Chagas parasite classification in blood sample images using different machine learning architectures.

Chagas disease is a life-threatening illness mainly found in Latin America. Early identification and diagnosis of Chagas disease are critical for reducing the death rate of individuals since cures and treatments are available at the acute stage. In this work, we test and compare several deep learning classification models on smear blood sample images for the task of Chagas parasite classification. Our experiments showed that the best classification model is a deep learning architecture based on a residual network together with separable convolution blocks as feature extractors and using a support vector machine algorithm as the classifier in the final layer. This optimized model, we named Res2_SVM, with a reduced number of parameters, achieved an accuracy of [Formula: see text], precision of [Formula: see text], recall of [Formula: see text], and F1-score of [Formula: see text] on our test dataset, overcoming other machine learning models.

Can AI chatbots accurately answer patient questions regarding vasectomies?

Artificial Intelligence (AI) has revolutionized the healthcare industry. There have been limited studies assessing AI model efficacy and accuracy in urology. To our knowledge, there is a lack in research looking at one of the most common urological procedures: the vasectomy. Ten frequently asked questions regarding vasectomies were individually entered into three different AI sources (ChatGPT, Bard & Bing) using free interfaces available to consumers. The responses were critically analyzed by three urologists and graded on a scale of 1 to 4 for clarity, accuracy, and evidence-based information, with 1 being the best and 4 being the worst. ChatGPT had the best average rating per question at 1.367, followed by Bard at 2.167 and Bing at 1.800(p = 0.000083). ChatGPT was found to provide significantly more satisfactory answers than both Bard (p = 0.00005) and Bing (p = 0.03988). The difference between Bard and Bing however was found to be insignificant (p = 0.09651). Overall, our study shows that AI Chatbots may provide mostly accurate information on frequently asked questions regarding vasectomies and is a reasonable resource for patients interested in the procedure to use. ChatGPT is the most accurate and concise of the chatbots assessed.

Ocular surface itch and pain: key differences and similarities between the two sensations.

PURPOSE OF REVIEW: To review the pathophysiology and treatment of ocular itch and pain, encompassing nociceptive and neuropathic categories. RECENT FINDINGS: Ocular itch and pain are sensations that arise from activation of ocular surface polymodal nerves. Nociceptive itch, commonly comorbid with ocular pain complaints, is mainly driven by a histamine-mediated type 1 hypersensitivity reaction. Beyond topical therapy, novel drug delivery systems are being explored to improve ocular residence time of nonsteroidal anti-inflammatory drugs (NSAIDs) and antihistamines. Nociceptive ocular pain can be driven by a variety of factors. Treatment focuses on addressing the causative sources of pain. Neuropathic ocular itch and pain are driven by nerve damage and dysfunction and as such, topical and oral neuromodulation have been explored as treatments. Oral neuromodulators include alpha 2 delta ligands, tricyclic antidepressants (TCAs), and low dose naltrexone. Novel therapies are being evaluated for both modalities such as difelikefalin (κ-opioid receptor agonist) for neuropathic itch and libvatrep (transient receptor potential vanilloid 1 antagonist) for neuropathic pain. SUMMARY: Both ocular itch and pain can be driven by nociceptive and/or neuropathic mechanisms. Identifying contributors to abnormal ocular sensations is vital for precise medical care. Novel therapeutics for these conditions aim to improve patient outcomes and quality of life.

Proteomics reveal cap-dependent translation inhibitors remodel the translation machinery and translatome.

Tactical disruption of protein synthesis is an attractive therapeutic strategy, with the first-in-class eIF4A-targeting compound zotatifin in clinical evaluation for cancer and COVID-19. The full cellular impact and mechanisms of these potent molecules are undefined at a proteomic level. Here, we report mass spectrometry analysis of translational reprogramming by rocaglates, cap-dependent initiation disruptors that include zotatifin. We find effects to be far more complex than simple "translational inhibition" as currently defined. Translatome analysis by TMT-pSILAC (tandem mass tag-pulse stable isotope labeling with amino acids in cell culture mass spectrometry) reveals myriad upregulated proteins that drive hitherto unrecognized cytotoxic mechanisms, including GEF-H1-mediated anti-survival RHOA/JNK activation. Surprisingly, these responses are not replicated by eIF4A silencing, indicating a broader translational adaptation than currently understood. Translation machinery analysis by MATRIX (mass spectrometry analysis of active translation factors using ribosome density fractionation and isotopic labeling experiments) identifies rocaglate-specific dependence on specific translation factors including eEF1ε1 that drive translatome remodeling. Our proteome-level interrogation reveals that the complete cellular response to these historical "translation inhibitors" is mediated by comprehensive translational landscape remodeling.

Bcl11b prevents fatal autoimmunity by promoting Treg cell program and constraining innate lineages in Treg cells.

Regulatory T (Treg) cells are essential for peripheral tolerance and rely on the transcription factor (TF) Foxp3 for their generation and function. Several other TFs are critical for the Treg cell program. We found that mice deficient in Bcl11b TF solely in Treg cells developed fatal autoimmunity, and Bcl11b-deficient Treg cells had severely altered function. Bcl11b KO Treg cells showed decreased functional marker levels in homeostatic conditions, inflammation, and tumors. Bcl11b controlled expression of essential Treg program genes at steady state and in inflammation. Bcl11b bound to genomic regulatory regions of Treg program genes in both human and mouse Treg cells, overlapping with Foxp3 binding; these genes showed altered chromatin accessibility in the absence of Bcl11b. Additionally, Bcl11b restrained myeloid and NK cell programs in Treg cells. Our study provides new mechanistic insights on the Treg cell program and identity control, with major implications for therapies in autoimmunity and cancer.