Cognitive performance in functional seizures compared with epilepsy and healthy controls: a systematic review and meta analysis.

BACKGROUND: Cognition is a core component of functional seizures, but the literature on cognition in this disorder has been heterogeneous, with no clear unifying profile emerging from individual studies. The aim of this study was to do a systematic review and meta-analysis of cognitive performance in adults with functional seizures compared with epilepsy (including left temporal lobe epilepsy) and compared with healthy non-seizure cohorts. METHODS: In this systematic review and meta-analysis, starting Feb 6, 2023, replicated and updated on Oct 31, 2023, a medical librarian searched MEDLINE, Embase, PsycINFO, and Web of Science. Inclusion criteria were full reports documenting raw or standardised cognitive test data in adults with functional seizures compared with adults with epilepsy, prospectively recruited healthy comparisons, or published norms. Grey literature was retained and there were no language or date restrictions. We excluded studies only reporting on mixed functional seizures and epilepsy, or mixed functional neurological samples, with no pure functional seizures group. Risk of bias was evaluated using a modified version of the Newcastle-Ottawa Scale. People with lived experiences were not involved in the design or execution of this study. This study is registered as CRD42023392385 in PROSPERO. FINDINGS: Of 3834 records initially identified, 84 articles were retained, including 8654 participants (functional seizures 4193, epilepsy 3638, and healthy comparisons 823). Mean age was 36 years (SD 12) for functional seizures, 36 years (12) for epilepsy, and 34 years (10) for healthy comparisons, and the proportion of women per group was 72% (range 18-100) for functional seizures, 59% (range 15-100) for epilepsy, and 69% (range 34-100) for healthy comparisons. Data on race or ethnicity were rarely reported in the individual studies. Risk of bias was moderate. Cognitive performance was better in people with functional seizures than those with epilepsy (Hedges' g=0·17 [95% CI 0·10-0·25)], p<0·0001), with moderate-to-high heterogeneity (Q[56]=128·91, p=0·0001, I2=57%). The functional seizures group performed better than the epilepsy group on global cognition and intelligence quotient (g=0·15 [0·02-0·28], p=0·022) and language (g=0·28 [0·14-0·43], p=0·0001), but not other cognitive domains. A larger effect was noted in language tests when comparing functional seizures with left temporal lobe epilepsy (k=5; g=0·51 [0·10 to 0·91], p=0·015). The functional seizures group underperformed relative to healthy comparisons (g=-0·61 [-0·78 to -0·44], p<0·0001), with significant differences in all cognitive domains. Meta regressions examining effects of multiple covariates on global cognition were not significant. INTERPRETATION: Patients with functional seizures have widespread cognitive impairments that are likely to be clinically meaningful on the basis of moderate effect sizes in multiple domains. These deficits might be slightly less severe than those seen in many patients with epilepsy but nevertheless argue for consideration of clinical assessment and treatment. FUNDING: Department of Veterans Affairs, Veterans Health Administration.

Prognostic PET [11C]-acetate uptake is associated with hypoxia gene expression in patients with late-stage hepatocellular carcinoma - a bench to bed study.

BACKGROUND: Positron Emission Tomography (PET) with combined [18F]-FDG and [11C]-acetate (dual-tracer) is used for the management of hepatocellular carcinoma (HCC) patients, although its prognostic value and underlying molecular mechanism remain poorly understood. We hypothesized that radiotracer uptake might be associated with tumor hypoxia and validated our findings in public and local human HCC cohorts. METHODS: Twelve orthotopic HCC xenografts were established using MHCC97L cells in female nude mice, with 5 having undergone hepatic artery ligation (HAL) to create tumor hypoxia in vivo. Tumors in both Control and HAL-treated xenografts were imaged with [11C]-acetate and [18F]-FDG PET-MR and RNA sequencing was performed on the resected tumors. Semiquantitative analysis of PET findings was then performed, and the findings were then validated on the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and patients from our institution. RESULTS: HAL-treated mice showed lower [11C]-acetate (HAL-treated vs. Control, tumor-to-liver SUV ratio (SUVTLR): 2.14[2.05-2.21] vs 3.11[2.75-5.43], p = 0.02) but not [18F]-FDG (HAL-treated vs. Control, SUVTLR: 3.73[3.12-4.35] vs 3.86[3.7-5.29], p = 0.83) tumor uptakes. Gene expression analysis showed the PET phenotype is associated with upregulation of hallmark hypoxia signature. The prognostic value of the hypoxia gene signature was tested on the TCGA-LIHC cohort with upregulation of hypoxia gene signature associated with poorer overall survival (OS) in late-stage (stage III and IV) HCC patients (n = 66, OS 2.05 vs 1.67 years, p = 0.046). Using a local cohort of late-stage HCC patients who underwent dual-tracer PET-CT, tumors without [11C]-acetate uptake are associated with poorer prognosis (n = 51, OS 0.25 versus 1.21 years, p < 0.0001) and multivariable analyses showed [11C]-acetate tumor uptake as an independent predictor of OS (HR 0.17 95%C 0.06-0.42, p < 0.0001). CONCLUSIONS: [11C]-acetate uptake is associated with alteration of tumor hypoxia gene expression and poorer prognosis in patients with advanced HCC.

