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Patient characteristics, clinical care, resource use and outcomes associated with admission to hospital for coronavirus disease 2019 (COVID-19) in Canada are not well described. We described all adults with COVID-19 or influenza discharged from inpatient medical services and medical–surgical intensive care units (ICUs) between Nov. 1, 2019, and June 30, 2020, at 7 hospitals in Toronto and Mississauga, Ontario. We compared patient outcomes using multivariable regression models, controlling for patient sociodemographic factors and comorbidity level. We validated the accuracy of 7 externally developed risk scores to predict mortality among patients with COVID-19. There were 1027 hospital admissions with COVID-19 (median age 65 yr, 59.1% male) and 783 with influenza (median age 68 yr, 50.8% male). Patients younger than 50 years accounted for 21.2% of all admissions for COVID-19 and 24.0% of ICU admissions. Compared with influenza, patients with COVID-19 had significantly greater in-hospital mortality (unadjusted 19.9% v. 6.1%, adjusted relative risk [RR] 3.46, 95% confidence interval [CI] 2.56–4.68), ICU use (unadjusted 26.4% v. 18.0%, adjusted RR 1.50, 95% CI 1.25–1.80) and hospital length of stay (unadjusted median 8.7 d v. 4.8 d, adjusted rate ratio 1.45, 95% CI 1.25–1.69). Thirty-day readmission was not significantly different (unadjusted 9.3% v. 9.6%, adjusted RR 0.98, 95% CI 0.70–1.39). Three points-based risk scores for predicting in-hospital mortality showed good discrimination (area under the receiver operating characteristic curve [AUC] ranging from 0.72 to 0.81) and calibration. During the first wave of the pandemic, admission to hospital for COVID-19 was associated with significantly greater mortality, ICU use and hospital length of stay than influenza. Simple risk scores can predict in-hospital mortality in patients with COVID-19 with good accuracy.

Disability-related considerations have largely been absent from the COVID-19 response, despite evidence that people with disabilities are at elevated risk for acquiring COVID-19. We evaluated clinical outcomes in patients who were admitted to hospital with COVID-19 with a disability compared with patients without a disability. We conducted a retrospective cohort study that included adults with COVID-19 who were admitted to hospital and discharged between Jan. 1, 2020, and Nov. 30, 2020, at 7 hospitals in Ontario, Canada. We compared in-hospital death, admission to the intensive care unit (ICU), hospital length of stay and unplanned 30-day readmission among patients with and without a physical disability, hearing or vision impairment, traumatic brain injury, or intellectual or developmental disability, overall and stratified by age (≤ 64 and ≥ 65 yr) using multivariable regression, controlling for sex, residence in a long-term care facility and comorbidity. Among 1279 admissions to hospital for COVID-19, 22.3% had a disability. We found that patients with a disability were more likely to die than those without a disability (28.1% v. 17.6%), had longer hospital stays (median 13.9 v. 7.8 d) and more readmissions (17.6% v. 7.9%), but had lower ICU admission rates (22.5% v. 28.3%). After adjustment, there were no statistically significant differences between those with and without disabilities for in-hospital death or admission to ICU. After adjustment, patients with a disability had longer hospital stays (rate ratio 1.36, 95% confidence interval [CI] 1.19–1.56) and greater risk of readmission (relative risk 1.77, 95% CI 1.14–2.75). In age-stratified analyses, we observed longer hospital stays among patients with a disability than in those without, in both younger and older subgroups; readmission risk was driven by younger patients with a disability. Patients with a disability who were admitted to hospital with COVID-19 had longer stays and elevated readmission risk than those without disabilities. Disability-related needs should be addressed to support these patients in hospital and after discharge.

