Notes

Challenges connected with retrospective investigation of quit ventricular operate using clinical echocardiograms from a multicenter research study.
Dynamic resistance, which can be used to express strength in the unit of stress and improve the reliability of the dynamic cone penetration test (DCPT), has been estimated by numerous methods. This study aims to compare different dynamic resistance estimation methods by using an instrumented dynamic cone penetrometer (IDCP). DCPTs are conducted using a standard dynamic cone penetrometer (DCP) and IDCP in the laboratory and field. Dynamic responses are obtained from the strain gauges and an accelerometer installed at the cone tip of the IDCP. The test results show that dynamic resistance is more efficient in distinguishing profiles than the dynamic cone penetration index. Among the methods to estimate the dynamic resistance at the cone tip, the force-velocity integration method and force integration method are more related to the conventional dynamic resistance considering the potential energy of the hammer than the force squared integration method. Additionally, the dynamic resistance estimated for a longer time period is more reliable, particularly for small driving rod lengths. Regarding the limitation of the dynamic response from an accelerometer in a previous study, the force-based dynamic resistance estimated for a longer time period can be used as the most reliable approach for further soil strength characterization.
From 2010 onwards, the city of Rio de Janeiro has undergone changes related to the 2014 FIFA World Cup and the 2016 Olympic Games, potentially affecting the respiratory health of inhabitants. Thus, the spatial distribution of respiratory hospitalizations (2008-2017) and the relationship between this outcome and potential air pollution sources in the city of Rio de Janeiro (2013-2017) were evaluated.

An ecological study was performed using the Bayesian model with multivariate Poisson regression for the period of the sporting events (2013-2017). The outcome was the ratio of hospitalizations for respiratory diseases by the population at risk. Data analysis was performed in the total population and by sex and age group. The air pollution-related variables included industrial districts, traffic density, tunnel portals, a seaport, airports, and construction/road work.

All explanatory variables, except tunnel portals, were associated with an increase in the outcome. Construction/road work showed a greater magnitude of association than the other pollution-related variables. Airports were associated with an increased hospitalization ratio among the ≥60 year-old group (mean = 2.46, 95% credible intervals = 1.35-4.46).

This study allows for a better understanding of the geographical distribution of respiratory problems in the city of Rio de Janeiro. Present results may contribute to improved healthcare planning and raise hypotheses concerning exposure to air pollution and respiratory hospitalizations.
This study allows for a better understanding of the geographical distribution of respiratory problems in the city of Rio de Janeiro. Present results may contribute to improved healthcare planning and raise hypotheses concerning exposure to air pollution and respiratory hospitalizations.A high-fat diet (HFD) quickly induces obesity with insulin resistance and hyperglycemia. We previously reported that a novel hypothalamic small protein, named neurosecretory protein GL (NPGL), stimulates feeding and fat accumulation in mice. However, the effects of NPGL on insulin sensitivity and glucose homeostasis remain unknown. Hence, we subjected NPGL-precursor gene (Npgl)-overexpressing mice to the oral glucose tolerance test (OGTT) and intraperitoneal insulin tolerance test (IPITT) under normal chow (NC) and HFD conditions. Npgl overexpression promoted body mass gain and tended to increase food intake of NC-fed mice, whereas it had little effect on HFD-fed mice. The OGTT showed elevated blood glucose and insulin levels in Npgl-overexpressing NC-fed mice 15 min after glucose administration. Both the OGTT and IPITT demonstrated that Npgl overexpression decreased blood glucose levels in HFD-fed mice 60 min after glucose and insulin treatments. Notably, Npgl overexpression increased adipose tissue masses only in NC-fed mice, and it decreased blood glucose and insulin levels in HFD-fed mice at the experimental end point. It also increased the mRNA expression of galanin, one of the feeding and metabolic regulatory neuropeptides, in the hypothalamus of HFD-fed mice. Therefore, NPGL may alleviate HFD-induced hyperglycemia and insulin resistance in mice.Various light sources have been applied to enhance the bleaching effect. This study was to identify the histological evaluation in oral soft tissues, as well as tooth color change after tooth bleaching by nonthermal atmospheric pressure plasma (NAPP). Nine New Zealand adult female rabbits were randomly divided into three groups (n = 3) group 1 received no treatment; group 2 was treated with NAPP and 15% carbamide peroxide (CP), which contains 5.4% H2O2, and group 3 was treated with 15% CP without NAPP. Color change (ΔE) was measured using the Shade Eye NCC colorimeter. Animals were euthanized one day later to analyze the histological responses occurring in oral soft tissues, including pulp, gingiva, tongue, buccal mucosa, and hard and soft palates. Changes in all samples were analyzed by hematoxylin and eosin staining and Masson's trichrome. Teeth treated with plasma showed higher ΔE than that obtained with bleaching agents alone. Overall, the histological characteristics observed no appreciable changes. The combinational treatment of plasma had not indicated inflammatory responses as well as thermal damages. NAPP did not cause histological damage in oral soft tissues during tooth bleaching. We suggest that NAPP could be a novel alternative energy source to conventional light sources for tooth bleaching.Face mask use is a critical behavior to prevent the spread of SARS-CoV-2. We aimed to evaluate the association between social integration and face mask use during the COVID-19 pandemic in a random sample of households in Utsunomiya City, Greater Tokyo, Japan. Data included 645 adults in the Utsunomiya COVID-19 seROprevalence Neighborhood Association (U-CORONA) study, which was conducted after the first wave of the pandemic, between 14 June 2020 and 5 July 2020, in Utsunomiya City. Social integration before the pandemic was assessed by counting the number of social roles, based on the Cohen's social network index. Face mask use before and during the pandemic was assessed by questionnaire, and participants were categorized into consistent mask users, new users, and current non-users. Multinomial logistic regression analysis was used to examine the association between lower social integration score and face mask use. To account for possible differential non-response bias, non-response weights were used. Of the 645 participants, 172 (26.7%) were consistent mask users and 460 (71.3%) were new users, while 13 (2.0%) were current non-users. Lower social integration level was positively associated with non-users (RRR 1.76, 95% CI 1.10, 2.82). Social integration may be important to promote face mask use.
Diabetic peripheral neuropathy (DSPN), a major form of diabetic neuropathy, is a complication that arises in long-term diabetic patients. Even though the application of machine learning (ML) in disease diagnosis is a very common and well-established field of research, its application in diabetic peripheral neuropathy (DSPN) diagnosis using composite scoring techniques like Michigan Neuropathy Screening Instrumentation (MNSI), is very limited in the existing literature.

