Olfactory-trigeminal integration in the primary olfactory cortex.

Humans naturally integrate signals from the olfactory and intranasal trigeminal systems. A tight interplay has been demonstrated between these two systems, and yet the neural circuitry mediating olfactory-trigeminal (OT) integration remains poorly understood. Using functional magnetic resonance imaging (fMRI), combined with psychophysics, this study investigated the neural mechanisms underlying OT integration. Fifteen participants with normal olfactory function performed a localization task with air-puff stimuli, phenylethyl alcohol (PEA; rose odor), or a combination thereof while being scanned. The ability to localize PEA to either nostril was at chance. Yet, its presence significantly improved the localization accuracy of weak, but not strong, air-puffs, when both stimuli were delivered concurrently to the same nostril, but not when different nostrils received the two stimuli. This enhancement in localization accuracy, exemplifying the principles of spatial coincidence and inverse effectiveness in multisensory integration, was associated with multisensory integrative activity in the primary olfactory (POC), orbitofrontal (OFC), superior temporal (STC), inferior parietal (IPC) and cingulate cortices, and in the cerebellum. Multisensory enhancement in most of these regions correlated with behavioral multisensory enhancement, as did increases in connectivity between some of these regions. We interpret these findings as indicating that the POC is part of a distributed brain network mediating integration between the olfactory and trigeminal systems. PRACTITIONER POINTS: Psychophysical and neuroimaging study of olfactory-trigeminal (OT) integration. Behavior, cortical activity, and network connectivity show OT integration. OT integration obeys principles of inverse effectiveness and spatial coincidence. Behavioral and neural measures of OT integration are correlated.

Hotspots of wetland loss to impervious surfaces in the conterminous United States.

In this study, a first wall-to-wall comparison between the National Wetlands Inventory (NWI) and the National Land Cover Database (NLCD) was conducted across the entire conterminous United States (CONUS) to evaluate U.S. wetland loss conditions. Annually, around 26 km2 of wetlands are lost to impervious surfaces across the CONUS. Spatially, wetland loss is not evenly distributed, with 90 % of losses occurring in only 9 % of the land area, forming hotspots around expanding urban regions such as Houston, Jacksonville, and Naples. Over the past few decades, Florida experienced the highest wetland loss (5.73 km2/year) among all states, while Houston had the most wetland loss (2.54 km2/year) among all metropolitan regions. Stepwise multiple regression models identified population growth and its associated demand for new housing as the major drivers for wetland loss. Wetland loss per population increase is the highest (>15 m2/person) in most metropolitan regions around the East Coast and Gulf of Mexico. Unfortunately, current wetland loss hotspots will likely suffer further losses in future decades due to projected population growth, with Houston, Cape Coral, and Miami metropolitan regions having the greatest projected wetland loss of 89.15 km2, 34.35 km2, and 28.20 km2, respectively. This study has identified wetland loss hotspots and their drivers across the U.S. that were not possible in previous sample-based studies. The findings are critical in wetland management and protection across the U.S.

Altered regional brain activity and functional connectivity in primary intravaginal anejaculation patients revealed by resting-state fMRI.

ABSTRACT: Ejaculation is regulated by the central nervous system. However, the central pathophysiology of primary intravaginal anejaculation (PIAJ) is unclear. The present study aimed to examine the changes in regional brain activity and functional connectivity underlying PIAJ. A total of 20 PIAJ patients and 16 healthy controls (HCs) were enrolled from September 2020 to September 2022 in the Department of Andrology, Nanjing Drum Tower Hospital (Nanjing, China). Magnetic resonance imaging data were acquired from all participants and then were preprocessed. The measures of fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) were calculated and compared between the groups. PIAJ patients showed increased fALFF values in the left precuneus compared with HCs. Additionally, PIAJ patients showed increased ReHo values in the left precuneus, left postcentral gyrus, left superior occipital gyrus, left calcarine fissure, right precuneus, and right middle temporal gyrus, and decreased ReHo values in the left inferior parietal gyrus, compared with HCs. Finally, brain regions with altered fALFF and ReHo values in PIAJ patients showed increased FC with widespread cortical regions, which included the frontal, parietal, temporal, and occipital regions, compared with HCs. In conclusion, increased regional brain activity in the parietal, temporal, and occipital regions, and increased FC between these brain regions, may be associated with PIAJ occurrence.

