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Ferroptosis has emerged as an attractive strategy in cancer therapy. Understanding the operational networks regulating ferroptosis may unravel vulnerabilities that could be harnessed for therapeutic benefit. Using CRISPR‐activation screens in ferroptosis hypersensitive cells, we identify the selenoprotein P (SELENOP) receptor, LRP8, as a key determinant protecting MYCN ‐amplified neuroblastoma cells from ferroptosis. Genetic deletion of LRP8 leads to ferroptosis as a result of an insufficient supply of selenocysteine, which is required for the translation of the antiferroptotic selenoprotein GPX4. This dependency is caused by low expression of alternative selenium uptake pathways such as system Xc − . The identification of LRP8 as a specific vulnerability of MYCN ‐amplified neuroblastoma cells was confirmed in constitutive and inducible LRP8 knockout orthotopic xenografts. These findings disclose a yet‐unaccounted mechanism of selective ferroptosis induction that might be explored as a therapeutic strategy for high‐risk neuroblastoma and potentially other MYCN ‐amplified entities. Synopsis The low‐density lipoprotein receptor (LRP8) was identified as a critical suppressor of ferroptosis in MYCN‐amplified neuroblastoma. Blocking selenium/selenocysteine uptake mechanisms via LRP8 offers a selective strategy to induce ferroptosis and disrupt GPX4 function. Ferroptosis, a cell death modality, is gaining interest as a therapeutic approach against challenging tumors. GPX4 is crucial for suppressing ferroptosis, but suitable in vivo inhibitors are lacking, limiting translation to cancer therapies. Genome‐wide and single‐cell CRISPR‐activation screens reveal LRP8 as a critical ferroptosis suppressor in MYCN‐amplified neuroblastoma. Blocking selenium/selenocysteine uptake via LRP8 disrupts GPX4 function and selectively induces ferroptotic cell death. LRP8 dependency emerges as the result of the low system Xc − activity suggesting that targeting LRP8 could be explore in other entities such as AML and lymphoma. Graphical Abstract The low‐density lipoprotein receptor (LRP8) was identified as a critical suppressor of ferroptosis in MYCN‐amplified neuroblastoma. Blocking selenium/selenocysteine uptake mechanisms via LRP8 offers a selective strategy to induce ferroptosis and disrupt GPX4 function.

Background Leishmaniasis is a virulent parasitic infection that causes a worldwide disease burden. Most treatments have toxic side-effects and efficacy has decreased due to the emergence of resistant strains. The outlook is worsened by the absence of promising drug targets for this disease. We have taken a computational approach to the detection of new drug targets, which may become an effective strategy for the discovery of new drugs for this tropical disease. Results We have predicted the protein interaction network of Leishmania major by using three validated methods: PSIMAP, PEIMAP, and iPfam. Combining the results from these methods, we calculated a high confidence network (confidence score > 0.70) with 1,366 nodes and 33,861 interactions. We were able to predict the biological process for 263 interacting proteins by doing enrichment analysis of the clusters detected. Analyzing the topology of the network with metrics such as connectivity and betweenness centrality, we detected 142 potential drug targets after homology filtering with the human proteome. Further experiments can be done to validate these targets. Conclusion We have constructed the first protein interaction network of the Leishmania major parasite by using a computational approach. The topological analysis of the protein network enabled us to identify a set of candidate proteins that may be both (1) essential for parasite survival and (2) without human orthologs. These potential targets are promising for further experimental validation. This strategy, if validated, may augment established drug discovery methodologies, for this and possibly other tropical diseases, with a relatively low additional investment of time and resources.

Aberrant expression of MYC transcription factor family members predicts poor clinical outcome in many human cancers. Oncogenic MYC profoundly alters metabolism and mediates an antioxidant response to maintain redox balance. Here we show that MYCN induces massive lipid peroxidation on depletion of cysteine, the rate-limiting amino acid for glutathione (GSH) biosynthesis, and sensitizes cells to ferroptosis, an oxidative, non-apoptotic and iron-dependent type of cell death. The high cysteine demand of MYCN -amplified childhood neuroblastoma is met by uptake and transsulfuration. When uptake is limited, cysteine usage for protein synthesis is maintained at the expense of GSH triggering ferroptosis and potentially contributing to spontaneous tumor regression in low-risk neuroblastomas. Pharmacological inhibition of both cystine uptake and transsulfuration combined with GPX4 inactivation resulted in tumor remission in an orthotopic MYCN -amplified neuroblastoma model. These findings provide a proof of concept of combining multiple ferroptosis targets as a promising therapeutic strategy for aggressive MYCN -amplified tumors.

