Mikulicz's disease combined with IgG4-related hypophysitis: a case report.

BACKGROUND: IgG4-related diseases are very uncommon, and its diagnosis and treatment are complicated as it encompasses multiple disciplines. CASE PRESENTATION: A 77-year-old woman was admitted with a jaw mass and nausea and vomiting. Laboratory tests showed elevated serum IgG4, pituitary MRI suggested thickening of the pituitary stalk, and head and neck CT suggested orbital and mandibular masses. Patients with mandibular mass were diagnosed with Mikulicz's disease with IgG4-related hypophysitis. We found no other evidence of causing thickening of the pituitary stalk. She was given oral prednisolone 30 mg daily, and her nausea and vomiting improved significantly, and the mandibular and ocular masses decreased in size. CONCLUSION: Mikulicz's disease combined with IgG4-related hypophysitis is a rare case of IgG4-RD in elderly women. IgG4-RD is one of the causes of head and neck exocrine gland mass and pituitary stalk thickening in the elderly.

Sleep Pattern, Genetic Susceptibility, and Abdominal Aortic Aneurysm in UK Biobank Participants: Large-Scale Cohort Study.

Background: Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality. Objectives: The authors aimed to explore the associations between sleep patterns and genetic susceptibility to AAA. Methods: We included 344,855 UK Biobank study participants free of AAA at baseline. A sleep pattern was defined by chronotype, sleep duration, insomnia, snoring, and daytime sleepiness, and an overall sleep score was constructed with a range from 0 to 5, where a high score denotes a healthy sleep pattern. Polygenic risk score based on 22 single nucleotide polymorphisms was categorized into tertiles and used to evaluate the genetic risk for AAA. Cox proportional hazards regression models were used to assess the association between sleep, genetic factors, and the incidence of AAA. Results: During a median of 12.59 years of follow-up, 1,622 incident AAA cases were identified. The HR per 1-point increase in the sleep score was 0.91 (95% CI: 0.86-0.96) for AAA. Unhealthy sleep patterns, defined as a sleep score ranging from 0 to 3, were found to be associated with a higher risk of AAA for the intermediate (HR: 1.18, 95% CI: 1.06-1.31) and poor sleep patterns (HR: 1.40, 95% CI: 1.13-1.73), respectively, compared to the healthy pattern. Participants with poor sleep patterns and high genetic risks had a 2.5-fold higher risk of AAA than those with healthy sleep patterns and low genetic risk. Conclusions: In this large prospective study, healthy sleep patterns were associated with a lower risk of AAA among participants with low, intermediate, or high genetic risk.

Evidence of microbiota-host dysbiosis between periodontitis and cerebral small vessel disease.

OBJECTIVES: To investigate the correlation between periodontitis and cerebral small vessel disease (CSVD) from the clinical and microbiological aspects. SUBJECTS AND METHODS: Periodontitis patients (CP group, n = 31) and CSVD patients (CSVD group, n = 30) were examined for neurological and periodontal condition. Subgingival plaque was collected and performed using 16S rRNA sequencing. Logistic regression and LASSO regression were used to analyze the periodontal parameters and subgingival microbiota related to CSVD, respectively. Inflammatory factors in gingival crevicular fluid (GCF) were also detected and compared between the two groups. RESULTS: Clinical attachment level (CAL), teeth number and plaque index demonstrated a significant difference between CP and CSVD group, meanwhile, CAL was independently associated with CSVD. Besides, the microbial richness and composition were distinct between two groups. Five genera related to periodontal pathogens (Treponema, Prevotella, Streptococcus, Fusobacterium, Porphyromonas) were screened out by LASSO regression, suggesting a potential association with CSVD. Finally, the levels of inflammatory factors in GCF were statistically higher in CSVD group than those in CP group. CONCLUSIONS: Cerebral small vessel disease patients demonstrated worse periodontal condition, meanwhile the interaction between microbiota dysbiosis and host factors (inflammation) leading to a better understanding of the association between periodontitis and CSVD.

