Machine learning models to predict systemic inflammatory response syndrome after percutaneous nephrolithotomy.

OBJECTIVE: The objective of this study was to develop and evaluate the performance of machine learning models for predicting the possibility of systemic inflammatory response syndrome (SIRS) following percutaneous nephrolithotomy (PCNL). METHODS: We retrospectively reviewed the clinical data of 337 patients who received PCNL between May 2020 and June 2022. In our study, 80% of the data were used as the training set, and the remaining data were used as the testing set. Separate prediction models based on the six machine learning algorithms were created using the training set. The predictive performance of each machine learning model was determined by the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity using the testing set. We used coefficients to interpret the contribution of each variable to the predictive performance. RESULTS: Among the six machine learning algorithms, the support vector machine (SVM) delivered the best performance with accuracy of 0.868, AUC of 0.942 (95% CI 0.890-0.994) in the testing set. Further analysis using the SVM model showed that prealbumin contributed the most to the prediction of the outcome, followed by preoperative urine culture, systemic immune-inflammation (SII), neutrophil to lymphocyte ratio (NLR), staghorn stones, fibrinogen, operation time, preoperative urine white blood cell (WBC), preoperative urea nitrogen, hydronephrosis, stone burden, sex and preoperative lymphocyte count. CONCLUSION: Machine learning-based prediction models can accurately predict the possibility of SIRS after PCNL in advance by learning patient clinical data, and should be used to guide surgeons in clinical decision-making.

Bi-parental graph strategy to represent and analyze hybrid plant genomes.

Hybrid plants are found extensively in the wild, and they often demonstrate superior performance of complex traits over their parents and other selfing plants. This phenomenon, known as heterosis, has been extensively applied in plant breeding for decades. However, the process of decoding hybrid plant genomes has seriously lagged due to the challenges associated with genome assembly and the lack of appropriate methodologies for their subsequent representation and analysis. Here, we present the assembly and analysis of two hybrids, an intraspecific hybrid between two maize (Zea may ssp. mays) inbred lines and an interspecific hybrid between maize and its wild relative teosinte (Zea may ssp. parviglumis), utilizing a combination of PacBio High Fidelity (HiFi) sequencing and chromatin conformation capture sequencing data. The haplotypic assemblies are well-phased at chromosomal scale, successfully resolving the complex loci with extensive parental structural variations (SVs). By integrating into a bi-parental genome graph, the haplotypic assemblies can facilitate downstream short-reads-based SV calling and allele-specific gene expression analysis, demonstrating outstanding advantages over a single linear genome. Our work offers a comprehensive workflow that aims to facilitate the decoding of numerous hybrid plant genomes, particularly those with unknown or inaccessible parentage, thereby enhancing our understanding of genome evolution and heterosis.

Advancements in Scaling Up Perovskite Solar Cells: From Small-Area Devices to Large-Scale Modules.

The power conversion efficiency (PCE) of perovskite solar cells (PSCs) has exceeded those of conventional thin-film solar cell technologies, and the speed at which this increase has been achieved is unprecedented in the history of photovoltaics. Despite the significant progress achieved by PSCs at the laboratory level, their commercial prospects still face two significant challenges: scaling up in size and ensuring long-term stability. Small-area devices (~1 cm2) are typically fabricated using spin-coating. However, this approach may not be suitable for preparing the large-area (>100 cm2) substrates required for commercialization. Thus, new materials and methods must be developed to facilitate the coating of large-area PSCs. This review will discuss the development of scaling up organic-inorganic hybrid PSCs and the challenges of increasing the device area. Furthermore, it will provide an overview of the methodologies for achieving high-efficiency perovskite solar modules.

Smart Response Biomaterials for Pain Management.

