Practical measurements distinguishing physiological and pathological stereoelectroencephalography channels based on high-frequency oscillations in the human brain.

OBJECTIVE: The present study aimed to identify various distinguishing features for use in the accurate classification of stereoelectroencephalography (SEEG) channels based on high-frequency oscillations (HFOs) inside and outside the epileptogenic zone (EZ). METHODS: HFOs were detected in patients with focal epilepsy who underwent SEEG. Subsequently, HFOs within the seizure-onset and early spread zones were defined as pathological HFOs, whereas others were defined as physiological. Three features of HFOs were identified at the channel level, namely, morphological repetition, rhythmicity, and phase-amplitude coupling (PAC). A machine-learning (ML) classifier was then built to distinguish two HFO types at the channel level by application of the above-mentioned features, and the contributions were quantified. Further verification of the characteristics and classifier performance was performed in relation to various conscious states, imaging results, EZ location, and surgical outcomes. RESULTS: Thirty-five patients were included in this study, from whom 166 104 pathological HFOs in 255 channels and 53 374 physiological HFOs in 282 channels were entered into the analysis pipeline. The results revealed that the morphological repetitions of pathological HFOs were markedly higher than those of the physiological HFOs; this was also observed for rhythmicity and PAC. The classifier exhibited high accuracy in differentiating between the two forms of HFOs, as indicated by an area under the curve (AUC) of 0.89. Both PAC and rhythmicity contributed significantly to this distinction. The subgroup analyses supported these findings. SIGNIFICANCE: The suggested HFO features can accurately distinguish between pathological and physiological channels substantially improving its usefulness in clinical localization. PLAIN LANGUAGE SUMMARY: In this study, we computed three quantitative features associated with HFOs in each SEEG channel and then constructed a machine learning-based classifier for the classification of pathological and physiological channels. The classifier performed well in distinguishing the two channel types under different levels of consciousness as well as in terms of imaging results, EZ location, and patient surgical outcomes.

Nanopore Current Events Magnifier (nanoCEM): a novel tool for visualizing current events at modification sites of nanopore sequencing.

Nanopore sequencing technologies have enabled the direct detection of base modifications in DNA or RNA molecules. Despite these advancements, the tools for visualizing electrical current, essential for analyzing base modifications, are often lacking in clarity and compatibility with diverse nanopore pipelines. Here, we present Nanopore Current Events Magnifier (nanoCEM, https://github.com/lrslab/nanoCEM), a Python command-line tool designed to facilitate the identification of DNA/RNA modification sites through enhanced visualization and statistical analysis. Compatible with the four preprocessing methods including 'f5c resquiggle', 'f5c eventalign', 'Tombo' and 'move table', nanoCEM is applicable to RNA and DNA analysis across multiple flow cell types. By utilizing rescaling techniques and calculating various statistical features, nanoCEM provides more accurate and comparable visualization of current events, allowing researchers to effectively observe differences between samples and showcase the modified sites.

Targeted Protein O-GlcNAcylation Using Bifunctional Small Molecules.

Protein O-linked ß-N-acetylglucosamine modification (O-GlcNAcylation) plays a crucial role in regulating essential cellular processes. The disruption of the homeostasis of O-GlcNAcylation has been linked to various human diseases, including cancer, diabetes, and neurodegeneration. However, there are limited chemical tools for protein- and site-specific O-GlcNAc modification, rendering the precise study of the O-GlcNAcylation challenging. To address this, we have developed heterobifunctional small molecules, named O-GlcNAcylation TArgeting Chimeras (OGTACs), which enable protein-specific O-GlcNAcylation in living cells. OGTACs promote O-GlcNAcylation of proteins such as BRD4, CK2α, and EZH2 in cellulo by recruiting FKBP12F36V-fused O-GlcNAc transferase (OGT), with temporal, magnitude, and reversible control. Overall, the OGTACs represent a promising approach for inducing protein-specific O-GlcNAcylation, thus enabling functional dissection and offering new directions for O-GlcNAc-targeting therapeutic development.