An efficient molten steel slag gas quenching process: Integrating carbon solidification and waste heat recovery.

The iron and steel-making industries have garnered significant attention in research related to low-carbon transitions and the reuse of steel slag. This industry is known for its high carbon emissions and the substantial amount of steel slag it generates. To address these challenges, a waste heat recovery process route has been developed for molten steel slag, which integrates CO2 capture and fixation as well as efficient utilization of steel slag. This process involves the use of lime kiln flue gas from the steel plant as the gas quenching agent, thereby mitigating carbon emissions and facilitating carbonation conversion of steel slag while simultaneously recovering waste heat. The established carbonation model of steel slag reveals that the insufficient diffusion of CO2 gas molecules within the product layer is the underlying mechanism hindering the carbonation performance of steel slag. This finding forms the basis for enhancing the carbonation performance of steel slag. The results of Aspen Plus simulation indicate that 1 t of steel slag (with a carbonation conversion rate of 15.169 %) can fix 55.19 kg of CO2, process 6.08 kmol of flue gas (with a carbon capture rate of 92.733 %), and recover 2.04 GJ of heat, 0.43 GJ of exergy, and 0.68 MWh of operating cost. These findings contribute to the development of sustainable and efficient solutions for steel slag management, with potential applications in the steel production industry and other relevant fields.

Computer vision models enable mixed linear modeling to predict arbuscular mycorrhizal fungal colonization using fungal morphology.

The presence of Arbuscular Mycorrhizal Fungi (AMF) in vascular land plant roots is one of the most ancient of symbioses supporting nitrogen and phosphorus exchange for photosynthetically derived carbon. Here we provide a multi-scale modeling approach to predict AMF colonization of a worldwide crop from a Recombinant Inbred Line (RIL) population derived from Sorghum bicolor and S. propinquum. The high-throughput phenotyping methods of fungal structures here rely on a Mask Region-based Convolutional Neural Network (Mask R-CNN) in computer vision for pixel-wise fungal structure segmentations and mixed linear models to explore the relations of AMF colonization, root niche, and fungal structure allocation. Models proposed capture over 95% of the variation in AMF colonization as a function of root niche and relative abundance of fungal structures in each plant. Arbuscule allocation is a significant predictor of AMF colonization among sibling plants. Arbuscules and extraradical hyphae implicated in nutrient exchange predict highest AMF colonization in the top root section. Our work demonstrates that deep learning can be used by the community for the high-throughput phenotyping of AMF in plant roots. Mixed linear modeling provides a framework for testing hypotheses about AMF colonization phenotypes as a function of root niche and fungal structure allocations.

Analysis of the differences in physicochemical properties, volatile compounds, and microbial community structure of pit mud in different time spaces.

Pit mud (PM) is among the key factors determining the quality of Nongxiangxing baijiu, a Chinese liquor. Microorganisms present inside PM are crucial for the unique taste and flavor of this liquor. In this study, headspace solid-phase microextraction was used in combination with gas chromatography and high-throughput sequencing to determine the volatile compounds and microbial community structure of 10- and 40-year PM samples from different spaces. The basic physicochemical properties of the PM were also determined. LEfSe and RDA were used to systematically study the PM in different time spaces. The physicochemical properties and ester content of the 40-year PM were higher than those of the 10-year PM, but the spatial distribution of the two years PM samples exhibited no consistency, except in terms of pH, available phosphorus content, and ester content. In all samples, 29 phyla, 276 families, and 540 genera of bacteria, including four dominant phyla and 20 dominant genera, as well as eight phyla, 24 families, and 34 genera of archaea, including four dominant phyla and seven dominant genera, were identified. The LEfSe analysis yielded 18 differential bacteria and five differential archaea. According to the RDA, the physicochemical properties and ethyl caproate, ethyl octanoate, hexanoic acid, and octanoic acid positively correlated with the differential microorganisms of the 40-year PM, whereas negatively correlated with the differential microorganisms of the 10-year PM. Thus, we inferred that Caproiciproducens, norank_f__Caloramatoraceae, and Methanobrevibacter play a dominant and indispensable role in the PM. This study systematically unveils the differences that affect the quality of PM in different time spaces and offers a theoretical basis for improving the declining PM, promoting PM aging, maintaining cellars, and cultivating an artificial PM at a later stage.

