Some dipeptides have been implicated in myocardial protection, but little is known about their membrane transporter PEPT2. The aim of this study was to determine whether the expression and activity of the cardiac-type PEPT2 cotransporter could be affected by ageing and/or hypertension. Sarcolemmal vesicles (SV) were isolated from the hearts of all rat groups using a standard procedure to investigate the transport activity and protein abundance by fluorescence spectroscopy and Western blot, respectively. SLC15A2 "PEPT2" gene expression was relatively quantified by RT-qPCR. In the Wistar rat groups, the protein and gene expression of PEPT2 were upregulated with ageing. These changes were accompanied by corresponding increases in the competitive inhibition and the transport rate (Vmax) of β-Ala-Lys (AMCA) into SV isolated from middle-aged hearts. Although, the transport rate of β-Ala-Lys (AMCA) into SV isolated from old hearts was significantly the lowest compared to middle-aged and young adult hearts, the inhibition percentage of β-Ala-Lys (AMCA) transport by Gly-Gln was the highest. In the WKY and SHR rat groups, Y-SHR hypertrophied hearts showed an increase in PEPT2 gene expression accompanied by a significant decrease in protein expression and activity. With advanced age, however, M-SHR hypertrophied hearts revealed significantly lower gene expression, but higher protein expression and activity than Y-SHR hearts. These findings suggest that increased expression of PEPT2 cotransporter in all types of middle-aged hearts could be exploited to facilitate di-and tripeptide transport by PEPT2 in these hearts, which subsequently could result in improved myocardial protection in these populations.Breast cancer (BC) is the leading cause of death among women worldwide. It affects in general women older than 40 years old. Medical images analysis is one of the most promising research areas since it provides facilities for diagnosis and decision-making of several diseases such as BC. This paper conducts a Structured Literature Review (SLR) of the use of Machine Learning (ML) and Image Processing (IP) techniques to deal with BC imaging. A set of 530 papers published between 2000 and August 2019 were selected and analyzed according to ten criteria year and publication channel, empirical type, research type, medical task, machine learning techniques, datasets used, validation methods, performance measures and image processing techniques which include image pre-processing, segmentation, feature extraction and feature selection. Results showed that diagnosis was the most used medical task and that Deep Learning techniques (DL) were largely used to perform classification. Furthermore, we found out that classification was the most ML objective investigated followed by prediction and clustering. Most of the selected studies used Mammograms as imaging modalities rather than Ultrasound or Magnetic Resonance Imaging with the use of public or private datasets with MIAS as the most frequently investigated public dataset. As for image processing techniques, the majority of the selected studies pre-process their input images by reducing the noise and normalizing the colors, and some of them use segmentation to extract the region of interest with the thresholding method. For feature extraction, we note that researchers extracted the relevant features using classical feature extraction techniques (e.g. Texture features, Shape features, etc.) or DL techniques (e. g. Cyclosporine A VGG16, VGG19, ResNet, etc.), and finally few papers used feature selection techniques in particular the filter methods.A total of fifty-five soil samples were collected from four locations, namely, residential, industrial, dumpsite, and sewage in Agbara industrial estate, Ogun state, Nigeria. The samples were analyzed using a high purity germanium detector (HPGe) to measure the activity concentration of radionuclides. Background radiation measurements were also taken at each point where soil samples were collected using Geiger Muller (GM) counter. The mean activity concentrations measured in the soil samples were 171.33 for 40K, 9.11 for 232Th, and 5.05 for 226Ra in Bq/kg. The mean absorbed dose rate in the air due to radionuclides (40K, 232Th, and 226Ra) in the soil is calculated to be 14.77 nGy/h, and the mean annual effective dose equivalent (AEDE) is 0.02 mSv/year. The mean equivalent dose rate (EDR) from GM counter for background radiation is 0.22 μSv/h, and the mean annual effective dose rate (AEDR) is 0.39 mSv/year. These values are below the world average values, except EDR and AEDR with mean values higher than the world standard. The comparison of radiation dose rates revealed that radionuclides contributed 6.7% to background radiation. The equivalent dose (EDorgans) for various organs of the body was calculated, and results showed that values do not pose any immediate health hazard. The excess lifetime cancer risk (ELCR) due to exposure to background radiation indicated that the dwellers and industrial workers in the study area may develop cancer over a lifetime due to accumulated dose. Diabetes and hypertension are two common comorbidities that affect breast cancer patients, particularly Black women. Disruption of chronic disease management during cancer treatment has been speculated. Therefore, this study examined the implementation of clinical practice guidelines and health outcomes for these comorbidities before and during cancer treatment. We used a population-based, prospective cohort of Black women diagnosed with breast cancer (2012-2016) in New Jersey (n = 563). Chronic disease management for diabetes and hypertension was examined 12 months before and after breast cancer diagnosis and compared using McNemar's test for matched paired and paired t tests. Among this cohort, 18.1% had a co-diagnosis of diabetes and 47.2% had a co-diagnosis of hypertension. Implementation of clinical practice guidelines and health outcomes that differed in the 12 months before and after cancer diagnosis included lipid screening (64.5% before versus 50.0% after diagnosis; p = 0.004), glucose screening (72.