Synthesis and characterization of low-dimensional N-heterocyclic carbene lattices.

The covalent interaction of N-heterocyclic carbenes (NHCs) with transition metal atoms gives rise to distinctive frontier molecular orbitals (FMOs). These emergent electronic states have spurred the widespread adoption of NHC ligands in chemical catalysis and functional materials. Although formation of carbene-metal complexes in self-assembled monolayers on surfaces has been explored, design and electronic structure characterization of extended low-dimensional NHC-metal lattices remains elusive. Here we demonstrate a modular approach to engineering one-dimensional (1D) metal-organic chains and two-dimensional (2D) Kagome lattices using the FMOs of NHC-Au-NHC junctions to create low-dimensional molecular networks exhibiting intrinsic metallicity. Scanning tunneling spectroscopy and first-principles density functional theory reveal the contribution of C-Au-C π-bonding states to dispersive bands that imbue 1D- and 2D-NHC lattices with exceptionally small work functions.

Regioselective On-Surface Synthesis of [3]Triangulene Graphene Nanoribbons.

The integration of low-energy states into bottom-up engineered graphene nanoribbons (GNRs) is a robust strategy for realizing materials with tailored electronic band structure for nanoelectronics. Low-energy zero-modes (ZMs) can be introduced into nanographenes (NGs) by creating an imbalance between the two sublattices of graphene. This phenomenon is exemplified by the family of [n]triangulenes (n ∈ N). Here, we demonstrate the synthesis of [3]triangulene-GNRs, a regioregular one-dimensional (1D) chain of [3]triangulenes linked by five-membered rings. Hybridization between ZMs on adjacent [3]triangulenes leads to the emergence of a narrow band gap, Eg,exp ∼ 0.7 eV, and topological end states that are experimentally verified using scanning tunneling spectroscopy. Tight-binding and first-principles density functional theory calculations within the local density approximation corroborate our experimental observations. Our synthetic design takes advantage of a selective on-surface head-to-tail coupling of monomer building blocks enabling the regioselective synthesis of [3]triangulene-GNRs. Detailed ab initio theory provides insights into the mechanism of on-surface radical polymerization, revealing the pivotal role of Au-C bond formation/breakage in driving selectivity.

Prediction of false-positive PI-RADS 5 lesions on prostate multiparametric MRI: development and internal validation of a clinical-radiological characteristics based nomogram.

BACKGROUND: To develop a risk model including clinical and radiological characteristics to predict false-positive The Prostate Imaging Reporting and Data System (PI-RADS) 5 lesions. METHODS: Data of 612 biopsy-naïve patients who had undergone multiparametric magnetic resonance imaging (mpMRI) before prostate biopsy were collected. Clinical variables and radiological variables on mpMRI were adopted. Lesions were divided into the training and validation cohort randomly. Stepwise multivariate logistic regression analysis with backward elimination was performed to screen out variables with significant difference. A diagnostic nomogram was developed in the training cohort and further validated in the validation cohort. Calibration curve and receiver operating characteristic (ROC) analysis were also performed. RESULTS: 296 PI-RADS 5 lesions in 294 patients were randomly divided into the training and validation cohort (208 : 88). 132 and 56 lesions were confirmed to be clinically significant prostate cancer in the training and validation cohort respectively. The diagnostic nomogram was developed based on prostate specific antigen density, the maximum diameter of lesion, zonality of lesion, apparent diffusion coefficient minimum value and apparent diffusion coefficient minimum value ratio. The C-index of the model was 0.821 in the training cohort and 0.871 in the validation cohort. The calibration curve showed good agreement between the estimation and observation in the two cohorts. When the optimal cutoff values of ROC were 0.288 in the validation cohort, the sensitivity, specificity, PPV, and NPV were 90.6%, 67.9%, 61.7%, and 92.7% in the validation cohort, potentially avoiding 9.7% unnecessary prostate biopsies. CONCLUSIONS: We developed and validated a diagnostic nomogram by including 5 factors. False positive PI-RADS 5 lesions could be distinguished from clinically significant ones, thus avoiding unnecessary prostate biopsy.