The intricate nature of pain classification and mechanism constantly affects the recovery of diseases and the well-being of patients. Key medical challenges persist in devising effective pain management strategies. Therefore, a comprehensive review of relevant methods and research advancements in pain management is conducted. This overview covers the main categorization of pain and its developmental mechanism, followed by a review of pertinent research and techniques for managing pain. These techniques include commonly prescribed medications, invasive procedures, and noninvasive physical therapy methods used in rehabilitation medicine. Additionally, for the first time, a systematic summary of the utilization of responsive biomaterials in pain management is provided, encompassing their response to physical stimuli such as ultrasound, magnetic fields, electric fields, light, and temperature, as well as changes in the physiological environment like reactive oxygen species (ROS) and pH. Even though the application of responsive biomaterials in pain management remains limited and at a fundamental level, recent years have seen the examination and debate of relevant research findings. These profound discussions aim to provide trends and directions for future research in pain management.

The chloroplast genome of a subtropical tree Sassafras randaiense (Hayata) Rehder, 1920 (Lauraceae).

The complete chloroplast genome sequence of Sassafras randaiense (Hayata) Rehder, 1920, a subtropical tree in the family Lauraceae, was determined. For a better understanding of the differences between S. randaiense and S. tzumu, the complete chloroplast genome of S. randaiense was sequenced and analyzed. The complete chloroplast genome is 151,781 bp in length, consisting of a pair of inverted repeat (IR) regions of 20,114 bp, one large single-copy (LSC) region of 92,740 bp, and one small single-copy (SSC) region of 18,813 bp. The overall GC content of the complete chloroplast genome is 39.2%. Further, maximum-likelihood phylogenetic analysis was conducted using 31 complete plastome sequences, which support that S. randaiense and S. tzumu are nested among the members of Cinnamomum, suggesting that Sassafras belongs to Cinnamomum.

Iguratimod ameliorates antibody-mediated rejection after renal transplant by modulating the Th17/Treg paradigm.

BACKGROUND: Iguratimod (IGU) is widely used in clinical practice due to its stable anti-inflammatory effects. Our previous studies have confirmed that the proportion of Th17/Treg balance in patients taking IGU altered significantly. This study aims to explore the role of IGU in antibody-mediated rejection (ABMR) and its potential mechanisms. METHODS: We conducted bioinformatics analysis of sequencing data from the GEO database to analyze the abundance of immune cell infiltration in transplanted kidney tissues. In vivo, IGU was intervened in a mice secondary skin transplantation model and a mice kidney transplantation ABMR model, and histological morphology of the grafts were examined by pathological staining, while relevant indicators were determined through qRT-PCR, immunohistochemistry, and enzyme-linked immunosorbent assay, observed T cell differentiation by flow cytometry, and preliminarily assessed the immunosuppressive effect of IGU. In vitro, we established Th17 and Treg cell induction and stimulation differentiation culture systems and added IGU for intervention to explore its effects on their differentiation. RESULTS: Through bioinformatics analysis, we found that Th17 and Treg may play important roles in the occurrence and development of ABMR. In vivo, we found that IGU could effectively reduce the damage caused by ABMR to the grafts, alleviate the infiltration of inflammatory cells in the graft tissues, and reduce the deposition of C4d in the grafts. Moreover, it is also found that IGU regulated the differentiation of Th17 and Treg cells in the spleen and peripheral blood and reduced the expression of IL-17A in the grafts and serum. In addition, same changes were observed in the induction and differentiation culture system of Th17 and Treg cells in vitro after the addition of IGU. CONCLUSION: IGU can inhibit the progression of ABMR by regulating the differentiation of Th17 and Treg cells, providing novel insights for optimizing clinical immunosuppressive treatment regimens.

Src inhibition modulates AMBRA1-mediated mitophagy to counteract endothelial-to-mesenchymal transition in renal allograft fibrosis.

