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Heat shock protein 90 (Hsp90) is an ATP-dependent molecular chaperone which is essential in eukaryotes. It is required for the activation and stabilization of a wide variety of client proteins and many of them are involved in important cellular pathways. Since Hsp90 affects numerous physiological processes such as signal transduction, intracellular transport, and protein degradation, it became an interesting target for cancer therapy. Structurally, Hsp90 is a flexible dimeric protein composed of three different domains which adopt structurally distinct conformations. ATP binding triggers directionality in these conformational changes and leads to a more compact state. To achieve its function, Hsp90 works together with a large group of cofactors, termed co-chaperones. Co-chaperones form defined binary or ternary complexes with Hsp90, which facilitate the maturation of client proteins. In addition, posttranslational modifications of Hsp90, such as phosphorylation and acetylation, provide another level of regulation. They influence the conformational cycle, co-chaperone interaction, and inter-domain communications. In this review, we discuss the recent progress made in understanding the Hsp90 machinery.

Posttraumatic stress disorder is associated with a high economic burden. Costs of treatment are known to be high, and cost-effectiveness has been analysed for several treatment options. As no review on economic aspects of posttraumatic stress disorder exists, the aim of this study was to systematically review costs-of-illness studies and economic evaluations of therapeutic treatment for posttraumatic stress disorder, and to assess their quality. A systematic literature search was performed in March 2017 and was last updated in February 2020 in the databases PubMed, PsychInfo and NHS Economic Evaluation Database. Cost-of-illness studies and economic evaluations of treatment for posttraumatic stress disorder were selected. Extracted cost data were categorized as direct costs and indirect costs and inflated to 2015 US-$ purchasing power parities (PPP). Quality was assessed using an adapted cost-of-illness studies quality checklist, the Consensus on Health Economic Criteria list, and the questionnaire to assess relevance and credibility of modelling studies by the International Society for Pharmacoeconomics and Outcome Research. In total, 13 cost-of-illness studies and 18 economic evaluations were included in the review. Annual direct excess costs ranged from 512 US-$ PPP to 19,435 US-$ PPP and annual indirect excess costs were 5,021 US-$ PPP per person. Trauma-focused cognitive-behavioural therapy (+selective serotonin re-uptake inhibitor) was found to be cost-effective compared with treatment as usual and no treatment. Overall, included studies were of low and moderate quality. Studies used inappropriate economic study designs and lacked information on the economic perspective used. Posttraumatic stress disorder is a major public health problem that causes high healthcare costs. While trauma-focused cognitive-behavioural therapy was found to be cost-effective, further investigations regarding pharmacotherapy and other treatments are necessary.

Ki67 index is now an essential part of classification of pancreatic neuroendocrine tumors. However, its adaptation into daily practice has been fraught with challenges related to counting methodology. In this study, three reviewers used four counting methodologies to calculate Ki67 index in 68 well-differentiated pancreatic neuroendocrine tumors: (1) ‘eye-ball’ estimation, which has been advocated as reliable and is widely used; (2) automated counting by image analyzer; (3) manual eye-counting (eye under a microscope without a grid); and (4) manual count of camera-captured/printed image. Pearson’s correlation ( R ) was used to measure pair-wise correlation among three reviewers using all four methodologies. Average level of agreement was calculated using mean of R values. The results showed that: (1) ‘eye-balling’ was least expensive and fastest (average time <1 min) but had poor reliability and reproducibility. (2) Automated count was the most expensive and least practical with major impact on turnaround time (limited by machine and personnel accessibility), and, more importantly, had inaccuracies in overcounting unwanted material. (3) Manual eye count had no additional cost, averaged 6 min, but proved impractical and poorly reproducible. (4) Camera-captured/printed image was most reliable, had highest reproducibility, but took longer than ‘eye-balling’. In conclusion, based on its comparatively low cost/benefit ratio and reproducibility, camera-captured/printed image appears to be the most practical for calculating Ki67 index. Although automated counting is generally advertised as the gold standard for index calculation, in this study it was not as accurate or cost-effective as camera-captured/printed image and was highly operator-dependent. ‘Eye-balling’ produces highly inaccurate and unreliable results, and is not recommended for routine use.

Involuntary movements develop after 1-4% of strokes and they have been reported in patients with ischemic and hemorrhagic strokes affecting the basal ganglia, thalamus, and/or their connections. Hemichorea-hemiballism is the most common movement disorder following a stroke in adults while dystonia is most common in children. Tremor, myoclonus, asterixis, stereotypies, and vascular parkinsonism are other movement disorders seen following stroke. Some of them occur immediately after acute stroke, some can develop later, and others may have delayed onset progressive course. Proposed pathophysiological mechanisms include neuronal plasticity, functional diaschisis, and age-related differences in brain metabolism. There are no guidelines regarding the management of post-stroke movement disorders, mainly because of their heterogeneity.