Olfactory deficit: a potential functional marker across the Alzheimer's disease continuum.

Alzheimer's disease (AD) is a prevalent form of dementia that affects an estimated 32 million individuals globally. Identifying early indicators is vital for screening at-risk populations and implementing timely interventions. At present, there is an urgent need for early and sensitive biomarkers to screen individuals at risk of AD. Among all sensory biomarkers, olfaction is currently one of the most promising indicators for AD. Olfactory dysfunction signifies a decline in the ability to detect, identify, or remember odors. Within the spectrum of AD, impairment in olfactory identification precedes detectable cognitive impairments, including mild cognitive impairment (MCI) and even the stage of subjective cognitive decline (SCD), by several years. Olfactory impairment is closely linked to the clinical symptoms and neuropathological biomarkers of AD, accompanied by significant structural and functional abnormalities in the brain. Olfactory behavior examination can subjectively evaluate the abilities of olfactory identification, threshold, and discrimination. Olfactory functional magnetic resonance imaging (fMRI) can provide a relatively objective assessment of olfactory capabilities, with the potential to become a promising tool for exploring the neural mechanisms of olfactory damage in AD. Here, we provide a timely review of recent literature on the characteristics, neuropathology, and examination of olfactory dysfunction in the AD continuum. We focus on the early changes in olfactory indicators detected by behavioral and fMRI assessments and discuss the potential of these techniques in MCI and preclinical AD. Despite the challenges and limitations of existing research, olfactory dysfunction has demonstrated its value in assessing neurodegenerative diseases and may serve as an early indicator of AD in the future.

The Value of 68Ga-PSMA PET/MRI for Classifying Patients with PI-RADS 3 Lesions on Multiparametric MRI: A Prospective Single-Center Study.

Prostate Imaging Reporting and Data System (PI-RADS) category 3 lesions remain a diagnostic challenge for detecting clinically significant prostate cancer (csPCa). This article evaluates the added value of 68Ga-labeled prostate-specific membrane antigen-11 (68Ga-PSMA) PET/MRI in classifying PI-RADS 3 lesions to avoid unnecessary biopsies. Methods: Sixty biopsy-naïve men with PI-RADS 3 lesions on multiparametric MRI were prospectively enrolled between February 2020 and October 2022. In all, 56 participants underwent 68Ga-PSMA PET/MRI and prostate systematic biopsy. 68Ga-PSMA PET/MRI was independently evaluated and reported by the 5-level PRIMARY score developed within the PRIMARY trial. Receiver-operating-characteristic curve analysis was used to estimate the diagnostic performance. Results: csPCa was detected in 8 of 56 patients (14.3%). The proportion of patients with csPCa and a PRIMARY score of 1, 2, 3, 4, and 5 was 0% (0/12), 0% (0/13), 6.3% (1/16), 38.5% (5/13), and 100% (2/2), respectively. The estimated area under the curve of the PRIMARY score was 0.91 (95% CI, 0.817-0.999). For a PRIMARY score of 4-5 versus a PRIMARY score of 1-3, the sensitivity, specificity, positive predictive value, and negative predictive value were 87.5%, 83.3%, 46.7%, and 97.5%, respectively. With a PRIMARY score of at least 4 to make a biopsy decision in men with PI-RADS 3 lesions, 40 of 48 patients (83.3%) could avoid unnecessary biopsies, at the expense of missing 1 of 8 (12.5%) csPCa cases. Conclusion: 68Ga-PSMA PET/MRI has great potential to classify patients with PI-RADS 3 lesions and help avoid unnecessary biopsies.

Multiomics identifies metabolic subtypes based on fatty acid degradation allocating personalized treatment in hepatocellular carcinoma.