Aberrant expression of MYC family members predicts poor clinical outcome in many human cancers. Oncogenic MYC profoundly alters metabolism and mediates an antioxidant response to maintain redox balance. Here we show that MYC induces massive lipid peroxidation upon depletion of cysteine, the rate-limiting amino acid for glutathione biosynthesis and sensitizes cells to ferroptosis, an oxidative, non-apoptotic and iron-dependent type of cell death. In MYCN-amplified childhood neuroblastoma, MYCN mediates resistance to ferroptosis by activating transsulfuration of methionine to cysteine. MYCN may contribute to spontaneous tumor regression in low-risk neuroblastomas by promoting ferroptosis in cells with epigenetically silenced cystathionine-beta-synthase, the rate-limiting enzyme for transsulfuration. We identified enzymes and antiporter proteins crucial to ferroptotic escape, providing multiple previously unknown sites that may be acted on therapeutically. Competing Interest Statement The authors have declared no competing interest.

The discovery of new genes regulating essential biological processes has become increasingly important, and CRISPRi has emerged as a powerful tool for achieving this goal. This method has been used in many model organisms to decrease the expression of specific genes and assess their impact on phenotype. Pooled CRISPRi libraries in bacteria have been particularly useful in discovering new regulators of growth, division, and other biological processes. However, these libraries rely on the induction of dCas9 via an inducible promoter, which can be problematic due to promoter leakiness. This is a widespread phenomenon of any inducible promoter that can result in the unwanted downregulation of genes and the emergence of genetic suppressors when essential genes are knocked down. To overcome this issue, we have developed a novel strategy that eliminates dCas9 leakiness and enables reversible knockdown control using the rapamycin-dependent degron system in Bacillus subtilis. This degron system causes rapid degradation of dCas9, resulting in an almost instant reset of the system. Our results demonstrate that it is possible to achieve zero CRISPRi activity in the uninduced state and full activity in the induced state. This improved CRISPRi system will enable researchers to investigate phenotypic changes more effectively while reducing the undesirable effects of leaky expression and noise in their phenotypic data. Moreover, a rapid degradation system could serve as a tool for dynamic perturbation before compensation mechanisms or stress responses kick in. Finally, this approach can be adapted to other organisms and other promoter-inducible systems, potentially opening up strategies for tighter control of gene expression.

Leishmaniasis is a virulent parasitic infection that causes a worldwide disease burden. Most treatments have toxic side-effects and efficacy has decreased due to the emergence of resistant strains. The outlook is worsened by the absence of promising drug targets for this disease. We have taken a computational approach to the detection of new drug targets, which may become an effective strategy for the discovery of new drugs for this tropical disease. We have predicted the protein interaction network of Leishmania major by using three validated methods: PSIMAP, PEIMAP, and iPfam. Combining the results from these methods, we calculated a high confidence network (confidence score > 0.70) with 1,366 nodes and 33,861 interactions. We were able to predict the biological process for 263 interacting proteins by doing enrichment analysis of the clusters detected. Analyzing the topology of the network with metrics such as connectivity and betweenness centrality, we detected 142 potential drug targets after homology filtering with the human proteome. Further experiments can be done to validate these targets. We have constructed the first protein interaction network of the Leishmania major parasite by using a computational approach. The topological analysis of the protein network enabled us to identify a set of candidate proteins that may be both (1) essential for parasite survival and (2) without human orthologs. These potential targets are promising for further experimental validation. This strategy, if validated, may augment established drug discovery methodologies, for this and possibly other tropical diseases, with a relatively low additional investment of time and resources.