Reduced Subjective Cognitive Concerns With Neurobehavioral Therapy in Functional Seizures and Traumatic Brain Injury.

OBJECTIVE: Functional seizures are common among people with traumatic brain injury (TBI). Subjective cognitive concerns refer to a person's own perception of problems with cognitive functioning in everyday life. The authors investigated the presence and correlates of subjective cognitive concerns and the response to neurobehavioral therapy among adults with TBI and functional seizures (TBI+FS group). METHODS: In this observational study, participants in the TBI+FS group (N=47) completed a 12-session neurobehavioral therapy protocol for seizures, while participants in the comparison group (TBI without seizures) (N=50) received usual treatment. Subjective cognitive concerns, objective cognition, mental health, and quality of life were assessed before and after treatment. Data collection occurred from 2018 to 2022. RESULTS: Baseline subjective cognitive concerns were reported for 37 (79%) participants in the TBI+FS group and 20 (40%) participants in the comparison group. In a multivariable regression model in the TBI+FS group, baseline global mental health (ß=-0.97) and obsessive-compulsive symptoms (ß=-1.01) were associated with subjective cognitive concerns at baseline. The TBI+FS group had fewer subjective cognitive concerns after treatment (η2=0.09), whereas the TBI comparison group showed a nonsignificant increase in subjective cognitive concerns. CONCLUSIONS: Subjective cognitive concerns are common among people with TBI and functional seizures and may be related to general mental health and obsessive-compulsive symptoms. Evidence-based neurobehavioral therapy for functional seizures is a reasonable treatment option to address such concerns in this population, although additional studies in culturally diverse samples are needed. In addition, people with functional seizures would likely benefit from rehabilitation specifically targeted toward cognitive functioning.

Enhancing Diagnostic Images to Improve the Performance of the Segment Anything Model in Medical Image Segmentation.

Medical imaging serves as a crucial tool in current cancer diagnosis. However, the quality of medical images is often compromised to minimize the potential risks associated with patient image acquisition. Computer-aided diagnosis systems have made significant advancements in recent years. These systems utilize computer algorithms to identify abnormal features in medical images, assisting radiologists in improving diagnostic accuracy and achieving consistency in image and disease interpretation. Importantly, the quality of medical images, as the target data, determines the achievable level of performance by artificial intelligence algorithms. However, the pixel value range of medical images differs from that of the digital images typically processed via artificial intelligence algorithms, and blindly incorporating such data for training can result in suboptimal algorithm performance. In this study, we propose a medical image-enhancement scheme that integrates generic digital image processing and medical image processing modules. This scheme aims to enhance medical image data by endowing them with high-contrast and smooth characteristics. We conducted experimental testing to demonstrate the effectiveness of this scheme in improving the performance of a medical image segmentation algorithm.

CT-based methods for assessment of metabolic dysfunction associated with fatty liver disease.