Chronic allograft dysfunction (CAD) poses a significant challenge in kidney transplantation, with renal vascular endothelial-to-mesenchymal transition (EndMT) playing a vital role. While renal vascular EndMT has been verified as an important contributing factor to renal allograft interstitial fibrosis/tubular atrophy in CAD patients, its underlying mechanisms remain obscure. Currently, Src activation is closely linked to organ fibrosis development. Single-cell transcriptomic analysis in clinical patients revealed that Src is a potential pivotal mediator in CAD progression. Our findings revealed a significant upregulation of Src which closely associated with EndMT in CAD patients, allogeneic kidney transplanted rats and endothelial cells lines. In vivo, Src inhibition remarkably alleviate EndMT and renal allograft interstitial fibrosis in allogeneic kidney transplanted rats. It also had a similar antifibrotic effect in two endothelial cell lines. Mechanistically, the knockout of Src resulted in an augmented AMBRA1-mediated mitophagy in endothelial cells. We demonstrate that Src knockdown upregulates AMBRA1 level and activates mitophagy by stabilizing Parkin's ubiquitination levels and mitochondrial translocation. Subsequent experiments demonstrated that the knockdown of the Parkin gene inhibited mitophagy in endothelial cells, leading to increased production of Interleukin-6, thereby inducing EndMT. Consequently, our study underscores Src as a critical mediator of renal vascular EndMT and allograft interstitial fibrosis, exerting its impact through the regulation of AMBRA1/Parkin-mediated mitophagy.

Lever-enabled milli-Newton mechanical force detection via a microbottle resonator.

We demonstrate a milli-Newton mechanical force sensor based on a whispering gallery mode microbottle resonator (MBR). A lever model is established by coupling the MBR with a tapered fiber, whose ratio of load arm to effort arm (RLE) is flexibly adjusted to enlarge the detection range. The mechanical force is induced by attaching a capillary on the MBR stem and applying the downward displacement, which deforms the MBR's radius and thus shifts the resonance wavelength. The dependence of the capillary displacement on the mechanical force is theoretically deduced and verified. Experimentally, the sensors with different RLEs are built, and the maximum sensitivity of -10.48 pm/mN with a resolution of 40 µN is obtained. The achieved detection range is 0-4 mN, which depends on the capillary displacement and RLE of the lever. With the merits of easy fabrication and flexible structure, the proposed sensor shows great potential in biomedical and structural health monitoring.

Rictor/mTORC2 signalling contributes to renal vascular endothelial-to-mesenchymal transition and renal allograft interstitial fibrosis by regulating BNIP3-mediated mitophagy.

BACKGROUND: Renal allograft interstitial fibrosis/tubular atrophy (IF/TA) constitutes the principal histopathological characteristic of chronic allograft dysfunction (CAD) in kidney-transplanted patients. While renal vascular endothelial-mesenchymal transition (EndMT) has been verified as an important contributing factor to IF/TA in CAD patients, its underlying mechanisms remain obscure. Through single-cell transcriptomic analysis, we identified Rictor as a potential pivotal mediator for EndMT. This investigation sought to elucidate the role of Rictor/mTORC2 signalling in the pathogenesis of renal allograft interstitial fibrosis and the associated mechanisms. METHODS: The influence of the Rictor/mTOR2 pathway on renal vascular EndMT and renal allograft fibrosis was investigated by cell experiments and Rictor depletion in renal allogeneic transplantation mice models. Subsequently, a series of assays were conducted to explore the underlying mechanisms of the enhanced mitophagy and the ameliorated EndMT resulting from Rictor knockout. RESULTS: Our findings revealed a significant activation of the Rictor/mTORC2 signalling in CAD patients and allogeneic kidney transplanted mice. The suppression of Rictor/mTORC2 signalling alleviated TNFα-induced EndMT in HUVECs. Moreover, Rictor knockout in endothelial cells remarkably ameliorated renal vascular EndMT and allograft interstitial fibrosis in allogeneic kidney transplanted mice. Mechanistically, Rictor knockout resulted in an augmented BNIP3-mediated mitophagy in endothelial cells. Furthermore, Rictor/mTORC2 facilitated the MARCH5-mediated degradation of BNIP3 at the K130 site through K48-linked ubiquitination, thereby regulating mitophagy activity. Subsequent experiments also demonstrated that BNIP3 knockdown nearly reversed the enhanced mitophagy and mitigated EndMT and allograft interstitial fibrosis induced by Rictor knockout. CONCLUSIONS: Consequently, our study underscores Rictor/mTORC2 signalling as a critical mediator of renal vascular EndMT and allograft interstitial fibrosis progression, exerting its impact through regulating BNIP3-mediated mitophagy. This insight unveils a potential therapeutic target for mitigating renal allograft interstitial fibrosis.

