Effect of Different Levels of Phosphorus and Method of Application on the Growth and Yield of Wheat

S. Noonari et al. 30

Incretin-Based Therapies for the Treatment of Type 2 Diabetes: Evaluation of the Risks and Benefits

Limited evidence suggests that GLP-I may also preserve ventricular function and improve outcomes in human subjects with heart failure or myocardial infarction (11,12). [...] both exenatide and liraglutide reduce blood pressure, body weight, and plasma lipid profiles in subjects with type 2 diabetes (13), raising the hope that longterm treatment with these agents may reduce the incidence of cardiovascular events.\n However, two safety issues have been raised - pancreatitis and medullary carcinoma of the thyroid

TB Hackathon: Development and Comparison of Five Models to Predict Subnational Tuberculosis Prevalence in Pakistan

Pakistan’s national tuberculosis control programme (NTP) is among the many programmes worldwide that value the importance of subnational tuberculosis (TB) burden estimates to support disease control efforts, but do not have reliable estimates. A hackathon was thus organised to solicit the development and comparison of several models for small area estimation of TB. The TB hackathon was launched in April 2019. Participating teams were requested to produce district-level estimates of bacteriologically positive TB prevalence among adults (over 15 years of age) for 2018. The NTP provided case-based data from their 2010–2011 TB prevalence survey, along with data relating to TB screening, testing and treatment for the period between 2010–2011 and 2018. Five teams submitted district-level TB prevalence estimates, methodological details and programming code. Although the geographical distribution of TB prevalence varied considerably across models, we identified several districts with consistently low notification-to-prevalence ratios. The hackathon highlighted the challenges of generating granular spatiotemporal TB prevalence forecasts based on a cross-sectional prevalence survey data and other data sources. Nevertheless, it provided a range of approaches to subnational disease modelling. The NTP’s use and plans for these outputs shows that, limitations notwithstanding, they can be valuable for programme planning

Innovation in the Breeding of Common Bean Through a Combined Approach of in vitro Regeneration and Machine Learning Algorithms

Common bean is considered a recalcitrant crop for in vitro regeneration and needs a repeatable and efficient in vitro regeneration protocol for its improvement through biotechnological approaches. In this study, the establishment of efficient and reproducible in vitro regeneration followed by predicting and optimizing through machine learning (ML) models, such as artificial neural network algorithms, was performed. Mature embryos of common bean were pretreated with 5, 10, and 20 mg/L benzylaminopurine (BAP) for 20 days followed by isolation of plumular apice for in vitro regeneration and cultured on a post-treatment medium containing 0.25, 0.50, 1.0, and 1.50 mg/L BAP for 8 weeks. Plumular apice explants pretreated with 20 mg/L BAP exerted a negative impact and resulted in minimum shoot regeneration frequency and shoot count, but produced longer shoots. All output variables (shoot regeneration frequency, shoot counts, and shoot length) increased significantly with the enhancement of BAP concentration in the post-treatment medium. Interaction of the pretreatment × post-treatment medium revealed the need for a specific combination for inducing a high shoot regeneration frequency. Higher shoot count and shoot length were achieved from the interaction of 5 mg/L BAP × 1.00 mg/L BAP followed by 10 mg/L BAP × 1.50 mg/L BAP and 20 mg/L BAP × 1.50 mg/L BAP. The evaluation of data through ML models revealed that R2 values ranged from 0.32 to 0.58 (regeneration), 0.01 to 0.22 (shoot counts), and 0.18 to 0.48 (shoot length). On the other hand, the mean squared error values ranged from 0.0596 to 0.0965 for shoot regeneration, 0.0327 to 0.0412 for shoot count, and 0.0258 to 0.0404 for shoot length from all ML models. Among the utilized models, the multilayer perceptron model provided a better prediction and optimization for all output variables, compared to other models. The achieved results can be employed for the prediction and optimization of plant tissue culture protocols used for biotechnological approaches in a breeding program of common beans

Clinicopathological Profile and Surgical Treatment of Abdominal Tuberculosis: A Single Centre Experience in Northwestern Tanzania.

