Breast cancer claims 11,400 lives on average every year in the UK, making it one of the deadliest diseases. Mammography is the gold standard for detecting early signs of breast cancer, which can help cure the disease during its early stages. However, incorrect mammography diagnoses are common and may harm patients through unnecessary treatments and operations (or a lack of treatment). Therefore, systems that can learn to detect breast cancer on their own could help reduce the number of incorrect interpretations and missed cases. Various deep learning techniques, which can be used to implement a system that learns how to detect instances of breast cancer in mammograms, are explored throughout this paper. Convolution Neural Networks (CNNs) are used as part of a pipeline based on deep learning techniques. A divide and conquer approach is followed to analyse the effects on performance and efficiency when utilising diverse deep learning techniques such as varying network architectures (VGG19, ResNet50, InceptionV3, DenseNet121, MobileNetV2), class weights, input sizes, image ratios, pre-processing techniques, transfer learning, dropout rates, and types of mammogram projections. This approach serves as a starting point for model development of mammography classification tasks. Practitioners can benefit from this work by using the divide and conquer results to select the most suitable deep learning techniques for their case out-of-the-box, thus reducing the need for extensive exploratory experimentation. Multiple techniques are found to provide accuracy gains relative to a general baseline (VGG19 model using uncropped 512 × 512 pixels input images with a dropout rate of 0.2 and a learning rate of 1 × 10−3) on the Curated Breast Imaging Subset of DDSM (CBIS-DDSM) dataset. These techniques involve transfer learning pre-trained ImagetNet weights to a MobileNetV2 architecture, with pre-trained weights from a binarised version of the mini Mammography Image Analysis Society (mini-MIAS) dataset applied to the fully connected layers of the model, coupled with using weights to alleviate class imbalance, and splitting CBIS-DDSM samples between images of masses and calcifications. Using these techniques, a 5.6% gain in accuracy over the baseline model was accomplished. Other deep learning techniques from the divide and conquer approach, such as larger image sizes, do not yield increased accuracies without the use of image pre-processing techniques such as Gaussian filtering, histogram equalisation and input cropping.

Traumatic brain injury (TBI) is associated with cardiovascular mortality in humans. Enhanced sympathetic activity following TBI may contribute to accelerated atherosclerosis. The effect of beta1-adrenergic receptor blockade on atherosclerosis progression induced by TBI was studied in apolipoprotein E deficient mice. Mice were treated with metoprolol or vehicle following TBI or sham operation. Mice treated with metoprolol experienced a reduced heart rate with no difference in blood pressure. Six weeks following TBI, mice were sacrificed for analysis of atherosclerosis. Total surface area and lesion thickness, analyzed at the level of the aortic valve, was found to be increased in mice receiving TBI with vehicle treatment but this effect was ameliorated in TBI mice receiving metoprolol. No effect of metoprolol on atherosclerosis was observed in mice receiving only sham operation. In conclusion, accelerated atherosclerosis following TBI is reduced with beta-adrenergic receptor antagonism. Beta blockers may be useful to reduce vascular risk associated with TBI.

Precision medicine is rapidly changing the diagnostic and treatment spectrum of oncology. In May 2019, comprehensive genomic profiling (CGP) (somatic and/or germline) was approved for reimbursement in Japan. While the promise of novel and targeted therapies has elevated hopes for the benefits of CGP, the lack of relevant genomic findings and/or limited access to relevant therapies remain important themes in this field. These challenges may also negatively influence the psychology of both cancer patients and their family members. However, few studies have reported longitudinal data on quality of life (QOL) with CGP. Here, we report the protocol of a prospective study, Q-CAT (QOL for Cancer genomics and Advanced Therapeutics among patients and their family members), which aims to explore the mental burden on patients and families arising from the implementation of CGP testing by collecting real-world longitudinal data using outcomes obtained with an electronic patient report, known as ePRO. This study has been registered with the Japan Registry of Clinical Trials (jRCT1030200039).