Integrating metagenomic and isolation strategies revealed high contamination of pathogenies and resistome in market shrimps.

This study employs a comprehensive approach combining metagenomic analysis and bacterial isolation to elucidate the microbial composition, antibiotic resistance genes (ARGs), and virulence factors (VFGs) present in shrimps from market and supermarket. Metagenomic analysis of shrimps revealed a dominance of Proteobacteria and Bacteroidetes with Firmicutes notably enriched in some samples. On the other hand, the dominant bacteria isolated included Citrobacter portucalensis, Escherichia coli, Salmonella enterica, Vibrio species and Klebsiella pneumonaie. Metagenomic analysis unveiled a diverse spectrum of 23 main types and 380 subtypes of ARGs in shrimp samples including many clinical significant ARGs such as blaKPC, blaNDM, mcr, tet(X4) etc. Genomic analysis of isolated bacterial strains identified 14 ARG types with 109 subtype genes, which complemented the metagenomic data. Genomic analysis also allowed us to identify a rich amount of MDR plasmids, which provided further insights into the dissemination of resistance genes in different species of bacteria in the same samples. Examination of VFGs and mobile genetic elements (MGEs) in both metagenomic and bacterial genomes revealed a complex landscape of factors contributing to bacterial virulence and genetic mobility. Potential co-occurrence patterns of ARGs and VFGs within human pathogenic bacteria underlined the intricate interplay between antibiotic resistance and virulence. In conclusion, this integrated analysis for the first time provides a comprehensive view and sheds new light on the potential hazards associated with shrimp products in the markets. The findings underscore the necessity of ongoing surveillance and intervention strategies to mitigate risks posed by antibiotic-resistant bacteria in the food supply chain using the novel comprehensive approaches.

Comprehensive genomic and plasmid characterization of multidrug-resistant bacterial strains by R10.4.1 nanopore sequencing.

The escalating prevalence of multidrug-resistant (MDR) bacteria pose a significant public health threat. Understanding the genomic features and deciphering the antibiotic resistance profiles of these pathogens is crucial for development of effective surveillance and treatment strategies. In this study, we employed the R10.4.1 nanopore sequencing technology, specifically through the use of the MinION platform, to analyze eight MDR bacterial strains originating from clinical, ecological and food sources. A single 72-hour sequencing run could yield approximately 12 million reads which covered a total of 34 gigabases (Gbp). The nanopore R10.4.1 data was processed using the Flye assembler, successfully assembling the genomes of eight bacterial strains and their 18 plasmids. Notably, the assemblies generated solely from R10.4.1 nanopore data closely matched those from next-generation sequencing data. Diverse antibiotic resistance patterns and specific resistance genes in the test strains were identified. Hospital strains that exhibited multidrug resistance were found to harbor various resistance genes that encode efflux pumps and extended-spectrum ß-lactamases. Environmental and food sources were found to display resistance profiles in a species-specific manner. The composition of structurally complex plasmids in the test strains could also be revealed by analysis of nanopore long reads, which also suggested evidence of horizontal transfer of plasmids between different bacterial species. These findings provide valuable insights into the genetic characteristics of MDR bacteria and demonstrating the practicality of nanopore sequencing technology for detecting of resistance elements in bacterial pathogens.

Deep Learning Approaches for Imaging-Based Automated Segmentation of Tuberous Sclerosis Complex.