BACKGROUND AND AIMS: Molecular classification is a promising tool for prognosis prediction and optimizing precision therapy for HCC. Here, we aimed to develop a molecular classification of HCC based on the fatty acid degradation (FAD) pathway, fully characterize it, and evaluate its ability in guiding personalized therapy. APPROACH AND RESULTS: We performed RNA sequencing (RNA-seq), PCR-array, lipidomics, metabolomics, and proteomics analysis of 41 patients with HCC, in which 17 patients received anti-programmed cell death-1 (PD-1) therapy. Single-cell RNA sequencing (scRNA-seq) was performed to explore the tumor microenvironment. Nearly, 60 publicly available multiomics data sets were analyzed. The associations between FAD subtypes and response to sorafenib, transarterial chemoembolization (TACE), immune checkpoint inhibitor (ICI) were assessed in patient cohorts, patient-derived xenograft (PDX), and spontaneous mouse model ls. A novel molecular classification named F subtype (F1, F2, and F3) was identified based on the FAD pathway, distinguished by clinical, mutational, epigenetic, metabolic, and immunological characteristics. F1 subtypes exhibited high infiltration with immunosuppressive microenvironment. Subtype-specific therapeutic strategies were identified, in which F1 subtypes with the lowest FAD activities represent responders to compounds YM-155 and Alisertib, sorafenib, anti-PD1, anti-PD-L1, and atezolizumab plus bevacizumab (T + A) treatment, while F3 subtypes with the highest FAD activities are responders to TACE. F2 subtypes, the intermediate status between F1 and F3, are potential responders to T + A combinations. We provide preliminary evidence that the FAD subtypes can be diagnosed based on liquid biopsies. CONCLUSIONS: We identified 3 FAD subtypes with unique clinical and biological characteristics, which could optimize individual cancer patient therapy and help clinical decision-making.

Abnormal cortical surface-based spontaneous and functional connectivity in the whole brain in lifelong premature ejaculation patients.

Recent research has highlighted structural and functional abnormalities in the cerebral cortex of patients with premature ejaculation (PE). These anomalies could play a pivotal role in the physiological mechanisms underlying PE. This study leveraged functional magnetic resonance imaging (fMRI), a noninvasive technique, to explore these neural mechanisms. We conducted resting-state fMRI scans on 36 PE patients and 22 healthy controls (HC), and collected data on Premature Ejaculation Diagnostic Tool (PEDT) scores and intravaginal ejaculation latency time (IELT). Employing a surface-based regional homogeneity (ReHo) approach, we analyzed local neural synchronous spontaneous activity, diverging from previous studies that utilized a volume-based ReHo method. Areas with significant ReHo differences between PE and HC groups underwent surface-based functional connectivity (FC) analysis. Significant discrepancies in ReHo and FC across the cortical surface were observed in the PE cohort. Notably, PE patients exhibited decreased ReHo in the left triangular inferior frontal gyrus and enhanced ReHo in the right middle frontal gyrus. The latter showed heightened connectivity with the left lingual gyrus and the right orbital superior frontal gyrus. Furthermore, a correlation between ReHo and FC values with PEDT scores and IELT was found in the PE group. Our findings, derived from surface-based fMRI data, underscore specific brain regions linked to the neurobiological underpinnings of PE.

Sparse-to-dense coarse-to-fine depth estimation for colonoscopy.

Colonoscopy, as the golden standard for screening colon cancer and diseases, offers considerable benefits to patients. However, it also imposes challenges on diagnosis and potential surgery due to the narrow observation perspective and limited perception dimension. Dense depth estimation can overcome the above limitations and offer doctors straightforward 3D visual feedback. To this end, we propose a novel sparse-to-dense coarse-to-fine depth estimation solution for colonoscopic scenes based on the direct SLAM algorithm. The highlight of our solution is that we utilize the scattered 3D points obtained from SLAM to generate accurate and dense depth in full resolution. This is done by a deep learning (DL)-based depth completion network and a reconstruction system. The depth completion network effectively extracts texture, geometry, and structure features from sparse depth along with RGB data to recover the dense depth map. The reconstruction system further updates the dense depth map using a photometric error-based optimization and a mesh modeling approach to reconstruct a more accurate 3D model of colons with detailed surface texture. We show the effectiveness and accuracy of our depth estimation method on near photo-realistic challenging colon datasets. Experiments demonstrate that the strategy of sparse-to-dense coarse-to-fine can significantly improve the performance of depth estimation and smoothly fuse direct SLAM and DL-based depth estimation into a complete dense reconstruction system.

