Context-aware single-cell multiomics approach identifies cell-type-specific lung cancer susceptibility genes.

Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, underlying mechanisms and target genes are largely unknown, as most risk-associated variants might regulate gene expression in a context-specific manner. Here, we generate a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Identified candidate cis-regulatory elements (cCREs) are largely cell type-specific, with 37% detected in one cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs combined with transcription factor footprinting prioritize the variants for 68% of the GWAS loci. CCV-colocalization and trait relevance score indicate that epithelial and immune cell categories, including rare cell types, contribute to lung cancer susceptibility the most. A multi-level cCRE-gene linking system identifies candidate susceptibility genes from 57% of the loci, where most loci display cell-category-specific target genes, suggesting context-specific susceptibility gene function.

Deep-learning-based segmentation of perivascular spaces on T2-Weighted 3T magnetic resonance images.

Purpose: Studying perivascular spaces (PVSs) is important for understanding the pathogenesis and pathological changes of neurological disorders. Although some methods for automated segmentation of PVSs have been proposed, most of them were based on 7T MR images that were majorly acquired in healthy young people. Notably, 7T MR imaging is rarely used in clinical practice. Herein, we propose a deep-learning-based method that enables automatic segmentation of PVSs on T2-weighted 3T MR images. Method: Twenty patients with Parkinson's disease (age range, 42-79 years) participated in this study. Specifically, we introduced a multi-scale supervised dense nested attention network designed to segment the PVSs. This model fosters progressive interactions between high-level and low-level features. Simultaneously, it utilizes multi-scale foreground content for deep supervision, aiding in refining segmentation results at various levels. Result: Our method achieved the best segmentation results compared with the four other deep-learning-based methods, achieving a dice similarity coefficient (DSC) of 0.702. The results of the visual count of the PVSs in our model correlated extremely well with the expert scoring results on the T2-weighted images (basal ganglia: rs = 0.845, P < 0.001; rs = 0.868, P < 0.001; centrum semiovale: rs = 0.845, P < 0.001; rs = 0.823, P < 0.001 for raters 1 and 2, respectively). Experimental results show that the proposed method performs well in the segmentation of PVSs. Conclusion: The proposed method can accurately segment PVSs; it will facilitate practical clinical applications and is expected to replace the method of visual counting directly on T1-weighted images or T2-weighted images.

Exploring thermophysical properties of CoCrFeNiCu high entropy alloy via molecular dynamics simulations.

High entropy alloys (HEAs) are alloys composed of five or more primary elements in equal or nearly equal proportions of atoms. In the present study, the thermophysical properties of the CoCrFeNiCu high entropy alloy (HEA) were investigated by a molecular dynamics (MD) method at nanoscale. The effects of the content of individual elements on lattice thermal conductivity k p were revealed, and the results suggested that adjusting the atomic content can be a way to control the lattice thermal conductivity of HEAs. The effects of temperature on k p were investigated quantitively, and a power-law relationship of k p with T -0.419 was suggested, which agrees with previous findings. The effects of temperature and the content of individual elements on volumetric specific heat capacity C v were also studied: as the temperature increases, the C v of all HEAs slightly decreases and then increases. The effects of atomic content on C v varied with the comprising elements. To further understand heat transfer mechanisms in the HEAs, the phonon density of states (PDOS) at different temperatures and varying atomic composition was calculated: Co and Ni elements facilitate the high-frequency vibration of phonons and the Cu environment weakens the heat transfer via low-frequency vibration of photons. As the temperature increases, the phonon mean free path (MFP) in the equiatomic CoCrFeNiCu HEA decreases, which may be attributed to the accelerated momentum of atoms and intensified collisions of phonons. The present research provides theoretical foundations for alloy design and have implications for high-performance alloy smelting.

Stearic acid alleviates aortic medial degeneration through maintaining mitochondrial dynamics homeostasis via inhibiting JNK/MAPK signaling.