Effect of surface functional groups of polystyrene micro/nano plastics on the release of NOM from flocs during the aging process.

Currently, the hidden risk of microplastics in the coagulation process has attracted much attention. However, previous studies aimed at improving the removal efficiency of microplastics and ignored the importance of interactions between microplastics and natural organic matter (NOM). This study investigated how polystyrene micro/nano particles impact the release of NOM during the aging of flocs formed by aluminum-based coagulants Al13 and AlCl3. The results elucidated that nano-particles with small particle sizes and agglomerative states are more likely to interact with coagulants. After 7 years of floc aging, the DOC content of the nano system decreased by more than 40%, while the micron system did not change significantly. During coagulation, the benzene rings in polystyrene particles form complexes with electrophilic aluminum ions through π-bonding, creating new Al-O bonds. NOM tends to adsorb at micro/nano plastic interfaces due to hydrophobic interactions and conformational entropy. In the aging process, the structure of PS-Al13 or PS-AlCl3 flocs and the functional groups on the surface of micro/nano plastics control the absorption and release of organic matter through hydrophobic, van der Waals forces, hydration, and polymer bridging. In the system with the addition of nano plastics, several DBPs such as TCAA, DCAA, TBM, DBCM and nitrosamines were reduced by more than 50%. The reaction order of different morphological structures and surface functional groups of microplastics to Al13 and AlCl3 systems is aromatic C-H > C-OH > C-O > NH2 > aromatic CC > aliphatic C-H and C-O>H-CO> NH2 >C-OH> aliphatic C-H. The results provided a new sight to explore the effect of micro/nano plastics on the release of NOM during flocs aging.

Stress and Deformation Analysis of Prestressed Wound Composite Components with an Arch-Shaped Metal Liner.

The stress distribution in prestressed filament wound components plays a crucial role in determining the quality of these components during their operational lifespan. This article proposes a physical model to analyze the stress and deformation of prestressed wound composite components with arch-shaped sections. Drawing upon the principles of beam theory, we delve into the analysis of prestressed wound components with metal liners featuring arch-shaped sections. Our investigation revealed a noteworthy phenomenon termed the "additional bending moment effect" within prestressed wound components with arch-shaped sections. Furthermore, this study establishes a relationship between this additional bending moment and the external pressure. In addition, a 3D finite element (FE) model for prestressed wound components with arch-shaped sections incorporating metal liners was developed. The model's accuracy was validated through a comparison with prestressed wound experiments, showcasing an error margin of less than 2%. In comparison with prestressed wound components with circular cross-sections under identical load and dimensional parameters, it was observed that prestressed wound components with arch-shaped sections exhibit stress distributions in the arc segments akin to their circular counterparts, with differences not exceeding 5%. Notably, when the ratio of the straight segment length to the inner diameter of the arc segment inner is less than 4, the deformation on the symmetric plane of the arc segment in an arch-shaped component can be effectively considered as the summation of deformations in equivalent-sized arc and straight segments under identical loading conditions. This yields an equivalent physical model and a streamlined analysis and design methodology for describing the deformation characteristics of prestressed wound components with arch-shaped sections.

Deep learning techniques for imaging diagnosis and treatment of aortic aneurysm.

