Paratuberculosis: The Hidden Killer of Small Ruminants

Paratuberculosis (PTB) is a contagious and chronic enteric disease of ruminants and many non-ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP), and is characterised by diarrhoea and progressive emaciation with consequent serious economic losses due to death, early culling, and reduced productivity. In addition, indirect economic losses may arise from trade restrictions. Besides being a production limiting disease, PTB is a potential zoonosis; MAP has been isolated from Crohn’s disease patients and was associated with other human diseases, such as rheumatoid arthritis, Hashimoto’s thyroiditis, Type 1 diabetes, and multiple sclerosis. Paratuberculosis in sheep and goats may be globally distributed though information on the prevalence and economic impact in many developing countries seem to be scanty. Goats are more susceptible to infection than sheep and both species are likely to develop the clinical disease. Ingestion of feed and water contaminated with faeces of MAP-positive animals is the common route of infection, which then spreads horizontally and vertically. In African countries, PTB has been described as a “neglected disease”, and in small ruminants, which support the livelihood of people in rural areas and poor communities, the disease was rarely reported. Prevention and control of small ruminants’ PTB is difficult because diagnostic assays demonstrate poor sensitivity early in the disease process, in addition to the difficulties in identifying subclinically infected animals. Further studies are needed to provide more insight on molecular epidemiology, transmission, and impact on other animals or humans, socio-economic aspects, prevention and control of small ruminant PTB

Seroprevalence of Mycobacterium avium subsp. paratuberculosis in Dairy Cattle in Khartoum State, Sudan

Paratuberculosis, caused by Mycobacterium avium subspecies paratuberculosis (MAP), is a chronic wasting disease mainly of domestic and wild ruminants. It occurs worldwide, causing significant economic losses through decreased productivity, low fertility, increased cull rates and mortality. It is listed by the OIE (World Organization for Animal Health) as a disease of concern to trade in animals. Prevalence of this disease can be studied by detecting anti-MAP antibodies by Enzyme linked immunosorbent Assay (ELISA). The aim of this study was to investigate the current prevalence of MAP infection in cattle in Khartoum State. The overall apparent prevalence of MAP infection was found to be 6.3% and 18.9% at animal and herd levels, respectively. All seropositive animals were cross-bred females of good body condition; most of them (>90%) were >3 years old and >50% were from medium-sized herds in Omdurman. No significant association (p > 0.05) was found between seropositivity and animal herd size. The prevalence of MAP infection in Khartoum State is still low to medium compared to other parts of the world, but it is comparable to those reported from other African countries. Further studies with the view of designing nationwide surveys in domestic ruminants and camels in other states of the country are needed for establishing control programmes

Mycobacterium avium subsp. paratuberculosis and microbiome profile of patients in a referral gastrointestinal diseases centre in the Sudan

Mycobacterium avium subsp. paratuberculosis (MAP) causes Johne’s disease in animals with zoonotic potential; it has been linked to many chronic diseases in humans, especially gastrointestinal diseases (GID). MAP has been extensively studied in Europe and America, but little reports were published from Africa. Sudan is a unique country with close contact between humans and livestock. Despite such interaction, the one health concept is neglected in dealing with cases of humans with GID. In this study, patients admitted to the reference GID hospital in the Sudan over a period of 8 months were screened for presence of MAP in their faeces or colonic biopsies. A total of 86 patients were recruited for this study, but only 67 were screened for MAP, as 19 did not provide the necessary samples for analysis. Both real-time PCR and culture were used to detect MAP in the collected samples and the microbial diversity in patients´ faecal samples was investigated using 16S rDNA nanopore sequencing. In total, 27 (40.3%) patients were MAP positive: they were 15 males and 12 females, of ages between 21 and 80 years. Logistic regression analysis revealed no statistical significance for all tested variables in MAP positive patients (occupation, gender, contact with animal, milk consumption, chronic disease, etc.). A unique microbiome profile of MAP-positive patients in comparison to MAP-negative was found. These findings suggest that a considerable proportion of the population could be MAP infected or carriers. Therefore, increase awareness at community level is urgently needed to decrease the risk of MAP at human/animal interface. This study represents the first report of MAP in humans in the Sudan; nevertheless, a better view of the situation of MAP in humans in the country requires a larger study including patients with other conditions.Additional co-authors: Ahmad Amanzada, Kamal H. Eltom , ElSagad Eltaye