Metabolic dysfunction-associated fatty liver disease (MAFLD), previously called metabolic nonalcoholic fatty liver disease, is the most prevalent chronic liver disease worldwide. The multi-factorial nature of MAFLD severity is delineated through an intricate composite analysis of the grade of activity in concert with the stage of fibrosis. Despite the preeminence of liver biopsy as the diagnostic and staging reference standard, its invasive nature, pronounced interobserver variability, and potential for deleterious effects (encompassing pain, infection, and even fatality) underscore the need for viable alternatives. We reviewed computed tomography (CT)-based methods for hepatic steatosis quantification (liver-to-spleen ratio; single-energy "quantitative" CT; dual-energy CT; deep learning-based methods; photon-counting CT) and hepatic fibrosis staging (morphology-based CT methods; contrast-enhanced CT biomarkers; dedicated postprocessing methods including liver surface nodularity, liver segmental volume ratio, texture analysis, deep learning methods, and radiomics). For dual-energy and photon-counting CT, the role of virtual non-contrast images and material decomposition is illustrated. For contrast-enhanced CT, normalized iodine concentration and extracellular volume fraction are explained. The applicability and salience of these approaches for clinical diagnosis and quantification of MAFLD are discussed.Relevance statementCT offers a variety of methods for the assessment of metabolic dysfunction-associated fatty liver disease by quantifying steatosis and staging fibrosis.Key points• MAFLD is the most prevalent chronic liver disease worldwide and is rapidly increasing.• Both hardware and software CT advances with high potential for MAFLD assessment have been observed in the last two decades.• Effective estimate of liver steatosis and staging of liver fibrosis can be possible through CT.

Pretreatment radiomic biomarker for immunotherapy responder prediction in stage IB-IV NSCLC (LCDigital-IO Study): a multicenter retrospective study.

BACKGROUND: The predictive efficacy of current biomarker of immune checkpoint inhibitors (ICIs) is not sufficient. This study investigated the causality between radiomic biomarkers and immunotherapy response status in patients with stage IB-IV non-small cell lung cancer (NSCLC), including its biological context for ICIs treatment response prediction. METHODS: CT images from 319 patients with pretreatment NSCLC receiving immunotherapy between January 2015 and November 2021 were retrospectively collected and composed a discovery (n=214), independent validation (n=54), and external test cohort (n=51). A set of 851 features was extracted from tumorous and peritumoral volumes of interest (VOIs). The reference standard is the durable clinical benefit (DCB, sustained disease control for more than 6 months assessed via radiological evaluation). The predictive value of combined radiomic signature (CRS) for pathological response was subsequently assessed in another cohort of 98 patients with resectable NSCLC receiving ICIs preoperatively. The association between radiomic features and tumor immune landscape on the online data set (n=60) was also examined. A model combining clinical predictor and radiomic signatures was constructed to improve performance further. RESULTS: CRS discriminated DCB and non-DCB patients well in the training and validation cohorts with an area under the curve (AUC) of 0.82, 95% CI: 0.75 to 0.88, and 0.75, 95% CI: 0.64 to 0.87, respectively. In this study, the predictive value of CRS was better than programmed cell death ligand-1 (PD-L1) expression (AUC of PD-L1 subset: 0.59, 95% CI: 0.50 to 0.69) or clinical model (AUC: 0.66, 95% CI: 0.51 to 0.81). After combining the clinical signature with CRS, the predictive performance improved further with an AUC of 0.837, 0.790 and 0.781 in training, validation and D2 cohorts, respectively. When predicting pathological response, CRS divided patients into a major pathological response (MPR) and non-MPR group (AUC: 0.76, 95% CI: 0.67 to 0.81). Moreover, CRS showed a promising stratification ability on overall survival (HR: 0.49, 95% CI: 0.27 to 0.89; p=0.020) and progression-free survival (HR: 0.43, 95% CI: 0.26 to 0.74; p=0.002). CONCLUSION: By analyzing both tumorous and peritumoral regions of CT images in a radiomic strategy, we developed a non-invasive biomarker for distinguishing responders of ICIs therapy and stratifying their survival outcome efficiently, which may support the clinical decisions on the use of ICIs in advanced as well as patients with resectable NSCLC.

Synergistic markers based on inter-covariate association estimate treatment option with lower propensity to covariates.

