Animal Resources Development Department

The present study was carried out to assess the influence of exogenous intravenous kisspeptin-10 on the follicular dynamics, hormonal profile, and expression pattern of KiSS1 and KiSS1R of Lakhimi cows of Assam during the estrus period. Cows were examined every alternate day during the estrous cycle using a linear array ultrasound scanner and profiled in an ovarian map. The follicular wave patterns were mostly (66.7%) 2-wave cycle and 33.3% with 3-wave cycle in both treated and control group of cows. Kisspeptin-10 induced an early emergence of follicular waves with more follicular count and accelerated growth of dominant follicle in both 2 and 3 waves in treated group compared to the control. Significant augmentation of serum concentration of progesterone (10th day), LH (day 1) and estradiol (on the day before estrus) in treated cows was observed, however the hormonal dynamics were similar to other mammals Administration of Kisspeptin-10 has elicited a significant rise in the serum kisspeptin level with gradual increase of the transcripts encoding Kiss1 and Kiss1R genes (highest on 3rd day of estrous cycle) and declined gradually till day 11. Both the transcripts encoding Kiss1 and Kiss1R genes were gradually increased from day 17 and were higher two days before the beginning of the next estrous cycle. Intravenous administration of exogenous Kisspeptin-10 can be promising approach to augment the ovarian follicular dynamics in regards to early onset of wave, follicular numbers and diameter, to explore the optimum fertility in indigenous cows, Lakhimi.

Background: Selective breeding in pigs based on a higher potential of disease resistance can be achieved by studying the association between immune responsiveness and susceptibility to infectious diseases. The early immune responsiveness of pigs assessed in a quantifiable scale for different determinant cytokine genes’ expression involved in regulation of immune response can be a major determinant for evaluating the immune responsiveness. Methods: In this study, we carried out the quantitative relative expression of candidate cytokine genes [Interleukin-1 beta-(IL1β), IL6, IL10 and tumor necrosis factor-alpha (TNFα) and toll-like receptor-4 (TLR4) gene expression in the lipopolysaccharide (LPS) stimulated peripheral blood mononuclear cells (PBMCs) of Zovawk (indigenous) and Large White Yorkshire (LWY-exotic) pig breeds using real-time PCR to understand the differences in swift immune responsiveness against gram-negative bacteria. Results: Zovawk PBMCs’ pro-inflammatory cytokines IL1β and IL6 expression increased rapidly with LPS stimulation up to 12 h, being significantly higher as early as 4 h compared to that of the LWY PBMCs. In Zovawk pigs, the pro-inflammatory cytokine genes’ expression was found to be quick and high; whereas, in LWY pigs the response was slow and low. Interestingly, the expression of IL10 was not detected in LPS-stimulated PBMCs of Zovawk pigs indicating that the remarkably higher expressions of IL6 and IL1b in response to LPS are within the threshold of the Zovawk pigs which have evolved through generations. Our findings clearly indicate the sturdy and early immune responsiveness of indigenous pigs against gram-negative bacteria over the exotic pigs.

This study sought to examine the immune response of rabbits fed different dietary levels of four common forages in Coastal Savannah Ecological Zone of Ghana. A total of 48 eight-week old mixed-breed rabbits were offered--concentrate containing graded levels of 0, 10, 20 and 30% Brassica oleracea outer leaves or Musa paradisiaca leaves, Megathyrsus maximus, and Stylosanthes guianensis aerial parts for one week and 12-weeks adaptation and testing periods respectively. Spleen from 8 representative rabbits from each treatment group were harvested at the end of the feeding period and used to determine the spleen indices. No significant differences were found in the body weights, 1926 to 2314g, spleen weights, 1.00 to 1.50g, and spleen indices, 0.05 to 0.07g of rabbits fed concentrate containing the graded levels of the leaves. Rabbits fed diets containing 10% inclusion level of Brassica oleracea had the highest body weight, while the highest spleen weight and spleen index were found in rabbits fed 30% inclusion level of Musa paradisiaca leaves and Stylosanthes guianensis aerial parts. The study concludes that feeding diets containing up to 30% inclusion level of Brassica oleracea outer leaves, Musa paradisiaca leave and Megathyrsus maximus and Stylosanthes guianensis aerial parts to growing rabbits enhance the immune response of the animals thereby ensuring good performance and health.