Aortic dissection is characterized pathologically by aortic medial degeneration (AMD) where disturbance of mitochondrial dynamics may be involved. Stearic acid (SA) can promote mitochondrial fusion and improve mitochondrial function. Here, we established an AMD mouse model through oral administration of ß-aminopropionitrile (BAPN) and a cellular model by treating primary vascular smooth muscle cells (VSMCs) with Angiotensin-II to explore the potential role of SA in AMD. Our results showed SA reduced AMD and prolonged survival of BAPN-treated mice. Excessive mitochondrial fission was observed during AMD both in vivo and in vitro, and SA reduced mitochondrial fission and increased fusion. Additionally, SA promoted expression of contractile phenotype markers of VSMCs. At the molecular level, SA reduced AMD by inhibiting JNK/MAPK signaling. Our study suggests SA can promote mitochondrial fusion and increase the contractile phenotype of VSMCs by inhibiting JNK/MAPK signaling, thereby reducing AMD formation and possibly the consequent risk of aortic dissection.

Genomic profiling and immune phenotyping of neuroendocrine bladder cancer.

PURPOSE: Neuroendocrine bladder cancer (NEBC) poses a formidable clinical challenge and attracts keen interests to explore immunotherapy as a viable treatment option. However, a comprehensive immunogenomic landscape has yet to be thoroughly investigated. EXPERIMENTAL DESIGN: Leveraging a long-term cohort of natural NEBC cases, we employed a multimodal approach integrating genomic (n = 19), transcriptomic (n = 3), single-cell RNA sequencing (n = 1), and immunohistochemical analyses (n = 34) to meticulously characterize the immunogenicity and immunotypes of primary NEBC tumors. Clinical, pathological, medical imaging, and treatment information was retrospectively retrieved and analyzed. RESULTS: Our study unveiled that despite a considerable mutational burden, NEBC was typically immunologically inactive, as manifested by 'immune-excluded' or 'immune-desert' microenvironment. Interestingly, a subset of mixed NEBC with concurrent urothelial bladder cancer (UBC) histology displayed an 'immune-infiltrated' phenotype with prognostic relevance. When compared to UBC, NEBC lesions were distinguished by a denser cellular composition and augmented peritumoral extracellular matrix, which might collectively impede lymphatic infiltration. As a result, single-agent immune checkpoint inhibitors demonstrated limited efficacy against NEBC, while pharmacologic immunostimulation with combination chemotherapy conferred a more favorable response. CONCLUSIONS: These new insights derived from genomic profiling and immune phenotyping pave the way for rational immunotherapeutic interventions in NEBC patients, with the potential to ultimately reduce mortality from this otherwise fatal disease.

GRADE guidance 39: using GRADE-ADOLOPMENT to adopt, adapt or create contextualized recommendations from source guidelines and evidence syntheses.

BACKGROUND AND OBJECTIVE: The Grading of Recommendations, Assessment, Development and Evaluations (GRADE)-ADOLOPMENT methodology has been widely used to adopt, adapt, or de novo develop recommendations from existing or new guideline and evidence synthesis efforts. The objective of this guidance is to refine the operationalization for applying GRADE-ADOLOPMENT. METHODS: Through iterative discussions, online meetings, and email communications, the GRADE-ADOLOPMENT project group drafted the updated guidance. We then conducted a review of handbooks of guideline-producing organizations, and a scoping review of published and planned adolopment guideline projects. The lead authors refined the existing approach based on the scoping review findings and feedback from members of the GRADE working group. We presented the revised approach to the group in November 2022 (approximately 115 people), in May 2023 (approximately 100 people), and twice in September 2023 (approximately 60 and 90 people) for approval. RESULTS: This GRADE guidance shows how to effectively and efficiently contextualize recommendations using the GRADE-ADOLOPMENT approach by doing the following: (1) showcasing alternative pathways for starting an adolopment effort; (2) elaborating on the different essential steps of this approach, such as building on existing evidence-to-decision (EtDs), when available or developing new EtDs, if necessary; and (3) providing examples from adolopment case studies to facilitate the application of the approach. We demonstrate how to use contextual evidence to make judgments about EtD criteria, and highlight the importance of making the resulting EtDs available to facilitate adolopment efforts by others. CONCLUSION: This updated GRADE guidance further operationalizes the application of GRADE-ADOLOPMENT based on over 6 years of experience. It serves to support uptake and application by end users interested in contextualizing recommendations to a local setting or specific reality in a short period of time or with limited resources.

Impact of systemic lupus erythematosus (SLE) on outcomes following aseptic and septic revision total knee arthroplasty: an analysis of the 2005-2018 nationwide inpatient sample.

