Spatial distribution and site-specific toxicity mechanisms of 6:2 fluorotelomer sulfonic acid in clam Mactra veneriformis by integrated mass spectrometry imaging and transcriptomics.

Discussion on “Interpretable medical deep framework by logits-constraint attention guiding graph-based multi-scale fusion for Alzheimer’s disease analysis” by J. Xu, C. Yuan, X. Ma, H. Shang, X. Shi & X. Zhu. (Pattern Recognition, vol. 152, 2024”)

Machine-learning-based pattern recognition and key discharge mode diagnosis of multi-source discharge in a real switch cabinet: A perspective from optical signals

Artificial intelligence (AI) systems are rapidly transforming the workplace, performing tasks once limited to human intelligence such as decision-making, prediction, and pattern recognition. While AI adoption offers opportunities to improve productivity, it can also create new occupational hazards and alter working conditions in ways that may harm worker health, safety, and wellbeing. Despite broader and growing attention to safe and responsible AI, there is limited integration of occupational health and safety (OHS) principles into AI design and adoption decisions. This paper outlines a framework for embedding an OHS perspective throughout the AI system life cycle, from problem definition to system retirement. The framework aims to ensure that safety, fairness, and worker wellbeing are prioritized in AI. We describe key OHS goals for each phase of the AI life cycle and describe practical strategies to support implementation. These strategies include participatory co-design with workers, equitable data collection, model training and validation that identify and minimize safety risks, transparent deployment practices, and continuous monitoring and retraining guided by risk management frameworks. We emphasize collaboration among AI system developers, OHS professionals, and worker and workplace representatives, to anticipate and address emerging risks. Integrating OHS principles into the AI system life cycle not only helps prevent harm but also fosters worker trust, strengthens system reliability, and promotes sustainable technological adoption. Embedding OHS principles into AI development ensures that the technology contributes to, rather than compromises, the protection and wellbeing of workers in a changing world of work.

Inflammation plays a key role in the formation, progression, and rupture of intracranial aneurysms, leading to aneurysmal subarachnoid hemorrhage. Pathogen PPRs (pattern recognition receptors) that are activated by pathogen-derived molecules are key mediators of the innate immune response against microbes. As PPRs are activated by molecules resembling microbes, that is, pathogen-associated molecular patterns or damage-associated molecular patterns that can be of nonmicrobial origin, exposure to pathogen-associated molecular patterns and damage-associated molecular patterns may promote an excessive inflammatory response, promoting excessive cell death and tissue remodeling. We present a narrative review describing the role of PPRs, pathogen-associated molecular patterns, and damage-associated molecular patterns in the formation, progression, and eventual rupture of intracranial aneurysms, as well as in the neuronal damage caused by aneurysmal subarachnoid hemorrhage. Furthermore, we discuss putative therapeutic approaches to prevent the death and disability caused by intracranial aneurysm rupture and subsequent aneurysmal subarachnoid hemorrhage.

Scavenger receptor B1 modulates antimicrobial peptide expression and cellular immunity against bacterial infection in Ostrinia furnacalis.

Plants activate induced defences through the recognition of molecular patterns. Like pathogen-associated molecular patterns, herbivore-associated molecular patterns (HAMPs) can be recognised by cell surface pattern recognition receptors, leading to defensive transcriptional changes in host plants. Herbivore-induced defensive outputs are regulated by the circadian clock, but the underlying molecular mechanisms remain unknown. To investigate how the plant circadian clock regulates transcriptional reprogramming of a specific HAMP-induced pathway, we characterised the daytime and nighttime transcriptional response to the caterpillar-derived HAMP peptide In11 in the legume crop cowpea (Vigna unguiculata). Using diel and free-running conditions, we found that daytime In11 elicitation resulted in stronger late-induced gene expression than nighttime. Plants with a conditional arrhythmic phenotype in constant light conditions lost time-of-day gated responses to In11 treatment, and this was associated with arrhythmic expression of circadian clock core transcription factor Late Elongated Hypocotyl VuLHY1 and VuLHY2. Reporter assays with VuLHY homologues indicated that they interact with the promoter of daytime In11-induced Kunitz Trypsin Inhibitor (VuKTI) via a canonical and a polymorphic CCA1/LHY binding site (CBS), consistent with a mechanism of direct regulation by circadian clock transcription factors. This study improves our understanding of the time-dependent mechanisms that regulate herbivore-induced gene expression.