Gastrointestinal parasites pose constant threat to dairy animals, greatly affecting their health, well-being, and production.The study was conducted to determine the prevalence of gastrointestinal parasites in dairy cattle in three agro-climatic zones of West Bengal, namely Zone-I (Hilly zone), Zone-II (New alluvial zone) and Zone-III (Coastal saline zone).A total of 1419 faecal samples were collected and analyzed through standard sedimentation and salt flotation technique.In total, 270 animal owners were interviewed in regards to deworming practices.Out of the total 465 samples analyzed, 176 (37.85%) samples were positive for mono or mixed infection in zone-I.The most prevalent were Strongyle (26.02%) followed by Amphistome (22.15%),Moniezia sp.(19.14%), oocyst of Eimeria spp.(12.04%),Fasciola sp.(4.09%), Strongyloides sp.(4.08%) and Toxocara sp.(1.72%).In zone-II, out of 481 samples, 157 (32.64%) were positive and the prevalence of parasites were as Strongyle (28.90%),Amphistome (26.20%),Fasciola sp.(14.14%),Strongyloides sp.(7.28%), Moniezia sp.(6.86%), Coccidian oocyst (4.99%), and Trichuris sp.(3.12%).Out of 473 samples in zone-III, 203 (42.92%) were positive.The highest percentage of samples were positive for Amphistome (31.92%) followed by Strongyle (18.82%),Fasciola sp.(10.99%),Strongyloides sp.(7.82%), Coccidian oocyst (5.92%), Moniezia sp.(4.02%) and Trichuris sp.(4.86%).The Chi square value indicates a highly significant difference between zones in the healthcare practice of administering dewormer to dairy animals.Overall, 44.81% farmers were deworming adult animals sometimes in all the zones and only 26.67% dewormed their calves frequently.The Chi square value indicates highly significant (p<0.01)difference in deworming of calves in different zones of West Bengal.The findings of the present study may help to develop a strategic control approach for gastrointestinal parasite infections in cattle.

Chopra, Hitesha; Chakraborty, Sandipb; Akash, Shopnilc,; Chakraborty, Chiranjibd; Dhama, Kuldeepe, Author Information

