, we hypothesised that functional network connectivity, as assessed using network-based statistics, would exhibit differences between treatment response subtypes of schizophrenia and healthy controls. Resting-state functional MRI data were obtained from 17 healthy controls as well as individuals with schizophrenia who responded well to first-line atypical antipsychotics (first-line responders; FLR, n=18), had failed at least two trials of antipsychotics but responded to clozapine (treatment-resistant schizophrenia; TRS, n=18), or failed at least two trials of antipsychotics and a trial of clozapine (ultra-treatment-resistant schizophrenia; UTRS, n=16). Data were pre-processed using the Advanced Normalization Toolkit and BrainWavelet Toolbox. Network connectivity was assessed using the Network-Based Statistics toolbox in Matlab. ANOVA revealed a significant difference in functional connectivity between groups that extended between cerebellar and parietal regions to the frontal cortex (p<0.05). Post-hoc t-tests revealed weaker network connectivity in individuals with UTRS compared with healthy controls but no other differences between groups. Results demonstrated distinct differences in functional connectivity between individuals with UTRS and healthy controls. Future work must determine whether these changes occur prior to the onset of treatment and if they can be used to predict resistance to antipsychotics during first-episode psychosis.
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