Much research in cognitive psychology has focused on the tendency to conserve limited cognitive resources. The CRT is the predominant measure of such miserly information processing, and also predicts a number of frequently studied decision-making traits (such as belief bias and need for cognition). However, many subjects from common subject populations have already been exposed to the questions, which might add considerable noise to data. Moreover, the CRT has been shown to be confounded with numeracy. To increase the pool of available questions and to try to address numeracy confounds, we developed and tested the CRT-2. CRT-2 questions appear to rely less on numeracy than the original CRT but appear to measure closely related constructs in other respects. Crucially, substantially fewer subjects from Amazon’s Mechanical Turk have been previously exposed to CRT-2 questions. Though our primary purpose was investigating the CRT-2, we also found that belief bias questions appear suitable as an additional source of new items. Implications and remaining measurement challenges are discussed.

The phytopathogenic basidiomycetous fungus, Rhizoctonia solani, has a wide range of host plants including members of the family Poaceae, causing damping-off and root rot diseases. In this study, we biosynthesized spherical-shaped silicon dioxide nanoparticles (SiO2 NPs; sized between 9.92 and 19.8 nm) using saffron extract and introduced them as a potential alternative therapeutic solution to protect wheat seedlings against R. solani. SiO2 NPs showed strong dose-dependent fungistatic activity on R. solani, and significantly reduced mycelial radial growth (up to 100% growth reduction), mycelium fresh and dry weight, and pre-, post-emergence damping-off, and root rot severities. Moreover, the impact of SiO2 NPs on the growth of wheat seedlings and their potential mechanism (s) for disease suppression was deciphered. SiO2 NPs application also improved the germination, vegetative growth, and vigor indexes of infected wheat seedlings which indicates no phytotoxicity on treated wheat seedlings. Moreover, SiO2 NPs enhanced the content of the photosynthetic pigments (chlorophylls and carotenoids), induced the accumulation of defense-related compounds (particularly salicylic acid), and alleviated the oxidative stress via stimulation of both enzymatic (POD, SOD, APX, CAT, and PPO) and non-enzymatic (phenolics and flavonoids) antioxidant defense machinery. Collectively, our findings demonstrated the potential therapeutic role of SiO2 NPs against R. solani infection via the simultaneous activation of a multilayered defense system to suppress the pathogen, neutralize the destructive effect of ROS, lipid peroxidation, and methylglyoxal, and maintain their homeostasis within R. solani-infected plants.

Synthetic Aperture Radar (SAR) observations are widely used in emergency response for flood mapping and monitoring. However, the current operational services are mainly focused on flood in rural areas and flooded urban areas are less considered. In practice, urban flood mapping is challenging due to the complicated backscattering mechanisms in urban environments and in addition to SAR intensity other information is required. This paper introduces an unsupervised method for flood detection in urban areas by synergistically using SAR intensity and interferometric coherence under the Bayesian network fusion framework. It leverages multi-temporal intensity and coherence conjunctively to extract flood information of varying flooded landscapes. The proposed method is tested on the Houston (US) 2017 flood event with Sentinel-1 data and Joso (Japan) 2015 flood event with ALOS-2/PALSAR-2 data. The flood maps produced by the fusion of intensity and coherence and intensity alone are validated by comparison against high-resolution aerial photographs. The results show an overall accuracy of 94.5% (93.7%) and a kappa coefficient of 0.68 (0.60) for the Houston case, and an overall accuracy of 89.6% (86.0%) and a kappa coefficient of 0.72 (0.61) for the Joso case with the fusion of intensity and coherence (only intensity). The experiments demonstrate that coherence provides valuable information in addition to intensity in urban flood mapping and the proposed method could be a useful tool for urban flood mapping tasks.

Diabetes is a worldwide epidemic, and associated neuropathy is its most costly and disabling complication. Given the rising prevalence of painful diabetic neuropathy, it is increasingly important that we understand the best ways to diagnose and treat this condition. Diagnostic tests in this field are evolving rapidly. These include the use of skin biopsies to measure small unmyelinated fibers, as well as even newer techniques that can measure both small unmyelinated fibers and large myelinated fibers in the same biopsy. The main treatments for painful diabetic neuropathy remain management of the underlying diabetes and drugs for the relief of pain. However, emerging evidence points to major differences between type 1 and type 2 diabetes, including the ability of glycemic control to prevent neuropathy. Enhanced glucose control is much more effective at preventing neuropathy in patients with type 1 diabetes than in those with type 2 disease. This dichotomy emphasizes the need to study the pathophysiologic differences between the two types of diabetes, because different treatments may be needed for each condition. The impact of the metabolic syndrome on neuropathy in patients with type 2 diabetes may account for the difference between the two types of diabetes and requires further study. Finally, neuropathic pain is under-recognized and undertreated despite an ever evolving list of effective drugs. Evidence exists to support several drugs, but the optimal sequence and combination of these drugs are still to be determined.