Background: Propensity constitutes a common problem in identifying clinical outcome prediction model whose covariates include the treatment option, which is assumed to be randomly assigned but indeed dependent of other covariates in the training data. The genuine effect of treatment option cannot be elucidated under the influence of propensity. Existing approaches, such as matched-pairs study design, still cannot solve the problem for imbalanced or small datasets. Methods: This work proposed an anti-propensity estimate of treatment option, which is generated by support vector classifier based on two synergistic markers that represent the lower and upper limits of inter-covariate association level. The algorithm for generating the synergistic markers was illustrated and the performance was evaluated on a public dataset of gene expression levels, which were obtained from surgically excised tumor samples in non-small cell lung cancer (NSCLC) patients where treatment option, i.e., adjuvant therapy or not, was known. Results: Six covariates represented by the expression levels of ZNF217, ERCC3, PMS1, PIK3CB, BARD1, and MAPK1, were selected to generate two synergistic markers and classifier for estimating the adjuvant therapy option with substantially attenuated propensity. The estimation accuracy attained an area under the receiver-operating characteristics curve, 0.78, in the test set. Conclusions: The proposed synergistic markers demonstrated a parsimonious and anti-propensity estimation of treatment option, which is ready for the further evaluation and application in the clinical outcome prediction model.

MDM-U-Net: A novel network for renal cancer structure segmentation.

Accurate segmentation of the renal cancer structure, including the kidney, renal tumors, veins, and arteries, has great clinical significance, which can assist clinicians in diagnosing and treating renal cancer. For accurate segmentation of the renal cancer structure in contrast-enhanced computed tomography (CT) images, we proposed a novel encoder-decoder structure segmentation network named MDM-U-Net comprising a multi-scale anisotropic convolution block, dual activation attention block, and multi-scale deep supervision mechanism. The multi-scale anisotropic convolution block was used to improve the feature extraction ability of the network, the dual activation attention block as a channel-wise mechanism was used to guide the network to exploit important information, and the multi-scale deep supervision mechanism was used to supervise the layers of the decoder part for improving segmentation performance. In this study, we developed a feasible and generalizable MDM-U-Net model for renal cancer structure segmentation, trained the model from the public KiPA22 dataset, and tested it on the KiPA22 dataset and an in-house dataset. For the KiPA22 dataset, our method ranked first in renal cancer structure segmentation, achieving state-of-the-art (SOTA) performance in terms of 6 of 12 evaluation metrics (3 metrics per structure). For the in-house dataset, our method achieves SOTA performance in terms of 9 of 12 evaluation metrics (3 metrics per structure), demonstrating its superiority and generalization ability over the compared networks in renal structure segmentation from contrast-enhanced CT scans.

Characterization of Infectious Keratitis in Opioid Users in a County Hospital Setting.

Purpose: To determine risk factors and clinical course of corneal ulcers in the setting of opioid use. Methods: A retrospective cohort study was performed of patients presenting with bacterial or fungal keratitis at a county hospital from 2010-2021. Subjects were separated into three groups: opioid drug users (heroin, methadone, fentanyl), non-opioid drug users, and non-drug users. 24 opioid users, 77 non-opioid drug users, and 38 non-drug users were included in the study. Chi-square and t-tests were used to compare hospitalization for corneal ulcer treatment; length of hospitalization; loss to follow-up; final best corrected visual acuity (BCVA); medication noncompliance; time to ulcer resolution; and visual disability (defined either by the legal limit for driving in California or the federal limit for blindness). Results: Opioid users had higher rates of unemployment (p=0.002), homelessness (p=0.018), and psychiatric conditions (p=0.024) compared with non-opioid and non-drug users. They had more severe presentations, with worse initial BCVA of the affected eye (p=0.003), larger ulcer size (p=0.023), and higher rates of individuals below the legal vision thresholds for driving (p=0.009) and blindness (p=0.033) at initial presentation. Opioid use was associated with increased rate of hospitalization (p<0.001), higher fortified antibiotic use (p=0.009), worse final BCVA of the affected eye (p=0.020), and increased rates of BCVA worse than the legal vision thresholds for driving (p=0.043) and blindness (p<0.001) on final presentation. Conclusions: Infectious keratitis associated with opioid use is associated with more severe presentations and poorer outcomes, including higher rates of visual disability.

Lipotoxicity-polarised macrophage-derived exosomes regulate mitochondrial fitness through Miro1-mediated mitophagy inhibition and contribute to type 2 diabetes development in mice.

