Residual Feed Intake (RFI) and Efficiency of Feed Utilization (EFU) of Total Mixed Ration (TMR) Fed Frisian Cross Bred Cows – a Case Study

Residual Feed Intake (RFI) is the difference between an animal’s actual feed and expected feed intakes for a given period of time. Literature shows that highly efficient animals have a negative or lower RFI. Thus understanding about RFI is important to maintain an efficient herd. A feeding trial was undertaken at a commercial farm in Sri Lanka having Frisian cross bred cows. The cows were fed with a grass-based Total Mixed Ration (TMR) having maize (Zea mays), CO3 (Pennisetum perpureum X Pennisetum americarnum), beer pulp (wet brewer’s grain), dhal meal (Lens culinaris), mineral mixture and commercial cattle feed. However, the milk yields were lower than expected affecting the farm profit. Thus a study was undertaken to test a new TMR with the hypothesis that the new TMR would enhance milk production of the cows. Eighteen, Frisian cross bred cows were randomly assigned into two groups (Treatment 1: existing TMR; TMR 1) and Treatment 2: new TMR; TMR 2), in a Randomized Complete Block Design (RCBD). Each treatment had three replicates. Data were collected (daily feed intake, milk yield and live body weight of cows) for a 28 day period. Residual Feed Intake was derived by a regression model using feed intake and live weight data. Efficiency of Feed Utilization was calculated using cumulative milk yield and feed intake data. The RFI in Treatment 1 (0.42± 0.197 kg/cow) was higher (P\u3c 0.05) than Treatment 2 (-0.45± 0.197 kg/cow). Efficiency of Feed Utilization in Treatment 2 (36% ± 0.797 ml/cow) was higher (P\u3c 0.05) than Treatment 1 (29% ± 0.797 ml/cow). The results show that the cows in Treatment 2 were more efficient than the cows in Treatment 1. Hence it can be concluded that the new TMR (TMR 2) consists of maize, CO3, Guinea grass (Panicum maximum), beer pulp, coconut (Cocos nucifera) poonac, rice bran, maize meal and mineral mixture was better than the exiting TMR (TMR 1)

Feeding Patterns and Milk Production of Small-Scale Dairy Farmers under Semi-Intensive and Extensive Cattle Management Systems in Sri Lanka

The main objective of the present study was to determine the feeding pattern and milk production of small-scale dairy farmers under semi-intensive and extensive management systems in the intermediate zone of Sri Lanka. This region is sandwiched between the Wet and Dry Zones, receives a mean annual rainfall of 1750-2500 mm, and covers an area of about 1.2 million ha. A survey was conducted with 60 farmers and data on their herd size, herd composition and breeds, management system, breeding method, milk production, feeding costs and returns of raising animals were collected. The results indicated that the majority of farmers conducted dairying as a part-time business in both semi-intensive (80%) and extensive (66%) management systems in the study area. The highest (P \u3c 0.05) average herd size was observed under semi-intensive systems (3.7 animal units (AU)), compared to extensive systems (2.7 AU). The farmers under the semi-intensive system maintained better feeding levels compared with the extensive system. The majority of farmers in the area depended on tethering and stall feeding as their main source of animal feed. Grasses grown on roadsides, paddy fields, neighbours’ land, government estates and tree leaves were the main feed resources available for both management systems. Rice (Oriza sativa) bran and coconut (Cocos nucifera) poonac were the main concentrate feed ingredients in the study area. Jersey crosses were the most popular dairy animals among semi-intensively managed farms, whereas Sahiwal crosses were most popular in extensive management systems. The average milk production under extensive systems was significantly lower (P \u3c 0.01) at 3.9 l/AU/day, compared to 5.4 l/AU/day under semi-intensive systems. Semi-intensive management systems also had the highest average monthly return per AU

Web Data Scraping Technology using TF-IDF to Enhance the Big Data Quality on Sentiment Analysis

Tourism is a booming industry, with huge future potential for global wealth and employment. There are countless data generated over social media sites every day creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization, TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm after pre-processing and cleaning the dataset, we have received an accuracy of 96.12% for the positive and negative sentiment analysis