Abdominal tuberculosis continues to be a major public health problem worldwide and poses diagnostic and therapeutic challenges to general surgeons practicing in resource-limited countries. This study was conducted to describe the clinicopathological profile and outcome of surgical treatment of abdominal tuberculosis in our setting and compare with what is described in literature. A prospective descriptive study of patients who presented with abdominal tuberculosis was conducted at Bugando Medical Centre (BMC) in northwestern Tanzania from January 2006 to February 2012. Ethical approval to conduct the study was obtained from relevant authorities. Statistical data analysis was performed using SPSS version 17.0. Out of 256 patients enrolled in the study, males outnumbered females. The median age was 28 years (range = 16-68 years). The majority of patients (77.3%) had primary abdominal tuberculosis. A total of 127 (49.6%) patients presented with intestinal obstruction, 106 (41.4%) with peritonitis, 17 (6.6%) with abdominal masses and 6 (2.3%) patients with multiple fistulae in ano. Forty-eight (18.8%) patients were HIV positive. A total of 212 (82.8%) patients underwent surgical treatment for abdominal tuberculosis. Bands /adhesions (58.5%) were the most common operative findings. Ileo-caecal region was the most common bowel involved in 122 (57.5%) patients. Release of adhesions and bands was the most frequent surgical procedure performed in 58.5% of cases. Complication and mortality rates were 29.7% and 18.8% respectively. The overall median length of hospital stay was 32 days and was significantly longer in patients with complications (p < 0.001). Advanced age (age ≥ 65 years), co-morbid illness, late presentation, HIV positivity and CD4+ count < 200 cells/μl were statistically significantly associated with mortality (p < 0.0001). The follow up of patients were generally poor as only 37.5% of patients were available for follow up at twelve months after discharge. Abdominal tuberculosis constitutes a major public health problem in our environment and presents a diagnostic challenge requiring a high index of clinical suspicion. Early diagnosis, early anti-tuberculous therapy and surgical treatment of the associated complications are essential for survival

Galectin-3 immunodetection in follicular thyroid neoplasms: a prospective study on fine-needle aspiration samples

Fine-needle aspiration cytology, which is well established to be accurate for the diagnosis of thyroid cancer, may be inconclusive for the follicular thyroid neoplasms. As galectin-3 was suggested to be a marker of malignant thyrocytes, we investigated whether this protein might be helpful in the diagnosis of aspirates classified as undeterminate by cytology. After establishing an easy processing of aspirates for galectin-3 immunodetection, a series of aspirates categorised as benign (n=63), malignant (n=17) or undeterminate (n=34) was prospectively analysed for galectin-3. Only the patients with malignant or undeterminate lesions underwent surgery. Most lesions (86%) diagnosed as malignant by cytology or after surgery were positive for galectin-3. The majority of lesions (94%) classified as benign by cytology or after surgery was negative for galectin-3. The positive and negative predictive values were 83 and 95%, respectively. When focusing on the undeterminate lesions, the sensitivity and specificity were 75 and 90%, respectively, while the positive and negative predictive values were 82 and 87%, respectively. The specificity and the positive predictive value were higher (100%) when considering the percentage of stained cells. Altogether these results show that galectin-3 constitutes a useful marker in the diagnosis of thyroid lesions classified as undeterminate by conventional cytology

TB hackathon : development and comparison of five models to predict subnational tuberculosis prevalence in Pakistan

Pakistan's national tuberculosis control programme (NTP) is among the many programmes worldwide that value the importance of subnational tuberculosis (TB) burden estimates to support disease control efforts, but do not have reliable estimates. A hackathon was thus organised to solicit the development and comparison of several models for small area estimation of TB. The TB hackathon was launched in April 2019. Participating teams were requested to produce district-level estimates of bacteriologically positive TB prevalence among adults (over 15 years of age) for 2018. The NTP provided case-based data from their 2010-2011 TB prevalence survey, along with data relating to TB screening, testing and treatment for the period between 2010-2011 and 2018. Five teams submitted district-level TB prevalence estimates, methodological details and programming code. Although the geographical distribution of TB prevalence varied considerably across models, we identified several districts with consistently low notification-to-prevalence ratios. The hackathon highlighted the challenges of generating granular spatiotemporal TB prevalence forecasts based on a cross-sectional prevalence survey data and other data sources. Nevertheless, it provided a range of approaches to subnational disease modelling. The NTP's use and plans for these outputs shows that, limitations notwithstanding, they can be valuable for programme planning