The present study presents a novel approach for identifying epileptogenic tubers in patients with tuberous sclerosis complex (TSC) and automating tuber segmentation using a three-dimensional convolutional neural network (3D CNN). The study retrospectively included 31 TSC patients whose lesions were manually annotated from multiparametric neuroimaging data. Epileptogenic tubers were determined via presurgical evaluation and stereoelectroencephalography recording. Neuroimaging metrics were extracted and compared between epileptogenic and non-epileptogenic tubers. Additionally, five datasets with different preprocessing strategies were used to construct and train 3D CNNs for automated tuber segmentation. The normalized positron emission tomography (PET) metabolic value was significantly lower in epileptogenic tubers defined via presurgical evaluation (p = 0.001). The CNNs showed high performance for localizing tubers, with an accuracy between 0.992 and 0.994 across the five datasets. The automated segmentations were highly correlated with clinician-based features. The neuroimaging characteristics for epileptogenic tubers were demonstrated, increasing surgical confidence in clinical practice. The validated deep learning detection algorithm yielded a high performance in determining tubers with an excellent agreement with reference clinician-based segmentation. Collectively, when coupled with our investigation of minimal input requirements, the approach outlined in this study represents a clinically invaluable tool for the management of TSC.

Identification of mitophagy-related hub genes during the progression of spinal cord injury by integrated multinomial bioinformatics analysis.

Spinal cord injury (SCI) is a disturbance of peripheral and central nerve conduction that causes disability in sensory and motor function. Currently, there is no effective treatment for SCI. Mitophagy plays a vital role in mitochondrial quality control during various physiological and pathological processes. The study aimed to elucidate the role of mitophagy and identify potential mitophagy-related hub genes in SCI pathophysiology. Two datasets (GSE15878 and GSE138637) were analyzed. Firstly, the differentially expressed genes (DEGs) were identified and mitophagy-related genes were obtained from GeneCards, then the intersection between SCI and mitophagy-related genes was determined. Next, we performed gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), protein-protein interaction network (PPI network), least absolute shrinkage and selection operator (LASSO), and cluster analysis to identify and define the hub genes in SCI. Finally, the link between hub genes and infiltrating immune cells was investigated and the potential transcriptional regulation/small molecular compounds to target hub genes were predicted. In total, SKP1 and BAP1 were identified as hub genes of mitophagy-related DEGs during SCI development and regulatory T cells (Tregs)/resting NK cells/activated mast cells may play an essential role in the progression of SCI. LINC00324 and SNHG16 may regulate SKP1 and BAP1, respectively, through miRNAs. Eleven and eight transcriptional factors (TFs) regulate SKP1 and BAP1, respectively, and six small molecular compounds target BAP1. Then, the mRNA expression levels of BAP1 and SKP1 were detected in the injured sites of spinal cord of SD rats at 6 h and 72 h after injury using RT-qPCR, and found that the level were decreased. Therefore, the pathways of mitophagy are downregulated during the pathophysiology of SCI, and SKP1 and BAP1 could be accessible targets for diagnosing and treating SCI.

Population pharmacokinetic approach to guide personalized sertraline treatment in Chinese patients.

Object: Sertraline is a first-line SSRI for the treatment of depression and has the same effectiveness along with a superior safety profile compared to other medications. There are few population pharmacokinetic (PPK) studies of sertraline and a lack of studies in the Chinese population. Therefore, we performed a PPK analysis of Chinese patients treated with sertraline to identify factors that can influence drug exposure. In addition, the dosing and discontinuation regimen of sertraline when applied to adolescents was explored. Methods: Sertraline serum drug concentration data were collected from 140 hospitalized patients to generate a sertraline PPK dataset, and data evaluation and examination of the effects of covariates on drug exposure in the final model were performed using nonlinear mixed-effects models (NONMEM) and first-order conditional estimation with interaction (FOCE-I). Examining rational medication administration and rational withdrawal of sertraline based on significant covariates and final modeling. Results: A one-compartment model with first-order absorption and elimination of sertraline was developed for Chinese patients with psychiatric disorders. Analysis of covariates revealed that age was a covariate that significantly affected sertraline CL/F (P < 0.01) and that sertraline clearance decreased progressively with aging, whereas other factors had no effect on CL/F and V/F of sertraline. In the age range of 11-79, there were 54 adolescent patients (about 1/3) aged 13-18 years, and the safe and effective optimal daily dose for adolescent patients based on the final model simulations was 50-250 mg/d. For adolescent patients, serum concentration fluctuations were moderate for OD doses of 50 mg and 100 mg, using a fixed dose-descent regimen. For patients with OD doses of 150-200 mg and BID doses of 100-200 mg, a more gradual decrease in serum concentration was achieved with a fixed dose interval of 7 or 14 days for 25 mg as the regimen of descent. Conclusions: To our knowledge, this may be the first PPK study of sertraline in Chinese patients. We found that age was an important factor affecting clearance in Chinese patients taking sertraline. Patients taking sertraline may be exposed to increased amounts of sertraline due to decreased clearance with increasing age. The rational dosing and safe discontinuation of sertraline in adolescent patients can be appropriately referenced to the results of the model simulation, thus providing assistance for individualized dosing in adolescents.

