Fetal heart rate responses in chronic hypoxaemia with superimposed repeated hypoxaemia consistent with early labour: a controlled study in fetal sheep.

OBJECTIVE: Deceleration area (DA) and capacity (DC) of the fetal heart rate can help predict risk of intrapartum fetal compromise. However, their predictive value in higher risk pregnancies is unclear. We investigated whether they can predict the onset of hypotension during brief hypoxaemia repeated at a rate consistent with early labour in fetal sheep with pre-existing hypoxaemia. DESIGN: Prospective, controlled study. SETTING: Laboratory. SAMPLE: Chronically instrumented, unanaesthetised near-term fetal sheep. METHODS: One-minute complete umbilical cord occlusions (UCOs) were performed every 5 minutes in fetal sheep with baseline pa O2 <17 mmHg (hypoxaemic, n = 8) and >17 mmHg (normoxic, n = 11) for 4 hours or until arterial pressure fell <20 mmHg. MAIN OUTCOME MEASURES: DA, DC and arterial pressure. RESULTS: Normoxic fetuses showed effective cardiovascular adaptation without hypotension and mild acidaemia (lowest arterial pressure 40.7 ± 2.8 mmHg, pH 7.35 ± 0.03). Hypoxaemic fetuses developed hypotension (lowest arterial pressure 20.8 ± 1.9 mmHg, P < 0.001) and acidaemia (final pH 7.07 ± 0.05). In hypoxaemic fetuses, decelerations showed faster falls in FHR over the first 40 seconds of UCOs but the final deceleration depth was not different to normoxic fetuses. DC was modestly higher in hypoxaemic fetuses during the penultimate (P = 0.04) and final (P = 0.012) 20 minutes of UCOs. DA was not different between groups. CONCLUSION: Chronically hypoxaemic fetuses had early onset of cardiovascular compromise during labour-like brief repeated UCOs. DA was unable to identify developing hypotension in this setting, while DC only showed modest differences between groups. These findings highlight that DA and DC thresholds need to be adjusted for antenatal risk factors, potentially limiting their clinical utility.

Ferroptosis-Related Long Noncoding RNA Signature Predicts Prognosis of Clear Cell Renal Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is very common and accounts for most kidney cancer deaths. While many studies are being conducted in finding the prognostic signatures of ccRCC, we believe that ferroptosis, which involves programmed cell death dependent on iron accumulation, has therapeutic potential in ccRCC. Recent research has shown that long noncoding RNAs (lncRNAs) are involved in ferroptosis-related tumour processes and are closely related to survival in patients with ccRCC. Hence, in this study we aim to further explore the role of ferroptosis-related lncRNAs (FRLs) in ccRCC, hoping to establish a signature to predict the survival outcome of ccRCC. We analysed transcriptome data from The Cancer Genome Atlas database (TCGA) and ferroptosis-related genes (FRGs) from FerrDb to identify FRLs using Pearson's correlation. Lasso Cox regression analysis and multivariate Cox proportional hazards models screened seventeen optimal FRLs for developing prognostic signatures. Kaplan-Meier survival curves and ROC curves were then plotted for validating the sensitivity, specificity, and accuracy of the identified signatures. Gene Set Enrichment Analysis and CIBERSORT algorithm were deployed to explore the role of these FRLs in the tumour microenvironment. It was concluded that these models demonstrate excellent performance in predicting prognosis among patients with ccRCC, also indicating association with the clinicopathologic parameters such as tumour grade, tumour stage and tumour immune infiltration. In conclusion, our findings provide novel insights into ferroptosis-related lncRNAs in ccRCC, which are important targets for investigating the tumorigenesis of ccRCC.

Machine Learning and Deep Learning Approaches in Breast Cancer Survival Prediction Using Clinical Data.

Breast cancer survival prediction can have an extreme effect on selection of best treatment protocols. Many approaches such as statistical or machine learning models have been employed to predict the survival prospects of patients, but newer algorithms such as deep learning can be tested with the aim of improving the models and prediction accuracy. In this study, we used machine learning and deep learning approaches to predict breast cancer survival in 4,902 patient records from the University of Malaya Medical Centre Breast Cancer Registry. The results indicated that the multilayer perceptron (MLP), random forest (RF) and decision tree (DT) classifiers could predict survivorship, respectively, with 88.2 %, 83.3 % and 82.5 % accuracy in the tested samples. Support vector machine (SVM) came out to be lower with 80.5 %. In this study, tumour size turned out to be the most important feature for breast cancer survivability prediction. Both deep learning and machine learning methods produce desirable prediction accuracy, but other factors such as parameter configurations and data transformations affect the accuracy of the predictive model.

