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Disseminated neoplasia (DN) is a form of cancer in bivalve molluscs that can be transmissible between individuals and in some cases across species. Neoplastic cells are highly proliferative, and infection is usually lethal. Commercially valuable bivalve species (mussels, cockles, softshell clams, and oysters) are affected by outbreaks of DN, making disease diagnosis and mitigation an important issue in ecological restoration efforts and aquaculture. Basket cockles (Clinocardiwn nuttallii) are native to the North American Pacific coast from California to Alaska. Recent concern from some Coast Salish Tribes regarding an observed long-term decline in basket cockle populations in Puget Sound. WA has increased interest in monitoring efforts and subsequent collection for aquarium-reared broodstock. Disseminated neoplasia was detected in Puget Sound basket cockle populations, delaying aquaculture efforts so that potential broodstock could be assessed for the presence of DN. This study details a minimally invasive, inexpensive, nonlethal method for high-throughput screening for DN in adult basket cockles. The hemolymph smear screening method to diagnose DN in C. nuttallii can be applied at field sites at low financial cost. Results of the hemolymph smear technique were validated against whole tissue histology, the standard method for DN diagnosis. Due to the similar cellular morphologies of DN in different bivalve species, it is proposed that hemolymph histology can likely be applied for diagnosing DN in other bivalves. KEY WORDS: disseminated neoplasia, Cltnocardiwn nuttallii, disease screening, tissue histology, basket cockle, INTRODUCTION Diverse bivalve species worldwide are susceptible to disseminated neoplasia (DN), a disease in which cancerous cells proliferate in the hemolymph--the blood-like fluid in molluscs containing a mixture of nutrients, [...]

Epithelial resident memory T (eTRM) cells serve as sentinels in barrier tissues to guard against previously encountered pathogens. How eTRM cells are generated has important implications for efforts to elicit their formation through vaccination or prevent it in autoimmune disease. Here, we show that during immune homeostasis, the cytokine transforming growth factor β (TGF-β) epigenetically conditions resting naïve CD8+ T cells and prepares them for the formation of eTRM cells in a mouse model of skin vaccination. Naïve T cell conditioning occurs in lymph nodes (LNs), but not in the spleen, through major histocompatibility complex class I-dependent interactions with peripheral tissue-derived migratory dendritic cells (DCs) and depends on DC expression of TGF-β-activating αV integrins. Thus, the preimmune T cell repertoire is actively conditioned for a specialized memory differentiation fate through signals restricted to LNs.