Systemic lupus erythematosus (SLE) can adversely affect surgical outcomes, and the impact on revision total knee arthroplasty (TKA) outcomes is unclear. This study aimed to explore the impact of SLE on in-patient outcomes of revision TKA. The Nationwide Inpatient Sample (NIS) database from 2005 to 2018 was searched for patients aged ≥ 18 years old who received revision TKA. Patients with and without SLE were propensity score matched (PSM) at a 1:4 ratio. Associations between SLE and in-hospital outcomes were examined using regression analyses. The study included 133,054 patients, with 794 having SLE. After 1:4 PSM, data of 3,970 patients were analyzed (SLE, 794; non-SLE, 3,176). Multivariate-adjusted analyses revealed that SLE patients had a significantly higher risk of postoperative complications (adjusted odds ratio [aOR] = 1.23, 95% confidence interval [CI]: 1.05-1.44, p = 0.011), non-routine discharge (aOR = 1.22, 95% CI: 1.02-1.46, p = 0.028), major blood loss (aOR = 1.19), respiratory failure/mechanical ventilation (aOR = 1.79), acute kidney injury (AKI) (aOR = 1.47), and wound dehiscence (aOR = 2.09). SLE patients also had a longer length of hospital stay (aBeta = 0.31) and greater total hospital costs (aBeta = 6.35) compared to non-SLE patients. Among those with aseptic failure, SLE patients had a significantly higher risk of postoperative complications (aOR = 1.23) and non-routine discharge (aOR = 1.36). SLE is independently associated with worse in-hospital outcomes in patients undergoing revision TKA. This study highlights the importance of heightened vigilance and tailored perioperative management for patients undergoing major surgeries in the background of SLE. Key Points • SLE significantly increases the risk of non-routine discharge, major blood loss, respiratory failure, acute kidney injury, and wound dehiscence, in patients undergoing aseptic and septic revision TKA. • Patients with SLE experience longer hospital stays and higher hospital costs compared to those without SLE. • The study's findings highlight the necessity for healthcare providers to consider the presence of SLE as a critical factor in preoperative planning and postoperative care to improve outcomes in revision TKA patients.

Dual-modal Photoacoustic and Ultrasound Imaging: from preclinical to clinical applications.

Photoacoustic imaging is a novel biomedical imaging modality that has emerged over the recent decades. Due to the conversion of optical energy into the acoustic wave, photoacoustic imaging offers high-resolution imaging in depth beyond the optical diffusion limit. Photoacoustic imaging is frequently used in conjunction with ultrasound as a hybrid modality. The combination enables the acquisition of both optical and acoustic contrasts of tissue, providing functional, structural, molecular, and vascular information within the same field of view. In this review, we first described the principles of various photoacoustic and ultrasound imaging techniques and then classified the dual-modal imaging systems based on their preclinical and clinical imaging applications. The advantages of dual-modal imaging were thoroughly analyzed. Finally, the review ends with a critical discussion of existing developments and a look toward the future.

Early-Life Exposure to 4-Hydroxy-4'-Isopropoxydiphenylsulfone Induces Behavioral Deficits Associated with Autism Spectrum Disorders in Mice.

Exposure to bisphenol A (BPA) during gestation and lactation is considered to be a potential risk factor for autism spectrum disorder (ASD) in both humans and animals. As a novel alternative to BPA, 4-hydroxy-4'-isopropoxydiphenylsulfone (BPSIP) is frequently detected in breast milk and placental barrier systems, suggesting potential transmission from the mother to offspring and increased risk of exposure. Gestation and lactation are critical periods for central nervous system development, which are vulnerable to certain environmental pollutants. Herein, we investigated the behavioral impacts and neurobiological effects of early-life exposure to BPSIP (0.02, 0.1, and 0.5 mg/kg body weight/day) in mice offspring. Behavioral studies indicated that BPSIP exposure induced ASD-like behaviors, including elevated anxiety-related behavior and decreased spatial memory, in both male and female pups. A distinct pattern of reduced social novelty was observed only in female offspring, accompanied by significant alterations in antioxidant levels. Transcriptome analysis demonstrated that differentially expressed genes (DEGs) were mainly enriched in pathways related to behaviors and neurodevelopment, which were consistent with the observed phenotype. Besides, a decrease in the protein levels of complex IV (COX IV) across all tested populations suggests a profound impact on mitochondrial function, potentially leading to abnormal energy metabolism in individuals with autism. Additionally, changes in synaptic proteins, evidenced by alterations in synapsin 1 (SYN1) and postsynaptic density protein-95 (PSD95) levels in the cerebellum and hippocampus, support the notion of synaptic involvement. These findings suggest that BPSIP may induce sex-specific neurotoxic effects that involve oxidative stress, energy generation, and synaptic plasticity.