AIMS/HYPOTHESIS: Insulin resistance is a major pathophysiological defect in type 2 diabetes and obesity. Numerous experimental and clinical studies have provided evidence that sustained lipotoxicity-induced mitophagy deficiency can exacerbate insulin resistance, leading to a vicious cycle between mitophagy dysfunction and insulin resistance, and thereby the onset of type 2 diabetes. Emerging evidence suggests that exosomes (Exos) from M2 macrophages play an essential role in modulating metabolic homeostasis. However, how macrophages are affected by lipotoxicity and the role of lipotoxicity in promoting macrophage activation to the M1 state have not been determined. The objective of this study was to determine whether M1 macrophage-derived Exos polarised by lipopolysaccharide (LPS) + palmitic acid (PA)-induced lipotoxicity contribute to metabolic homeostasis and impact the development of insulin resistance in type 2 diabetes. METHODS: Lipotoxicity-polarised macrophage-derived M1 Exos were isolated from bone marrow (C57BL/6J mouse)-derived macrophages treated with LPS+PA. Exos were characterised by transmission electron microscopy, nanoparticle tracking analysis and western blotting. Flow cytometry, H&E staining, quantitative real-time PCR, immunofluorescence, glucose uptake and output assays, confocal microscopy imaging, western blotting, GTTs and ITTs were conducted to investigate tissue inflammation, mitochondrial function and insulin resistance in vitro and in vivo. The roles of miR-27-3p and its target gene Miro1 (also known as Rhot1, encoding mitochondrial rho GTPase 1) and relevant pathways were predicted and assessed in vitro and in vivo using specific miRNA mimic, miRNA inhibitor, miRNA antagomir and siRNA. RESULTS: miR-27-3p was highly expressed in M1 Exos and functioned as a Miro1-inactivating miRNA through the miR-27-3p-Miro1 axis, leading to mitochondria fission rather than fusion as well as mitophagy impairment, resulting in NOD-like receptor 3 inflammatory activation and development of insulin resistance both in vivo and in vitro. Inactivation of miR-27-3p induced by M1 Exos prevented type 2 diabetes development in high-fat-diet-fed mice. CONCLUSIONS/INTERPRETATION: These findings suggest that the miR-27-3p-Miro1 axis, as a novel regulatory mechanism for mitophagy, could be considered as a new therapeutic target for lipotoxicity-related type 2 diabetes disease development.

Improvements in Montreal Cognitive Assessment scores after neurobehavioral therapy in adults with functional (nonepileptic) seizures and traumatic brain injury.

Cognitive functioning impacts clinical symptoms, treatment response, and quality of life in adults with functional/nonepileptic seizures (FS/NES), but no study to date examines effects of behavioral FS/NES treatment on cognition in these patients. We hypothesized that there would be a reduction in cognitive symptoms in participants with FS/NES and traumatic brain injury (TBI) following neurobehavioral therapy (NBT). We also hypothesized that select seizure-related, medication, subjective cognitive, and mental health symptoms would be negatively correlated with improvements in cognitive performance after NBT. Participants were 37 adults with TBI + FS/NES and 35 adults with TBI only, recruited from medical centers in the northeastern or southeastern U.S. TBI + FS/NES participants completed a 12 session NBT intervention, and TBI without seizures participants were not treated. All participants completed pre-post assessments of cognition (Montreal Cognitive Assessment [MoCA]) and baseline sociodemographic factors and mental health symptoms. Pre-post MoCA scores increased significantly in TBI + FS/NES participants (28/37 [75.7%] improved) but not in TBI comparisons (10/35 [28.6%] improved). Language, memory, and visuospatial/executive functions, but not attention, improved over time in the TBI + FS/NES group. Gains in cognition were concentrated in those TBI + FS/NES participants with likely baseline cognitive impairments (MoCA total score <26), and 9/17 of these participants moved from the "impaired" range at baseline (<26) to the "intact" range at endpoint (≥26). Lastly, participants taking fewer medications and reporting lower subjective cognitive difficulties at baseline showed larger pre-post MoCA total score improvements. Overall, results from this study suggest the potential for positive change in cognition in FS/NES and co-occurring TBI using evidence-based psychotherapy.

Consensus Statements on Precision Oncology in the China Greater Bay Area.