Reconfiguration of brain network dynamics underlying spatial deficits in subjective cognitive decline.

Brain dynamics and the associations with spatial navigation in individuals with subjective cognitive decline (SCD) remain unknown. In this study, a hidden Markov model (HMM) was inferred from resting-state functional magnetic resonance imaging data in a cohort of 80 SCD and 77 normal control (NC) participants. By HMM, 12 states with distinct brain activity were identified. The SCD group showed increased fractional occupancy in the states with less activated ventral default mode, posterior salience, and visuospatial networks, while decreased fractional occupancy in the state with general network activation. The SCD group also showed decreased probabilities of transition into and out of the state with general network activation, suggesting an inability to dynamically upregulate and downregulate brain network activity. Significant correlations between brain dynamics and spatial navigation were observed. The combined features of spatial navigation and brain dynamics showed an area under the curve of 0.854 in distinguishing between SCD and NC. The findings may provide exploratory evidence of the reconfiguration of brain network dynamics underlying spatial deficits in SCD.

Spatial navigation is associated with subcortical alterations and progression risk in subjective cognitive decline.

BACKGROUND: Subjective cognitive decline (SCD) may serve as a symptomatic indicator for preclinical Alzheimer's disease; however, SCD is a heterogeneous entity regarding clinical progression. We aimed to investigate whether spatial navigation could reveal subcortical structural alterations and the risk of progression to objective cognitive impairment in SCD individuals. METHODS: One hundred and eighty participants were enrolled: those with SCD (n = 80), normal controls (NCs, n = 77), and mild cognitive impairment (MCI, n = 23). SCD participants were further divided into the SCD-good (G-SCD, n = 40) group and the SCD-bad (B-SCD, n = 40) group according to their spatial navigation performance. Volumes of subcortical structures were calculated and compared among the four groups, including basal forebrain, thalamus, caudate, putamen, pallidum, hippocampus, amygdala, and accumbens. Topological properties of the subcortical structural covariance network were also calculated. With an interval of 1.5 years ± 12 months of follow-up, the progression rate to MCI was compared between the G-SCD and B-SCD groups. RESULTS: Volumes of the basal forebrain, the right hippocampus, and their respective subfields differed significantly among the four groups (p < 0.05, false discovery rate corrected). The B-SCD group showed lower volumes in the basal forebrain than the G-SCD group, especially in the Ch4p and Ch4a-i subfields. Furthermore, the structural covariance network of the basal forebrain and right hippocampal subfields showed that the B-SCD group had a larger Lambda than the G-SCD group, which suggested weakened network integration in the B-SCD group. At follow-up, the B-SCD group had a significantly higher conversion rate to MCI than the G-SCD group. CONCLUSION: Compared to SCD participants with good spatial navigation performance, SCD participants with bad performance showed lower volumes in the basal forebrain, a reorganized structural covariance network of subcortical nuclei, and an increased risk of progression to MCI. Our findings indicated that spatial navigation may have great potential to identify SCD subjects at higher risk of clinical progression, which may contribute to making more precise clinical decisions for SCD individuals who seek medical help.

Alterations in Dynamic Functional Connectivity in Patients with Cerebral Small Vessel Disease.