Customized T-time inner sampling network with uncertainty-aware data augmentation strategy for multi-annotated lesion segmentation.

Segmentation in medical images is inherently ambiguous. It is crucial to capture the uncertainty in lesion segmentations to assist cancer diagnosis and further interventions. Recent works have made great progress in generating multiple plausible segmentation results as diversified references to account for the uncertainty in lesion segmentations. However, the efficiency of existing models is limited, and the uncertainty information lying in multi-annotated datasets remains to be fully utilized. In this study, we propose a series of methods to corporately deal with the above limitation and leverage the abundant information in multi-annotated datasets: (1) Customized T-time Inner Sampling Network to promote the modeling flexibility and efficiently generate samples matching the ground-truth distribution of a number of annotators; (2) Uncertainty Degree defined for quantitatively measuring the uncertainty of each sample and the imbalance of the whole multi-annotated dataset from a brand new perspective; (3) Uncertainty-aware Data Augmentation Strategy to help probabilistic models adaptively fit samples with different ranges of uncertainty. We have evaluated each of them on both the publicly available lung nodule dataset and our in-house Liver Tumor dataset. Results show that our proposed methods achieves the overall best performance on both accuracy and efficiency, demonstrating its great potential in lesion segmentations and more downstream tasks in real clinical scenarios.

Pollution loads in the middle-lower Yangtze river by coupling water quality models with machine learning.

Pollution control and environmental protection of the Yangtze River have received major attention in China. However, modeling the river's pollution load remains challenging due to limited monitoring and unclear spatiotemporal distribution of pollution sources. Specifically, anthropogenic activities' contribution to the pollution have been underestimated in previous research. Here, we coupled a hydrodynamic-based water quality (HWQ) model with a machine learning (ML) model, namely attention-based Gated Recurrent Unit, to decipher the daily pollution loads (i.e., chemical oxygen demand, COD; total phosphorus, TP) and their sources in the Middle-Lower Yangtze River from 2014 to 2018. The coupled HWQ-ML model outperformed the standalone ML model with KGE values ranging 0.77-0.91 for COD and 0.47-0.64 for TP, while also reducing parameter uncertainty. When examining the relative contributions at the Middle Yangtze River Hankou cross-section, we observed that the main stream and tributaries, lateral anthropogenic discharges, and parameter uncertainty contributed 15, 66, and 19% to COD, and 58, 35, and 7% to TP, respectively. For the Lower Yangtze River Datong cross-section, the contributions were 6, 69, and 25% for COD and 41, 42, and 17% for TP. According to the attention weights of the coupled model, the primary drivers of lateral anthropogenic pollution sources, in descending order of importance, were temperature, date, and precipitation, reflecting seasonal pollution discharge, industrial effluent, and first flush effect and combined sewer overflows, respectively. This study emphasizes the synergy between physical modeling and machine learning, offering new insights into pollution load dynamics in the Yangtze River.

Effects of H9N2 avian influenza virus infection on metabolite content and gene expression in chick DF1 cells.