BACKGROUND: Next-generation sequencing comprehensive genomic panels (NGS CGPs) have enabled the delivery of tailor-made therapeutic approaches to improve survival outcomes in patients with cancer. Within the China Greater Bay Area (GBA), territorial differences in clinical practices and health care systems and strengthening collaboration warrant a regional consensus to consolidate the development and integration of precision oncology (PO). Therefore, the Precision Oncology Working Group (POWG) formulated standardized principles for the clinical application of molecular profiling, interpretation of genomic alterations, and alignment of actionable mutations with sequence-directed therapy to deliver clinical services of excellence and evidence-based care to patients with cancer in the China GBA. METHODS: Thirty experts used a modified Delphi method. The evidence extracted to support the statements was graded according to the GRADE system and reported according to the Revised Standards for Quality Improvement Reporting Excellence guidelines, version 2.0. RESULTS: The POWG reached consensus in six key statements: harmonization of reporting and quality assurance of NGS; molecular tumor board and clinical decision support systems for PO; education and training; research and real-world data collection, patient engagement, regulations, and financial reimbursement of PO treatment strategies; and clinical recommendations and implementation of PO in clinical practice. CONCLUSION: POWG consensus statements standardize the clinical application of NGS CGPs, streamline the interpretation of clinically significant genomic alterations, and align actionable mutations with sequence-directed therapies. The POWG consensus statements may harmonize the utility and delivery of PO in China's GBA.

Bioinformatics Identification of Regulatory Genes and Mechanism Related to Hypoxia-Induced PD-L1 Inhibitor Resistance in Hepatocellular Carcinoma.

The combination of a PD-L1 inhibitor and an anti-angiogenic agent has become the new reference standard in the first-line treatment of non-excisable hepatocellular carcinoma (HCC) due to the survival advantage, but its objective response rate remains low at 36%. Evidence shows that PD-L1 inhibitor resistance is attributed to hypoxic tumor microenvironment. In this study, we performed bioinformatics analysis to identify genes and the underlying mechanisms that improve the efficacy of PD-L1 inhibition. Two public datasets of gene expression profiles, (1) HCC tumor versus adjacent normal tissue (N = 214) and (2) normoxia versus anoxia of HepG2 cells (N = 6), were collected from Gene Expression Omnibus (GEO) database. We identified HCC-signature and hypoxia-related genes, using differential expression analysis, and their 52 overlapping genes. Of these 52 genes, 14 PD-L1 regulator genes were further identified through the multiple regression analysis of TCGA-LIHC dataset (N = 371), and 10 hub genes were indicated in the protein-protein interaction (PPI) network. It was found that POLE2, GABARAPL1, PIK3R1, NDC80, and TPX2 play critical roles in the response and overall survival in cancer patients under PD-L1 inhibitor treatment. Our study provides new insights and potential biomarkers to enhance the immunotherapeutic role of PD-L1 inhibitors in HCC, which can help in exploring new therapeutic strategies.

Early metabolic derangements and unfavorable outcomes in pediatric traumatic brain injury: a retrospective multi-center cohort study.

Background: To study the association in moderate and severe pediatric traumatic brain injury (TBI) between hyperglycemia, hyperlactatemia, acidosis and unfavorable outcome, as assessed by Pediatric Cerebral Performance Category (PCPC) on discharge from the pediatric intensive care unit (PICU). Methods: Children <16 years old with TBI and Glasgow Coma Scale (GCS) ≤13 in an Asian multi-center PICU TBI cohort from January 2014 to October 2017 were included in this study. We defined unfavorable outcome as PCPC ≥3-moderate disability, severe disability, vegetative state, and death. We performed logistic regression to investigate the association between metabolic changes with unfavorable outcome. We divided hyperglycemia (glucose >11.1 mmol/L) during PICU admission into early-onset (within 24 h), late-onset (beyond 48 h) and persistent (throughout first 72 h). Results: Among the 305 children analyzed, 136 (44.6%) had unfavorable outcome. Children with unfavorable outcome were more likely to have early hyperglycemia (75/136, 55.1% vs. 33/169, 19.5%; P<0.001), high lactate levels >2.0 mmol/L (74/136, 54.4% vs. 56/169, 32.5%; P<0.001) and initial acidosis (85/136, 62.5% vs. 78/169, 56.1%; P=0.003) compared to those with favorable outcome. After adjusting for gender, GCS ≤8 and presence of polytrauma, early hyperglycemia [adjusted odds ratio (aOR) =3.68, 95% CI: 2.12-6.39, P<0.001] and late hyperglycemia (aOR =13.30, 95% CI: 1.64-107.8, P=0.015] were independently associated with unfavorable outcome. All children with persistent hyperglycemia died. Conclusions: We described unfavorable outcome in pediatric TBI especially with persistent hyperglycemia. Future trials should investigate the causal relationship between glycemic trends, early intervention and outcome in this cohort.