Small fiber neuropathy (SFN) affects small-diameter sensory and autonomic nerve fibers, leading to chronic pain and autonomic dysfunction. While SFN can be associated with diabetes and autoimmune diseases, a significant proportion of cases are idiopathic. Although immune-mediated mechanisms are being recognized increasingly in SFN, their precise role remains unclear. This study investigates the presence of autoantibodies against interferon-induced GTP-binding protein MX (MX1) in SFN patients and explores their potential pathogenic role. A total of 59 patients with skin biopsy-confirmed SFN and 20 healthy controls were recruited. Serum samples were analyzed for the presence of anti-MX1 autoantibodies using enzyme-linked immunosorbent assay (ELISA). Immunohistochemistry was performed on rat sciatic nerves to assess the localization of patient IgG to unmyelinated nerve fibers, and immunocytochemistry and flow cytometry confirmed specific binding to MX1. Functional characterization of MX1 was conducted using whole-cell patch-clamp recordings in dorsal root ganglion (DRG) neurons overexpressing MX1. Additionally, protein interactions between MX1 and transient receptor potential cation channel subfamily C member 6 (TRPC6) were assessed using co-immunoprecipitation and surface biotinylation assays. Anti-MX1 autoantibody levels were significantly elevated in SFN patients compared to controls ( p  = 0.0278), particularly in the autoimmune SFN subgroup. Patient sera exhibited IgG binding to unmyelinated nerve fibers, with idiopathic and autoimmune SFN cases showing similar staining patterns, suggesting a similar immune-mediated mechanism. Immunocytochemistry showed binding to HEK293-MX1 cells and flow cytometry revealed higher MX1/WT fluorescence intensity ratios in patient sera, further confirming specific immune recognition of MX1. Patch-clamp recordings demonstrated that MX1 overexpression in DRG neurons led to significant membrane depolarization and increased action potential firing frequency ( p  < 0.0001), indicating heightened neuronal excitability. However, MX1 did not directly interact with TRPC6 or alter its function, suggesting an alternative pathway for its effects. The addition of anti-MX1 IgG did not further modify DRG electrophysiology, implying that the autoimmune component may contribute to SFN pathogenesis through indirect mechanisms. Our findings support the hypothesis that MX1 influences neuronal excitability and plays a role in SFN pathophysiology. Future studies should validate these findings in larger cohorts and explore potential therapeutic strategies targeting MX1-associated pathways in SFN.

This study aimed to compare the outcomes of single-incision laparoscopic cholecystectomy (SILC) versus conventional 4-port laparoscopic cholecystectomy (LC). From November 2009 to August 2010, 51 patients with symptomatic gallstone or gallbladder polyps were randomized to SILC (n = 24) or 4-port LC (n = 27). Mean surgical time (43.5 vs 46.5 min), median blood loss (1 vs 1 mL) and mean hospital stay (1.5 vs 1.8 d) were similar for both the SILC and 4-port LC group. There were no open conversions and no major complications. The mean total wound length of the SILC group was significantly shorter (1.76 vs 2.25 cm). The median visual analogue pain score at 6 hours after surgery was similar (4.5 vs 4.0) but the SILC group had a significantly worse pain score on day 7 (1 vs 0). There was no difference in time to resume usual activity (mean, 5.6 vs 5.0 d). The median cosmetic score of SILC was significantly higher than at 3 months after surgery (7 vs 6). SILC was feasible and safe for properly selected patients in experienced hands.

How consciousness is lost in states such as sleep or anesthesia remains a mystery. To gain insight into this phenomenon, concurrent recordings of electrophysiology signals in the anterior cingulate cortex and whole‐brain functional magnetic resonance imaging (fMRI) are conducted in rats exposed to graded propofol, undergoing the transition from consciousness to unconsciousness. The results reveal that upon the loss of consciousness (LOC), there is a sharp increase in low‐frequency power of the electrophysiological signal. Additionally, fMRI signals exhibit a cascade of deactivation across a pathway including the hippocampus, thalamus, and medial prefrontal cortex (mPFC) surrounding the moment of LOC, followed by a broader increase in brain activity across the cortex during sustained unconsciousness. Furthermore, sliding window analysis demonstrates a temporary increase in synchrony of fMRI signals across the hippocampus‐thalamus‐mPFC pathway preceding LOC. These data suggest that LOC may be triggered by sequential activities in the hippocampus, thalamus, and mPFC, while wide‐spread activity increases in other cortical regions commonly observed during anesthesia‐induced unconsciousness may be a consequence, rather than a cause of LOC. Taken together, the study identifies a cascade of neural events unfolding as the brain transitions into unconsciousness, offering insight into the systems‐level neural mechanisms underpinning LOC. How consciousness is lost in states such as sleep or anesthesia remains a subject of mystery. To gain insight into this phenomenon, concurrent recordings of electrophysiology and whole‐brain fMRI are conducted in rats exposed to graded propofol, undergoing the transition from consciousness to unconsciousness. The results reveal a cascade of neural events surrounding the moment of LOC.

To investigate and compare the diagnostic ability of corneal tomography and biomechanical and combined parameters for detection of corneal ectasia. Consecutive patients with subclinical keratoconus (SCKC) and age-matched controls were included. Only one eye from each patient was selected for analysis. The final D value from the Belin/Ambrósio Enhanced Ectasia Display (BAD) was obtained from the Pentacam (Oculus Optikgeräte, Wetzlar, Germany). The tomographic biomechanical index (TBI) was derived from the Pentacam and Corvis ST (Oculus Optikgeräte). Classification analysis between normal and subclinical keratoconus (SCKC) was evaluated using receiver operating characteristic (ROC) curves. The area under the ROC curve (AUC) and partial AUC (pAUC) with specificity of 80% or greater were compared. Twenty-three eyes with SCKC and 37 normal eyes were included. All Pentacam-derived parameters (P < .001) and all but two Corvis ST-derived parameters (P < .020) were significantly different between normal and SCKC eyes. A significant difference was found in the final D value (P ≤ .020) and TBI (P ≤ .040) between normal and SCKC eyes. For differentiating normal and SCKC eyes, TBI and BAD final D value demonstrated the highest AUC (0.925 and 0.786, respectively) and pAUC (0.150 and 0.088, respectively). TBI demonstrated 84.4% sensitivity and 82.4% specificity using a cut-off of 0.16. Comparative analysis between these parameters showed that AUC and pAUC of TBI were significantly higher than all parameters from Pentacam (P ≤ .032). In the current study, combined use of tomographic and biomechanical parameters demonstrated a higher capability in differentiating normal and SCKC eyes when compared to tomographic analysis alone. [J Refract Surg. 2018;34(9):616-621.].

