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This study examined upper limb kinematics under simulated visually impaired conditions. By investigating how upper limb movements adapt in these circumstances, we aimed to gain insights that may prove valuable for both healthy populations and those with clinical conditions. Data, including 3D marker-based motion capture and accelerometer readings, were collected from seven healthy volunteers walking on a treadmill at 1.5 m/s under two conditions: without glasses (NG) and with stroboscopic glasses (G). Each walking condition lasted 2 minutes, and two 10-second recordings were analyzed from the midpoint of each session. Contrary to our hypothesis, simulated visual impairment with stroboscopic eyewear at 6Hz did not statistically affect upper limb kinematics, specifically in terms of wrist acceleration and hand distance in the frontal plane. Future research should explore varied visual impairment conditions, extend task durations, and investigate the relationship between subjective gait difficulties and biomechanical data.

<abstract> <p>We developed an artificial neural network (ANN) to predict mole fractions in the extractive distillation of an n-hexane and ethyl acetate mixture, which are common organic solvents in chemical and pharmaceutical manufacturing. The ANN was trained on 250 data pairs from simulations in DWSIM software. The training dataset consisted of four inputs: Feed flow inlet (T1-F), Feed Stream Mass Flow temperature pressure (FM1-F), Make-up stream mass flow (FM2-MU), and ERC tower reflux ratio (RR-ERC). The ANN demonstrated the ability to forecast four output variables (neurons): Mole fraction of n-hexane in the distillate of EDC (XHE-EDC), Mole fraction of N-methyl-2 pyrrolidone in the bottom of EDC (XNMP-EDC), Mole fraction of ethyl acetate in the distillate of ERC (XEA-ERC), and Mole fraction of N-methyl-2 pyrrolidone in the bottom of ERC (XNMP-ERC).The ANN architecture contained 80 hidden neurons. Bayesian regularization training yielded high prediction accuracy (MSE = 2.56 × 10<sup>–7</sup>, R = 0.9999). ANOVA statistical validation indicated that ANN could reliably forecast mole fractions. By integrating this ANN into process control systems, manufacturers could enhance product quality, decrease operating expenses, and mitigate composition variability risks. This data-driven modeling approach may also optimize energy consumption when combined with genetic algorithms. Further research will validate predictions onsite and explore hybrid energy optimization technologies.</p> </abstract>

Abstract Employees are commonly defaulted into either a homogeneous passive investment such as a target‐date fund, or into a managed account that offers personalization and access to an advisor. Higher performance among investors in target‐date funds suggests a possible behavioral benefit of a passive default that requires no active monitoring by investors. Access to a human advisor and an asset allocation matched to employee risk preferences can also help investors avoid trading after a market decline. This paper explores the relationship between trading activity and advice‐seeking behavior among 5 million US DC participants during the COVID‐19 pandemic, comparing self‐directors and target‐date fund investors to those using managed accounts service. We find participants who use target‐date funds are less likely to phone during a market crash. Participants in managed accounts are the least likely to trade after seeking advice. These findings are consistent with the hypothesis that passive default can improve outcomes where active choice can harm outcomes, and personalized defaults with access to advice can help participants avoid investment mistakes.