After viral infection, the virus relies on the host cell's complex metabolic and biosynthetic machinery for replication. However, the impact of avian influenza virus (AIV) on metabolites and gene expression in poultry cells remains unclear. To investigate this, we infected chicken embryo fibroblasts DF1 cells with H9N2 AIV at an MOI of 3. Our aim was to explore how H9N2 AIV alters DF1 cells metabolic pathways to facilitate its replication. We employed metabolomics and transcriptomics techniques to analyze changes in metabolite content and gene expression. Metabolomics analysis revealed a significant increase in glutathione-related metabolites, including reduced glutathione (GSH), oxidized glutathione (GSSG) and total glutathione (T-GSH) upon H9N2 AIV infection in DF1 cells. Elisa results confirmed elevated levels of GSH, GSSG, and T-GSH consistent with metabolomics findings, noting a pronounced increase in GSSG compared to GSH. Transcriptomics showed significant alterations in genes involved in glutathione synthesis and metabolism post-H9N2 infection. However, adding the glutathione synthesis inhibitor BSO exogenously significantly promoted H9N2 replication in DF1 cells. This was accompanied by increased mRNA levels of pro-inflammatory cytokines (IL-1ß, IFN-γ) and decreased mRNA levels of anti-inflammatory cytokines (TGF-ß, IL-13). BSO also reduced catalase (CAT) gene expression and inhibited its activity, leading to higher reactive oxygen species (ROS) and malondialdehyde (MDA) level in DF1 cells. qPCR results indicated decreased mRNA levels of Nrf2, NQO1, and HO-1 with BSO, ultimately increasing oxidative stress in DF1 cells. Therefore, the above results indicated that H9N2 AIV infection in DF1 cells activated the glutathione metabolic pathway to enhance the cell's self-defense mechanism against H9N2 replication. However, when GSH synthesis is inhibited within the cells, it leads to an elevated oxidative stress level, thereby promoting H9N2 replication within the cells through Nrf2/HO-1 pathway. This study provides a theoretical basis for future rational utilization of the glutathione metabolic pathway to prevent viral replication.

Unlocking synergies of drawdown operation: Multi-objective optimization of reservoir emergency storage capacity.

Optimizing reservoir drawdown operations holds significant implications for hydropower generation, water supply, and drought mitigation strategies. However, achieving multi-objective optimization in reservoir drawdown operations poses fundamental challenges, particularly considering emergency storage capacity and seasonal drought patterns. This study introduces a novel multi-objective optimization framework tailored for a mega reservoir, focusing on drawdown operations to enhance hydropower generation and water supply reliability. A drawdown operation model leveraging a multi-objective ant lion optimizer is developed to simultaneously maximize reservoir hydropower output and minimize water shortage rates. China's Three Gorges Reservoir (TGR), situated over the upper reaches of the Yangtze River, constitutes the case study, with the standard operation policy (SOP) serving as a benchmark. Results showcase the efficacy of the proposed method, with substantial improvements observed: a 10.6% increase in hydropower output, a 6.0% reduction in water shortage days, and a 9.5% decrease in minimal reservoir water release compared to SOP. This study provides robust technical and scientific bolster to optimize reservoir ESC and enhance the synergy between hydropower generation, water supply, and drought resilience. Additionally, it offers decision-makers actionable strategies that account for emergency water supply capacities. These strategies aim to support mega reservoir's resilience against extreme drought events facilitating the collaboration between modelers and policy-makers, by means of intelligent optimization and decision-making technologies.

Protocol for preparing mammalian skin samples encompassing hair follicles for spatial transcriptomics.

Spatial transcriptomics enables a single-cell resolution view of gene expression patterns in tissues, providing insight into their biological functions. However, applying this approach to the skin presents inherent challenges. Here, we present a protocol for preparing mammalian skin samples encompassing hair follicles for spatial transcriptomics. We describe steps for sample preparation, embedding, acquisition of frozen slices, RNA quality control, tissue mounting, fixation, staining, and imaging. We then detail procedures for permeabilization, reverse transcription, and cDNA collection. For complete details on the use and execution of this protocol, please refer to Chen et al.1.

Host-specific SRSF7 regulates polymerase activity and replication of influenza A virus.

Avian influenza viruses crossing the host barrier to infect humans have caused great panic in human society and seriously threatened public health. Herein, we revealed that knockdown of SRSF7 significantly down-regulated influenza virus titers and viral protein expression. We further observed for the first time that human SRSF7, but not avian SRSF7, significantly inhibited polymerase activity (PB2627E). Molecular mapping demonstrated that amino acids 206 to 228 of human SRSF7 play a decisive role in regulating the polymerase activity, which contains the amino acid motif absent in avian SRSF7. Importantly, our results illustrated that the PB2627K-encoding influenza virus induces SRSF7 protein degradation more strongly via the lysosome pathway and not via the proteasome pathway. Functional enrichment analysis of SRSF7-related KEGG pathways indicated that SRSF7 is closely related to cell growth and death. Lastly, our results showed that knocking down SRSF7 interferes with normal polymerase activity. Taken together, our results advance our understanding of interspecies transmission and our findings point out new targets for the development of drugs preventing or treating influenza virus infection.