Comparison of Fully Automated and Semi-Automated Methods for Species Identification.

The process of manual species identification is a daunting task, so much so that the number of taxonomists is seen to be declining. In order to assist taxonomists, many methods and algorithms have been proposed to develop semi-automated and fully automated systems for species identification. While semi-automated tools would require manual intervention by a domain expert, fully automated tools are assumed to be not as reliable as manual or semiautomated identification tools. Hence, in this study we investigate the accuracy of fully automated and semi-automated models for species identification. We have built fully automated and semi-automated species classification models using the monogenean species image dataset. With respect to monogeneans' morphology, they are differentiated based on the morphological characteristics of haptoral bars, anchors, marginal hooks and reproductive organs (male and female copulatory organs). Landmarks (in the semi-automated model) and shape morphometric features (in the fully automated model) were extracted from four monogenean species images, which were then classified using k-nearest neighbour and artificial neural network. In semi-automated models, a classification accuracy of 96.67 % was obtained using the k-nearest neighbour and 97.5 % using the artificial neural network, whereas in fully automated models, a classification accuracy of 90 % was obtained using the k-nearest neighbour and 98.8 % using the artificial neural network. As for the crossvalidation, semi-automated models performed at 91.2 %, whereas fully automated models performed slightly higher at 93.75 %.

Automated otolith image classification with multiple views: an evaluation on Sciaenidae.

Combined multiple 2D views (proximal, anterior and ventral aspects) of the sagittal otolith are proposed here as a method to capture shape information for fish classification. Classification performance of single view compared with combined 2D views show improved classification accuracy of the latter, for nine species of Sciaenidae. The effects of shape description methods (shape indices, Procrustes analysis and elliptical Fourier analysis) on classification performance were evaluated. Procrustes analysis and elliptical Fourier analysis perform better than shape indices when single view is considered, but all perform equally well with combined views. A generic content-based image retrieval (CBIR) system that ranks dissimilarity (Procrustes distance) of otolith images was built to search query images without the need for detailed information of side (left or right), aspect (proximal or distal) and direction (positive or negative) of the otolith. Methods for the development of this automated classification system are discussed.

Selenium accumulation by forage and grain crops and volatilization from seleniferous soils amended with different organic materials.

Greenhouse and field experiments were conducted to study the direct and residual effect of applying different organic materials on Se accumulation by crops and volatilization from seleniferous soils of northwestern India. Among organic manures, press mud and poultry manures proved 4-5 times more effective in reducing Se accumulation by different crops than farmyard manure. Efficiency of organic manures increased with increase in application rates. Application of both press mud and poultry manures reduced Se accumulation by 44-97% in wheat (Triticum aestivum) and rapeseed (Brassica napus) shoots in the greenhouse; 85-92% in wheat straw, 45-74% in wheat grains, 45-74% in rapeseed straw and 76-92% in rapeseed grains under field conditions. Both the manures remained highly effective in reducing Se accumulation by the crops following wheat and rapeseed and the extent of reduction varied from 50% to 87% in maize (Zea mays) and cowpeas (Vigna sinensis) in the greenhouse and 40-89% in maize and rice (Oryza sativa) crops under field situation. Rate of Se volatilization by wheat and rapeseed crops increased by 1.8-4.0 times; the greatest increase was observed with press mud followed by poultry manure, arhar (Cajanus cajan) leaves and farmyard manure. After 134d of incubation of 500g soil amended with 2% of plant tissues, the maximum amount of Se was volatilized with cowpea leaves (385ng) followed by wheat grains, leaves of maize, sugarcane (Saccharum officcinarum), arhar, poplar (Populus deltoides) and the control (91ng). The results of this study convincingly prove the usefulness of applying press mud and poultry manure in enhancing volatilization and retarding the transfer of Se from soil to plant in seleniferous soils.

Bioavailability of selenium to forage crops in a sandy loam soil amended with Se-rich plant materials.