Effects of Kinesio taping on lower limb biomechanical characteristics during unexpected jumping in patients with chronic ankle instability.

PURPOSE: The current biomechanical research on the application of Kinesio taping (KT) to patients with chronic ankle instability (CAI) has focused on testing the expected movements. However, unexpected movements are more common in actual sports. Therefore, the present study aimed to investigate the effects of KT on the biomechanical characteristics of the knee and ankle joints during unexpected jumping movements. METHODS: Twenty-one patients with unilateral CAI were recruited to capture the biomechanical parameters during unexpected jumping movements under different interventions: no taping (NT), placebo taping (PT), and KT. A one-way repeated measures analysis of variance was used to compare the differences in knee and ankle biomechanical characteristics among patients with CAI between the three intervention conditions. RESULTS: At initial contact, the KT group demonstrated a significant decrease in ankle plantarflexion and knee flexion angles compared to the NT group (p < 0.05). At the early landing phase, the KT group had a significant increase in peak ankle dorsiflexion angle, peak ankle eversion angle, peak ankle dorsiflexion moment, and peak ankle eversion moment compared to the NT and PT groups (p < 0.05). Furthermore, the KT group had a significantly reduced peak knee flexion angle, peak knee eversion angle, and peak vertical ground reaction force (p < 0.05) compared to the NT and PT groups. CONCLUSION: KT significantly improves the sprain-prone touchdown posture of patients with CAI. And reducing the risk of ankle sprains during the early landing phase by promoting ankle dorsiflexion and eversion angles and moments.

Localizing seizure onset zone by a cortico-cortical evoked potentials-based machine learning approach in focal epilepsy.

OBJECTIVE: We aimed to develop a new approach for identifying the localization of the seizure onset zone (SOZ) based on corticocortical evoked potentials (CCEPs) and to compare the connectivity patterns in patients with different clinical phenotypes. METHODS: Fifty patients who underwent stereoelectroencephalography and CCEP procedures were included. Logistic regression was used in the model, and six CCEP metrics were input as features: root mean square of the first peak (N1RMS) and second peak (N2RMS), peak latency, onset latency, width duration, and area. RESULTS: The area under the curve (AUC) for localizing the SOZ ranged from 0.88 to 0.93. The N1RMS values in the hippocampus sclerosis (HS) group were greater than that of the focal cortical dysplasia (FCD) IIa group (p < 0.001), independent of the distance between the recorded and stimulated sites. The sensitivity of localization was higher in the seizure-free group than in the non-seizure-free group (p = 0.036). CONCLUSIONS: This new method can be used to predict the SOZ localization in various focal epilepsy phenotypes. SIGNIFICANCE: This study proposed a machine-learning approach for localizing the SOZ. Moreover, we examined how clinical phenotypes impact large-scale abnormality of the epileptogenic networks.

Utilization of nanopore direct RNA sequencing to analyze viral RNA modifications.