One stepping stone for reducing the maternal mortality is to identify severe maternal morbidity (SMM) using Electronic Health Records (EHRs). We aim to develop a pipeline to represent and classify the unstructured text of maternal progress notes in eight classes according to the silver labels defined by the ICD-10 codes associated with SMM. We preprocessed the text, removing protected health information (PHI) and reducing stop words. We built different pipelines to classify the SMM by the combination of six word-embeddings schemes, three different approaches for the representation of the documents (average, clustering, and principal component analysis), and five well-known machine learning classifiers. Additionally, we implemented an algorithm for typos and misspelling adjustment based on the Levenshtein distance to the Spanish Billion Word Corpus dictionary. We analyzed 43,529 documents constructed by an average of 4.15 progress notes from 22,937 patients. The pipeline with the best performance was the one that included Word2Vec, typos and spelling adjustment, document representation by PCA, and an SVM classifier. We found that it is possible to identify conditions such as miscarriage complication or hypertensive disorders from clinical notes written in Spanish, with a true positive rate higher than 0.85. This is the first approach to classify SMM from the unstructured text contained in the maternal EHRs, which can contribute to the solution of one of the most important public health problems in the world. Future works must test other representation and classification approaches to detect the risk of SMM.

To determine whether the use of Evidence to Decision (EtD) frameworks is associated to higher quality of both guidelines and individual recommendations. We identified guidelines recently published by international organizations that have methodological guidance documents for their development. Pairs of researchers independently extracted information on the use of these frameworks, appraised the quality of the guidelines using the Appraisal of Guidelines, Research and Evaluation II Instrument (AGREE-II), and assessed the clinical credibility and implementability of the recommendations with the Appraisal of Guidelines for REsearch & Evaluation Recommendations Excellence (AGREE-REX) tool. We conducted both descriptive and inferential analyses. We included 66 guidelines from 17 different countries, published in the last 5 years. Thirty guidelines (45%) used an EtD framework to formulate their recommendations. Compared to those that did not use a framework, those using an EtD framework scored higher in all domains of both AGREE-II and AGREE-REX (P < 0.05). Quality scores did not differ between the use of the The Grading of Recommendations Assessment, Development and Evaluation–EtD framework (17 guidelines) or another EtD framework (13 guidelines) (P > 0.05). The use of EtD frameworks is associated with guidelines of better quality, and more credible and transparent recommendations. Endorsement of EtD frameworks by guideline developing organizations will likely increase the quality of their guidelines.

Background: Bone Marrow Aspirate (BMA) allows the study, staging and monitoring of multiple conditions with bone marrow involvement. The BMA report is a crucial component of the post-analytical stage and significantly influences the veterinarian's understanding and decision-making process. Objective: To describe the zoographic, clinical, and quality characteristics of BMA reports, as well as the frequency of diagnoses and associated factors in dogs and cats treated at veterinary centers in Colombia from 2012 to 2023. Methods: This was a cross-sectional descriptive study. Data on zoographic and clinical variables were extracted from BMA reports and consultations; the frequency of diagnoses and associated factors were determined. Adherence to reporting quality was evaluated using established guidelines for BMA in dogs, cats, and humans. Results: A total of 135 BMA reports were reviewed from eight veterinary institutions: 116 for dogs and 19 for cats, with a mean age of 5.22 ± 3 years; 53% were males. The most common indication for BMA was anemia, alone or with other abnormalities. The least adhered-to reporting elements were puncture site (91.9%), relevant clinical data (85.2%), and morphological evaluation by cell line (52.6%). Additionally, 27.4% of the reports were excluded due to poor sample quality. The most frequent diagnosis in dogs was hypoplasia (36.1%), while in cats, it was neoplasia (40.0%). Erythroid hyperplasia and neoplasms were more prevalent in males, whereas granulocytic hypoplasia was more common in females. Conclusions: BMA as a diagnostic tool in dogs and cats in Colombia is rare. A significant proportion of samples did not meet quality criteria, and there was low adherence to reporting guidelines.

The POCUS-CA (Point-of-care ultrasound in cardiac arrest) is a diagnostic tool in the Intensive Care Unit and Emergency Department setting. The literature indicates that in the patient in a cardiorespiratory arrest it can provide information of the etiology of the arrest in patients with non-defibrillable rhythms, assess the quality of compressions during cardiopulmonary resuscitation (CPR), and define prognosis of survival according to specific findings and, thus, assist the clinician in decision-making during resuscitation. This narrative review of the literature aims to expose the usefulness of ultrasound in the setting of cardiorespiratory arrest as a tool that allows making a rapid diagnosis and making decisions about reversible causes of this entity. More studies are needed to support the evidence to make ultrasound part of the resuscitation algorithms. Teamwork during cardiopulmonary resuscitation and the inclusion of ultrasound in a multidisciplinary approach is important to achieve a favorable clinical outcome.