Diagnostic efficiency on ultrasound shear wave elastography in evaluation of steatosis severity for non-alcoholic fatty liver disease: a rat model.

BACKGROUND: The pathological feature of steatosis affects the elasticity values measured by shear wave elastography (SWE) is still controversial in non-alcoholic fatty liver disease (NAFLD). The aim of this study is to demonstrate the influence of steatosis on liver stiffness measured by SWE on a rat model with NAFLD and analyze feasibility of SWE for grading steatosis in absence of fibrosis. METHODS: Sixty-six rats were fed with methionine choline deficient diet or standard diet to produce various stages of steatosis; 48 rats were available for final analysis. Rats underwent abdominal ultrasound SWE examination and pathological assessment. Liver histopathology was analyzed to assess the degree of steatosis, inflammation, ballooning, and fibrosis according to the non-alcoholic fatty liver disease activity score. The diagnostic performance of SWE for differentiating steatosis stages was estimated according to the receiver operating characteristic (ROC) curve. Decision curve analysis (DCA) was conducted to determine clinical usefulness and the areas under DCA (AUDCAs) calculated. RESULTS: In multivariate analysis, steatosis was an independent factor affecting the mean elastic modules (B = 1.558, P < 0.001), but not inflammation (B = - 0.031, P = 0.920) and ballooning (B = 0.216, P = 0.458). After adjusting for inflammation and ballooning, the AUROC of the mean elasticity for identifying S ≥ S1 was 0.956 (95%CI: 0.872-0.998) and the AUDCA, 0.621. The AUROC for distinguishing S ≥ S2 and S = S3 was 0.987 (95%CI: 0.951-1.000) and 0.920 (95%CI: 0.816-0.986) and the AUDCA was 0.506 and 0.256, respectively. CONCLUSIONS: Steatosis is associated with liver stiffness and SWE may have the feasibility to be introduced as an assistive technology in grading steatosis for patients with NAFLD in absence of fibrosis.

Deep learning attention-guided radiomics for COVID-19 chest radiograph classification.

Background: Accurate assessment of coronavirus disease 2019 (COVID-19) lung involvement through chest radiograph plays an important role in effective management of the infection. This study aims to develop a two-step feature merging method to integrate image features from deep learning and radiomics to differentiate COVID-19, non-COVID-19 pneumonia and normal chest radiographs (CXR). Methods: In this study, a deformable convolutional neural network (deformable CNN) was developed and used as a feature extractor to obtain 1,024-dimensional deep learning latent representation (DLR) features. Then 1,069-dimensional radiomics features were extracted from the region of interest (ROI) guided by deformable CNN's attention. The two feature sets were concatenated to generate a merged feature set for classification. For comparative experiments, the same process has been applied to the DLR-only feature set for verifying the effectiveness of feature concatenation. Results: Using the merged feature set resulted in an overall average accuracy of 91.0% for three-class classification, representing a statistically significant improvement of 0.6% compared to the DLR-only classification. The recall and precision of classification into the COVID-19 class were 0.926 and 0.976, respectively. The feature merging method was shown to significantly improve the classification performance as compared to using only deep learning features, regardless of choice of classifier (P value <0.0001). Three classes' F1-score were 0.892, 0.890, and 0.950 correspondingly (i.e., normal, non-COVID-19 pneumonia, COVID-19). Conclusions: A two-step COVID-19 classification framework integrating information from both DLR and radiomics features (guided by deep learning attention mechanism) has been developed. The proposed feature merging method has been shown to improve the performance of chest radiograph classification as compared to the case of using only deep learning features.

A high fat diet in glutamate 3-/Y mice causes changes in behavior that resemble human intellectual disability.