In this study, the MNSI data were collected from the Epidemiology of Diabetes Interventions and Complications (EDIC) clinical trials. Two different datasets with different MNSI variable combinations based on the results from the eXtreme Gradient Boosting feature ranking technique were used to analyze the performance of eight different conventional ML algorithms.

The random forest (RF) classifier outperformed other ML models for both datasets. However, all ML models showed almost perfect reliability based on Kappa statistics and a high correlation between the predicted output and actual class of the EDIC patients when all six MNSI variables were considered as inputs.

This study suggests that the RF algorithm-based classifier using all MNSI variables can help to predict the DSPN severity which will help to enhance the medical facilities for diabetic patients.
This study suggests that the RF algorithm-based classifier using all MNSI variables can help to predict the DSPN severity which will help to enhance the medical facilities for diabetic patients.
Interleukin-6 (IL-6) released by cancer-associated fibroblasts (CAFs) has been shown to associate with the malignant behavior of cholangiocarcinoma (CCA). Here, we aimed to validate with clinical and molecular data the hypothesis that CAF infiltration and release of IL-6 predict poor prognosis in CCA patients following dysregulation of autophagy in cancer cells.

Stromal IL-6 and cancer-cell-associated autophagy proteins LC3 and p62 were assayed by Tissue MicroArray immunohistochemistry and their expression correlated with overall survival (OS) in a cohort of 70 CCA patients. The 5-FU cytotoxicity and autophagy were determined in CCA cells cultured with CAF-conditioned medium.

We show that patients bearing a CCA with low production of stromal IL-6 and active autophagy flux in the cancer cells have the best prognosis and this correlates with a more effective response to post-operative chemotherapy. A similar trend was observed in CCA patients from the TCGA database. In vitro genetic manipulation of IL-6 production by primary CAFs isolated from human CCA showed that IL-6 impairs the autophagy-associated apoptotic response to 5-FU in human CCA cells. Stromal IL-6 inhibition of autophagy in cancer cells was confirmed in an animal model of CCA.

Our data support a therapeutic strategy that includes autophagy-enhancing drugs along with adjuvants limiting the stromal inflammation (i.e., the secretion of IL-6) to improve the survival of CCA patients.
Our data support a therapeutic strategy that includes autophagy-enhancing drugs along with adjuvants limiting the stromal inflammation (i.e., the secretion of IL-6) to improve the survival of CCA patients.Despite the recent introduction of mold-active antifungal prophylaxis (MAP), breakthrough invasive fungal infections (b-IFI) still represent a possible complication and a cause of morbidity and mortality in hematological patients and allogeneic hematopoietic stem-cell transplantation recipients (HSCT). Data on incidence and type of b-IFI are limited, although they are mainly caused by non-fumigatus Aspergillus and non-Aspergillus molds and seem to depend on specific antifungal prophylaxis and patients' characteristics. Herein, we described the clinical presentation and management of two cases of rare b-IFI which recently occurred at our institution in patients undergoing HSCT and receiving MAP. The management of b-IFI is challenging due to the lack of data from prospective trials and high mortality rates. A thorough analysis of risk factors, ongoing antifungal prophylaxis, predisposing conditions and local epidemiology should drive the choice of antifungal treatments. Early broad-spectrum preemptive therapy with a lipid formulation of amphotericin-B, in combination with a different mold-active azole plus/minus terbinafine, is advisable.
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