Dear Editor, Before the advent of the era of mobiles, medical technologies were primarily known as classic devices for medical purpose viz., stents, prosthetics, implants etc. The evolution of wearables, sensors along with smart phones and systems of communication has brought revolution in clinical practice with the ability to contain tools of artificial intelligence (AI) powered in tiny sizes. Certainly, AI has brought revolution in the medical sciences and can be understood commonly as the component of computer science capable of dealing with complex problems with several applications in areas with vast data1. Intelligent AI-powered technologies in the medical field have made people enthusiastic partly due to its ability to enable a 4P’s model that indicate predictive, preventive, participatory and personalized2,3. Successful application of AI in the field of radiology, dermatology and pathology is reflected with the speed of diagnosis exceeding that of experts in the medical field. Moreover, the accuracy of diagnosis through implementation of AI technologies is very high paralleling medical experts4. Analysis of medical images viz., X-rays, ultrasounds, MRI, computerized tomography scans and dual-energy X-ray absorptiometry can be done through AI algorithms. This provides assistance to healthcare professionals for identification and diagnosis of diseases rapidly with more accuracy. Analysis of large amount of patient data can be done by AI. These data may be related to 2D/3D imaging in the medical field, bio signals (viz., electrocardiography, electroencephalography, electromyography etc), vital signs like temperature of the body, pulse rate, rate of respiration and blood pressure, information related to demography, medical history and results of laboratory test. By this way, the decision making process may be supported and provision of prediction results with accuracy is possible. The diversity of the data of patients in terms of multimodal data is a smart solution (optimal) that can facilitate diagnostic decisions in a better way on the basis of more than one finding in images, signals, representation in text form etc. By integration of more than one data sources, the diagnosticians can gain a better understanding of the health of the patient in a comprehensive manner and the underlying root causes in relation to the symptoms of the diseases can also be understood. The chances of misdiagnosis also get minimized in that way. Healthcare providers can be helped by multimodal data which help them in better diagnosis and monitoring of the progress of a clinical condition over time. This allows therapeutic management of chronic illnesses in a more effective way. By the use of medical data (multimodal), the explainable AI (XAI)-based diagnosticians can determine potential problems of health at an early stage before the condition becomes grave and threatens life of the patient. Further, Clinical Decision Support Systems (CDSSs) (AI-powered) provides assistance in real-time and ensures support to make informed decisions about care of the patient in a better way. Automation of routine tasks is possible through application of XAI tools. This frees the healthcare professionals for focusing on more complex care of patients5,6. One of the earliest applications of AI in clinical practice is the detection of atrial fibrillation at an early stage. Food and Drug Administration (FDA) has approved AliveCor in the year 2014 for their mobile application Kardia. This allows monitoring of electrocardiogram (smart phone based) and helps in detecting atrial fibrillation3. Approval of a software program had been done by the FDA in the year 2020 allowing medical professionals to perform ultrasound imaging of heart without any special training. It utilizes AI for providing real-time guidance and also has the capability of saving images of diagnostic quality. It acts as a co-pilot for the people who perform an ultrasound scan and can give instructions on the mechanisms involved in manipulating the transducer. Moreover, automated feedback on the image quality of diagnostic importance is also provided7. Several AI-based techniques viz. machine as well as deep learning models are being used by researchers for detecting the diseases of heart, skin, liver, Alzheimer’s disease, which requires early diagnosis8. Machine learning has an added value for processing of image where identification of early signs of disease through classical tools is not possible. This is especially true for cancer, the diagnosis of which frequently requires assistance of AI approaches. It is applicable for developing nations too where the resources, cost of healthcare and other shortcomings resist the provision of care optimally. FDA has given a breakthrough status to AI for an algorithm (AI-based) which has the ability of diagnosing cancer in computational histopathology with tremendous precision. This facilitates pathologist to obtain time for focusing on important slides. It is possible to develop a cost-effective point of care diagnostic for lymphoma on the basis of basic imaging along with deep learning9,10. By the application of fuzzy clustering method and neural network, successful classification and detection of people at greater risk of influenza has been done by using rate of respiration, heart rate and facial temperature. It is to be noted here that there is difference between fuzzy clustering methods and k-means clustering because of the addition of fuzzifier and membership values. Thus in contrast to the non-fuzzy clustering methods, each point can belong to more than one cluster. This in turn reflects the capability of developing efficacious methods for identification of population at risk. In more sophisticated contexts, the application of methods of machine learning can be done. For example, when support vector machine (SVM) learning algorithm, Matlab, leave one out cross-validation method, and nested one-versus-one SVM are used combinedly, the sequences of the genes of the bacteria can be separated in a better way thereby aiding in diagnosis more efficiently. Interestingly, there exists artificial immune recognition system for diagnosis of various diseases by using the properties of immune system such as immunological memory which is in line with the development of AI tools on the basis of cognitive function of human. The artificial immune recognition system that utilize supervised methods of machine learning is found to be more accurate. Another pandemic infection that puts the life of the patient at risk is malaria. Diagnosis of malaria takes much time and intervention of various health services may become essential. Development of machine learning algorithms has been done for detection of red blood cells infected with the parasite from in-line holographic microscopy (digital) data which is a relatively cost-effective technology. Various machine learning algorithms have been tried for improvement of the diagnostic capacity for malaria. Best accuracy is shown by the model trained by SVM11. In clinical practice, the application of AI for the purpose of diagnosis holds promise of further developments and has evolved rapidly in combination with other modern fields of teleconsultation and genomics. It is mandatory for the progress in science to remain extremely thorough and careful along with transparency for development of new solutions for improvement of healthcare in modern times. But it must not be forgotten that the focus of the health policies should be to tackle the financial issues in association with development of various AI tools for the progress of clinical medicine. Last but not the least, the experts in the medical field should understand in a better way to decide how exactly AI should be used for diagnosis of different diseases and illnesses. This will lead to fruitful proposals and formulating action pans in a more appropriate manner in the future for developing and exploring highly beneficial AI-based techniques in the medical field. Ethical approval No ethical approval required for these type of articles. Consent Informed consent was not required for this correspondence article. Source of funding No funding received. Author contribution S.C.: conceptualization and writing original draft. H.C.: conceptualization and writing original draft. S.A.: review and editing. C.C.: review and editing. K.D.: review and editing. Conflicts of interest disclosure Authors declare no conflict of interest. Research registration unique identifying number (UIN) Not applicable. Guarantor Shopnil Akash.

This study was conducted to investigate the effects of dietary rice brewer waste (RBW) on growth performance, nutrient utilization and nitrogen balance in growing rabbits. Thirty growing rabbits (758±25.7g initial body weight) were randomly assigned to control and four treatment groups (containing RBW) in a completely randomized design with six rabbits per group. The study lasted 6weeks for measurements of feed intake and growth performance followed by a five-day metabolic trial to determine nutrient digestibility and nitrogen balance. The five diets contained RBW at 0% RBW (control group), unsterilized RBW at 10% and 20% and sterilized RBW at 10% and 20% in the concentrates. The average daily body weight gain (ADG) in the 20% unsterilized RBW group was higher (p<0.01) than the control group. No statistically significant difference (p=0.089) of ADG was observed for the control vs. the sterilized groups, but the overall ADG was better (p=0.044) in the unsterilized RBW groups than the sterilized RBW groups. The daily dry matter intake in unsterilized and sterilized RBW groups was higher (p<0.01) than the control group. However, no difference (p=0.22) was found between the unsterilized and sterilized RBW. The feed conversion ratio (FCR) was lower for the unsterilized RBW groups vs. the control group (p=0.041), but there was no difference of FCR in the control vs. sterilized RBW groups (p=0.37) and the unsterilized RBW groups vs. unsterilized RBW groups (p=0.14). The digestibility of organic matter, crude protein and crude fibre was greater (p<0.01) in the unsterilized and sterilized RBW groups than the control group. The nitrogen balance and efficiency of nitrogen utilization were also higher in the unsterilized and sterilized RBW groups than the control group (p<0.01). The study showed that the dietary RBW could improve growth performance and nutrient utilization in growing rabbits with superior responses for the unsterilized RBW.

