Accurate and timely detection of weeds between and within crop rows in the early growth stage is considered one of the main challenges in site-specific weed management (SSWM). In this context, a ...robust and innovative automatic object-based image analysis (OBIA) algorithm was developed on Unmanned Aerial Vehicle (UAV) images to design early post-emergence prescription maps. This novel algorithm makes the major contribution. The OBIA algorithm combined Digital Surface Models (DSMs), orthomosaics and machine learning techniques (Random Forest, RF). OBIA-based plant heights were accurately estimated and used as a feature in the automatic sample selection by the RF classifier; this was the second research contribution. RF randomly selected a class balanced training set, obtained the optimum features values and classified the image, requiring no manual training, making this procedure time-efficient and more accurate, since it removes errors due to a subjective manual task. The ability to discriminate weeds was significantly affected by the imagery spatial resolution and weed density, making the use of higher spatial resolution images more suitable. Finally, prescription maps for in-season post-emergence SSWM were created based on the weed maps—the third research contribution—which could help farmers in decision-making to optimize crop management by rationalization of the herbicide application. The short time involved in the process (image capture and analysis) would allow timely weed control during critical periods, crucial for preventing yield loss.
Scope
Dysbiosis of gut microbiota is involved in metabolic syndrome (MetS) development, which has a different incidence between men (M) and women (W). The differences in gut microbiota in MetS ...patients are explored according to gender, and whether consuming two healthy diets, Mediterranean (MED) and low‐fat (LF), may, over time, differentially shape the gut microbiota dysbiosis according to gender is evaluated.
Materials and Methods
All the women from the CORDIOPREV study whose feces samples were available and a similar number of men, matched by the main metabolic variables (N = 246, 123 women and 123 men), and categorized according to the presence or not of MetS are included. Gut microbiota is analyzed at baseline and after 3 years of dietary intervention.
Results
Higher abundance of Collinsella, Alistipes, Anaerotruncus, and Phascolarctobacterium genera is observed in MetS‐W than in MetS‐M, whereas the abundance of Faecalibacterium and Prevotella genera is higher in MetS‐M than in MetS‐W. Moreover, higher levels of Desulfovibrio, Roseburia, and Holdemania are observed in men than in women after the consumption of the LF diet.
Conclusion
The results suggest the potential involvement of differences in gut microbiota in the unequal incidence of metabolic diseases between genders, and a sex‐dependent effect on shaping the gut microbiota according to diet.
Dysbiosis of gut microbiota is involved in the development of metabolic syndrome, whose incidence is different between men and women. This work provides evidence of a different gut microbiota composition in metabolic syndrome, according to gender. Moreover, the study shows a differential shaping of the gut microbiota according to the gender in metabolic syndrome patients after the consumption of a Mediterranean or a low‐fat diet for three years.
Despite the existence of good catalogues of cancer genes.sup.1,2, identifying the specific mutations of those genes that drive tumorigenesis across tumour types is still a largely unsolved problem. ...As a result, most mutations identified in cancer genes across tumours are of unknown significance to tumorigenesis.sup.3. We propose that the mutations observed in thousands of tumours--natural experiments testing their oncogenic potential replicated across individuals and tissues--can be exploited to solve this problem. From these mutations, features that describe the mechanism of tumorigenesis of each cancer gene and tissue may be computed and used to build machine learning models that encapsulate these mechanisms. Here we demonstrate the feasibility of this solution by building and validating 185 gene-tissue-specific machine learning models that outperform experimental saturation mutagenesis in the identification of driver and passenger mutations. The models and their assessment of each mutation are designed to be interpretable, thus avoiding a black-box prediction device. Using these models, we outline the blueprints of potential driver mutations in cancer genes, and demonstrate the role of mutation probability in shaping the landscape of observed driver mutations. These blueprints will support the interpretation of newly sequenced tumours in patients and the study of the mechanisms of tumorigenesis of cancer genes across tissues.
Objectives
We sought to validate a deep learning algorithm designed to predict an ejection fraction (EF) less than or equal to 35% based on the 12‐lead electrocardiogram (ECG) in a large prospective ...cohort.