The fatal triad in pcr-negative pediatric autopsies: A focus on aspiration, occult sepsis, and underlying immune dysfunction.

Neuroinflammation is triggered by the recognition of damage-associated molecular patterns (DAMPs) by pattern recognition receptors (PRRs). Toll-like receptors (TLRs)/MyD88 is the PRR pathway that mediates inflammatory signaling. We investigated the functions of Myd88 in retinal degeneration and neuroinflammation in a mouse model of retinitis pigmentosa (RP). Rd10 mice were crossed with Myd88-/- mice to produce rd10; Myd88-/- mice. The retinal phenotype was assessed by TUNEL, hematoxylin and eosin (H&E) staining, and electroretinography. Retinal microglia were immunostained with Iba-1. Retinal mRNA profiles associated with neuroinflammation were analyzed using a NanoString Neuroinflammation panel. Myd88 deficiency increased the number of TUNEL-positive cells in the outer nuclear layer (ONL) and exacerbated ONL thinning at postnatal day 18 and 21 (P < 0.01, each). Consistent with these findings, the scotopic electroretinogram (ERG) showed lower b-wave amplitudes in rd10; Myd88-/- mice compared with rd10 mice (P < 0.01). Microglial infiltration into the outer retina showed an early but transient increase at P18, followed by a reduction at P21 in rd10; Myd88-/- mice. Retinal mRNA profiling revealed increased expression of Ifitm3 and Serpina3n, markers of astrocytic glia, in rd10; Myd88-/- mice. Immunostaining confirmed the upregulation of IFITM3 and SERPINA3N in astrocytes and Müller cells in rd10; Myd88-/- mice. Myd88 deficiency accelerates retinal degeneration in rd10 mice, accompanied by an earlier onset of microglial infiltration and altered glia-related gene expression.

Italian Society of Clinical Pathology and Laboratory Medicine (SIPMeL) guidelines on the use of autoantibody tests in the diagnosis of autoimmune liver diseases.

Addictive behaviors, including both substance use disorders and behavioral addictions, arise from complex interactions among biological, psychological, social, and environmental factors including digital ones. This review focuses on the assessment of social and psychological risk and protective factors, highlighting how artificial intelligence and machine learning approaches complement conventional qualitative and quantitative methodologies. The aim is to clarify how these tools can enhance understanding, prediction, and prevention of addictive behaviors. Recent research identifies impulsivity, emotion dysregulation, peer norms, and family functioning as central psychosocial risk factors for addictive behaviors. Protective factors - such as self-efficacy, social support, and family cohesion - moderate these risks. Conventional analyses provide foundational evidence, while ML methods (predictive machine learning, explainable artificial intelligence, reinforcement learning) now enable integration of multimodal data, detection of nonlinear patterns, and identification of latent psychosocial profiles. Emerging studies demonstrate potential for early-warning prediction and personalized intervention design. AI/ML offers unprecedented opportunities to advance addiction science by handling high-dimensional psychosocial and behavioral data. Yet, ethical, interpretative, and causal challenges persist. The most promising path forward lies in synergizing theory-driven analytics with data-driven AI approaches to achieve more precise and contextually grounded prevention and intervention strategies for addictive behaviors.

Imaging, Management, and Treatment of Orbital Trauma.

Differential transcriptomic analysis of the head kidney in Coregonus migratorius naturally infected with Dibothriocephalus dendriticus.