Uganda has had repeated outbreaks of Rift Valley fever (RVF) since March 2016 when human and livestock cases were reported in Kabale after a long interval. The disease has a complex and poorly described transmission patterns which involves several mosquito vectors and mammalian hosts (including humans). We conducted a national serosurvey in livestock to determine RVF virus (RVFV) seroprevalence, risk factors, and to develop a risk map that could be used to guide risk-based surveillance and control measures. A total of 3,253 animals from 175 herds were sampled. Serum samples collected were screened at the National Animal Disease Diagnostics and Epidemiology Centre (NADDEC) using a competition multispecies anti-RVF IgG ELISA kit. Data obtained were analyzed using a Bayesian model that utilizes integrated nested Laplace approximation (INLA) and stochastic partial differential equation (SPDE) approaches to estimate posterior distributions of model parameters, and account for spatial autocorrelation. Variables considered included animal level factors (age, sex, species) and multiple environmental data including meteorological factors, soil types, and altitude. A risk map was produced by projecting fitted (mean) values, from a final model that had environmental factors onto a spatial grid that covered the entire domain. The overall RVFV seroprevalence was 11.39% (95% confidence interval: 10.35–12.51%). Higher RVFV seroprevalences were observed in older animals compared to the young, and cattle compared to sheep and goats. RVFV seroprevalence was also higher in areas that had (i) lower precipitation seasonality, (ii) haplic planosols, and (iii) lower cattle density. The risk map generated demonstrated that RVF virus was endemic in several regions including those that have not reported clinical outbreaks in the northeastern part of the country. This work has improved our understanding on spatial distribution of RVFV risk in the country as well as RVF burden in livestock. Author summary: Outbreaks of Rift Valley fever occur periodically in Uganda in livestock and humans. An Initial outbreak was reported in Kabale in March 2016 after a long quiescent period. Factors that trigger these outbreaks have not been fully described, but above-normal precipitation and flooding are known to be important causes. This paper presents a study that was conducted in the country to analyse RVF virus seroprevalence and risk factors for exposure in livestock. The study also mapped spatial distribution of RVFV seroprevalence. Data used in the study were generated from a national cross-sectional serosurvey that involved cattle, sheep and goats. Results obtained showed that the national RVFV seroprevalence was 11.39%, with 95% confidence interval of 10.35–12.51%. Cattle had higher RVFV seroprevalence compared to sheep and goats. Environmental factors that were associated with increased seroprevalence were low precipitation seasonality, haplic planosols, and low cattle density. Prevalence maps generated showed that the southwestern, central and parts of the northeastern regions had higher seroprevalence compared to other regions of the country. These can be used to guide the surveillance of the disease in the country.

Conservation of endangered fishes commonly includes captive breeding, applied research, and management. Since 1996, a captive breeding program has existed for the federally threatened and California endangered Delta Smelt Hypomesus transpacificus, an osmerid fish endemic to the upper San Francisco Estuary. Although this program serves as a captive refuge population, with experimental releases being initiated to supplement the wild population, it was uncertain how individuals would survive, feed, and maintain condition outside hatchery conditions. We evaluated this and the effects of three enclosure designs (41% open, 63% open, and 63% open with partial outer mesh wrap) on growth, survival, and feeding efficacy of cultured Delta Smelt at two locations (Sacramento River near Rio Vista, CA and in Sacramento River Deepwater Ship Channel) in the wild. Enclosures exposed fish to semi-natural conditions (ambient environmental fluctuations and wild food resources) but prevented escape and predation. After four weeks, survival was high for all enclosure types (94–100%) at both locations. The change in condition and weight was variable between sites, increasing at the first location but decreasing at the second location. Gut content analysis showed that fish consumed wild zooplankton that came into the enclosures. Cumulatively, results show that captive-reared Delta Smelt can survive and forage successfully when housed in enclosures under semi-natural conditions in the wild. When comparing enclosure types, we observed no significant difference in fish weight changes (p = 0.58–0.81 across sites). The success of housing captive-reared Delta Smelt in enclosures in the wild provides preliminary evidence that these fish may be suitable to supplement the wild population in the San Francisco Estuary. Furthermore, these enclosures are a new tool to test the efficacy of habitat management actions or to acclimate fish to wild conditions as a soft release strategy for recently initiated supplementation efforts.

