IoT Ecosystems Enable Smart Communication Solutions: A Case Study

The Internet of Things (IoT) is a platform for innovation, allowing people to invest in and use IoT to improve life, business, and society. It will be applicable to all or any industry sectors, verticals, people, machines, and everything. This creates difficult requirements in terms of higher system capacity, extremely low latency, such as for the tactile Internet, extremely high throughput values, a wide range of services, such as IoT and M2M, and a more uninterrupted experience. As a symbiotic confluence of up to date and existing technologies, the IOT architecture will use Hetnet RAN, Cloud enhanced RAN, and SW defined data centres to combine novel and legacy technologies. As a result, IOT will combine next-generation largearea extensible service experiences anytime and anywhere, with ultra-dense installations, nearzero latency, and GB experiences–when and where it matters. Collaboration on research, standardisation, and spectrum sharing with the IT/Internet world, industry verticals, policymakers, and academia is a significant success element. Trillions of dollars in smart ecosystems prospects covering secure connections, digital service enablement, applications and repair provisioning, and a wide range of internet of things and consumer applications are available to communications service providers and enterprises

Barriers and Goals of Care Expressed by Patients Living with Advanced Breast Cancer during an APRN-Led Navigation Visit

Abbey Kaler pictured.https://openworks.mdanderson.org/aprn-week-23/1017/thumbnail.jp

Deep Learning-based Gated Recurrent Unit Approach to Stock Market Forecasting: An Analysis of Intel\u27s Stock Data

The stock price index prediction is a very challenging task that\u27s because the market has a very complicated nonlinear movement system. This fluctuation is influenced by many different factors. Multiple examples demonstrate the suitability of Machine Learning (ML) models like Neural Network algorithms (NN) and Long Short-Term Memory (LSTM) for such time series predictions, as well as how frequently they produce satisfactory outcomes. However, relatively few studies have employed robust feature engineering sequence models to forecast future prices. In this paper, we propose a cutting-edge stock price prediction model based on a Deep Learning (DL) technique. We chose the stock data for Intel, the firm with one of the quickest growths in the past ten years. The experimental results demonstrate that, for predicting this particular stock time series, our suggested model outperforms the current Gated Recurrent Unit (GRU) model. Our prediction approach reduces inaccuracy by taking into account the random nature of data on a big scale

Rapid Breast Cancer Disease Progression Following Cyclin Dependent Kinase 4 and 6 Inhibitor Discontinuation.

Background: CDK 4 and 6 inhibitors (CDK4/6i), which arrest unregulated cancer cell proliferation, show clinical efficacy in breast cancer. Unexpectedly, a patient treated on a CDK4/6i-based trial, as first-line therapy in metastatic breast cancer, developed rapid disease progression following discontinuation of study drug while receiving standard second-line therapy off trial. We thus sought to expand this observation within a population of patients treated similarly at The University of Texas MD Anderson Cancer Center. Methods: Using an IRB-approved protocol, 4 patients previously enrolled on CDK4/6i trials were analyzed for outcomes after discontinuing study drug. These patients were treated on a randomized trial of first-line endocrine therapy +/- a CDK4/6i. Rapid disease progression was defined as progression occurring within 4 months of CDK4/6i discontinuation. Results: In total, 4 patients developed rapid disease progression and died; 2 of whom died within 6 months of CDK4/6i discontinuation. Conclusion: This case series suggests a potential for rapid disease progression following CDK4/6i discontinuation. However, the clinical course following progression must be validated in large CDK4/6i clinical trials and standard-of-care cohorts. If confirmed, such observations may alter the algorithm for subsequent therapy in patients with disease progression on CDK4/6i. Nevertheless, the need remains to define a mechanistic basis for this rapid progression and formulate alternative therapeutic strategies

Starting a New Oral Oncology Agent in the Midst of the Pandemic

Abbey Kaler pictured. Breast Medical Oncology Kaler A, McClosky V, Raghavendra AS, Tripathy D. Oral Oncolytics: Using Remote Technology to Improve Access, Operational Efficiency, and Satisfaction. Clinical journal of oncology nursing. 2022;26(3):308-312. doi:10.1188/22.CJON.308-312https://openworks.mdanderson.org/aprn-week-22/1002/thumbnail.jp

Green synthesized silver nanoparticles destroy multidrug resistant bacteria via reactive oxygen species mediated membrane damage