Acoustic emission-based interpretable unsupervised clustering for damage pattern recognition in steel-concrete hybrid structures

The tumor microenvironment is increasingly recognized as a complex ecosystem in which the intra-tumoral microbiota (comprising bacteria, fungi, viruses, etc.) plays a pivotal, underappreciated role in cancer biology. This review systematically summarizes the latest research into the origins, diversity, and functional mechanisms of intra-tumoral microbiota, emphasizing their dual roles in tumor formation, progression, and response to treatment. Using high-throughput sequencing, spatial multi-omics, and integrative bioinformatics, we identify the multifactorial origins of tumor-resident microbiota, including translocation from adjacent tissues, hematogenous dissemination, and viral genomic integration. We also examine the significant inter- and intra-tumoral microbial heterogeneity influenced by anatomical, environmental, and immunological factors, and the tissue-specific functional effects of important microbial species. We detail the mechanisms by which the intra-tumoral microbiota modulate innate and adaptive immunity through pattern recognition receptor signaling, microbial antigen presentation, and microbial metabolite production, ultimately influencing tumor microenvironment composition, immune cell dynamics, and therapeutic efficacy. Finally, we critically evaluate emerging microbiota-targeted therapeutic strategies, including engineered bacteria, antibiotics, bacteriophages, and oncolytic viruses, while outlining the technical, mechanistic, and regulatory challenges that hinder their clinical translation. Our synthesis highlights the need for rigorous multi-omics profiling, causal inference, and smart delivery systems to exploit the intra-tumoral microbiota for precision oncology. This paradigm shift offers unprecedented opportunities for personalized diagnosis and therapy, marking a new frontier in cancer research and treatment.

Edwardsiella tarda infection induces PANoptosis in gill cells of Japanese flounder Paralichthys olivaceus.

ADP-heptose/ALPK1 signaling pathway: Function, regulation, and involvement in diseases.

Transcriptome alterations induced by acute and persistent human bocavirus 1 infection in human airway epithelial cells.

Astrocytes, long considered supportive cells of the central nervous system (CNS), have critical roles in innate immunity. This Review explores immune signaling pathways in astrocytes, including pattern recognition through Toll-like receptors, nucleic acid sensors and inflammasomes. These pathways enable the detection of danger signals and initiate protective responses and endogenous innate immune functions. Downstream signaling pathways, including the interferon, NF-κB and STAT3 pathways, mediate astrocyte reactivity and drive cytokine secretion, antiviral responses, phagocytosis and many other immune functions. While these responses are crucial for CNS health, their dysregulation can contribute to chronic inflammation and neurodegeneration in conditions such as Alzheimer's disease, Parkinson's disease, multiple sclerosis and amyotrophic lateral sclerosis. Additionally, astrocytes exhibit regional heterogeneity in their immune behaviors, which may influence disease trajectories. We highlight unresolved questions regarding the immune functions of astrocytes, their interplay with professional immune cells and their dual protective and pathological roles.

Chitooligosaccharides, such as chitin, are essential components of fungal cell walls and have thus naturally been selected as microbe-associated molecular patterns detected by plants to initiate defense mechanisms. These molecules are typically recognized by the lysin motif receptor-like kinases (LysM RLKs) at the plasma membrane. While chitin perception is well elucidated in Arabidopsis thaliana and other plant species, the recognition mechanisms of its deacetylated form, chitosan, remain poorly investigated despite its use as a biocontrol strategy to protect crops against pathogens. Here, we investigated the role of the two grapevine orthologs of AtLYK4, which participate in the tripartite complex for chitin perception in A. thaliana. Using a dual approach consisting of the functional complementation of the atlyk4/5 double mutant and CRISPR-Cas9 genome editing in Vitis vinifera, we showed that VvLYK4-2 is involved in both chitosan- and chitin-induced immune responses, encompassing MAPK phosphorylation and defense gene expression. Furthermore, grapevine in vitro plantlets lacking VvLYK4-2 exhibited a significantly reduced response to chitosan while retaining a low-intensity response to chitin, potentially due to the presence of VvLYK5-1. Finally, VvLYK4-2 produced in a heterologous system showed binding to chitosan oligomers and, to a lesser extent, to chitin oligomers. These findings indicate that this pattern recognition receptor plays a crucial role in the perception of chitosan oligomers and has thus potential for selective breeding purposes. This discovery may also help to better understand the partial lack of efficacy of chitosan-based plant defense stimulants used in viticulture.