Anomaly Detection Method for Lithium-Ion Battery Cells Based on Time Series Decomposition and Improved Manhattan Distance Algorithm.

Abnormalities in individual lithium-ion batteries can cause the entire battery pack to fail, thereby the operation of electric vehicles is affected and safety accidents even occur in severe cases. Therefore, timely and accurate detection of abnormal monomers can prevent safety accidents and reduce property losses. In this paper, a battery cell anomaly detection method is proposed based on time series decomposition and an improved Manhattan distance algorithm for actual operating data of electric vehicles. First, time series decomposition is performed on the voltage data of all battery cells in the battery pack to obtain the voltage trend component of each cell. Then, the improved Manhattan distance algorithm is utilized to calculate and compare the Manhattan distance values between adjacent cell trend components, to determine the abnormal cells inside the battery pack. Furthermore, the Manhattan distance values at the same sampling moment are calculated within the data sequence to detect the specific time when the abnormal cells malfunction. The data analysis and experimental verification results based on actual vehicle operating conditions indicate that this method can accurately identify an abnormal cell within the battery pack and diagnose the specific moment of abnormality in the battery cell at an early stage of failure, with good robustness.

FBN1 knockout promotes cervical artery dissection by inducing N-glycosylation alternation of extracellular matrix proteins in rat VSMCs.

FBN1 mutation promotes the degeneration of microfibril structures and extracellular matrix (ECM) integrity in the tunica media of the aorta in Marfan syndrome. However, whether FBN1 modulates cervical artery dissection (CAD) development and the potential molecular mechanisms of abnormal FBN1 in CAD remains elusive. In this study, FBN1 deficiency participated in the development of CAD and influenced the proliferation, apoptosis, and migration of vascular smooth muscle cells. FBN1 knockout induced alternations in mRNA levels of the transcriptome, protein expression of the proteome, and abundance of N-glycosylation of the N-glycoproteome. Comprehensive analysis of multiple omics showed up-regulation in mRNA levels of ECM proteins; yet, both the ECM protein levels and relative abundance of N-glycosylation were decreased. Moreover, we performed in vivo experiments to confirm the altered glycosylation of proteins in vascular smooth muscle cells. In conclusion, FBN1 deletion in vascular smooth muscle cells can result in altered N-glycosylation of ECM protein, which were critical for the stability of ECM and the process of CAD. This may open the way for a novel therapeutic strategy to treat people with CAD.

Advances in sequencing-based studies of microDNA and ecDNA: Databases, identification methods, and integration with single-cell analysis.

Extrachromosomal circular DNA (eccDNA) is a class of circular DNA molecules that originate from genomic DNA but are separate from chromosomes. They are common in various organisms, with sizes ranging from a few hundred to millions of base pairs. A special type of large extrachromosomal DNA (ecDNA) is prevalent in cancer cells. Research on ecDNA has significantly contributed to our comprehension of cancer development, progression, evolution, and drug resistance. The use of next-generation (NGS) and third-generation sequencing (TGS) techniques to identify eccDNAs throughout the genome has become a trend in current research. Here, we briefly review current advances in the biological mechanisms and applications of two distinct types of eccDNAs: microDNA and ecDNA. In addition to presenting available identification tools based on sequencing data, we summarize the most recent efforts to integrate ecDNA with single-cell analysis and put forth suggestions to promote the process.