Modifications on viral RNAs (vRNAs), either genomic RNAs or RNA transcripts, have complex effects on the viral life cycle and cellular responses to viral infection. The advent of Oxford Nanopore Technologies Direct RNA Sequencing provides a new strategy for studying RNA modifications. To this end, multiple computational tools have been developed, but a systemic evaluation of their performance in mapping vRNA modifications is lacking. Here, 10 computational tools were tested using the Sindbis virus (SINV) RNAs isolated from infected mammalian (BHK-21) or mosquito (C6/36) cells, with in vitro-transcribed RNAs serving as modification-free control. Three single-mode approaches were shown to be inapplicable in the viral context, and three out of seven comparative methods required cutoff adjustments to reduce false-positive predictions. Utilizing optimized cutoffs, an integrated analysis of comparative tools suggested that the intersected predictions of Tombo_com and xPore were significantly enriched compared with the background. Consequently, a pipeline integrating Tombo_com and xPore was proposed for vRNA modification detection; the performance of which was supported by N6-methyladenosine prediction in severe acute respiratory syndrome coronavirus 2 RNAs using publicly available data. When applied to SINV RNAs, this pipeline revealed more intensive modifications in subgenomic RNAs than in genomic RNAs. Modified uridines were frequently identified, exhibiting substantive overlapping between vRNAs generated in different cell lines. On the other hand, the interpretation of other modifications remained unclear, underlining the limitations of the current computational tools despite their notable potential.IMPORTANCEComputational approaches utilizing Oxford Nanopore Technologies Direct RNA Sequencing data were almost exclusively designed to map eukaryotic epitranscriptomes. Therefore, extra caution must be exercised when using these tools to detect vRNA modifications, as in most cases, vRNA modification profiles should be regarded as unknown epitranscriptomes without prior knowledge. Here, we comprehensively evaluated the performance of 10 computational tools in detecting vRNA modification sites. All tested single-mode methods failed to differentiate native and in vitro-transcribed samples. Using optimized cutoff values, seven tested comparative tools generated very different predictions. An integrated analysis showed significant enrichment of Tombo_com and xPore predictions against the background. A pipeline for vRNA modification detection was proposed accordingly and applied to Sindbis virus RNAs. In conclusion, our study underscores the need for the careful application of computational tools to analyze viral epitranscriptomics. It also offers insights into alphaviral RNA modifications, although further validation is required.

Hypometabolic patterns are related to post-surgical seizure outcomes in focal cortical dysplasia: A semi-quantitative study.

OBJECTIVE: Fluorine-18-fluorodeoxyglucose-positron emission tomography (FDG-PET) is routinely used for presurgical evaluation in many epilepsy centers. Hypometabolic characteristics have been extensively examined in prior studies, but the metabolic patterns associated with specific pathological types of drug-resistant epilepsy remain to be fully defined. This study was developed to explore the relationship between metabolic patterns or characteristics and surgical outcomes in type I and II focal cortical dysplasia (FCD) patients based on results from a large cohort. METHODS: Data from individuals who underwent epilepsy surgery from 2014 to 2019 with a follow-up duration of over 3 years and a pathological classification of type I or II FCD in our hospital were retrospectively analyzed. Hypometabolic patterns were quantitatively identified via statistical parametric mapping (SPM) and qualitatively analyzed via visual examination of PET-MRI co-registration images. Univariate analyses were used to explore the relationship between metabolic patterns and surgical outcomes. RESULTS: In total, this study included data from 210 patients. Following SPM calculations, four hypometabolic patterns were defined including unilobar, multi-lobar, and remote patterns as well as cases where no pattern was evident. In type II FCD patients, the unilobar pattern was associated with the best surgical outcomes (p = 0.014). In visual analysis, single gyrus (p = 0.032) and Clear-cut hypometabolism edge (p = 0.040) patterns exhibited better surgery outcomes in the type II FCD group. CONCLUSIONS: PET metabolic patterns are well-correlated with the prognosis of type II FCD patients. However, similar correlations were not observed in type I FCD, potentially owing to the complex distribution of the epileptogenic region. PLAIN LANGUAGE SUMMARY: In this study, we demonstrated that FDG-PET was a crucial examination for patients with FCD, which was a common cause of epilepsy. We compared the surgical prognosis for patients with different hypometabolism distribution patterns and found that clear and focal abnormal region in PET was correlated with good surgical outcome in type II FCD patients.