Agriculture is the mainstream of livelihood security in northern plains of India, however, production of all crops is below expected levels. Various studies have indicated that impact of recent technological innovations is not up to desired levels. The present study was conducted to evaluate profitability of various models in existing and intervened integrated farming system (IFS) along with acceptance of farmers in northern plains of Uttar Pradesh, India. Twenty farmers from each district viz. Barabanki and Raebareli, were monitored with all accessible records. Various interventions in their farming system were made which included new technology of rural poultry production (Model‐1), infertility control, vegetable production using our bio‐enhancer (CSR‐BIO), gladiolus, banana (G‐9 variety), guava (semi‐intensive), goat and awareness about improved composting and quality seeds. The pre‐dominant farming system with 16 families was paddy‐wheat‐fallow with benefit: cost (B: C) ratio of 1.83. This was followed by paddy‐wheat‐green gram‐bovines in 7 families with B: C ratio of 1.66. The highest B: C ratio of 4.78 was observed in model‐R i.e. vegetables cultivations on river bank due to varietal and CSRBIO interventions. The lowest B: C ratio (2.09) in post intervention period was observed in model‐O (guava‐bovine‐vegetables) due to no return from guava in first 2 years. The family annual income in the survey increased significantly. The IFS models, if introduced, are highly useful and uniform acceptance of the components takes time. From the present study, it clearly emerged that IFS gives higher B: C ratio than the existing cropping/ farming system.

Mastitis (inflammation of mammary gland) is a most devastating disease condition in terms of economic losses occurring throughout the world. The etiological agents may vary from place to place depending on climate; animal species and animal husbandry and include wide variety of gram positive and gram negative bacteria; and fungi. They may be either contagious viz. Staphylococcus aureus; Streptococcus agalactiae or environmental viz. S. dysgalactiae, S. uberis, Corynebacterium bovis and Coagulase negative Staphylococcus. Conventional diagnostic tests viz. California Mastitis Test (CMT); R-mastitest and Mast-O-test methods are applied under field conditions; whereas somatic cell count and Bulk Tank Somatic Cell Count (BTSCC) are useful for early mastitis detection and detection of sub clinical or chronic mastitis respectively. In vitro culture based diagnosis require further study as they can detect only viable cells. The advent of Polymerase Chain Reaction (PCR) technology along with its various versions like multiplex and real time PCR has improved the rapidity and sensitivity of diagnosis. Circulating micro RNA (miRNA) based diagnosis; immune assay and proteomics based detection along with biochips and biosensors prove to be asset to diagnosticians for advanced diagnosis of this economically important condition. Improvement of milking hygiene; implementation of post-milking teat disinfection; regular control of the milking equipments; implementation of milking order; Improvement of bedding material are the general measures to prevent new cases of mastitis. The use of antibiotics (intramammary infusions; bacteriocins) and herbs (Terminalia spp.) are important for prophylaxis and therapeutics. Vaccines viz. cell based; Recombinant (staphylococcal enterotoxin type C mutant) or chimeric (pauA); live (S. uberis 0140J stain based) and bacterial surface extract based; DNA-based and DNA-protein based have greatly aided in management of bovine mastitis. Quorum sensing and disease resistant breeding using novel biomarkers viz. toll like receptors (TLR) 2 and 4, interleukin (IL) 8; breast cancer type 1 susceptibility protein (BRCA1) and calcium channel voltage-dependent alpha 2/delta sub unit 1 (CACNA2D1) are also indispensable. This mini review gives an overview of all these different aspects that act as trend setters as far as the diagnosis and control of bovine mastitis is concerned to help the diagnosticians; epidemiologists and researchers not to remain ignorant about this grave condition.

Every time a drug is administered to the animal to treat an ailment, no matter whether it is acute or chronic manifestation, it usually goes together with some other prescription medicine, OTC (Over the counter) formulation, herbs or even food. All the xenobiotics such as drugs, toxins and food components as well as the endogenous compound that are formed in the animal body as a routine phenomenon exert a stimulatory or inhibitory effect on the different physiological and biochemical processes going in the body. These effects may alter the normal metabolism and/or drug transport or its efficacy drastically and thus expose the man and animals to the risk of a potentially dangerous interaction. The present review discusses these potential reactions and their mechanisms that help in navigating the hazardous combinations of drugs with other medicines, food, herbs, vitamins and minerals with confidence.