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Lessons learned and study results from HIVCore, an HIV implementation science initiative

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138261/1/jia21261.pd

Studi Penggunaan Perangkat Lunak Pengendali Biaya Proyek Pada Perusahaan Konstruksi di Makassar

Pengendalian biaya proyek yang efektif dibutuhkan untuk memberikan peringatan sedini mungkin ketika terjadi varian terhadap biaya. Sehingga tindakan perbaikan yang tepat dapat dengan cepat diambil sebelum nantinya menjadi terlambat untuk melakukan suatu tindakan. Oleh karena itu, perlunya pemanfatan perangkat lunak yang dapat membantu dalam menyediakan informasi yang dibutuhkan untuk mengendalikan biaya secara cepat dan tepat.\ud Penelitian ini dimaksudkan untuk mengidentifikasi sejauh mana penggunaan perangkat lunak dalam kegiatan pengendalian biaya proyek di Makassar. Pengambilan data dilakukan melalui penyebaran kuesioner dan wawancara kepada para responden secara individual.\ud Dari hasil penelitian ditemukan gambaran bahwa belum adanya software khusus yang digunakan dalam mendukung kegiatan pengendalian biaya proyek, karena semua responden pada perusahaan konstruksi di Makassar masih sebatas menggunakan MS. Excel, sehingga belum bisa memperoleh manfaat optimal dari penggunaan perangkat lunak

Introducing Urdu Digits Dataset with Demonstration of an Efficient and Robust Noisy Decoder-Based Pseudo Example Generator

In the present work, we propose a novel method utilizing only a decoder for generation of pseudo-examples, which has shown great success in image classification tasks. The proposed method is particularly constructive when the data are in a limited quantity used for semi-supervised learning (SSL) or few-shot learning (FSL). While most of the previous works have used an autoencoder to improve the classification performance for SSL, using a single autoencoder may generate confusing pseudo-examples that could degrade the classifier’s performance. On the other hand, various models that utilize encoder–decoder architecture for sample generation can significantly increase computational overhead. To address the issues mentioned above, we propose an efficient means of generating pseudo-examples by using only the generator (decoder) network separately for each class that has shown to be effective for both SSL and FSL. In our approach, the decoder is trained for each class sample using random noise, and multiple samples are generated using the trained decoder. Our generator-based approach outperforms previous state-of-the-art SSL and FSL approaches. In addition, we released the Urdu digits dataset consisting of 10,000 images, including 8000 training and 2000 test images collected through three different methods for purposes of diversity. Furthermore, we explored the effectiveness of our proposed method on the Urdu digits dataset by using both SSL and FSL, which demonstrated improvement of 3.04% and 1.50% in terms of average accuracy, respectively, illustrating the superiority of the proposed method compared to the current state-of-the-art models

SQL and NoSQL Database Software Architecture Performance Analysis and Assessments—A Systematic Literature Review

The competent software architecture plays a crucial role in the difficult task of big data processing for SQL and NoSQL databases. SQL databases were created to organize data and allow for horizontal expansion. NoSQL databases, on the other hand, support horizontal scalability and can efficiently process large amounts of unstructured data. Organizational needs determine which paradigm is appropriate, yet selecting the best option is not always easy. Differences in database design are what set SQL and NoSQL databases apart. Each NoSQL database type also consistently employs a mixed-model approach. Therefore, it is challenging for cloud users to transfer their data among different cloud storage services (CSPs). There are several different paradigms being monitored by the various cloud platforms (IaaS, PaaS, SaaS, and DBaaS). The purpose of this SLR is to examine the articles that address cloud data portability and interoperability, as well as the software architectures of SQL and NoSQL databases. Numerous studies comparing the capabilities of SQL and NoSQL of databases, particularly Oracle RDBMS and NoSQL Document Database (MongoDB), in terms of scale, performance, availability, consistency, and sharding, were presented as part of the state of the art. Research indicates that NoSQL databases, with their specifically tailored structures, may be the best option for big data analytics, while SQL databases are best suited for online transaction processing (OLTP) purposes