Laminin and biomimetic extracellular elasticity enhance functional differentiation in mammary epithelia

In the mammary gland, epithelial cells are embedded in a ‘soft' environment and become functionally differentiated in culture when exposed to a laminin-rich extracellular matrix gel. Here, we define the processes by which mammary epithelial cells integrate biochemical and mechanical extracellular cues to maintain their differentiated phenotype. We used single cells cultured on top of gels in conditions permissive for β-casein expression using atomic force microscopy to measure the elasticity of the cells and their underlying substrata. We found that maintenance of β-casein expression required both laminin signalling and a ‘soft' extracellular matrix, as is the case in normal tissues in vivo, and biomimetic intracellular elasticity, as is the case in primary mammary epithelial organoids. Conversely, two hallmarks of breast cancer development, stiffening of the extracellular matrix and loss of laminin signalling, led to the loss of β-casein expression and non-biomimetic intracellular elasticity. Our data indicate that tissue-specific gene expression is controlled by both the tissues' unique biochemical milieu and mechanical properties, processes involved in maintenance of tissue integrity and protection against tumorigenesis

Overexpression of podocalyxin-like protein is an independent factor of poor prognosis in colorectal cancer

Background:Podocalyxin-like 1 (PODXL) is a cell-adhesion glycoprotein and stem cell marker that has been associated with an aggressive tumour phenotype and poor prognosis in several forms of cancer. In this study, we investigated the prognostic impact of PODXL expression in colorectal cancer (CRC).Methods:Using tissue microarrays and immunohistochemistry, PODXL expression was evaluated in 536 incident CRC cases from a prospective, population-based cohort study. Kaplan-Meier analysis and Cox proportional hazards modelling were used to assess the impact of PODXL expression on cancer-specific survival (CSS) and overall survival (OS).Results:High PODXL expression was significantly associated with unfavourable clinicopathological characteristics, a shorter CSS (hazard ratio (HR)=1.98; 95% confidence interval (CI) 1.38-2.84, P<0.001) and 5-year OS (HR=1.85; 95% CI 1.29-2.64, P=0.001); the latter remaining significant in multivariate analysis (HR=1.52; 95% CI 1.03-2.25, P=0.036). In addition, in curatively resected stage III (T1-4, N1-2, M0) patients (n=122) with tumours with high PODXL expression, a significant benefit from adjuvant chemotherapy was demonstrated (p(interaction) =0.004 for CSS and 0.015 for 5-year OS in multivariate analysis).Conclusion:Podocalyxin-like 1 expression is an independent factor of poor prognosis in CRC. Our results also suggest that PODXL may be a useful marker to stratify patients for adjuvant chemotherapy

The CD34-Related Molecule Podocalyxin Is a Potent Inducer of Microvillus Formation

BACKGROUND: Podocalyxin is a CD34-related transmembrane protein involved in hematopoietic cell homing, kidney morphogenesis, breast cancer progression, and epithelial cell polarization. Although this sialomucin has been shown to block cell adhesion, the mechanisms involved remain enigmatic. It has, however, been postulated that the adaptor proteins NHERF-1 and 2 could regulate apical targeting of Podocalyxin by linking it to the actin cytoskeleton. PRINCIPAL FINDINGS: Here, in contrast, we find that full-length Podocalyxin acts to recruit NHERF-1 to the apical domain. Moreover, we show that ectopic expression of Podocalyxin in epithelial cells leads to microvillus formation along an expanded apical domain that extends laterally to the junctional complexes. Removal of the C-terminal PDZ-binding domain of Podocalyxin abolishes NHERF-1 recruitment but, surprisingly, has no effect on the formation of microvilli. Instead, we find that the extracellular domain and transmembrane region of Podocalyxin are sufficient to direct recruitment of filamentous actin and ezrin to the plasma membrane and induce microvillus formation. CONCLUSIONS/SIGNIFICANCE: Our data suggest that this single molecule can modulate NHERF localization and, independently, act as a key orchestrator of apical cell morphology, thereby lending mechanistic insights into its multiple roles as a polarity regulator, tumor progression marker, and anti-adhesin