Background
Patients undergoing routine ECG may have undetected left ventricular (LV) dysfunction that warrants further echocardiographic assessment. However, identification of these patients can be challenging.
Methods
We applied the algorithm to all ECGs interpreted by the Mayo Clinic ECG laboratory in September 2018. The performance of the algorithm was tested among patients with recent echocardiographic assessments of LV function. We also applied the algorithm in patients with no recent echocardiographic assessments of LV function to determine the rate of new “positive screens.”
Results
Among 16 056 adult patients who underwent routine ECG, 8600 (age 67.1 ± 15.2 years, 45.6% male), had a transthoracic echocardiogram (TTE) and 3874 patients had a TTE and ECG less than 1 month apart. Among these patients, the algorithm was able to detect an EF less than or equal to 35% with 86.8% specificity, 82.5% sensitivity, and 86.5% accuracy, (area under the curve, 0.918). Among 474 “false‐positives screens,” 189 (39.8%) had an EF of 36% to 50%. Among patients with no prior TTE, the algorithm identified 3.5% of the patients with suspected EF less than or equal to 35%. Exploratory analysis suggests false positives could be reduced by assessing NT‐pro‐BNP after the initial “positive screen.”
Conclusions
A deep learning algorithm detected depressed LV function with good accuracy in routine practice. Further studies are needed to validate the algorithm in patients with no prior echocardiogram and to assess the impact on echocardiography utilization, cost, and clinical outcomes.
A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One ...milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer.
Background Digital health interventions (DHI) have been shown to improve intermediates of cardiovascular health, but their impact on cardiovascular (CV) outcomes has not been fully explored. The aim ...of this study was to determine whether DHI administered during cardiac rehabilitation (CR) would reduce CV-related emergency department (ED) visits and rehospitalizations in patients after percutaneous coronary intervention (PCI) for acute coronary syndrome (ACS). Methods We randomized patients undergoing CR following ACS and PCI to standard CR (n = 40) or CR + DHI (n = 40) for 3 months with 3 patients withdrawing from CR prior to initiation in the treatment arm and 6 in the control group. The DHI incorporated an online and smartphone-based CR platform asking the patients to report of dietary and exercise habits throughout CR as well as educational information toward patients' healthy lifestyles. We obtained data regarding ED visits and rehospitalizations at 180 days, as well as other metrics of secondary CV prevention at baseline and 90 days. Results Baseline demographics were similar between the groups. The DHI + CR group had improved weight loss compared to the control group (−5.1 ± 6.5 kg vs. −0.8 ± 3.8 kg, respectively, P = .02). Those in the DHI + CR group also showed a non-significant reduction in CV-related rehospitalizations plus ED visits compared to the control group at 180 days (8.1% vs 26.6%; RR 0.30, 95% CI 0.08-1.10, P = .054). Conclusions The current study demonstrated that complementary DHI significantly improves weight loss, and might offer a method to reduce CV-related ED visits plus rehospitalizations in patients after ACS undergoing CR. The study suggests a role for DHI as an adjunct to CR to improve secondary prevention of CV disease. Trial registration This trial is registered at clinicaltrials.gov ( NCT01883050 ).