Factors influencing concentrations of risperidone and 9-hydroxyrisperidone in psychiatric outpatients taking immediate-release formulations of risperidone.

OBJECTIVES: To analyze the factors affecting the concentrations of the active moiety of risperidone (RIS) and its active metabolite 9-hydroxyrisperidone (9-OH-RIS) in psychiatric outpatients taking immediate-release formulations. METHODS: This is a retrospective study on the therapeutic drug monitoring (TDM) data regarding RIS and 9-OH-RIS in adult psychiatric outpatients. TDM data with simultaneous RIS and 9-OH-RIS monitoring from March 2018 to February 2020 and relevant medical records (including dosage, dosage form, sex, age, diagnosis, combined medication, and comorbid disease) from 399 adult psychiatric outpatients (223 males and 176 females) were included in this study. RESULTS: The daily dose of RIS was 5.56 ± 2.05 mg, the concentration of total active moiety was 42.35 ± 25.46 ng/mL, and the dose-adjusted plasma concentration (C/D) of active moiety was 7.83 ± 3.87 (ng/ml)/(mg/day). Dose, sex, and age were identified as important factors influencing concentrations of RIS and 9-OH-RIS in adult psychiatric outpatients. CONCLUSIONS: Individualized medication adjustments should be made according to the specific conditions of psychiatric outpatients. The findings strongly support the use of TDM to guide dosing decisions in psychiatric outpatients taking RIS.

Global genomic profiling of Klebsiella pneumoniae: A spatio-temporal population structure analysis.

Klebsiella pneumoniae is an important clinical bacterial pathogen that has hypervirulent and multidrug-resistant variants. Uniform Manifold Approximation and Projection (UMAP) was used to cluster genomes of 16 797 K. pneumoniae strains collected, based on core genome distance, in over 100 countries during the period 1937 to 2021. A total of 60 high-density genetic clusters of strains representing the major epidemic strains were identified among these strains. Using UMAP bedding, the relationship between genetic cluster, capsular polysaccharide (KL) types and sequence type (ST) of the strains was clearly demonstrated, with some important STs, such as ST11 and ST258, found to contain multiple clusters. Strains within the same cluster often exhibited significant diverse features, such as originating from different areas and being isolated in different years, as well as carriage of different resistance and virulence genes. These data enable the routes of evolution of the globally prevalent K. pneumoniae strains to be traced. Alarmingly, carbapenem-resistant K. pneumoniae strains accounted for 51.7% of the test strains and worldwide transmission was observed. Carbapenem-resistant and hypervirulent K. pneumoniae strains are mainly reported in China; however, these strains are increasingly reported in other parts of the world. Also identified in this study were several key genetic loci that facilitate development of a new K. pneumoniae typing method to differentiate between high- and low-risk strains. In particular, the acrR, ompK35 and hha genes were predicted to play a key role in expression of the resistance and virulence phenotypes.

Magnetic resonance-guided laser interstitial thermal therapy vs. open surgery for drug-resistant mesial temporal lobe epilepsy: a propensity score matched retrospective cohort study.

