Adapting and implementing training, guidelines and treatment cards to improve primary care-based hypertension and diabetes management in a fragile context: results of a feasibility study in Sierra Leone

Background Sierra Leone, a fragile country, is facing an increasingly significant burden of non-communicable diseases (NCDs). Facilitated by an international partnership, a project was developed to adapt and pilot desktop guidelines and other clinical support tools to strengthen primary care-based hypertension and diabetes diagnosis and management in Bombali district, Sierra Leone between 2018 and 2019. This study assesses the feasibility of the project through analysis of the processes of intervention adaptation and development, delivery of training and implementation of a care improvement package and preliminary outcomes of the intervention. Methods A mixed-method approach was used for the assessment, including 51 semi-structured interviews, review of routine treatment cards (retrieved for newly registered hypertensive and diabetic patients from June 2018 to March 2019 followed up for three months) and mentoring data, and observation of training. Thematic analysis was used for qualitative data and descriptive trend analysis and t-test was used for quantitative data, wherever appropriate. Results A Technical Working Group, established at district and national level, helped to adapt and develop the context-specific desktop guidelines for clinical management and lifestyle interventions and associated training curriculum and modules for community health officers (CHOs). Following a four-day training of CHOs, focusing on communication skills, diagnosis and management of hypertension and diabetes, and thanks to a CHO-based mentorship strategy, there was observed improvement of NCD knowledge and care processes regarding diagnosis, treatment, lifestyle education and follow up. The intervention significantly improved the average diastolic blood pressure of hypertensive patients (n = 50) three months into treatment (98 mmHg at baseline vs. 86 mmHg in Month 3, P = 0.001). However, health systems barriers typical of fragile settings, such as cost of transport and medication for patients and lack of supply of medications and treatment equipment in facilities, hindered the optimal delivery of care for hypertensive and diabetic patients. Conclusion Our study suggests the potential feasibility of this approach to strengthening primary care delivery of NCDs in fragile contexts. However, the approach needs to be built into routine supervision and pre-service training to be sustained. Key barriers in the health system and at community level also need to be addressed

The Astropy Project: Building an inclusive, open-science project and status of the v2.0 core package

The Astropy project supports and fosters the development of open-source and openly-developed Python packages that provide commonly-needed functionality to the astronomical community. A key element of the Astropy project is the core package Astropy, which serves as the foundation for more specialized projects and packages. In this article, we provide an overview of the organization of the Astropy project and summarize key features in the core package as of the recent major release, version 2.0. We then describe the project infrastructure designed to facilitate and support development for a broader ecosystem of inter-operable packages. We conclude with a future outlook of planned new features and directions for the broader Astropy project

Extraction of speaker-specific excitation information from linear prediction residual of speech

In this paper, through different experimental studies we demonstrate that the excitation component of speech can be exploited for speaker recognition studies. Linear prediction (LP) residual is used as a representation of excitation information in speech. The speaker-specific information in the excitation of voiced speech is captured using the AutoAssociative Neural Network (AANN) models. The decrease in the error during training and recognizing correct speakers during testing demonstrates that the excitation component of speech contains speaker-specific information and is indeed being captured by the AANN models. The study on the effect of different LP orders demonstrates that for a speech signal sampled at 8 kHz, the LP residual extracted using LP order in the range 8-20 best represents the speaker-specific excitation information. It is also demonstrated that the proposed speaker recognition system using excitation information and AANN models requires significantly less amount of data both during training as well as testing, compared to the speaker recognition system using vocal tract information. Finally the speaker recognition studies on NIST 2002 database demonstrates that even though, the recognition performance from the excitation information alone is poor, when combined with evidence from vocal tract information, there is significant improvement in the performance. This result demonstrates the complementary nature of the excitation component of speech

Rlip Depletion Suppresses Growth of Breast Cancer

RLIP76 (RAL-binding protein-1, Rlip) is a stress-protective mercapturic-acid-pathway transporter protein that also plays a key role in regulating clathrin-dependent endocytosis as a Ral effector. Targeted inhibition or depletion of Rlip causes regression of xenografts of many cancers and is capable of abrogating tumor formation in p53-null mice. This is associated with the reversion of the abnormal methylomic profile of p53-null mice to wild-type. In a query of The Cancer Genome Atlas (TCGA) databases, we found that Rlip expression was associated with poor survival and with significant differences in the frequencies of PIK3CA mutation, MYC amplification, and CDKN2A/B deletion, which were the most commonly mutated, amplified, and deleted genes, respectively, among TCGA breast cancer patients. We conducted the present study to further examine the effects of Rlip inhibition and to evaluate the in vitro and in vivo efficacy in breast cancer. Using immunogold electron microscopy, we found that plasma-membrane Rlip was accessible to cell-surface antibodies in the MCF7 (ER+) breast cancer cell line. Rlip depletion resulted in decreased survival of MCF7 and MDA-MB-231 cells and increased terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) positivity and DNA laddering, indicating apoptotic cell death. Additionally, in vitro knockdown of Rlip inhibited EGF endocytosis and WNT/MAPK signaling. Xenograft studies in nude mice showed regression of breast cancer via antisense-mediated depletion of Rlip mRNA as well as by anti-Rlip antibody. Finally, knockdown of Rlip by antisense locked nucleic acid oligonucleotides increased markers for apoptotic signaling and decreased markers for proliferation, angiogenesis, and cell cycling in MCF7 and MDA-MB-231luc xenografts. Our findings validate Rlip as an attractive target in breast cancer

The Astropy Project: Building an Open-science Project and Status of the v2.0 Core Package

The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package astropy, which serves as the foundation for more specialized projects and packages. In this article, we provide an overview of the organization of the Astropy project and summarize key features in the core package, as of the recent major release, version 2.0. We then describe the project infrastructure designed to facilitate and support development for a broader ecosystem of interoperable packages. We conclude with a future outlook of planned new features and directions for the broader Astropy Project.