Monitoring chronic stress in pigs is not only essential in view of animal welfare but is also important for the farmer, given that stress influences the zootechnical performance of the pigs and increases their susceptibility to infectious diseases. To investigate the use of saliva as a non-invasive, objective chronic stress monitoring tool, twenty-four 4-day-old piglets were transferred to artificial brooders. At the age of 7 days, they were assigned to either the control or the stressed group and reared for three weeks. Piglets in the stressed group were exposed to overcrowding, absence of cage enrichment, and frequent mixing of animals between pens. Shotgun analysis using an isobaric labelling method (iTRAQ) for tandem mass spectrometry performed on saliva samples taken after three weeks of chronic stress identified 392 proteins, of which 20 proteins displayed significantly altered concentrations. From these 20 proteins, eight were selected for further validation using parallel reaction monitoring (PRM). For this validation, saliva samples that were taken one week after the start of the experiment and samples that were taken at the end of the experiment were analysed to verify the profile over time. We wanted to investigate whether the candidate biomarkers responded fast or rather slowly to the onset of chronic exposure to multiple stressors. Furthermore, this validation could indicate whether age influenced the baseline concentrations of these salivary proteins, both in healthy and stressed animals. This targeted PRM analysis confirmed that alpha-2-HS-glycoprotein was upregulated in the stressed group after one and three weeks, while odorant-binding protein, chitinase, long palate lung and nasal epithelium protein 5, lipocalin-1, and vomeromodulin-like protein were present in lower concentrations in the saliva of the stressed pigs, albeit only after three weeks. These results indicate that the porcine salivary proteome is altered by chronic exposure to multiple stressors. The affected proteins could be used as salivary biomarkers to identify welfare problems at the farm and facilitate research to optimise rearing conditions.

The pathogenesis of testicular germ cell tumours (GCTs) is still incompletely understood. Any progress in its understanding must derive from observational studies. Recently, it has been suggested that the incidence of GCTs may follow a seasonal pattern based on circannual changes in the Vitamin D serum levels, with maximum incidence rates in winter months. To examine this promising hypothesis, we studied monthly incidence rates of testicular GCTs in Germany by analysing 30,988 GCT cases aged 15–69 years, diagnosed during 2009–2019. Monthly incident case numbers with data regarding histology and patient age were obtained from the Robert Koch Institut, Berlin, along with annual male population counts. We used precision weighting for deriving pooled monthly incidence rates for GCTs of the period 2009–2019. We stratified pooled rates by histology (seminoma and nonseminoma) and age (15–39 and 40–69 years). By assuming a cyclical effect, we used an estimator of the intensity of seasonal occurrence and report seasonal relative risks (RR). The mean monthly incidence rate was 11.93/105 person-months. The seasonal RR for testicular cancer over-all is 1.022 (95% CI 1.000–1.054). The highest seasonal RR was found in the subgroup of nonseminoma aged 15–39 years, with a RR 1.044 (95% CI 1.000–1.112). The comparison of the pooled monthly rates of the winter months (October—March) with the summer months (April-September) revealed a maximum relative difference of 5% (95% CI 1–10%) for nonseminoma, aged 15–39 years. We conclude that there is no evidence of a seasonal variation of incidence rates of testicular cancer. Our results are at odds with an Austrian study, but the present data appear sound because the results were obtained with precision weighted monthly incidence rates in a large population of GCT cases.