Objective: This study aims to review the application of deep learning techniques in the imaging diagnosis and treatment of aortic aneurysm (AA), focusing on screening, diagnosis, lesion segmentation, surgical assistance, and prognosis prediction. Methods: A comprehensive literature review was conducted, analyzing studies that utilized deep learning models such as Convolutional Neural Networks (CNNs) in various aspects of AA management. The review covered applications in screening, segmentation, surgical planning, and prognosis prediction, with a focus on how these models improve diagnosis and treatment outcomes. Results: Deep learning models demonstrated significant advancements in AA management. For screening and diagnosis, models like ResNet achieved high accuracy in identifying AA in non-contrast CT scans. In segmentation, techniques like U-Net provided precise measurements of aneurysm size and volume, crucial for surgical planning. Deep learning also assisted in surgical procedures by accurately predicting stent placement and postoperative complications. Furthermore, models were able to predict AA progression and patient prognosis with high accuracy. Conclusion: Deep learning technologies show remarkable potential in enhancing the diagnosis, treatment, and management of AA. These advancements could lead to more accurate and personalized patient care, improving outcomes in AA management.

Identification of Y‒linked biomarkers and exploration of immune infiltration of normal-appearing gray matter in multiple sclerosis by bioinformatic analysis.

Background: The knowledge of normal‒appearing cortical gray matter (NAGM) in multiple sclerosis (MS) remains unclear. In this study, we aimed to identify diagnostic biomarkers and explore the immune infiltration characteristics of NAGM in MS through bioinformatic analysis and validation in vivo. Methods: Differentially expressed genes (DEGs) were analyzed. Subsequently, the functional pathways of the DEGs were determined. After screening the overlapping DEGs of MS with two machine learning methods, the biomarkers' efficacy and the expression levels of overlapping DEGs were calculated. Quantitative reverse transcription polymerase chain reaction (qRT‒PCR) identified the robust diagnostic biomarkers. Additionally, infiltrating immune cell populations were estimated and correlated with the biomarkers. Finally, the characteristics of immune infiltration of NAGM from MS were evaluated. Results: A total of 98 DEGs were identified. They participated in sensory transduction of the olfactory system, synaptic signaling, and immune responses. Nine overlapping genes were screened by machine learning methods. After verified by ROC curve, four genes, namely HLA‒DRB1, RPS4Y1, EIF1AY and USP9Y, were screened as candidate biomarkers. The mRNA expression of RPS4Y1 and USP9Y was significantly lower in MS patients than that in the controls. They were selected as the robust diagnostic biomarkers for male MS patients. RPS4Y1 and USP9Y were both positively correlated with memory B cells. Moreover, naive CD4+ T cells and monocytes were increased in the NAGM of MS patients compared with those in controls. Conclusions: Low expressed Y‒linked genes, RPS4Y1 and USP9Y, were identified as diagnostic biomarkers for MS in male patients. The inhomogeneity of immune cells in NAGM might exacerbate intricate interplay between the CNS and the immune system in the MS.

Association of UGT1A Gene Polymorphisms with BKV Infection in Renal Transplantation Recipients.

BACKGROUND: BK virus (BKV) infection is an opportunistic infectious complication and constitutes a risk factor for premature graft failure in kidney transplantation. Our research aimed to identify associations and assess the impact of single-nucleotide polymorphisms (SNPs) on metabolism-related genes in patients who have undergone kidney transplantation with BKV infection.

Material/Methods: The DNA samples of 200 eligible kidney transplant recipients from our center, meeting the inclusion criteria, have been collected and extracted. Next-generation sequencing was used to genotype SNPs on metabolism-associated genes (CYP3A4/5/7, UGT1A4/7/8/9, UGT2B7). A general linear model (GLM) was used to identify and eliminate confounding factors that may influence the outcome events. Multiple inheritance models and haplotype analyses were utilized to identify variation loci associated with infection caused by BKV and ascertain haplotypes, respectively.