Cerebral small vessel disease (CSVD) is a common disease that seriously endangers people's health, and is easily overlooked by both patients and clinicians due to its near-silent onset. Dynamic functional connectivity (DFC) is a new concept focusing on the dynamic features and patterns of brain networks that represents a powerful tool for gaining novel insight into neurological diseases. To assess alterations in DFC in CSVD patients, and the correlation of DFC with cognitive function. We enrolled 35 CSVD patients and 31 normal control subjects (NC). Resting-state functional MRI (rs-fMRI) with a sliding-window approach and k-means clustering based on independent component analysis (ICA) was used to evaluate DFC. The temporal properties of fractional windows and the mean dwell time in each state, as well as the number of transitions between each pair of DFC states, were calculated. Additionally, we assessed the functional connectivity (FC) strength of the dynamic states and the associations of altered neuroimaging measures with cognitive performance. A dynamic analysis of all included subjects suggested four distinct functional connectivity states. Compared with the NC group, the CSVD group had more fractional windows and longer mean dwell times in state 4 characterized by sparse FC both inter-network and intra-networks. Additionally, the CSVD group had a reduced number of windows and shorter mean dwell times compared to the NC group in state 3 characterized by highly positive FC between the somatomotor and visual networks, and negative FC in the basal ganglia and somatomotor and visual networks. The number of transitions between state 2 and state 3 and between state 3 and state 4 was significantly reduced in the CSVD group compared to the NC group. Moreover, there was a significant difference in the FC strength between the two groups, and the altered temporal properties of DFC were significantly related to cognitive performance. Our study indicated that CSVD is characterized by altered temporal properties in DFC that may be sensitive neuroimaging biomarkers for early disease identification. Further study of DFC alterations could help us to better understand the progressive dysfunction of networks in CSVD patients.

Altered spontaneous brain activity as a potential imaging biomarker for generalized and focal to bilateral tonic-clonic seizures: A resting-state fMRI study.

OBJECTIVE: We aimed to determine whether alterations in spontaneous regional brain activity in those with generalized tonic-clonic seizures (GTCS) and focal to bilateral tonic-clonic seizures (FBTCS) and explore whether the alterations could be used as biomarkers to classify disease subtypes through support vector machine analysis (SVM). METHODS: The fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) from resting-state functional magnetic resonance imaging (rs-fMRI) data were extracted from 57 patients with GTCS, 35 patients with FBTCS, and 50 age-matched and sex-matched normal controls (NCs) using the DPARSF 5.0 toolbox. Between-group comparisons were adjusted for covariates (age, sex, and equipment). Correlation analyses between imaging biomarkers and the frequency or duration of seizure activity were calculated using partial correlations. The differential imaging indicators, age, and sex were considered as the discriminative features in the SVM to evaluate classification performance. RESULTS: The patients with GTCS showed lower fALFF values (voxel p < 0.001, cluster p < 0.05, Gaussian random field corrected, GRF corrected) in the right postcentral gyrus and precentral gyrus and lower ReHo values (GRF corrected) in the middle temporal gyrus than the NCs. The patients with FBTCS showed higher fALFF (GRF corrected) values in the right postcentral and precentral gyrus and higher ReHo (GRF corrected) values in the right postcentral gyrus. Both fALFF (GRF corrected) and ReHo (GRF corrected) values were lower in the right postcentral gyrus and precentral gyrus in the GTCS group than in the FBTCS group. In patients with FBTCS, fALFF values in the right postcentral and precentral gyrus were positively correlated with duration (r = 0.655, p = 0.008, Bonferroni corrected) in the low-duration group, and ReHo values in the right postcentral gyrus were positively correlated with frequency (r = 0.486, p = 0.022, uncorrected) in the low-frequency group. SVM results showed receiver operating characteristic curves of 0.89, 0.87, and 0.76 for the classification between GTCS and NC, between FBTCS and NC, and GTCS and FBTCS, respectively. SIGNIFICANCE: This study detected alterations in fALFF and ReHo in the postcentral gyrus and precentral gyrus in patients with GTCS and FBTCS, which might contribute to understanding the pathogenesis, disease classification, and clinical targeted therapy.

Magnetic nanometer combined with microwave: Novel rapid thawing promotes phenolics release in frozen-storage lychee.