Background: An accurate prognostic tool is essential to aid clinical decision-making (e.g., patient triage) and to advance personalized medicine. However, such a prognostic tool is lacking for acute pancreatitis (AP). Increasingly machine learning (ML) techniques are being used to develop high-performing prognostic models in AP. However, methodologic and reporting quality has received little attention. High-quality reporting and study methodology are critical for model validity, reproducibility, and clinical implementation. In collaboration with content experts in ML methodology, we performed a systematic review critically appraising the quality of methodology and reporting of recently published ML AP prognostic models. Methods/findings: Using a validated search strategy, we identified ML AP studies from the databases MEDLINE and EMBASE published between January 2021 and December 2023. We also searched pre-print servers medRxiv, bioRxiv, and arXiv for pre-prints registered between January 2021 and December 2023. Eligibility criteria included all retrospective or prospective studies that developed or validated new or existing ML models in patients with AP that predicted an outcome following an episode of AP. Meta-analysis was considered if there was homogeneity in the study design and in the type of outcome predicted. For risk of bias (ROB) assessment, we used the Prediction Model Risk of Bias Assessment Tool. Quality of reporting was assessed using the Transparent Reporting of a Multivariable Prediction Model of Individual Prognosis or Diagnosis—Artificial Intelligence (TRIPOD+AI) statement that defines standards for 27 items that should be reported in publications using ML prognostic models. The search strategy identified 6,480 publications of which 30 met the eligibility criteria. Studies originated from China (22), the United States (4), and other (4). All 30 studies developed a new ML model and none sought to validate an existing ML model, producing a total of 39 new ML models. AP severity (23/39) or mortality (6/39) were the most common outcomes predicted. The mean area under the curve for all models and endpoints was 0.91 (SD 0.08). The ROB was high for at least one domain in all 39 models, particularly for the analysis domain (37/39 models). Steps were not taken to minimize over-optimistic model performance in 27/39 models. Due to heterogeneity in the study design and in how the outcomes were defined and determined, meta-analysis was not performed. Studies reported on only 15/27 items from TRIPOD+AI standards, with only 7/30 justifying sample size and 13/30 assessing data quality. Other reporting deficiencies included omissions regarding human–AI interaction (28/30), handling low-quality or incomplete data in practice (27/30), sharing analytical codes (25/30), study protocols (25/30), and reporting source data (19/30). Conclusions: There are significant deficiencies in the methodology and reporting of recently published ML based prognostic models in AP patients. These undermine the validity, reproducibility, and implementation of these prognostic models despite their promise of superior predictive accuracy. Registration: Research Registry (reviewregistry1727) Author summary: Why was this study done?: Acute pancreatitis is a common gastrointestinal disorder that affects a million patients worldwide annually and has an extremely variable disease course. Using artificial intelligence (AI), many researchers have developed prediction tools to help forecast acute pancreatitis (AP) patients' course (e.g., tool to predict who will develop a more severe form of disease). Before using AI-based prediction tools to care for patients, it is extremely important to appraise the study design and conduct of the studies that produced the tools to ensure that the tools will not lead to misleading results and worse yet, widen health disparities. What did the researchers do and find?: We conducted a comprehensive assessment of all the published and unpublished AI models for AP patients in the past 3 years by searching all the major medical databases. We focused on appraising the quality of the methods and whether the model-building project was transparently reported from start to finish, using established quality standards. Unfortunately, almost all studies omitted taking steps to ensure that AI model will not discriminate against certain populations. Most studies did not take steps to avoid misleadingly optimistic results. Many studies did not provide enough information about how the prediction tool was built, their research methods. For example, only 15 out of 27 key reporting items were included in the paper. What do these findings mean?: The AI prediction tools used to predict outcomes for AP patients have significant flaws in how they are designed and reported so they are not ready to be implemented into clinical care. Concerted efforts are needed to improve the quality of the study design, conduct of the study, and reporting of the studies so clinically useful and accurate AI prediction tools can be built and used. Patient and stakeholder engagement to inform study design and interdisciplinary collaboration between data scientists, clinicians, and content experts are top priorities for future research in this area. Brian Critelli, Amier Hassan and colleagues systematically review studies published in 2021-2023 that use machine learning to develop prognostic models in acute pancreatitis and critically appraise the quality of methodology and reporting therein. [ABSTRACT FROM AUTHOR]

Background Following endoscopic retrograde cholangiopancreatography (ERCP), post-ERCP pancreatitis (PEP) is the most common complication. The host's innate immune response to periprocedural pancreatic injury is the hallmark of its pathogenesis. Investigating cytokine signatures associated with PEP and its risk factors can guide understanding of PEP immunopathogenesis. Methods We conducted a single-center, prospective, observational pilot study in adults at high-risk for PEP. Seven serum cytokines relevant to early acute pancreatitis pathogenesis, angiopoietin-2, hepatocyte growth factor (HGF), interleukin-6 (IL-6), IL-8, monocyte chemotactic protein-1, resistin, and soluble tumor necrosis factor-a receptor 1, were measured in sera collected 2 h pre- and post-ERCP. Levels were compared among healthy controls and ERCP participants who either did or did not develop PEP. Heat maps were constructed to perform a multidimensional exploratory analysis that aimed to determine the cytokine signatures associated with PEP and its participant-related risk factors (female sex, young age, and obesity). Results A total of 65 participants were enrolled (36 undergoing ERCP and 29 healthy controls). Eight of the 36 (22.2%) ERCP participants developed PEP. Baseline IL-8 levels measured before ERCP were elevated in participants who developed PEP (7.5 vs. 14.8 pg/mL, P=0.02), and most strongly upregulated in women under 40 years of age. HGF levels post-ERCP were higher in participants with PEP (738.0 vs. 556.6 pg/mL, P=0.04), and most strongly upregulated in obese participants. Conclusions Pre-ERCP IL-8 and post-ERCP HGF are associated with the development of PEP. Findings from this pilot study can inform the design of translational work in the immunopathogenesis of PEP. [ABSTRACT FROM AUTHOR]