The effects of filtration (F) and alpha-amylase depletion (AD) were assessed in n = 34 saliva samples. Each saliva sample was split into three aliquots and treated as follows: (1) no treatment; (2) 0.45μm commercial filter; and (3) 0.45μm commercial filter and affinity depletion of alpha-amylase. Then, a panel of biochemical biomarkers consisting of amylase, lipase, alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), creatine kinase (CK), calcium, phosphorus, total protein, albumin, urea, creatinine, cholesterol, triglycerides, and uric acid was measured. Differences between the different aliquots were observed in all measured analytes. The most marked changes were found in triglycerides and lipase data for filtered samples, and in alpha-amylase, uric acid, triglycerides, creatinine, and calcium results in alpha-amylase-depleted aliquots. In conclusion, the salivary filtration and amylase depletion methods employed in this report caused significant changes in saliva composition measurements. Based on these results, it would be recommended to consider the possible effects of these treatments in salivary biomarkers when filtration or amylase depletion is performed.

Given that Thoroughbred horses’ canter is an asymmetric gait, not only speed but also leading or trailing limbs could affect muscle activities. However, the muscle activity during a canter remains poorly understood. Hence, we aimed to investigate speed and lead-side (leading or trailing) effects on surface electromyography (sEMG) during a canter. The sEMG data were recorded from left Musculus brachiocephalicus (Br), M. infraspinatus (Inf), long head of M. triceps brachii (TB), M. gluteus medius (GM), M. semitendinosus (ST), and M. flexor digitorum longus of seven Thoroughbreds with hoof-strain gauges at the left hooves. Horses cantered on a flat treadmill at 7, 10, and 13 m/s for 25 s each without lead change. Subsequently, the horses trotted for 3 min and cantered at the same speed and duration in the opposite lead side (“leading” at the left lead and “trailing” at the right lead). The order of the lead side and speed was randomized. The mean of 10 consecutive stride durations, duty factors, integrated-EMG values (iEMG) for a stride, and muscle onset and offset timing were compared using a generalized mixed model (P < 0.05). Stride durations and duty factors significantly decreased with speed regardless of the lead side. In all muscles, iEMG at 13 m/s significantly increased compared with 7 m/s (ranging from +15% to +134%). The lead-side effect was noted in the iEMG of Br (leading > trailing, +47%), Inf (leading > trailing, +19%), GM (leading < trailing, +20%), and ST (leading < trailing, +19%). In TB, GM, and ST, muscle onset in trailing was earlier than the leading, while offset in the leading was earlier in Br. In conclusion, different muscles have different responses to speed and lead side; thus, both the lead side and running speed should be considered during training and/or rehabilitation including canter or gallop.

Food habits and oral hygiene are critical attributes for physiochemical environment of the oral cavity. Consumption of intoxicating substances such as betel nut (’Tamul’), alcohol, smoking and chewing tobacco may strongly influence the oral ecosystem including commensal microbes. Therefore, a comparative assessment of microbes in the oral cavity between individuals consuming intoxicating substances and non-consumers may indicate the influence of these substances. Oral swabs were collected from consumers of intoxicating substances and non- consumers of Assam, India, microbes were isolated by culturing on Nutrient agar and identified by phylogenetic analysis of their 16S rRNA gene sequences. The risks of consumption of intoxicating substance on occurrence of microbes and health conditions were estimated using binary logistic regression. Mostly pathogens and opportunistic pathogens were found in the oral cavity of consumers and oral cancer patients which included Pseudomonas aeruginosa, Serratia marcescens, Rhodococcus antrifimi, Paenibacillus dendritiformis, Bacillus cereus, Staphylococcus carnosus, Klebsiella michiganensis and Pseudomonas cedrina. Enterobacter hormaechei was found in the oral cavity of cancer patients but not in other cases. Pseudomonas sp. were found to be widely distributed. The risk of occurrence of these organisms were found in between 0.01 and 2.963 odds and health conditions between 0.088 and 10.148 odds on exposure to different intoxicating substances. When exposed to microbes, the risk of varying health conditions ranged between 0.108 and 2.306 odds. Chewing tobacco showed a higher risk for oral cancer (10.148 odds). Prolonged exposure to intoxicating substances conduce a favorable environment for the pathogens and opportunistic pathogens to colonize in the oral cavity of individuals consuming intoxicating substances.