Cattle Identification Using Muzzle Images and Deep Learning Techniques

Traditional animal identification methods such as ear-tagging, ear notching, and branding have been effective but pose risks to the animal and have scalability issues. Electrical methods offer better tracking and monitoring but require specialized equipment and are susceptible to attacks. Biometric identification using time-immutable dermatoglyphic features such as muzzle prints and iris patterns is a promising solution. This project explores cattle identification using 4923 muzzle images collected from 268 beef cattle. Two deep learning classification models are implemented - wide ResNet50 and VGG16\_BN and image compression is done to lower the image quality and adapt the models to work for the African context. From the experiments run, a maximum accuracy of 99.5\% is achieved while using the wide ResNet50 model with a compression retaining 25\% of the original image. From the study, it is noted that the time required by the models to train and converge as well as recognition time are dependent on the machine used to run the model.Comment: 8 pages, 4 figures, 2 table

Expanding the Grading of Recommendations Assessment, Development, and Evaluation (Ex-GRADE) for Evidence-Based Clinical Recommendations: Validation Study

Clinicians use general practice guidelines as a source of support for their intervention, but how much confidence should they place on these recommendations? How much confidence should patients place on these recommendations? Various instruments are available to assess the quality of evidence of research, such as the revised Wong scale (R-Wong) which examines the quality of research design, methodology and data analysis, and the revision of the assessment of multiple systematic reviews (R-AMSTAR), which examines the quality of systematic reviews

MasakhaNEWS:News Topic Classification for African languages

African languages are severely under-represented in NLP research due to lack of datasets covering several NLP tasks. While there are individual language specific datasets that are being expanded to different tasks, only a handful of NLP tasks (e.g. named entity recognition and machine translation) have standardized benchmark datasets covering several geographical and typologically-diverse African languages. In this paper, we develop MasakhaNEWS -- a new benchmark dataset for news topic classification covering 16 languages widely spoken in Africa. We provide an evaluation of baseline models by training classical machine learning models and fine-tuning several language models. Furthermore, we explore several alternatives to full fine-tuning of language models that are better suited for zero-shot and few-shot learning such as cross-lingual parameter-efficient fine-tuning (like MAD-X), pattern exploiting training (PET), prompting language models (like ChatGPT), and prompt-free sentence transformer fine-tuning (SetFit and Cohere Embedding API). Our evaluation in zero-shot setting shows the potential of prompting ChatGPT for news topic classification in low-resource African languages, achieving an average performance of 70 F1 points without leveraging additional supervision like MAD-X. In few-shot setting, we show that with as little as 10 examples per label, we achieved more than 90\% (i.e. 86.0 F1 points) of the performance of full supervised training (92.6 F1 points) leveraging the PET approach

Actin inhibition increases megakaryocyte proplatelet formation through an apoptosis-dependent mechanism.

BACKGROUND:Megakaryocytes assemble and release platelets through the extension of proplatelet processes, which are cytoplasmic extensions that extrude from the megakaryocyte and form platelets at their tips. Proplatelet formation and platelet release are complex processes that require a combination of structural rearrangements. While the signals that trigger the initiation of proplatelet formation process are not completely understood, it has been shown that inhibition of cytoskeletal signaling in mature megakaryocytes induces proplatelet formation. Megakaryocyte apoptosis may also be involved in initiation of proplatelet extension, although this is controversial. This study inquires whether the proplatelet production induced by cytoskeletal signaling inhibition is dependent on activation of apoptosis. METHODS:Megakaryocytes derived from human umbilical cord blood CD34+ cells were treated with the actin polymerization inhibitor latrunculin and their ploidy and proplatelet formation were quantitated. Apoptosis activation was analyzed by flow cytometry and luminescence assays. Caspase activity was inhibited by two compounds, ZVAD and QVD. Expression levels of pro-survival and pro-apoptosis genes were measured by quantitative RT-PCR. Protein levels of Bcl-XL, Bax and Bak were measured by western blot. Cell ultrastructure was analyzed by electron microscopy. RESULTS:Actin inhibition resulted in increased ploidy and increased proplatelet formation in cultured umbilical cord blood-derived megakaryocytes. Actin inhibition activated apoptosis in the cultured cells. The effects of actin inhibition on proplatelet formation were blocked by caspase inhibition. Increased expression of both pro-apoptotic and pro-survival genes was observed. Pro-survival protein (Bcl-xL) levels were increased compared to levels of pro-apoptotic proteins Bak and Bax. Despite apoptosis being activated, the megakaryocytes underwent minimal ultrastructural changes during actin inhibition. CONCLUSIONS:We report a correlation between increased proplatelet formation and activation of apoptosis, and that the increase in proplatelet formation in response to actin inhibition is caspase dependent. These findings support a role for apoptosis in proplatelet formation in this model

Megakaryocyte ultrastructure showing early signs of apoptosis in actin polymerization inhibitor treated megakaryocytes, such as enlarged peripheral margin with concentration of granules towards the center of the cell and more frequently displayed cytoplasmic blebbing.

<p>A) Untreated control B) Actin polymerization inhibitor treated.</p

Actin polymerization inhibitor (Latrunculin) treatment does not affect proplatelet formation and platelet structure.

<p>A) Preplatelet-like cell protrusions stained with β- tubulin and showing characteristic circumferential loops of microtubules. B) Caspase inhibition with ZVAD-FMK or Q-VD-OPH inhibits proplatelet formation from actin polymerization inhibitor treated megakaryocytes. Y-axis represents the sum of all proplatelet (PP) segments counted inside of grids in 10 random field images (40x magnification). C,D) Light microscopy images showing decreased proplatelet formation after caspase inhibitor treatment: C) Actin polymerization inhibitor treated D) ZVAD-FMK E) Q-VD-OPH. * p<0.05</p

Actin inhibitor (Latrunculin) induces apoptosis activation in cultured megakaryocytes.

<p>A) FACS analysis of apoptosis activation by measuring Mitochondrial Outer Membrane Potential (MOMP) and phosphatidyl serine (PS) externalization B) Luminescence activity measuring Caspase 3 and 7 activity were measured using Caspase-Glo 3/7 Assay. Actin inhibition induces overexpression of both pro-apoptotic and pro-survival genes and increases BCL-XL protein synthesis C) RT-PCR analysis of mRNA expression of pro-apoptotic genes: BAX, BAK, BNIP3 and BNIP3L and pro-survival genes: BCL-2, BCL-XL, IGF1R and CFLAR relative to untreated control. BCL-XL protein showed increased synthesis with actin polymerization inhibitor treatment D) Western Blot (density ratio = 1.34 compared to untreated control) and E) Intracellular protein quantification with FACS. * p<0.05; ** p<0.005</p

Actin polymerization inhibitor (Latrunculin) increases megakaryocyte maturation and proplatelet formation.

<p>A,B) FACS profiles of propidium iodide staining indicating ploidy of control (A) and latrunculin treated (B) cells. C) Actin inhibition increases the levels of polyploid megakaryocytes in culture. Y axis represents the % of cells with ploidy ≥8N. D,E) Wright-Giemsa stained megakaryocytes showing increased polyploidization with actin-inhibitor treatement: D) Untreated control E) Actin polymerization inhibitor treated. F) Actin inhibition increases the levels of megakaryocytes proplatelet formation in culture. Y-axis represents the sum of all proplatelet (PP) segments counted inside of grids in 10 random field images (40x magnification). G,H) Light microscopy images showing increased proplatelet formation after actin polymerization inhibitor treatment: G) Untreated control H) Actin polymerization inhibitor treated. * p<0.05</p