Myofibroblasts are the major source of extracellular matrix components that accumulate during tissue fibrosis, and hepatic stellate cells (HSCs) are believed to be the major source of myofibroblasts in the liver. To date, robust systems to genetically manipulate these cells have not been developed. We report that Cre under control of the promoter of Pdgfrb (Pdgfrb-Cre) inactivates loxP-flanked genes in mouse HSCs with high efficiency. We used this system to delete the gene encoding α(v) integrin subunit because various α(v)-containing integrins have been suggested as central mediators of fibrosis in multiple organs. Such depletion protected mice from carbon tetrachloride-induced hepatic fibrosis, whereas global loss of β₃, β₅ or β₆ integrins or conditional loss of β₈ integrins in HSCs did not. We also found that Pdgfrb-Cre effectively targeted myofibroblasts in multiple organs, and depletion of the α(v) integrin subunit using this system was protective in other models of organ fibrosis, including pulmonary and renal fibrosis. Pharmacological blockade of α(v)-containing integrins by a small molecule (CWHM 12) attenuated both liver and lung fibrosis, including in a therapeutic manner. These data identify a core pathway that regulates fibrosis and suggest that pharmacological targeting of all α(v) integrins may have clinical utility in the treatment of patients with a broad range of fibrotic diseases.

Pore-forming toxins (PFTs) are the largest class of bacterial toxins and contribute to virulence by triggering host cell death. Vertebrates also express endogenous pore-forming proteins that induce cell death as part of host defense. To mitigate damage and promote survival, cells mobilize membrane repair mechanisms to neutralize and counteract pores, but how these pathways are activated is poorly understood. Here, we use a transposon-based gene activation screen to discover pathways that counteract the cytotoxicity of the archetypal PFT Staphylococcus aureus α-toxin. We identify the endolysosomal protein LITAF as a mediator of cellular resistance to PFT-induced cell death that is active against both bacterial toxins and the endogenous pore, gasdermin D, a terminal effector of pyroptosis. Activation of the ubiquitin ligase NEDD4 by potassium efflux mobilizes LITAF to recruit the endosomal sorting complexes required for transport (ESCRT) machinery to repair damaged membrane. Cells lacking LITAF, or carrying naturally occurring disease-associated mutations of LITAF, are highly susceptible to pore-induced death. Notably, LITAF-mediated repair occurs at endosomal membranes, resulting in expulsion of damaged membranes as exosomes, rather than through direct excision of pores from the surface plasma membrane. These results identify LITAF as a key effector that links sensing of cellular damage to repair. Editor's summary: Membrane pores caused by bacterial pore-forming toxins (PFTs) or endogenous pore-forming proteins can trigger cell death. Membrane repair machinery can promote cell survival and resistance to PFTs, but the cellular mechanisms underlying defense against these toxins are not well defined. Stefani et al. performed a transposon mutagenesis screen to identify genes involved in resistance to Staphylococcus aureus α-toxin–induced cell death. They identified that LITAF, an endolysosomal protein, was required for cell survival after α-toxin– and gasdermin D–induced cell death. K+ efflux through membrane pores promoted LITAF localization to endosomes containing α-toxin and initiated assembly of ESCRT machinery, resulting in secretion of damaged membrane in exosomes. This work uncovers a key role for LITAF in sensing plasma membrane damage and activating membrane repair machinery. —Hannah Isles [ABSTRACT FROM AUTHOR]

Aims αv integrins are implicated in fibrosis in a number of organs through their ability to activate TGF-β. However their role in vascular fibrosis and collagen accumulation is only partially understood. Here we have used αv conditional knockout mice and cell lines to determine how αv contributes to vascular smooth muscle cell (VSMC) function in vascular fibrosis and the role of TGF-β in that process. Methods and results Angiotensin II (Ang II) treatment causes upregulation of αv and β3 expression in the vessel wall, associated with increased collagen deposition. We found that deletion of αv integrin subunit from VSMCs (αvSMKO) protected mice against angiotensin II-induced collagen production and assembly. Transcriptomic analysis of the vessel wall in αvSMKO mice and controls identified a significant reduction in expression of fibrosis and related genes in αvSMKO mice. In contrast, αvSMKO mice showed prolonged expression of CD109, which is known to affect TGF-β signalling. Using cultured mouse and human VSMCs, we showed that overexpression of CD109 phenocopied knockdown of αv integrin, attenuating collagen expression, TGF-β activation, and Smad2/3 signalling in response to angiotensin II or TGF-β stimulation. CD109 and TGF-β receptor were internalized in early endosomes. Conclusion We identify a role for VSMC αv integrin in vascular fibrosis and show that αv acts in concert with CD109 to regulate TGF-β signalling. [ABSTRACT FROM AUTHOR]