Circlehunter: a tool to identify extrachromosomal circular DNA from ATAC-Seq data.

In cancer, extrachromosomal circular DNA (ecDNA), or megabase-pair amplified circular DNA, plays an essential role in intercellular heterogeneity and tumor cell revolution because of its non-Mendelian inheritance. We developed circlehunter ( https://github.com/suda-huanglab/circlehunter ), a tool for identifying ecDNA from ATAC-Seq data using the enhanced chromatin accessibility of ecDNA. Using simulated data, we showed that circlehunter has an F1 score of 0.93 at 30× local depth and read lengths as short as 35 bp. Based on 1312 ecDNAs predicted from 94 publicly available datasets of ATAC-Seq assays, we found 37 oncogenes contained in these ecDNAs with amplification characteristics. In small cell lung cancer cell lines, ecDNA containing MYC leads to amplification of MYC and cis-regulates the expression of NEUROD1, resulting in an expression pattern consistent with the NEUROD1 high expression subtype and sensitive to Aurora kinase inhibitors. This showcases that circlehunter could serve as a valuable pipeline for the investigation of tumorigenesis.

Antinociceptive effects of bupivacaine injected within the internal abdominis rectus sheath in standing healthy horses.

OBJECTIVE: To evaluate a regional anesthetic technique for blocking the abdominal midline in horses. STUDY DESIGN: Anatomical description and prospective, crossover, placebo-controlled, blinded study. ANIMALS: Adult horses; two cadavers, six healthy animals. METHODS: In stage 1, 0.5% methylene blue with 0.25% bupivacaine (0.5 mL kg-1) was injected using ultrasonography into the internal rectus abdominis sheath (RAS) of two cadavers with a one-point or two-point technique. The dye spread was described after the dissection of the abdomens. In stage 2, each horse was injected with 1 mL kg-1 of 0.9% NaCl (treatment PT) or 0.2% bupivacaine (treatment BT) using a two-point technique. The abdominal midline mechanical nociceptive threshold (MNT) was measured with a 1 mm blunted probe tip and results analyzed with mixed-effect anova. Signs of pelvic limb weakness were recorded. RESULTS: The cadaver dissections showed staining of the ventral branches from the eleventh thoracic (T11) to the second lumbar (L2) nerve with the one-point technique and T9-L2 with the two-point technique. Baseline MNTs were, mean ± standard deviation, 12.6 ± 1.6 N and 12.4 ± 2.4 N in treatments PT and BT, respectively. MNT increased to 18.9 ± 5.8 N (p = 0.010) at 30 minutes, and MNT was between 9.4 ± 2.0 and 15.3 ± 3.4 N from 1 to 8 hours (p > 0.521) in treatment PT. MNTs in treatment BT were 21.1 ± 5.9 to 25.0 ± 0.1 N from 30 minutes to 8 hours (p < 0.001). MNTs after the RAS injections were higher in treatment BT than PT (p = 0.007). No pelvic limb weakness was observed. CONCLUSIONS AND CLINICAL RELEVANCE: Antinociception of at least 8 hours without pelvic limb weakness was observed in the abdominal midline in standing horses after the RAS block. Further investigations are necessary to evaluate suitability for ventral celiotomies.

Identification of a novel eighteen-gene signature of recurrent metastasis neuroblastoma.

