Early Intensive Nutrition Intervention with Dietary Counseling and Oral Nutrition Supplement Prevents Weight Loss in Patients with Advanced Lung Cancer Receiving Chemotherapy: A Clinical Prospective Study

【Background】 Weight loss in patients with cancer is caused by cancer cachexia and chemotherapy-induced nausea and vomiting (CINV). Recent developments in antiemetic drugs have substantially improved CINV, but nutritional intervention did not improve body weight. This study aimed to investigate the effects of nutrition intervention with appropriate antiemetic treatment in patients with non-small-cell lung cancer during chemotherapy. 【Methods】 Patients received individualized nutrition counseling by a registered dietitian and were provided with oral supplements for 90 days. Body weight and other parameters were measured at baseline and after 90-day intervention. To evaluate this nutrition intervention, patients were also retrospectively set as control, and then body weight change was compared with inverse probability of treatment weights (IPTW) analysis. 【Results】 Ten patients received individualized nutrition counseling and were provided with oral supplements for 90 days. Of them, 7 patients consumed nutritional supplements, and the mean intake was 130 kcal/day. After 90-day intervention, the patients did not show significant weight and BMI loss during the course of cytotoxic chemotherapy. A total of 38 patients were retrospectively enrolled as controls. The number of the patients who gain the body weight after 90 days in the study cohort was significantly larger than that in the retrospective controls with the IPTW analysis (Odds Ratio (OR) = 8.4; 95% Confidence Interval (CI): 1.6-42; P = 0.01). 【Conclusion】 Early intensive nutrition intervention with appropriate antiemetic treatment prevents weight loss. Nutrition interventions might be also beneficial for quality of life, treatment response and survival

Novel functional anti-HER3 monoclonal antibodies with potent anti-cancer effects on various human epithelial cancers

Resistance of progressive cancers against chemotherapy is a serious clinical problem. In this context, human epidermal growth factor receptor 3 (HER3) can play important roles in drug resistance to HER1- and HER2- targeted therapies. Since clinical testing of anti-HER3 monoclonal antibodies (mAbs) such as patritumab could not show remarkable effect compared with existing drugs, we generated novel mAbs against anti-HER3. Novel rat mAbs reacted with HEK293 cells expressing HER3, but not with cells expressing HER1, HER2 or HER4. Specificity of mAbs was substantiated by the loss of mAb binding with knockdown by siRNA and knockout of CRISPR/Cas9-based genome-editing. Analyses of CDR sequence and germline segment have revealed that seven mAbs are classified to four groups, and the binding of patritumab was inhibited by one of seven mAbs. Seven mAbs have shown reactivity with various human epithelial cancer cells, strong internalization activity of cell-surface HER3, and inhibition of NRG1 binding, NRG1-dependent HER3 phosphorylation and cell growth. Anti-HER3 mAbs were also reactive with in vivo tumor tissues and cancer tissue-originated spheroid. Ab4 inhibited in vivo tumor growth of human colon cancer cells in nude mice. Present mAbs may be superior to existing anti-HER3 mAbs and support existing anti-cancer therapeutic mAbs

Estimating actual inspiratory muscle pressure from airway occlusion pressure at 100 msec

Background: Quantification of the patient’s respiratory effort during mechanical ventilation is very important and calculating the actual muscle pressure (Pmus) during mechanical ventilation is a cumbersome task and usually requires an esophageal balloon manometry. Airway occlusion pressure at 100 milliseconds (P0.1) can easily be obtained non-invasively. There has been no study investigating the association between Pmus and P0.1. Therefore, we aimed to investigate whether P0.1 correlate to Pmus and can be used to estimate actual Pmus Materials and Methods: A bench study using lung simulator (ASL 5000) to simulate an active breathing patient with Pmus from 1 to 30 cmH2O by increments of 1 was conducted. Twenty active breaths were measured in each Pmus. The clinical scenario was constructed as a normal lung with a fixed setting of compliances of 60 mL/cmH2O and resistances of 10 cmH2O/l/sec. All experiments were conducted using the pressure support ventilation mode (PSV) on a Hamilton-G5 ventilator (Hamilton Medical AG, Switzerland), Puritan Bennett 840TM (Covidien-Nellcor, CA) and Avea (CareFusion, CA). Main results: There was significant correlation between P 0.1 and Pmus (correlation coefficient = - 0.992, 95% CI: -0.995 to -0.988, P-value<0.001). The equation was calculated as follows: Pmus = -2.99 x (P0.1) + 0.53 Conclusion: Estimation of Pmus using P 0.1 as a substitute is feasible, available, and reliable. Estimation of Pmus has multiple implications, especially in weaning of mechanical ventilation, adjusting ventilator support, and calculating respiratory mechanics during invasive mechanical ventilation. Keywords: P 0.1, Inspiratory occlusion pressure, WOB, Esophageal balloon, mechanical ventilators, respiratory failur

Effects of a 3-D, aquatic vegetation patch on the flow: A numerical approach

This numerical study investigated the effects of a vegetation patch on the flow of a channel. The numerical approach consisted of a CFD, 3-D model that applied the RANS equations to simulate the flow field, and the VOF model to represent the free surface. The patch altered the initial flow by inducing regions of reduced velocity in the patch wake (approximately 40% reduction), and regions of enhanced velocity around of the patch (approximately 16% increase), and these regions extended throughout the water depth. Also, the patch induced a small change of 3.83% in the water surface, in the streamwise direction

Effects of a 3-D, aquatic vegetation patch on the flow: A numerical approach

This numerical study investigated the effects of a vegetation patch on the flow of a channel. The numerical approach consisted of a CFD, 3-D model that applied the RANS equations to simulate the flow field, and the VOF model to represent the free surface. The patch altered the initial flow by inducing regions of reduced velocity in the patch wake (approximately 40% reduction), and regions of enhanced velocity around of the patch (approximately 16% increase), and these regions extended throughout the water depth. Also, the patch induced a small change of 3.83% in the water surface, in the streamwise direction