Cognitive impairment in individuals with intellectual disability (ID) is characterized by developmental delay and deficits in language and memory. Ionotropic AMPA mediate the majority of excitatory synaptic transmission in the central nervous system and are essential for the induction and maintenances of long-term potentiation (LTP) and long-term depression (LTD), two cellular models of learning and memory underlie many the symptoms of ID. Clinical research has found obese male patients with GluA3 interrupted underlie the symptom of ID. We tested GluA3-/Y mice under high fat diet (HFD) stress on a series of behavioral paradigms associated with symptoms of ID: wild type mice showed significant levels of sociability, while GluA3-/Y mice did not. Wild type mice showed significant preference for social novelty, while GluA3-/Y mice did not. Normal scores on relevant control measures confirmed general health and physical abilities in both GluA3-/Y and wild type mice (WT), ruling out artifactual explanations for social deficits. GluA3-/Y mice also showed working spatial memory behavior impairment in Y-maze test and abnormal anxiety in open-field test, compared to wild-type littermate controls. GluA3-/Y mice had a significantly reduced spontaneous activities tested by elevated plus maze, display both low social approach and resistance to change in routine on the T-maze, consistent with an ID-like phenotype. These findings demonstrate that selective gene deletion of GluA3 receptor in male mice under oxidative stress induced phenotypic abnormalities related to ID-like symptoms.

Risk Factors Predicting Loss to Follow-Up, Medication Noncompliance, and Poor Visual Outcomes Among Patients With Infectious Keratitis at a Public County Hospital.

PURPOSE: Infectious keratitis is a vision-threatening condition requiring close follow-up and disciplined eye drop administration to achieve resolution. Although patients presenting to county hospitals often have more severe presentations, there is a paucity of risk and outcomes data in this setting. This study investigates risk factors predicting loss to follow-up (LTFU), medication noncompliance, and poor outcomes for infectious keratitis in the county hospital setting. METHODS: This was a retrospective case-control study at Zuckerberg San Francisco General Hospital and Trauma Center. Inclusion criteria were patients who had corneal cultures for suspected infectious bacterial or fungal keratitis between 2010 and 2021. Exclusion criteria were patients with viral keratitis only. Multivariable logistic regression was used to analyze the relationship of social and medical risk factors with LTFU, medication noncompliance, worsened visual acuity (VA), and delayed resolution time. RESULTS: Of 174 patients with infectious keratitis in this analysis, 69 (40.0%) had LTFU. Unemployment was associated with increased risk of LTFU (odds ratio 2.58, P = 0.049) and worse final VA ( P = 0.001). Noncompliance trended toward an association with homelessness (odds ratio 3.48, P = 0.095). Increasing age correlated with longer resolution time, with each 1-year increase associated with delayed resolution by 0.549 days ( P = 0.042). CONCLUSIONS: Patients experiencing unemployment, homelessness, or increased age demonstrate higher risk for treatment barriers including loss to follow-up and medication noncompliance, resulting in worse VA and delayed time to resolution. These risk factors should be considered when determining the need for more deliberate follow-up measures in patients with infectious keratitis.

Characterization of Polymicrobial and Antibiotic-Resistant Infectious Keratitis in a County Hospital Setting.

Purpose: Infectious keratitis is a serious cause of visual impairment, particularly in low-income communities. This study examines the associations between social risk factors and polymicrobial keratitis, multidrug resistance, pathogen spectrum, and outcomes at a county hospital. Methods: We performed a retrospective study of Zuckerberg San Francisco General Hospital patients treated for infectious keratitis from 2010-2021. Multivariable regression was performed to analyze the relationships between social, medical, and psychiatric risk factors with polymicrobial growth, multidrug resistance, and clinical outcomes. Results: Of 174 patients with infectious keratitis, 44 (25%) had polymicrobial growth. Six patients (14%) with polymicrobial growth had multidrug-resistant organisms. Homeless patients were more likely to present with polymicrobial infection (OR 3.4, p = 0.023), and polymicrobial infections were associated with multidrug-resistant organisms (p = 0.018). Smoking, drug use, HIV positivity, prior corneal pathology, and contact lens use were not associated with an increased risk of polymicrobial infection. Eleven patients (6.3%) were started on topical antibiotics prior to presentation; of these, none developed polymicrobial infections or multidrug-resistant organisms. Polymicrobial infections increased the likelihood to initiation of fortified antibiotics (OR 2.9, p = 0.011) but did not impact ulcer size, final visual acuity, time to resolution, or likelihood of emergent procedures. Conclusions: Homelessness correlates with an increased risk of polymicrobial keratitis and subsequent multidrug resistance, supporting initiation of broad antibiotic coverage in this population. Prior topical antibiotics did not increase risk of polymicrobial infection. Polymicrobial infection did not significantly worsen clinical outcomes.