Neuroblastoma is the most common malignant tumor in childhood, and metastases occur in more than 30% patients. Recurrent metastasis is the main cause of poor prognosis and high mortality in neuroblastoma. In this regard, there is still a lack of sufficient biomarkers and effective therapies. Therefore, we performed a multi-omics analysis of neuroblastoma patients from Therapeutically Applicable Research To Generate Effective Treatments (TARGET). With clinical relapse site information, tumor samples derived from the primary site were divided into recurrent metastasis and primary tumor groups. The initial gene signature was obtained by comparing RNA-Seq and copy number variation differences. Survival data was used to further filter prognosis-related genes. This 18-gene signature consists of three clusters: tumor suppression, cell proliferation, and immunity. A super enhancer is involved in the enhanced expression of NCAPG in cluster2 together with IRF3. Based on the gene signature expression in primary neuroblastoma, it is possible to predict tumor metastasis before it occurs. According to the anticancer drug dataset of Genomics of Drug Sensitivity in Cancer (GDSC), vinorelbine and docetaxel were predicted to have high sensitivity against recurrent metastatic neuroblastoma. In conclusion, our study offers a novel metastasis biomarker and helps understand the mechanisms of tumor recurrent metastasis. KEY MESSAGES: We identified a novel eighteen-gene signature of recurrent metastasis neuroblastoma and build risk and classification models. We dissected the regulatory role of NCAPG in signatures. We found immune exhaustion and immunosuppression in recurrent metastasis neuroblastoma. Vinorelbine and docetaxel were predicted to have high sensitivity against recurrent metastatic neuroblastoma.

Deep medullary veins: a promising neuroimaging marker for mild cognitive impairment in outpatients.

BACKGROUND AND PURPOSE: Mild cognitive impairment is an age-dependent pre-dementia state caused by varied reasons. Early detection of MCI helps handle dementia. Vascular factors are vital for the occurrence of MCI. This study investigates the correlation between deep medullary veins and multi-dimensional cognitive outcomes. MATERIALS AND METHODS: A total of 73 participants with MCI and 32 controls were enrolled. Minimum Mental State Examination and Montreal Cognitive Assessment were used to examine the global cognitive function, and different cognitive domains were measured by specific neuropsychological tests. MRI was used to assess the visibility of the DMV and other neuroimage markers. RESULTS: DMV score was statistically significantly higher in the MCI group compared with the control group (P = 0.009) and independently related to MCI (P = 0.007). Linear regression analysis verified that DMV score was linearly related to global cognition, memory, attention, and executive function after adjusting for cerebrovascular risk factors. CONCLUSION: DMV score was independently related to the onset of MCI, and correlates with overall cognition, memory, attention, and executive function in outpatients.

CIDP-like autoimmune nodopathy complicated with focal segmental glomerulosclerosis: a case study and literature review.

BACKGROUND: This study aimed to investigate the role of neurofascin186 (NF186) in the pathogenesis of the concurrent focal segmental glomerulosclerosis (FSGS) in CIDP-like autoimmune nodopathy patients. METHODS: We presented a case of CIDP-like autoimmune nodopathy complicated with FSGS. We measured NF186 antibodies by cell-binding assay (CBA) method. We performed immunofluorescence analysis in the renal cryosection samples from a patient with minimal nephropathy with rabbit anti-NF186 antibody or NF186 antibody positive human serum. Then we performed western blotting of recombinant NF186 protein and component of NF186 including Ig and FNIII domains incubating with human serum and corresponding rabbit polyclonal antibody. Cases of CIDP complicated with FSGS were searched form PubMed and reviewed. RESULTS: We reported a 66-year-old Chinese woman with CIDP-like autoimmune nodopathy and concurrent FSGS. Her NF186 antibody was positive. The fluorescent signal for NF186 was detected in the renal tissue sections of the patient with minimal nephropathy. The staining for NF186 matched the podocyte spatially. In western blotting analysis, patients had antibodies in their serum recognizing the NF186 protein and their antibodies recognized the Ig domain of NF186. 3 cases of CIDP-like autoimmune nodopathy with positive NF186 antibody and FSGS have been reported. All these patients were responsive to corticosteroids rather than the intravenous immunoglobulin, in terms of both the neuropathy and renal disease. CONCLUSIONS: NF186 was probably a targeted antigen in the pathogenesis of concurrent FSGS in CIDP-like autoimmune nodopathy with positive NF186 antibody. CIDP-like autoimmune nodopathy with positive NF186 antibody and FSGS is a rare entity, which may be responsive to corticosteroids combined with immunosuppressant.