Results: A total of 141 SNPs located on metabolism-related genes were identified. After Hardy-Weinberg equilibrium (HWE) and minor allele frequency (MAF) analysis, 21 tagger SNPs were selected for further association analysis. Based on GLM results, no confounding factor was significant in predicting the incidence of BK polyomavirus-associated infection. Then, multiple inheritance model analyses revealed that the risk of BKV infection was significantly associated with rs3732218 and rs4556969. Finally, we detect significant associations between haplotype T-A-C of block 2 (rs4556969, rs3732218, rs12468274) and infection caused by BKV (P = 0.0004).

Conclusions: We found that genetic variants in the UGT1A gene confer BKV infection susceptibility after kidney transplantation.

Optimization and mechanism of the novel eco-friendly additives for solidification and stabilization of dredged sediment.

Solidification/stabilization technology is commonly used in the rehabilitation of dredged sediment due to its cost-effectiveness. However, traditional solidification/stabilization technology relies on cement, which increases the risk of soil alkalization and leads to increased CO2 emissions during cement production. To address this issue, this study proposed an innovative approach by incorporating bentonite and citrus peel powder as additives in the solidifying agent, with the aim of reducing cement usage in the dredged sediment solidification process. The research results showed that there is a significant interaction among cement, bentonite, and citrus peel powder. After response surface methodology (RSM) optimization, the optimal ratio of the cementitious mixture was determined to be 14.86 g/kg for cement, 5.85 g/kg for bentonite, and 9.31 g/kg for citrus peel powder. The unconfined compressive strength (UCS) of the solidified sediments reached 3144.84 kPa. The reaction products of the solidification materials, when mixed with sediment, facilitated adsorption, gelation, and network structure connection. Simultaneously, the leaching concentration of heavy metals was significantly decreased with five heavy metals (Zn, As, Cd, Hg, and Pb) leaching concentrations decreasing by more than 50%, which met the prescribed thresholds for green planting. This study demonstrated the ecological benefits of employing bentonite and citrus peel powder in the solidification process of dredged sediment, providing an effective solution for sediment solidification.

Knockdown of RGMA improves ischemic stroke via Reprogramming of Neuronal Metabolism.

Neuronal energy metabolism dysregulation is involved in various pathologies of Ischemia-reperfusion (I/R), yet the role of RGMA in neuronal metabolic reprogramming has not been reported. In this study, we found that RGMA expression significantly increased after I/R, and compared to control mice, mice with MCAO/R showed an increase in glycolytic metabolic products and the expression of glycolytic pathway proteins. Furthermore, RGMA levels are closely related to neuronal energy metabolism. We discovered that knockdown of RGMA can shift neuronal energy metabolism towards oxidative phosphorylation and the pentose phosphate pathway, thereby protecting mice from ischemic reperfusion injury. Mechanistically, knockdown of RGMA can downregulate PGK1 expression, reducing the increase in glycolytic flux following ischemia reperfusion. Moreover, we found that knockdown of RGMA can reduce the interaction between USP10 and PGK1, thus affecting the ubiquitination degradation of PGK1. In summary, our data suggest that RGMA may regulate neuronal energy metabolism by inhibiting the USP10-mediated deubiquitination of PGK1, thus protecting it from I/R injury. This study provides new ideas for clarifying the intrinsic mechanism of neuronal damage after I/R.

A CNN-SVR model for NO2 profile prediction based on MAX-DOAS observations: The influence of Chinese New Year overlapping the 2020 COVID-19 lockdown on vertical distributions of tropospheric NO2 in Nanjing, China.