Abstract Background: KRAS mutations occur in ~30% of NSCLC and KRAS G12C is the most common subtype (~40%). Co-mutations can impact NSCLC prognosis and tx response. Methods: This retrospective study used the nationwide (US-based) de-identified Flatiron Health-Foundation Medicine clinico-genomic database (FH-FMI CGDB; January 1, 2011 to March 31, 2022). De-identified data originated from ~280 US cancer clinics (~800 sites of care). This study is based on tissue-based assay (FoundationOne CDx). Pts were aged ≥18 years; had KRAS G12C-mutated, advanced/metastatic NSCLC, and had received ≥1 line of tx, with 1L tx initiated after October 1, 2016. Pts were categorized by presence (m) or absence (wt) of single co-mutations in STK11, KEAP1, or TP53; pts with EGFR, ALK, ROS1, BRAF, MET, or NTRK alterations were excluded. Key endpoints included overall survival (OS) and real-world progression-free survival (rwPFS). Statistical methods included a univariate Cox hazard model. Results: Among 847 pts with KRAS G12C-mutated NSCLC, co-mutations of STK11 were seen in 24%, KEAP1 in 14%, and TP53 in 51%. Based on non-missing records (82%), low tumor mutational burden (<10 mut/Mb) was more frequent in the STK11m vs wt group (72% vs 55%; p<0.001), not significantly different in the KEAP1m vs wt group (53% vs 60%; p=0.145), and less frequent in pts with TP53m vs wt (50% vs 69%; p<0.001). Negative PD-L1 status (<1%) was more frequent in pts with STK11 (50% vs 18%; p<0.001) or KEAP1 (41% vs 23%; p<0.001) mutations, and less frequent in pts with TP53 mutations (15% vs 37%; p<0.001). STK11 or KEAP1 co-mutations were associated with shorter rwPFS and OS, particularly in pts treated with immunotherapy (IO)-based 1L tx (Table 1). TP53 status did not significantly impact pt outcomes in the 1L setting. Conclusions: In this real-world analysis, STK11 or KEAP1 co-mutations were associated with PD-L1-negative tumors and poor outcomes with IO-based tx in KRAS G12C-mutated NSCLC. Table 1. rwPFS and OS by co-mutation status, and OS by 1L treatment and co-mutation status rwPFS and OS by co-mutation status rwPFS All (N=846) STK11m (n=206) STK11wt (n=640) KEAP1m (n=121) KEAP1wt (n=725) TP53m (n=429) TP53wt (n=417) Median, months (95% CI) 5.0 (4.5-5.7) 4.0 (3.1-4.9) 5.6 (4.9-6.2) 3.8 (2.7-4.8) 5.6 (4.7-6.2) 5.3 (4.6-6.1) 4.7 (4.0-5.7) HR (95% CI); p value - 1.38 (1.16-1.64); <0.001 1.46 (1.18-1.80); <0.001 0.87 (0.75-1.01); 0.07 OS All (N=847) STK11m (n=206) STK11wt (n=641) KEAP1m (n=121) KEAP1wt (n=726) TP53m (n=429) TP53wt (n=418) Median, months (95% CI) 11.9 (10.2-14.3) 9.4 (7.2-13.8) 12.4 (10.8-15.0) 7.6 (5.4-9.4) 13.5 (11.0-15.1) 11.0 (9.2-14.4) 12.7 (10.4-15.3) HR (95% CI); p value - 1.40 (1.15-1.70); <0.001 1.59 (1.26-2.00); <0.001 0.98 (0.83-1.17); 0.85 OS by 1L treatment and co-mutation status IO + chemotherapy STK11m (n=106) STK11wt (n=228) KEAP1m (n=53) KEAP1wt (n=281) TP53m (n=162) TP53wt (n=172) Median, months (95% CI) 6.9 (4.5-9.4) 11.3 (9.0-14.8) 7.9 (4.5-10.3) 10.2 (7.7-12.9) 9.3 (6.6-11.9) 10.9 (7.2-14.0) HR (95% CI); p value 1.75 (1.33-2.31); <0.0001 1.60 (1.13-2.26); 0.01 1.04 (0.80-1.36); 0.75 IO monotherapy STK11m (n=33) STK11wt (n=181) KEAP1m (n=29) KEAP1wt (n=185) TP53m (n=111) TP53wt (n=103) Median, months (95% CI) 9.7 (2.8-16.9) 16.1 (10.7-23.3) 5.7 (3.9-14.3) 16.6 (10.8-23.0) 15.1 (9.1-22.4) 14.6 (8.9-23.0) HR (95% CI); p value 1.54 (0.97-2.46); 0.07 1.81 (1.12-2.90); 0.01 0.96 (0.68-1.37); 0.83 Chemotherapy only STK11m (n=56) STK11wt (n=188) KEAP1m (n=28) KEAP1wt (n=216) TP53m (n=130) TP53wt (n=114) Median, months (95% CI) 18.6 (10.2-22.8) 13.5 (9.5-15.3) 7.8 (5.0-17.4) 14.5 (11.1-16.3) 12.0 (8.9-16.0) 15.0 (11.1-19.5) HR (95% CI); p value 0.84 (0.57-1.25); 0.40 1.31 (0.82-2.10); 0.26 1.12 (0.81-1.54); 0.49 CI, confidence interval; HR, hazard ratio. Citation Format: Marcelo V. Negrao, Wen-Hsing Wu, Colin R. Lindsay, Rafael Caparica, Vincent Prêtre, Yehrim Kang, Nydia Caro, Anna Farago, Fen Ye, Gilberto de Castro Jr. Real-world clinical characteristics and treatment (tx) outcomes by co-mutation status in patients (pts) with KRAS G12C-mutated non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 918.