In classical inverse linear optimization, one assumes that a given solution is a candidate to be optimal. Real data are imperfect and noisy, so there is no guarantee that this assumption is satisfied. Inspired by regression, this paper presents a unified framework for cost function estimation in linear optimization comprising a general inverse optimization model and a corresponding goodness-of-fit metric. Although our inverse optimization model is nonconvex, we derive a closed-form solution and present the geometric intuition. Our goodness-of-fit metric, ρ , the coefficient of complementarity , has similar properties to R 2 from regression and is quasi-convex in the input data, leading to an intuitive geometric interpretation. While ρ is computable in polynomial time, we derive a lower bound that possesses the same properties, is tight for several important model variations, and is even easier to compute. We demonstrate the application of our framework for model estimation and evaluation in production planning and cancer therapy. This paper was accepted by Yinyu Ye, optimization.

Toxin B (TcdB) is a major pathogenic factor of Clostridum difficile. However, the mechanism by which TcdB exerts its cytotoxic action in host cells is still not completely known. Herein, we report for the first time that TcdB induced autophagic cell death in cultured human colonocytes. The induction of autophagy was demonstrated by the increased levels of LC3‐II, formation of LC3+ autophagosomes, accumulation of acidic vesicular organelles and reduced levels of the autophagic substrate p62/SQSTM1. TcdB‐induced autophagy was also accompanied by the repression of phosphoinositide 3‐kinase (PI3K)/Akt/mechanistic target of rapamycin (mTOR) complex 1 activity. Functionally, pharmacological inhibition of autophagy by wortmannin or chloroquine or knockdown of autophagy‐related genes Beclin 1, Atg5 and Atg7 attenuated TcdB‐induced cell death in colonocytes. Genetic ablation of Atg5, a gene required for autophagosome formation, also mitigated the cytotoxic effect of TcdB. In conclusion, our study demonstrated that autophagy serves as a pro‐death mechanism mediating the cytotoxic action of TcdB in colonocytes. This discovery suggested that blockade of autophagy might be a novel therapeutic strategy for C. difficile infection.

Defining demographic and ecological threshold of population persistence can assist in informing conservation management. We undertook such analyses for the Indo-Pacific humpback dolphin ( Sousa chinensis ) in the Pearl River Delta (PRD) region, southeast China. We use adult survival estimates for assessments of population status and annual rate of change. Our estimates indicate that, given a stationary population structure and minimal risk scenario, ~2000 individuals (minimum viable population in carrying capacity, MVP k ) can maintain the population persistence across 40 generations. However, under the current population trend (~2.5% decline/annum), the population is fast approaching its viability threshold and may soon face effects of demographic stochasticity. The population demographic trajectory and the minimum area of critical habitat (MACH) that could prevent stochastic extinction are both highly sensitive to fluctuations in adult survival. For a hypothetical stationary population, MACH should approximate 3000-km 2 . However, this estimate increases four-fold with a 5% increase of adult mortality and exceeds the size of PRD when calculated for the current population status. On the other hand, cumulatively all current MPAs within PRD fail to secure the minimum habitat requirement to accommodate sufficiently viable population size. Our findings indicate that the PRD population is deemed to become extinct unless effective conservation measures can rapidly reverse the current population trend.

Out-of-hospital cardiac arrest is a significant public health issue, and treatment, namely, cardiopulmonary resuscitation and defibrillation, is very time sensitive. Public access defibrillation programs, which deploy automated external defibrillators (AEDs) for bystander use in an emergency, reduce the time to defibrillation and improve survival rates. In this paper, we develop models to guide the deployment of public AEDs. Our models generalize existing location models and incorporate differences in bystander behavior. We formulate three mixed integer nonlinear models and derive equivalent integer linear reformulations or easily computable bounds. We use kernel density estimation to derive a spatial probability distribution of cardiac arrests that is used for optimization and model evaluation. Using data from Toronto, Canada, we show that optimizing AED deployment outperforms the existing approach by 40% in coverage, and substantial gains can be achieved through relocating existing AEDs. Our results suggest that improvements in survival and cost-effectiveness are possible with optimization. This paper was accepted by Dimitris Bertsimas, optimization .