Magnetic nanometer combined with microwave thawing (MN-MT) could become a novel solution to challenges uneven and overheating of microwave thawing (MT), while retaining high thawing efficiency, compared to conventional water immersion thawing (WT). In this study, MN-MT was applied to thaw fruit (lychee as an example) for the first time, and was evaluated by comparison with WT, MT and water immersion combined with microwave thawing (WI-MT). Results showed that MN-MT could significantly shorten the thawing time of frozen lychee by 80.67%, 25.86% and 18.83% compared to WT, MT and WI-MT, respectively. Compared to WT, MN-MT was the only thawing treatment which significantly enhanced the release of quercetin-3-O-rutinose-7-O-α-l-rhamnoside, according to HPLC-DAD. Meanwhile, thermal-sensitive procyanidin B2, phenylpropionic acid and protocatechuic acid were found to be protected from degradations only by MN-MT based on UPLC-ESI-QTOF-MS/MS results. In summary, MN-MT is a potential novel treatment for rapid thawing and quality maintenance of frozen fruits.

Deep Learning for Detection of Intracranial Aneurysms from Computed Tomography Angiography Images.

The accuracy of computed tomography angiography (CTA) image interpretation depends on the radiologist. This study aims to develop a new method for automatically detecting intracranial aneurysms from CTA images using deep learning, based on a convolutional neural network (CNN) implemented on the DeepMedic platform. Ninety CTA scans of patients with intracranial aneurysms are collected and divided into two datasets: training (80 subjects) and test (10 subjects) datasets. Subsequently, a deep learning architecture with a three-dimensional (3D) CNN model is implemented on the DeepMedic platform for the automatic segmentation and detection of intracranial aneurysms from the CTA images. The samples in the training dataset are used to train the CNN model, and those in the test dataset are used to assess the performance of the established system. Sensitivity, positive predictive value (PPV), and false positives are evaluated. The overall sensitivity and PPV of this system for detecting intracranial aneurysms from CTA images are 92.3% and 100%, respectively, and the segmentation sensitivity is 92.3%. The performance of the system in the detection of intracranial aneurysms is closely related to their size. The detection sensitivity for small intracranial aneurysms (≤ 3 mm) is 66.7%, whereas the sensitivity of detection for large (> 10 mm) and medium-sized (3-10 mm) intracranial aneurysms is 100%. The deep learning architecture with a 3D CNN model on the DeepMedic platform can reliably segment and detect intracranial aneurysms from CTA images with high sensitivity.

Effects and central mechanism of electroacupuncture and MRI-navigated rTMS for PSD: study protocol for an fMRI-based single-center, randomized, controlled, open-label trial.

Background: Post-stroke depression (PSD) is the most common mental complication after stroke and has a serious impact on functional outcomes and quality of life for stroke patients. Antidepressants are the first-line treatment for PSD; however, many reported side effects remain. Clinical research and practice guidelines have shown that electro-acupuncture (EA) or rTMS have a positive effect on PSD. However, there are few clinical studies on EA and MRI-navigated rTMS for PSD that explore the fMRI-based central mechanism in depression. Methods: In this randomized, controlled, open-label trial, 64 patients with PSD will be randomly allocated into the experiment group (n = 32) or control group (n = 32). The experiment group will receive EA and MRI-navigated rTMS and the control group will receive MRI-navigated rTMS treatment, in 12-20 sessions over 4 weeks. In addition, 10 healthy people for fMRI scanning will be recruited as a healthy control group without any intervention. The primary outcome will be the change from baseline in the Hamilton Depression Scale-24 item (HAMD-24) scores at week 4. The primary analysis of the central mechanism will mainly involve cortical morphology, local spontaneous brain activity, and the default mode network (DMN) functional connectivity based on fMRI at 0 and 4 weeks. Secondary outcomes will include the neuro-patho-physiological and quality of life changes in cortical excitability, determined using the motor evoked potential test (MEP), National Institutes of Health Stroke Scale (NIHSS), EuroQol Five Dimensions Questionnaire (EQ-5D) Scale, Modified Barthel Index (MBI) Scale, and Health Scale of Traditional Chinese Medicine (HSTCM). Additional indicators will include the Acceptability Questionnaire and Health Economics Evaluation (cost-effectiveness analysis) to assess the acceptability and economic practicality of the treatment under study. Outcomes will be assessed at baseline and post intervention. Discussion: EA and MRI-navigated rTMS therapy could become an alternative treatment for PSD, and it is expected that this trial will provide reliable clinical evidence and a potential central mechanism for the future use of EA and MRI-navigated rTMS for PSD. Clinical trial registration: NCT05516680, ClinicalTrials.gov (registered in August 2022).