Effectiveness and safety of Chinese herbal footbaths as an adjuvant therapy for dysmenorrhea: a systematic review and meta-analysis.

Objectives: To evaluate the effectiveness and safety of Chinese herbal footbaths (CHF) as an adjunctive therapy in managing dysmenorrhea. Methods: Ten electronic databases were searched to identify eligible randomized clinical trials (RCTs) from inception until June 2023. Outcome measurements encompassed the total effective rate, visual analog scale (VAS) score of pain intensity, Cox menstrual symptom scale (CMSS) score, symptom score, Traditional Chinese Medicine (TCM) syndrome scale, and any reported adverse events. The methodological quality of the included studies was assessed with the Cochrane collaboration tool. Review Manager 5.3 software was employed for quantitative synthesis, and funnel plots were utilized to evaluate potential reporting bias. Results: Eighteen RCTs with 1,484 dysmenorrhea patients were included. The aggregated results suggested that the adjunctive CHF could significantly ameliorate dysmenorrhea, as evident from the improved total effective rate [risk ratio (RR) 1.18, 95% confidence interval (CI): 1.12 to 1.23, P < 0.00001], VAS (MD 0.88, 95% CI: 0.68 to 1.09, P < 0.00001), CMSS (MD 3.61, 95% CI: 2.73 to 4.49, P < 0.00001), symptom score (SMD 1.09, 95% CI: 0.64 to 1.53, P < 0.00001), and TCM syndrome scale (MD 3.76, 95% CI: 2.53 to 4.99, P < 0.0001). In addition, CHF presented fewer adverse events with a better long-term effect (RR 1.34, 95% CI: 1.11 to 1.63, P < 0.01) and diminished recurrence rate (RR 0.19, 95% CI: 0.09 to 0.39, P < 0.0001). Conclusion: Current evidence implies that CHF may be an effective and safe adjunctive therapy for patients with dysmenorrhea. However, the methodological quality of the studies included was undesirable, necessitating further verification with more well-designed and high-quality multicenter RCTs. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=188256, identifier registration number.

Transcriptomic changes and gene fusions during the progression from Barrett's esophagus to esophageal adenocarcinoma.

The incidence of esophageal adenocarcinoma (EAC) has surged by 600% in recent decades, with a dismal 5-year survival rate of just 15%. Barrett's esophagus (BE), affecting about 2% of the population, raises the risk of EAC by 40-fold. Despite this, the transcriptomic changes during the BE to EAC progression remain unclear. Our study addresses this gap through comprehensive transcriptomic profiling to identify key mRNA signatures and genomic alterations, such as gene fusions. We performed RNA-sequencing on BE and EAC tissues from 8 individuals, followed by differential gene expression, pathway and network analysis, and gene fusion prediction. We identified mRNA changes during the BE-to-EAC transition and validated our results with single-cell RNA-seq datasets. We observed upregulation of keratin family members in EAC and confirmed increased levels of keratin 14 (KRT14) using immunofluorescence. More differentiated BE marker genes are downregulated during progression to EAC, suggesting undifferentiated BE subpopulations contribute to EAC. We also identified several gene fusions absent in paired BE and normal esophagus but present in EAC. Our findings are critical for the BE-to-EAC transition and have the potential to promote early diagnosis, prevention, and improved treatment strategies for EAC.

Sodium arsenite induces aggresome formation by promoting PICK1 BAR domain homodimer formation.

The aggresome is a perinuclear structure that sequesters misfolded proteins. It's implicated in various neurodegenerative diseases. The perinuclear structure enriched with PICK1 was found to be inducible by cellular stressors, colocalizing with microtubule-organizing center (MTOC) markers and ubiquitin, hence classifying it as an aggresome. Sodium arsenite but not arsenate was found to potently induce aggresome formation through an integrated stress response (ISR)-independent pathway. In HEK293T cells, under arsenite stress, PICK1 localization to the aggresome was prioritized, and formation of PICK1 homodimers was favored. Additionally, PICK1 could enhance protein entry into aggresomes. This study shows that arsenite can induce the formation of both RNA stress granules and aggresomes at the same time, and that PICK1 shows conditional localization to aggresomes, suggesting a possible involvement of PICK1 in neurodegenerative diseases. [Media: see text] [Media: see text].