Clinical and prognostic features of Heidenhain variant of Creutzfeldt-Jakob disease: A retrospective case series study.

BACKGROUND: Heidenhain variant of Creutzfeldt-Jakob disease (CJD) remains a diagnostic challenge in clinical practice. We aimed to describe the clinical and prognostic features of Heidenhain cases, through a case series study. METHODS: We retrospectively reviewed the definite or probable CJD cases admitted to two tertiary referral university hospitals over a decade to identify Heidenhain cases and investigated their survival status by telephone follow-up. Their clinical characteristics, neuroimaging features, electroencephalography (EEG) results, cerebrospinal fluid profiles, and PRNP gene mutations were also analyzed. RESULTS: Of a total of 85 CJD cases, 20 (24%) Heidenhain cases (11 women [55%]; median age, 64 years [range, 44-72 years]) were identified. The median survival time was 22 weeks (range, 5-155 weeks). The median duration of isolated visual symptoms was 3 weeks (range, 1-12 weeks). The most common early visual symptom was blurred vision (16/20, 80%), followed by diplopia (6/20, 30%). The prevalence significantly increased for complex visual hallucination (p = 0.005) and cortical blindness (p = 0.046) as the disease progressed. The positive rate of serial magnetic resonance images (20/20, 100%) was higher than that of serial EEGs (16/20, 80%). Two patients (2/10, 20%) had pathogenic PRNP mutations, E196A and T188K, respectively. Heidenhain cases with PRNP mutations had significantly longer survival time than those without PRNP mutations (p = 0.047). CONCLUSIONS: Besides blurred vision (80%), diplopia (30%) was also a frequent early visual symptom among Heidenhain cases. Heidenhain phenotype can occur in genetic CJD cases. PRNP mutation status might be an important prognostic factor for Heidenhain cases.

Human induced pluripotent stem cells derived from a patient with a mutation of FBN1c.1858C > T (p. Pro620Ser).

Mutation of FBN1 has certain relation with the incidence of cranial cervical artery dissection. Our study reprogrammed human induced pluripotent stem cells (iPSCs) from peripheral blood mononuclear cells (PBMC) of a patient with a mutation of FBN1c.1858C > T (p. Pro620Ser). The generated iPSCs express pluripotent cell markers with no mycoplasma contamination. Besides, it has normal karyotype and could differentiate into mesoderm, endoderm and neuronal layers. We also identified it has the same specific mutation with our patient.

Rhythmic Component Analysis Tool (RCAT): A Precise, Efficient and User-Friendly Tool for Circadian Clock Genes Analysis.

High-throughput next-generation sequencing (NGS) technologies and real-time circadian dynamics reporting systems produce large amounts of experimental data on RNA and protein levels in the field of circadian rhythm and therefore require statistical knowledge and computational skills for quantitative analysis. Although there are many software applications that can process these data, they are often difficult to use and computationally inefficient. Hence, a convenient, user-friendly tool that can accurately acquire rhythmic components (period, amplitude, and phase) of circadian clock genes is necessary. Here, we develop a new analysis tool named rhythmic component analysis tool (RCAT), which has an easily understood interface featuring a one-button operation, that presents all results as tables and images and automatically saves them as CSV files. We use the relative amplitude error (RAE), widely-adopted criteria on the circadian research field to estimate the quality of results. To illustrate the analytical ability of the RCAT under different situations, we generate four groups of time-series data by CircaInSilico (a web server for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms) with different collection intervals and amplitude ranges and use RCAT to analyze them. To demonstrate the effectiveness of RCAT, we analyze two sets of case studies with time-series data: one set uses microarray and RNA-Seq data from the gene expression omnibus (GEO) repository to identify core clock genes (CCGs) with significant periodicity in the liver, and the other set uses real-time fluorescence reporting data collected by Lumicycle® (a commonly-used luminometer) to calculate the precise period, amplitude and phase. In these examples, most cycling samples are successfully detected by the RCAT within a short collection time, and accurate rhythmic components are also successfully computed. These results indicate that RCAT improves flexibility and convenience in periodic oscillation data analysis. RCAT, is freely available at: https://github.com/lzbbest/Rhythmic-Component-Analysis-Tool/releases . It, as a cross-platform software, can be run not only on Linux, but also on Win10, Win8 and Win7.