AbstractThe growing need of antimicrobial agent for novel therapies against multi-drug resistant bacteria has drawn researchers to green nanotechnology. Especially, eco-friendly biosynthesis of silver nanoparticles (Ag NPs) has shown its interesting impact against bacterial infection in laboratory research. In this study, a simple method was developed to form Ag NPs at room temperature, bio-reduction of silver ions from silver nitrate salt by leaf extract from Ocimum gratissimum. The Ag NPs appear to be capped with plant proteins, but are otherwise highly crystalline and pure. The Ag NPs have a zeta potential of −15mV, a hydrodynamic diameter of 31nm with polydispersity index of 0.65, and dry sizes of 18±3nm and 16±2nm, based on scanning and transmission electron microscopy respectively. The minimum inhibitory concentration (MIC) of the Ag NPs against a multi-drug resistant Escherichia coli was 4μg/mL and the minimum bactericidal concentration (MBC) was 8μg/mL, while the MIC and MBC against a resistant strain of Staphylococcus aureus were slightly higher at 8μg/mL and 16μg/mL respectively. Further, the Ag NPs inhibited biofilm formation by both Escherichia coli and S. aureus at concentrations similar to the MIC for each strain. Treatment of E. coli and S. aureus with Ag NPs resulted in damage to the surface of the cells and the production of reactive oxygen species. Both mechanisms likely contribute to bacterial cell death. In summary, this new method appears promising for green biosynthesis of pure Ag NPs with potent antimicrobial activity

Phase III Trial Evaluating Letrozole As First-Line Endocrine Therapy With or Without Bevacizumab for the Treatment of Postmenopausal Women With Hormone Receptor-Positive Advanced-Stage Breast Cancer: CALGB 40503 (Alliance)

PURPOSE: To investigate whether anti-vascular endothelial growth factor therapy with bevacizumab prolongs progression-free survival (PFS) when added to first-line letrozole as treatment of hormone receptor-positive metastatic breast cancer (MBC). PATIENTS AND METHODS: Women with hormone receptor-positive MBC were randomly assigned 1:1 in a multicenter, open-label, phase III trial of letrozole (2.5 mg orally per day) with or without bevacizumab (15 mg/kg intravenously once every 3 weeks) within strata defined by measurable disease and disease-free interval. This trial had 90% power to detect a 50% improvement in median PFS from 6 to 9 months. Using a one-sided α = .025, a target sample size of 352 patients was planned. RESULTS: From May 2008 to November 2011, 350 women were recruited; 343 received treatment and were observed for efficacy and safety. Median age was 58 years (range, 25 to 87 years). Sixty-two percent had measurable disease, and 45% had de novo MBC. At a median follow-up of 39 months, the addition of bevacizumab resulted in a significant reduction in the hazard of progression (hazard ratio, 0.75; 95% CI, 0.59 to 0.96; P = .016) and a prolongation in median PFS from 15.6 months with letrozole to 20.2 months with letrozole plus bevacizumab. There was no significant difference in overall survival (hazard ratio, 0.87; 95% CI, 0.65 to 1.18; P = .188), with median overall survival of 43.9 months with letrozole versus 47.2 months with letrozole plus bevacizumab. The largest increases in incidence of grade 3 to 4 treatment-related toxicities with the addition of bevacizumab were hypertension (24% v 2%) and proteinuria (11% v 0%). CONCLUSION: The addition of bevacizumab to letrozole improved PFS in hormone receptor-positive MBC, but this benefit was associated with a markedly increased risk of grade 3 to 4 toxicities. Research on predictive markers will be required to clarify the role of bevacizumab in this setting

Locally advanced breast cancers are more likely to present as Interval Cancers: results from the I-SPY 1 TRIAL (CALGB 150007/150012, ACRIN 6657, InterSPORE Trial)

Interval cancers (ICs), defined as cancers detected between regular screening mammograms, have been shown to be of higher grade, larger size, and associated with lower survival, compared with screen-detected cancers (SDCs) and comprise 17% of cancers from population-based screening programs. We sought to determine the frequency of ICs in a study of locally advanced breast cancers, the I-SPY 1 TRIAL. Screening was defined as having a mammogram with 2 years, and the proportion of ICs at 1 and 2 years was calculated for screened patients. Differences in clinical characteristics for ICs versus SDCs and screened versus non-screened cancers were assessed. For the 219 evaluable women, mean tumor size was 6.8 cm. Overall, 80% of women were over 40 and eligible for screening; however, only 31% were getting screened. Among women screened, 85% were ICs, with 68% diagnosed within 1 year of a previously normal mammogram. ICs were of higher grade (49% vs. 10%) than SDCs. Among non-screened women, 28% (43/152) were younger than the recommended screening age of 40. Of the entire cohort, 12% of cancers were mammographically occult (MO); the frequency of MO cancers did not differ between screened (11%) and non-screened (15%). ICs were common in the I-SPY 1 TRIAL suggesting the potential need for new approaches beyond traditional screening to reduce mortality in women who present with larger palpable cancers

Pathologic Complete Response Predicts Recurrence-Free Survival More Effectively by Cancer Subset: Results From the I-SPY 1 TRIAL—CALGB 150007/150012, ACRIN 6657

Neoadjuvant chemotherapy for breast cancer provides critical information about tumor response; how best to leverage this for predicting recurrence-free survival (RFS) is not established. The I-SPY 1 TRIAL (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis) was a multicenter breast cancer study integrating clinical, imaging, and genomic data to evaluate pathologic response, RFS, and their relationship and predictability based on tumor biomarkers