In this study, a hybrid model, the convolutional neural network-support vector regression model, was adopted to achieve prediction of the NO2 profile in Nanjing from January 2019 to March 2021. Given the sudden decline in NO2 in February 2020, the contribution of the Coronavirus Disease-19 (COVID-19) lockdown, Chinese New Year (CNY), and meteorological conditions to the reduction of NO2 was evaluated. NO2 vertical column densities (VCDs) from January to March 2020 decreased by 59.05% and 32.81%, relative to the same period in 2019 and 2021, respectively. During the period of 2020 COVID-19, the average NO2 VCDs were 50.50% and 29.96% lower than those during the pre-lockdown and post-lockdown periods, respectively. The NO2 volume mixing ratios (VMRs) during the 2020 COVID-19 lockdown significantly decreased below 400 m. The NO2 VMRs under the different wind fields were significantly lower during the lockdown period than during the pre-lockdown period. This phenomenon could be attributed to the 2020 COVID-19 lockdown. The NO2 VMRs before and after the CNY were significantly lower in 2020 than in 2019 and 2021 in the same period, which further proves that the decrease in NO2 in February 2020 was attributed to the COVID-19 lockdown. Pollution source analysis of an NO2 pollution episode during the lockdown period showed that the polluted air mass in the Beijing-Tianjin-Hebei was transported southwards under the action of the north wind, and the subsequent unfavorable meteorological conditions (local wind speed of < 2.0 m/sec) resulted in the accumulation of pollutants.

Coalescence-Induced Jumping of Nanodroplets in a Perpendicular Electric Field: A Molecular Dynamics Study.

Coalescence-induced jumping has promised a substantial reduction in the droplet detachment size and consequently shows great potential for heat-transfer enhancement in dropwise condensation. In this work, using molecular dynamics simulations, the evolution dynamics of the liquid bridge and the jumping velocity during coalescence-induced nanodroplet jumping under a perpendicular electric field are studied for the first time to further promote jumping. It is found that using a constant electric field, the jumping performance at the small intensity is weakened owing to the continuously decreased interfacial tension. There is a critical intensity above which the electric field can considerably enhance the stretching effect with a stronger liquid-bridge impact and, hence, improve the jumping performance. For canceling the inhibition effect of the interfacial tension under the condition of the weak electric field, a square-pulsed electric field with a paused electrical effect at the expansion stage of the liquid bridge is proposed and presents an efficient nanodroplet jumping even using the weak electric field.

Prevalence of small vessel disease and incidental DWI-positive lesions in patients with aneurysmal subarachnoid hemorrhage versus intracerebral hemorrhage.

INTRODUCTION: Aneurysmal subarachnoid hemorrhage (aSAH) and intracerebral hemorrhage (ICH) are main forms of hemorrhagic stroke. Data regarding cerebral small vessel disease (SVD) burden and incidental small lesions on diffusion-weighted imaging (DWI) following aSAH are sparse. PATIENTS AND METHODS: We retrospectively analyzed a prospective cohort of aSAH and ICH patients with brain MRI within 30 days after onset from March 2015 to January 2023. White matter hyperintensity (WMH), lacune, perivascular space, cerebral microbleed (CMB), total SVD score, and incidental DWI lesions were assessed and compared between aSAH and ICH. Clinical and radiological characteristics associated with small DWI lesions in aSAH were investigated. RESULTS: We included 180 patients with aSAH (median age [IQR] 53 [47-61] years) and 299 with ICH (63 [53-73] years). DWI lesions were more common in aSAH than ICH (47.8% vs 14.4%, p < 0.001). Higher total SVD score was associated with ICH versus aSAH irrespective of hematoma location, whereas DWI lesions and strictly lobar CMBs were correlated with aSAH. Multivariable analysis showed that shorter time from onset to MRI, anterior circulation aneurysm rupture, CMB ⩾ 5, and total SVD score were associated with DWI lesions in aSAH. DISCUSSION AND CONCLUSION: Incidental DWI lesions and strictly lobar CMBs were more frequent in aSAH versus ICH whereas ICH had higher SVD burden. Incidental DWI lesions in aSAH were associated with multiple clinical and imaging factors. Longitudinal studies to investigate the dynamic change and prognostic value of the covert hemorrhagic and ischemic lesions in aSAH seem justified.