Greenhouse experiments were conducted to study the bioavailability of selenium (Se) to sorghum (Sorghum bicolor L.), maize (Zea mays L.) and berseem (Trifolium alexandrinum L.) fodders in a sandy loam soil amended with different levels of Se-rich wheat (Triticum aestivum L.) and raya (Brassica juncea L. Czern) straw containing 53.3 and 136.7microg Seg(-1), respectively. Each of the fodder crops was grown after incorporation of Se-rich materials either individually or in a sequence - sorghum-maize-berseem by incorporating Se-rich straws only to the first crop. Application of Se-rich straws to each crop, even at the greatest rate of 1%, did not have any detrimental effect on dry matter yield of different crops. With increase in the level of wheat straw from 0% to 1%, Se content in sorghum and maize plants increased to greatest level of 1.3 and 1.5microg g(-1), respectively, at 0.3% of applied straw and thereafter it decreased consistently. In case of raya straw, the greatest Se content in sorghum (2.3microg g(-1)) and maize (3.0microg g(-1)) was recorded at 0.3% and 0.4% of the applied straw, respectively. Unlike sorghum and maize fodders, Se content in all the four cuts of berseem continued to increase with increase in the level of applied straws and for different cuts of berseem it varied from 1.6 to 2.3 and 3.4 to 4.3microg g(-1) in case of wheat and raya straw, respectively. Similar variations in Se content of different fodder crops were recorded when these were grown in the sequence - sorghum-maize-berseem; but Se content was 2-4 times lower than when each crop was grown with fresh application of Se-rich straw. None of the fodders absorbed Se in levels toxic for animal consumption (>5microg g(-1)) even at the greatest level of applied straw. Of the total Se added through Se-rich straws, utilization of Se was not more than 2% in case of sorghum and maize crops and up to 5% in case of berseem. At the time of sowing of sorghum, hot water soluble Se (HWS-Se) in soils treated with different levels of Se-rich wheat and raya straw, respectively, varied from 18 to 36 and 18 to 79microg kg(-1). Whereas in case of berseem, it varied from 33 to 101 and 33 to 154microg kg(-1), respectively. HWS-Se present at the sowing time of berseem was significantly correlated with Se content of all the four cuts in the soil treated with Se-rich straws; the coefficients of correlation 'r' varied between 0.79 (p0.05) and 0.99 (p0.001). Selenium-rich materials supplied significant amounts of S, P and micronutrients to the growing fodder crops. These investigations suggest that Se-rich raya and wheat straw may be disposed off safely in soils used for growing fodders.

Effects of dietary taurine on auditory function in full-term infants.

Three groups of neonates fed taurine supplemented infant formula, non-supplemented infant formula or breast milk, respectively, were studied from birth to 12 weeks of age. In addition to the measurement of whole blood taurine content, auditory function was monitored using auditory brainstem responses (ABRs) and transient evoked otoacoustic emissions (TEOAEs). The results showed a significant reduction in whole blood taurine concentration in the non-supplemented formula group. In addition, there was a significant drop in whole blood taurine levels in all 3 groups over the first four weeks of life. ABR wave latencies were significantly shorter in the non-supplemented group, with wave V showing the greatest reductions. Falling taurine levels after full-term birth may aid synaptic maturation/efficiency within the auditory system. TEOAE responses were significantly larger over the low to mid frequencies in the breast fed group suggesting improved middle ear function.

Accumulation of selenium in sugarcane (Sachharum officinarum Linn.) in seleniferous areas of Punjab, India.

A survey was conducted during 1986-88 to assess the level and pattern of accumulation of selenium in sugarcane plants in seleniferous areas of Punjab (India). Total and water-extractable (available) selenium ranged from 0.55 to 2.58 (mean 1.43 ± 0.67) mg kg(-1) and from 0.02 to 0.05 (mean 0.033 ± 0.007) mg kg(-1), respectively, in seleniferous areas. Corresponding values from non-seleniferous areas were 0.23-0.55 (mean 0.36 ± 0.08) mg kg(-1) and 0.015-0.025 (mean 0.020 ± 0.003) mg kg(-1), respectively. Sugarcane tops from seleniferous areas accumulated high levels of selenium ranging from 7.9 to 67.5 mg kg(-1). These selenium levels were 6-14 times higher than those from non-seleniferous areas. During the early stages of growth (June), the selenium content was highest but decreased during the months of July and August and then did not change up to maturity. In the seleniferous areas sugarcane tops and canes at maturity contained 5.7-9.5 and 1.8-2.1 mg Se kg(-1), respectively. However, the tops and canes of plants growing near the permanent boundary (bundh) contained 9.5-18.8 and 2.1-2.4 mg Se kg(-1), respectively.In a field experiment on sugarcane, application of gypsum up to 1 ton ha(-1) resulted in a significant reduction of selenium content in sugarcane tops as well as in the cane. Selenium content in sugarcane tops at maturity was reduced from 15.16 to 5.08 mg kg(-1) by applying gypsum of 1 ton ha(-1).