Summary Background The Foundation for the National Institutes of Health Sarcopenia Project validated cutpoints for appendicular lean mass (ALM) to identify individuals at risk for functional ...impairment. Recognizing possible underlying mechanisms between adipose tissue and muscle, we sought to apply the recent definitions and determine the relationship with markers of glucose homeostasis and inflammation in individuals with sarcopenia and sarcopenic obesity. Methods The National Health and Nutrition Examination Surveys 1999-2004 were used to identify 4,984 adults aged ≥60 years with DEXA measures. Sarcopenia was defined using ALM (men<19.75 kg, women<15.02 kg) and ALM adjusted for body mass index (BMI; men<0.789 kg/m2 , women<0.512 kg/m2 ). Sarcopenic obesity was defined as subjects fulfilling the criteria for sarcopenia and obesity by body fat (men ≥25%, women ≥35%). We assessed the association between ALM and ALM:BMI with inflammatory and markers of glucose homestasis, both as continuous variables but also classifying as having sarcopenic obesity or not after adjusting for confounding variables including pro-inflammatory chronic diseases such as diabetes and cancer. Results Mean age was 71.1 years (56.5%) females. Prevalence of sarcopenia and sarcopenic obesity were (ALM definition: 29.9 and 24.4%; ALM:BMI definition: 23.0 and 22.7%). There were significant associations with ALM and ln C-reactive protein (β=0.0287;p=0.001), fibrinogen (β=0.519;p<0.001), and HOMA-IR (β=0.359;p<0.001). Using ALM:BMI, significant associations were observed with ln CRP (β=-2.58;p=0.001), fibrinogen (β=-124.2;p<0.001), and HOMA-IR (β=-6.63;p<0.001). Sarcopenic obesity using the ALM:BMI definition demonstrated significant associations with CRP (β=0.422;p<0.001), fibrinogen (β=22.5;p<0.001), but not HOMA-IR (β=1.19;p=0.13). Strong associations with seen with increased levels of fibrinogen and CRP with sarcopenic obesity (ALM:BMI definition) that persisted after adjusting for diabetes and cancer. Conclusions Biologically plausible associations exist between ALM:BMI and inflammation and HOMA-IR that were not observed when using ALM alone. Future study should validate each of these definitions to prevent disparate results from being determined.
Obesity remains a major public health problem, affecting almost half of adults in the United States. Increased risk of cardiovascular disease (CVD) and CVD mortality are major obesity-related ...complications, and management guidelines now recommend weight loss as a key strategy for the primary prevention of CVD in patients with overweight or obesity. The recently demonstrated efficacy of some pharmacologic therapies for chronic weight management may encourage health care professionals to recognize obesity as a treatable serious chronic disease and motivate patients to re-engage with weight loss when previous attempts have been ineffective or unsustainable. This review article summarizes the benefits and challenges associated with lifestyle changes, bariatric surgery, and historical pharmacologic interventions in the treatment of obesity, and focuses on the current evidence for the efficacy and safety of the newer glucagon-like peptide-1 receptor agonist medications in the management of obesity and potential reduction of CVD risk. We conclude that the available evidence demonstrates glucagon-like peptide-1 receptor agonists should be strongly considered in clinical practice for the treatment of obesity and reduction of CVD risk in people with type 2 diabetes. If ongoing research proves glucagon-like peptide-1 receptor agonists to be effective in reducing the risk of CVD onset in patients with obesity, irrespective of type 2 diabetes status, it will herald a new treatment paradigm in this setting, and now is the time for health care professionals to better recognize the benefits of these agents.
Objectives
To determine the prevalence range for sarcopenic obesity and its relationship with sex, age, and ethnicity.
Design
Cross‐sectional analysis of a population‐based sample.
Setting
...Noninstitutionalized persons in the United States participating in the National Health and Nutrition Examination Surveys 1999–2004.
Participants
Subsample of 4,984 subjects aged 60 and older with dual‐energy X‐ray absorptiometry body composition data.
Measurements
Eight definitions of sarcopenic obesity identified from six studies found using a systematic literature review (Baumgartner, Bouchard, Davison, Zoico, Levine, Kim‐1,2,3) were applied to the sample. Results were stratified according to sex, age, and ethnicity.
Results
Prevalence of sarcopenic obesity ranged from 4.4% to 84.0% in men and from 3.6% to 94.0% in women. Prevalence was higher in men using definitions from Baumgartner (17.9% vs 13.3%, P < .001), Levine (14.2% vs 6.6%, P < .001), and Kim‐1 (30.0% vs 9.3%, P < .001); lower for men using the Davison (4.4% vs 11.1%, P < .001) and Kim‐2 (83.7% vs 94.0%) definitions; and the same for men and women using the Bouchard (45.3% vs 44.3%, P = .32) and Kim‐3 (75.6% vs 77.0%, P = .51) definitions. For all but one definition, sarcopenic obesity increased with each decade and was lower in non‐Hispanic blacks than whites.
Conclusion
Prevalence of sarcopenic obesity in older adults varies up to 26‐fold depending on current research definitions. Such a high degree of variability suggests the need to establish consensus criteria that can be reliably applied across clinical and research settings.
PDF