A growing number of population pharmacokinetic analyses of therapeutic monoclonal antibodies (mAbs) have been published in the scientific literature. The aims of this article are to summarize the findings from these studies and to relate the findings to the general pharmacokinetic and structural characteristics of therapeutic mAbs. A two-compartment model was used in the majority of the population analyses to describe the disposition of the mAb. Population estimates of the volumes of distribution in the central (V 1 ) and peripheral (V 2 ) compartments were typically small, with median (range) values of 3.1 (2.4–5.5) L and 2.8 (1.3–6.8) L, respectively. The estimated between-subject variability in the V 1 was usually moderate, with a median (range) coefficient of variation (CV) of 26% (12–84%). Between-subject variability in other distribution-related parameters such as the V 2 and intercompartmental clearance were often not estimated. Although the pharmacokinetic models used most frequently in the population analyses were models with linear clearance, other models with nonlinear, or parallel linear and nonlinear clearance pathways were also applied, as many therapeutic mAbs are eliminated via saturable target-mediated mechanisms. Population estimates of the maximum elimination rate (V max ) and the mAb concentration at which elimination was at half maximum for Michaelis-Menten-type elimination pathways varied considerably among the different therapeutic mAbs. However, estimates of the total clearance (CL) of mAbs with linear clearance characteristics and of the clearance of mAbs via the linear clearance pathway (CL L ) with parallel linear and nonlinear clearance were quite similar for the different mAbs and typically ranged from 0.2 to 0.5 L/day, which is relatively close to the estimated clearance of endogenous IgG of 0.21 L/day. The between-subject variability in the V max , CL and CL L was moderate to high, with estimated CVs ranging from 15% to 65%. Measures of body size were the covariates most commonly identified as influencing the pharmacokinetics of therapeutic mAbs. In summary, many features of the population pharmacokinetics of currently used therapeutic mAbs are similar, despite differences in their pharmacological targets and studied patient populations.

Background: Day-of-surgery cancellation (DoSC) represents a substantial wastage of hospital resources and can cause significant inconvenience to patients and families. Cancellation is reported to impact between 2% and 20% of the 50 million procedures performed annually in American hospitals. Up to 85% of cancellations may be amenable to the modification of patients’ and families’ behaviors. However, the factors underlying DoSC and the barriers experienced by families are not well understood. Objective: This study aims to conduct a geospatial analysis of patient-specific variables from electronic health records (EHRs) of Cincinnati Children’s Hospital Medical Center (CCHMC) and of Texas Children’s Hospital (TCH), as well as linked socioeconomic factors measured at the census tract level, to understand potential underlying contributors to disparities in DoSC rates across neighborhoods. Methods: The study population included pediatric patients who underwent scheduled surgeries at CCHMC and TCH. A 5-year data set was extracted from the CCHMC EHR, and addresses were geocoded. An equivalent set of data >5.7 years was extracted from the TCH EHR. Case-based data related to patients’ health care use were aggregated at the census tract level. Community-level variables were extracted from the American Community Survey as surrogates for patients’ socioeconomic and minority status as well as markers of the surrounding context. Leveraging the selected variables, we built spatial models to understand the variation in DoSC rates across census tracts. The findings were compared to those of the nonspatial regression and deep learning models. Model performance was evaluated from the root mean squared error (RMSE) using nested 10-fold cross-validation. Feature importance was evaluated by computing the increment of the RMSE when a single variable was shuffled within the data set. Results: Data collection yielded sets of 463 census tracts at CCHMC (DoSC rates 1.2%-12.5%) and 1024 census tracts at TCH (DoSC rates 3%-12.2%). For CCHMC, an L2-normalized generalized linear regression model achieved the best performance in predicting all-cause DoSC rate (RMSE 1.299%, 95% CI 1.21%-1.387%); however, its improvement over others was marginal. For TCH, an L2-normalized generalized linear regression model also performed best (RMSE 1.305%, 95% CI 1.257%-1.352%). All-cause DoSC rate at CCHMC was predicted most strongly by previous no show. As for community-level data, the proportion of African American inhabitants per census tract was consistently an important predictor. In the Texas area, the proportion of overcrowded households was salient to DoSC rate. Conclusions: Our findings suggest that geospatial analysis offers potential for use in targeting interventions for census tracts at a higher risk of cancellation. Our study also demonstrates the importance of home location, socioeconomic disadvantage, and racial minority status on the DoSC of children’s surgery. The success of future efforts to reduce cancellation may benefit from taking social, economic, and cultural issues into account.