BACKGROUND: Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) and traditional open surgery (OS) are effective and safe options for patients with drug-resistant mesial temporal lobe epilepsy (DR-mTLE). However, their superiority in seizure control and preservation of functional abilities remains unclear. This study aimed to compare the surgical outcomes of MRgLITT and OS. MATERIALS AND METHODS: This multicenter retrospective cohort study included patients with DR-mTLE who underwent MRgLITT or OS at three centres between 2015 and 2023. The data on patient demographics, presurgical non-invasive evaluation, stereoelectroencephalography (SEEG) implantation, memory alteration, and seizure outcomes were collected. Propensity score matching (PSM) analysis was conducted for the comparison of seizure control and functional preservation between two surgical approaches. RESULTS: Of the 244 individuals who met the study criteria, 33 underwent MRgLITT and 211 OS. The median (interquartile range) age at seizure onset was 22.0 (13.0) and 12.3 (10.0) years in the MRgLITT and OS groups, respectively. The first PSM, based on demographic and non-invasive information, resulted in 26 matched pairs for the primary analysis. There were no significant differences in memory preservation ( P = 0.95) or surgical outcomes ( P = 0.96) between the groups. The second PSM, based on demographics and SEEG implantation, yielded 32 matched pairs for the sensitivity analysis, showing similar results. Subset analysis of early and late MRgLITT cases revealed no statistically significant differences in the proportion of patients with memory decline ( P = 0.42) or seizure control ( P = 1.00). Patients who underwent SEEG implantation were 96% less likely to achieve seizure freedom after MRgLITT ( P = 0.02). CONCLUSION: Minimally invasive MRgLITT is associated with memory preservation and seizure control, similar to traditional OS. MRgLITT is effective and safe for DR-mTLE and is relevant for future prospective randomized trials on dominant-side mTLE, providing practical implications for guiding neurosurgeons in the selection of surgical approaches.

Neural network mapping of gelastic behavior in children with hypothalamus hamartoma.

BACKGROUND: Hypothalamus hamartomas (HHs) are rare, congenital, tumor-like, and nonprogressive malformations resulting in drug-resistant epilepsy, mainly affecting children. Gelastic seizures (GS) are an early hallmark of epilepsy with HH. The aim of this study was to explore the disease progression and the underlying physiopathological mechanisms of pathological laughter in HH. METHODS: We obtained clinical information and metabolic images of 56 HH patients and utilized ictal semiology evaluation to stratify the specimens into GS-only, GS-plus, and no-GS subgroups and then applied contrasted trajectories inference (cTI) to calculate the pseudotime value and evaluate GS progression. Ordinal logistic regression was performed to identify neuroimaging-clinical predictors of GS, and then voxelwise lesion network-symptom mapping (LNSM) was applied to explore GS-associated brain regions. RESULTS: cTI inferred the specific metabolism trajectories of GS progression and revealed increased complexity from GS to other seizure types. This was further validated via actual disease duration (Pearson R = 0.532, P = 0.028). Male sex [odds ratio (OR) = 2.611, P = 0.013], low age at seizure onset (OR = 0.361, P = 0.005), high normalized HH metabolism (OR = - 1.971, P = 0.037) and severe seizure burden (OR = - 0.006, P = 0.032) were significant neuroimaging clinical predictors. LNSM revealed that the dysfunctional cortico-subcortico-cerebellar network of GS and the somatosensory cortex (S1) represented a negative correlation. CONCLUSIONS: This study sheds light on the clinical characteristics and progression of GS in children with HH. We identified distinct subtypes of GS and demonstrated the involvement of specific brain regions at the cortical-subcortical-cerebellar level. These valuable results contribute to our understanding of the neural correlates of GS.

Synthesis of peptidomimetics as antibiotic adjuvants for combination with aztreonam to combat MDR Pseudomonas aeruginosa.

Pseudomonas aeruginosa is one of the multipledrug-resistant (MDR) Gram-negative pathogens with few drugs available for treatment. Antibiotic adjuvant approach provides an alternative and complementary strategy. In this study, the stereo-structure-activity relationship of monobactams against MDR Gram-negative organisms was extended. Meanwhile, a series of novel peptidemimetic derivatives as antibiotic adjuvants was synthesized and evaluated for their synergistic effects with aztreonam (AZT) against P. aeruginosa, using dipeptide PAßN as the lead. Among the analogues, compound 22j showed a significant synergistic effect against MDR P. aeruginosa in vitro and in vivo, presumably through the mechanism of affecting the permeability of outer membrane. Thus, we identified 22j as a novel peptidemimetic lead compound to potentiate the activity of AZT against MDR P. aeruginosa, which is worthy of further development as antibiotic adjuvant candidates.