A Clustering-Enhanced Memetic Algorithm for the Quadratic Minimum Spanning Tree Problem.

The quadratic minimum spanning tree problem (QMSTP) is a spanning tree optimization problem that considers the interaction cost between pairs of edges arising from a number of practical scenarios. This problem is NP-hard, and therefore there is not a known polynomial time approach to solve it. To find a close-to-optimal solution to the problem in a reasonable time, we present for the first time a clustering-enhanced memetic algorithm (CMA) that combines four components, i.e., (i) population initialization with clustering mechanism, (ii) a tabu-based nearby exploration phase to search nearby local optima in a restricted area, (iii) a three-parent combination operator to generate promising offspring solutions, and (iv) a mutation operator using Lévy distribution to prevent the population from premature. Computational experiments are carried on 36 benchmark instances from 3 standard sets, and the results show that the proposed algorithm is competitive with the state-of-the-art approaches. In particular, it reports improved upper bounds for the 25 most challenging instances with unproven optimal solutions, while matching the best-known results for all but 2 of the remaining instances. Additional analysis highlights the contribution of the clustering mechanism and combination operator to the performance of the algorithm.

The Degree of Plasma Oxidized Low-Density Lipoprotein Level Decrease Is Related to Clinical Outcomes for Patients with Acute Ischemic Stroke.

OBJECTIVE: To investigate the relationship between the decrease of plasma oxidized low-density lipoprotein (oxLDL) levels and clinical outcomes in patients with acute atherosclerosis-related ischemic stroke. METHODS: We recruited acute ischemic stroke patients within 3 days of onset consecutively. Plasma oxLDL levels were measured on the second day after admission and before discharge (10-14 days after stroke onset). Initial stroke severity was assessed by the National Institutes of Health Stroke Scale (NIHSS) scores, and infarct volume was measured using diffusion-weighted imaging (DWI) by the ITK-SNAP software. Clinical outcomes were evaluated by DWI volumes in the acute phase, neurological improvement at discharge, and favorable functional prognosis at 90 days. Logistic regression was performed to evaluate the association between oxLDL level decrease and clinical outcomes. RESULTS: 207 patients were enrolled in this study. Compared with the mild decrease of the oxLDL level group, patients with a significant decrease of the oxLDL level group were more likely to have a higher ratio of neurological improvement at discharge (55.07% vs. 14.49%, p < 0.01) and favorable functional prognosis at 90 days (91.30% vs. 55.07%, p < 0.01). In multivariable logistic regression, the degree of oxLDL level decrease was related to neurological improvement at discharge and favorable functional prognosis at 90 days (p < 0.01). Patients with significant decrease were more likely to have neurological improvement at discharge (OR = 7.92, 95% CI, 3.14-19.98, and p < 0.01) and favorable functional prognosis at 90 days (OR = 7.46, 95% CI, 2.40-23.23, and p < 0.01) compared to patients with mild decrease of oxLDL level. The DWI volumes in patients with different oxLDL level decrease groups had no statistical difference (p = 0.41), and the Spearman's rho between oxLDL level decrease and DWI infarct volumes was -0.03, but no statistical difference (p = 0.72). CONCLUSIONS: The degree of oxLDL level decrease is related to neurological improvement at discharge and favorable functional prognosis at 90 days for patients with acute atherosclerosis-related ischemic stroke, but not with infarct volume in the acute phase.