Development of a clinical decision model for thyroid nodules

<p>Abstract</p> <p>Background</p> <p>Thyroid nodules represent a common problem brought to medical attention. Four to seven percent of the United States adult population (10–18 million people) has a palpable thyroid nodule, however the majority (>95%) of thyroid nodules are benign. While, fine needle aspiration remains the most cost effective and accurate diagnostic tool for thyroid nodules in current practice, over 20% of patients undergoing FNA of a thyroid nodule have indeterminate cytology (follicular neoplasm) with associated malignancy risk prevalence of 20–30%. These patients require thyroid lobectomy/isthmusectomy purely for the purpose of attaining a definitive diagnosis. Given that the majority (70–80%) of these patients have benign surgical pathology, thyroidectomy in these patients is conducted principally with diagnostic intent. Clinical models predictive of malignancy risk are needed to support treatment decisions in patients with thyroid nodules in order to reduce morbidity associated with unnecessary diagnostic surgery.</p> <p>Methods</p> <p>Data were analyzed from a completed prospective cohort trial conducted over a 4-year period involving 216 patients with thyroid nodules undergoing ultrasound (US), electrical impedance scanning (EIS) and fine needle aspiration cytology (FNA) prior to thyroidectomy. A Bayesian model was designed to predict malignancy in thyroid nodules based on multivariate dependence relationships between independent covariates. Ten-fold cross-validation was performed to estimate classifier error wherein the data set was randomized into ten separate and unique train and test sets consisting of a training set (90% of records) and a test set (10% of records). A receiver-operating-characteristics (ROC) curve of these predictions and area under the curve (AUC) were calculated to determine model robustness for predicting malignancy in thyroid nodules.</p> <p>Results</p> <p>Thyroid nodule size, FNA cytology, US and EIS characteristics were highly predictive of malignancy. Cross validation of the model created with Bayesian Network Analysis effectively predicted malignancy [AUC = 0.88 (95%CI: 0.82–0.94)] in thyroid nodules. The positive and negative predictive values of the model are 83% (95%CI: 76%–91%) and 79% (95%CI: 72%–86%), respectively.</p> <p>Conclusion</p> <p>An integrated predictive decision model using Bayesian inference incorporating readily obtainable thyroid nodule measures is clinically relevant, as it effectively predicts malignancy in thyroid nodules. This model warrants further validation testing in prospective clinical trials.</p

CSM-CERES-Rice model to determine management strategies for lowland rice production

The cropping system model, namely, the crop environment resource synthesis-rice (CSM-CERES-Rice) model, is a decision supporting tool for the design of crop management. This study aimed to determine management practices for increasing rice (Oryza sativa L.) production in Laos by using the CSM-CERES-Rice model. The model was evaluated with data sets from the TDK8 and TDK11 cultivars in farmers’ fields in the Vientiane plain in 2012. Anthesis and harvesting dates, growth and yield for various management scenario combinations (eight transplanting dates × two levels of plant densities × three rates of nitrogen (N) fertilizer application) for both cultivars were simulated by the model from 1980 to 2012. The model evaluation results showed strong agreement between simulated and observed data for days to harvest with a difference within four days. The model provided acceptable accuracy for grain yields with normalized root mean square error values ranging between 1 and 16 %. The results from the model application indicated that TDK8 and TDK11 produced similar yields. Transplanting TDK8 with two plant densities produced similar yields. The highest yield for both cultivars was achieved on the transplanting date of 15 Jan. N-fertilizer application at 60 and 120 kg N ha−1 was able to increase yield for TDK8 by 50 and 87 %, respectively, and for TDK11 by 54 and 70 %, respectively. Rice transplanted on 15 Jan with 5 seedlings hill−1 and N-fertilizer at 120 kg N ha−1 had the highest average yield for both cultivars with 6,460 and 6,351 kg ha−1 for TDK8 and TDK11, respectively. The CSM-CERES-Rice model is an alternative tool in determining crop management practices for rice production