Pretreatment mortality risk prediction model in patients with polymyositis/dermatomyositis-associated interstitial lung disease.

OBJECTIVES: Risk prediction for patients with polymyositis/dermatomyositis-associated interstitial lung disease (PM/DM-ILD) is challenging due to heterogeneity in the disease course. We aimed to develop a mortality risk prediction model for PM/DM-ILD. METHODS: This prognostic study analysed patients with PM/DM-ILD admitted to Nanjing Drum Hospital from 2016 to 2021. The primary outcome was mortality within 1 year. We used a least absolute shrinkage and selection operator (LASSO) logistic regression model to identify predictive laboratory indicators. These indicators were used to create a laboratory risk score, and we developed a mortality risk prediction model by incorporating clinical factors. The evaluation of model performance encompassed discrimination, calibration, clinical utility and practical application for risk prediction and prognosis. RESULTS: Overall, 418 patients with PM/DM-ILD were enrolled and randomly divided into development (n=282) and validation (n=136) cohorts. LASSO logistic regression identified four optimal features in the development cohort, forming a laboratory risk score: C reactive protein, lactate dehydrogenase, CD3+CD4+ T cell counts and PO2/FiO2. The final prediction model integrated age, arthralgia, anti-melanoma differentiation-associated gene 5 antibody status, high-resolution CT pattern and the laboratory risk score. The prediction model exhibited robust discrimination (area under the receiver operating characteristic: 0.869, 95% CI 0.811 to 0.910), excellent calibration and valuable clinical utility. Patients were categorised into three risk groups with distinct mortality rates. The internal validation, sensitivity analyses and comparative assessments against previous models further confirmed the robustness of the prediction model. CONCLUSIONS: We developed and validated an evidence-based mortality risk prediction model with simple, readily accessible clinical variables in patients with PM/DM-ILD, which may inform clinical decision-making.

Synergistic detoxification efficiency and mechanism of triclocarban degradation by a bacterial consortium in the liver-gut-microbiota axis of zebrafish (Danio rerio).

Triclocarban (TCC), an emerging organic contaminant, poses a potential threat to human health with long-term exposure. Here, Rhodococcus rhodochrous BX2 and Pseudomonas sp. LY-1 were utilized to degrade TCC at environmental related concentrations for enhancing TCC biodegradation and investigating whether the toxicity of intermediate metabolites is lower than that of the parent compound. The results demonstrated that the bacterial consortium could degrade TCC by 82.0% within 7 days. The calculated 96 h LC50 for TCC, as well as its main degradation product 3,4-Dichloroaniline (DCA) were 0.134 mg/L and 1.318 mg/L respectively. Biodegradation also alleviated histopathological lesions induced by TCC in zebrafish liver and gut tissues. Liver transcriptome analysis revealed that biodegradation weakened differential expression of genes involved in disrupted immune regulation and lipid metabolism caused by TCC, verified through RT-qPCR analysis and measurement of related enzyme activities and protein contents. 16 S rRNA sequencing indicated that exposure to TCC led to gut microbial dysbiosis, which was efficiently improved through TCC biodegradation, resulting in decreased relative abundances of major pathogens. Overall, this study evaluated potential environmental risks associated with biodegradation of TCC and explored possible biodetoxification mechanisms, providing a theoretical foundation for efficient and harmless bioremediation of environmental pollutants.

Combining array tomography with electron tomography provides insights into leakiness of the blood-brain barrier in mouse cortex.

Like other volume electron microscopy approaches, automated tape-collecting ultramicrotomy (ATUM) enables imaging of serial sections deposited on thick plastic tapes by scanning electron microscopy (SEM). ATUM is unique in enabling hierarchical imaging and thus efficient screening for target structures, as needed for correlative light and electron microscopy. However, SEM of sections on tape can only access the section surface, thereby limiting the axial resolution to the typical size of cellular vesicles with an order of magnitude lower than the acquired xy resolution. In contrast, serial-section electron tomography (ET), a transmission electron microscopy-based approach, yields isotropic voxels at full EM resolution, but requires deposition of sections on electron-stable thin and fragile films, thus making screening of large section libraries difficult and prone to section loss. To combine the strength of both approaches, we developed 'ATUM-Tomo, a hybrid method, where sections are first reversibly attached to plastic tape via a dissolvable coating, and after screening detached and transferred to the ET-compatible thin films. As a proof-of-principle, we applied correlative ATUM-Tomo to study ultrastructural features of blood-brain barrier (BBB) leakiness around microthrombi in a mouse model of traumatic brain injury. Microthrombi and associated sites of BBB leakiness were identified by confocal imaging of injected fluorescent and electron-dense nanoparticles, then relocalized by ATUM-SEM, and finally interrogated by correlative ATUM-Tomo. Overall, our new ATUM-Tomo approach will substantially advance ultrastructural analysis of biological phenomena that require cell- and tissue-level contextualization of the finest subcellular textures.