Improved understanding of factors that influence metastatic development in localized ccRCC is greatly needed to aid accurate prediction of disease recurrence, clinical decision-making, and future adjuvant clinical trial design. Our analysis implicates intratumoral myeloid inflammation as a key driver of metastasis in patients and a novel immunocompetent mouse model. This article is highlighted in the In This Issue feature, p. 2221.

Osteoporosis is characterized by bone loss. The present study aims to investigate the effects of bovine colostrum (BC) on bone metabolism using ovariectomized (OVX) and orchidectomized (ORX) rat models. Twenty-seven-week-old Wistar Han rats were randomly assigned as: (1) placebo control, (2) BC supplementation dose 1 (BC1: 0.5 g/day/OVX, 1 g/day/ORX), (3) BC supplementation dose 2 (BC2: 1 g/day/OVX, 1.5 g/day/ORX) and (4) BC supplementation dose 3 (BC3: 1.5 g/day/OVX, 2 g/day/ORX). Bone microarchitecture, strength, gene expression of VEGFA, FGF2, RANKL, RANK and OPG, and bone resorption/formation markers were assessed after four months of BC supplementation. Compared to the placebo, OVX rats in the BC1 group exhibited significantly higher cortical bone mineral content and trabecular bone mineral content (p < 0.01), while OVX rats in the BC3 group showed significantly higher trabecular bone mineral content (p < 0.05). ORX rats receiving BC dose 2 demonstrated significantly higher levels of trabecular bone mineral content (p < 0.05). Serum osteocalcin in the ORX was pointedly higher in all BC supplementation groups than the placebo (BC1: p < 0.05; BC2, BC3: p < 0.001). Higher doses of BC induced significantly higher relative mRNA expression of OPG, VEGFA, FGF2 and RANKL (p < 0.05). BC supplementation improves bone metabolism of OVX and ORX rats, which might be associated with the activation of the VEGFA, FGF2 and RANKL/RANK/OPG pathways.

Parkinson's disease is a progressive neurodegenerative disorder correlating with dysfunction or deprivation of brains dopaminergic neurons, lack of dopamine, and the formation of abnormal protein particles. There are several clinical tests for detection of Parkinson's disease, but nowadays a demand is rising for an objective assessment of symptoms and health-related outcomes. The rapid development of sensor-based technological devices permits conducting measurements without bias that they are able to be used in scientific research and clinical practice. This paper provides a technical overview of the available commercial wearable systems for monitoring and supporting Parkinson's disease management, taking into account their validity and reliability. The understanding of the current state-of-the-art could help patients and clinicians significantly improve Parkinson's disease management by minimizing health care costs and increasing patient's quality of life. © 2021 Bharati Vidyapeeth, New Delhi. Copy Right in Bulk will be transferred to IEEE by Bharati Vidyapeeth.