A Simplified and Ultrafast Pipeline for Site-Specific Quantitative Chemical Proteomics.

Activity-based proteome profiling (ABPP) is a powerful chemoproteomic technology for global profiling of protein activity and modifications. The tandem orthogonal proteolysis-ABPP (TOP-ABPP) strategy utilizes a clickable enrichment tag with cleavable linkers to enable direct identification of probe-labeled residue sites within the target proteins. However, such a site-specific chemoproteomic workflow requires a long operation time and complex sample preparation procedures, limiting its wide applications. In the current study, we developed a simplified and ultrafast peptide enrichment and release TOP-ABPP ("superTOP-ABPP") pipeline for site-specific quantitative chemoproteomic analysis with special agarose resins that are functionalized with azide groups and acid-cleavable linkers. The azide groups allow enrichment of peptides that are labeled by the alkynyl probe through a one-step click reaction, which can be conveniently released by acid cleavage for subsequent LC-MS/MS analysis. In comparison with the traditional TOP-ABPP method, superTOP-ABPP cuts down the averaged sample preparation time from 25 to 9 h, and significantly improves the sensitivity and coverage of site-specific cysteinome profiling. The method can also be seamlessly integrated with reductive dimethylation to enable quantitative chemoproteomic analysis with a high accuracy. The simplified and ultrafast superTOP-ABPP will become a valuable tool for site-specific quantitative chemoproteomic studies.

Altered Metabolic Networks in Mesial Temporal Lobe Epilepsy with Focal to Bilateral Seizures.

This study was designed to identify whether the metabolic network changes in mesial temporal lobe epilepsy (MTLE) patients with focal to bilateral tonic-clonic seizures (FBTCS) differ from changes in patients without FBTCS. This retrospective analysis enrolled 30 healthy controls and 54 total MTLE patients, of whom 27 had FBTCS. Fluorodeoxyglucose positron emission tomography (FDG-PET) data and graph theoretical analyses were used to examine metabolic connectivity. The differences in metabolic networks between the three groups were compared. Significant changes in both local and global network topology were evident in FBTCS+ patients as compared to healthy controls, with a lower assortative coefficient and altered betweenness centrality in 15 brain regions. While global network measures did not differ significantly when comparing FBTCS- patients to healthy controls, alterations in betweenness centrality were evident in 13 brain regions. Significantly altered betweenness centrality was also observed in four brain regions when comparing patients with and without FBTCS. The study revealed greater metabolic network abnormalities in MTLE patients with FBTCS as compared to FBTCS- patients, indicating the existence of distinct epileptogenic networks. These findings can provide insight into the pathophysiological basis of FBTCS.

Additive Conformational Engineering To Improve the PbI2 Framework for Efficient and Stable Perovskite Solar Cells.

The PbI2 framework is critical for two-step fabricated perovskite solar cells. This study investigates the effects of introducing two functional urea-based molecules, biuret (BU) and dithiobiuret (DTBU), into the PbI2 precursor solution on the absorber layer and overall device performance. BU, which contains C═O, enhanced device performance and stability, whereas DTBU, which contains C═S, had negative effects. Research analysis revealed the differences in the spatial structures of the two urea-based molecules. The introduction of symmetrical BU molecules facilitated the crystallization of PbI2, whereas the introduction of DTBU with a twisted molecular structure led to inferior crystallization performance of PbI2. The perovskite thin film, obtained by introducing BU into the PbI2 precursor solution, demonstrated superior performance, characterized by a decreased defect density and an extended carrier lifetime. The device performance and stability were enhanced, resulting in higher open-circuit voltage and fill factor. The highest achieved power conversion efficiency was 23.50%. After 1300 h of storage under unpackaged conditions at 30-40% humidity, the devices maintained 93% of their initial efficiency. Conversely, the devices prepared with DTBU doping exhibited inferior performance and stability, displaying power conversion efficiency below 10% and faster degradation under the same humidity conditions.