MFG-E8 has guiding significance for the prognosis and treatment of sepsis.

Sepsis remains a significant clinical challenge. Ferroptosis is involved in the pathogenesis of sepsis. Ferroptosis is associated with oxidative stress, and excessive oxidative stress is suppressed by milk fat globule epidermal growth factor 8 (MFG-E8) under various conditions. However, the role of MFG-E8 in sepsis-induced ferroptosis and oxidative stress is still unclear. First, we collected blood samples from patients with sepsis and detected the expression of serum MFG-E8. Then, the relationship between serum concentrations of MFG-E8 and disease severity was detected. Finally, the effects of MFG-E8 treatment on ferroptosis and oxidative stress in the livers of septic mice were determined. The expression of serum MFG-E8 in healthy subjects was notably higher than that in septic patients. In addition, when nonsurvivors and survivors of sepsis were compared, MFG-E8 levels were considerably lower in the former. The ROC curve for MFG-E8 was also generated. The area under the curve for MFG-E8 was 0.768 (95% confidence interval [CI] 0.627-0.909, p = 0.003). The patients were separated into two groups based on the MFG-E8 cut-off value of 3.86 ng/mL. According to the Kaplan‒Meier survival analysis, patients with low MFG-E8 levels had a significantly decreased 28-day survival rate compared with patients with high MFG-E8 levels. High MFG-E8 levels were substantially related to a decreased risk of death, as demonstrated by the Cox proportional hazard model that we utilized. In addition, compared with sham mice, septic mice exhibited liver and kidney damage, and MFG-E8 may have protective effects. The survival study indicated that MFG-E8 could effectively improve the survival rate of septic mice. Treatment with MFG-E8 suppresses oxidative stress and ferroptosis in the livers of septic mice. Serum MFG-E8 levels are lower in septic patients and are negatively related to disease severity. Treatment with MFG-E8 suppresses oxidative stress and ferroptosis in the livers of septic mice, contributing to significantly improved survival in septic mice. These findings showed that MFG-E8 could be a new sepsis predictive biomarker. MFG-E8 may have therapeutic potential in the treatment of sepsis.

Mental health and chest CT scores mediate the relationship between COVID-19 vaccination status and seroconversion time: A cross-sectional observational study in B.1.617.2 (Delta) infection patients.

Background: The coronavirus disease (COVID-19) pandemic, which has been ongoing for more than 2 years, has become one of the largest public health issues. Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is one of the most important interventions to mitigate the COVID-19 pandemic. Our objective is to investigate the relationship between vaccination status and time to seroconversion. Methods: We conducted a cross-sectional observational study during the SARS-CoV-2 B.1.617.2 outbreak in Jiangsu, China. Participants who infected with the B.1.617.2 variant were enrolled. Cognitive performance, quality of life, emotional state, chest computed tomography (CT) score and seroconversion time were evaluated for each participant. Statistical analyses were performed using one-way ANOVA, univariate and multivariate regression analyses, Pearson correlation, and mediation analysis. Results: A total of 91 patients were included in the analysis, of whom 37.3, 25.3, and 37.3% were unvaccinated, partially vaccinated, and fully vaccinated, respectively. Quality of life was impaired in 30.7% of patients, especially for mental component summary (MCS) score. Vaccination status, subjective cognitive decline, and depression were risk factors for quality-of-life impairment. The chest CT score mediated the relationship of vaccination status with the MCS score, and the MCS score mediated the relationship of the chest CT score with time to seroconversion. Conclusion: Full immunization course with an inactivated vaccine effectively lowered the chest CT score and improved quality of life in hospitalized patients. Vaccination status could influence time to seroconversion by affecting CT score and MCS score indirectly. Our study emphasizes the importance of continuous efforts in encouraging a full vaccination course.