Covariation of preadult environmental exposures, adult brain imaging phenotypes, and adult personality traits.

Exposure to preadult environmental exposures may have long-lasting effects on mental health by affecting the maturation of the brain and personality, two traits that interact throughout the developmental process. However, environment-brain-personality covariation patterns and their mediation relationships remain unclear. In 4297 healthy participants (aged 18-30 years), we combined sparse multiple canonical correlation analysis with independent component analysis to identify the three-way covariation patterns of 59 preadult environmental exposures, 760 adult brain imaging phenotypes, and five personality traits, and found two robust environment-brain-personality covariation models with sex specificity. One model linked greater stress and less support to weaker functional connectivity and activity in the default mode network, stronger activity in subcortical nuclei, greater thickness and volume in the occipital, parietal and temporal cortices, and lower agreeableness, consciousness and extraversion as well as higher neuroticism. The other model linked higher urbanicity and better socioeconomic status to stronger functional connectivity and activity in the sensorimotor network, smaller volume and surface area and weaker functional connectivity and activity in the medial prefrontal cortex, lower white matter integrity, and higher openness to experience. We also conducted mediation analyses to explore the potential bidirectional mediation relationships between adult brain imaging phenotypes and personality traits with the influence of preadult environmental exposures and found both environment-brain-personality and environment-personality-brain pathways. We finally performed moderated mediation analyses to test the potential interactions between macro- and microenvironmental exposures and found that one category of exposure moderated the mediation pathways of another category of exposure. These results improve our understanding of the effects of preadult environmental exposures on the adult brain and personality traits and may facilitate the design of targeted interventions to improve mental health by reducing the impact of adverse environmental exposures.

Gut Microbiota Moderates Multimodal Brain Structure-Function Integration and Behavioral Cognition in Growth Hormone Deficient Children.

INTRODUCTION: Previous brain studies of growth hormone deficiency (GHD) often used single-modal neuroimaging, missing the complexity captured by multimodal data. Growth hormone affects gut microbiota and metabolism in GHD. However, from a gut-brain axis (GBA) perspective, the relationship between abnormal GHD brain development and microbiota alterations remains unclear. The ultimate goal is to uncover the manifestations underlying GBA abnormalities in GHD and idiopathic short stature (ISS). METHODS: Participants included 23 GHD and 25 ISS children. The fusion independent component analysis was applied to integrate multimodal brain data (high-resolution structural, diffusion tensor, and resting-state functional MRI) covering regional homogeneity (ReHo), amplitude of low frequency fluctuations (ALFF), and white matter fractional anisotropy (FA). Gut microbiome diversity and metabolites were analyzed using 16S sequencing and proton nuclear magnetic resonance (1H-NMR). Associations between multimodal neuroimaging and cognition were assessed using moderation analysis. RESULTS: Six independent components (IC) of ReHo, ALFF, and FA differed significantly between GHD and ISS patients, with three functional components linked to the processing speed index. GHD individuals showed higher levels of acetate, nicotinate, and lysine in microbiota metabolism. Higher alpha diversity in GHD strengthened connections between ReHo-IC1, ReHo-IC5, ALFF-IC1, and the processing speed index, while increasing agathobacter levels in ISS weakened the link between ALFF-IC1 and the speech comprehension index. CONCLUSIONS: Our findings uncover differing brain structure and functional fusion in GHD, alongside microbiota metabolism of short-chain fatty acids. Additionally, microbiome influences connections between neuroimaging and cognition, offering insight into diverse GBA patterns in GHD and ISS, enhancing our understanding of the disease's pathophysiology and interventions.

Impact of different growth hormone levels on gut microbiota and metabolism in short stature.

BACKGROUND: Growth hormone deficiency(GHD) and idiopathic short stature(ISS) are the primary causes of short stature in children. Animal experiments have revealed a link between growth hormone(GH), gut microbiota and metabolism, however, limited information is available from human trials. METHODS: Fecal samples collected from GHD (n = 36), ISS (n = 32) and healthy control (HC) children(n = 16) were subjected to microbiome (16 S rRNA gene sequencing) and metabolome (nuclear magnetic resonance,NMR) analyses. RESULTS: GHD, ISS and HC exhibit distinct differences in beta diversity of gut microbiota.In addition, short stature (GHD and ISS) exhibit higher relative abundance of Prevotellaceae_NK3B31_group at genus level compared to HC, whereas Rodentibacter, Rothia, and Pelomonas showed lower abundance. Additionally,Fusobacterium_mortiferum was identified as the characteristic species of GHD. Moreover, glucose metabolism, pyruvate metabolism and pyrimidine metabolism might play significant roles for distinguishing between GHD and normal GH groups (ISS and HC). Furthermore, a disease prediction model based on differential bacteria and metabolites between GHD and ISS exhibited high diagnostic value. CONCLUSION: These findings highlight the characteristics of different GH levels on the gut microbiota and metabolism in children, providing novel perspectives for early diagnosis and prognostic treatment of short stature with abnormal GH levels. IMPACT: The key message of our study is to identify human-relevant gut microbiota and host metabolic patterns that are interfered with growth hormone levels, and to develop biomarker models to identify short stature associated with growth hormone deficiency. We used idiopathic short stature as a control group for growth hormone deficiency, complementing the absence of height as a factor in the existing literature. Our study ultimately hopes to shed new light on the diagnosis and treatment of short stature children associated with growth hormone deficiency.

Dual-energy computed tomography for predicting histological grading and survival in patients with pancreatic ductal adenocarcinoma.

OBJECTIVES: We evaluated the value of dual-energy computed tomography (DECT) parameters derived from pancreatic ductal adenocarcinoma (PDAC) to discriminate between high- and low-grade tumors and predict overall survival (OS) in patients. METHODS: Data were retrospectively collected from 169 consecutive patients with pathologically confirmed PDAC who underwent third-generation dual-source DECT enhanced dual-phase scanning before surgery between January 2017 and March 2023. Patients with prior treatments, other malignancies, small tumors, or poor-quality scans were excluded. Two radiologists evaluated three clinical and seven radiological features and measured sixteen DECT-derived parameters. Univariate and multivariate analyses were applied to select independent predictors. A prediction model and a corresponding nomogram were developed, and the area under the curve (AUC), calibration, and clinical applicability were assessed. The correlations between factors and OS were evaluated using Kaplan-Meier survival and Cox regression analyses. RESULTS: One hundred sixty-nine patients were randomly divided into training (n = 118) and validation (n = 51) cohorts, among which 43 (36.4%) and 19 (37.3%) had high-grade PDAC confirmed by pathology, respectively. The vascular invasion, normalized iodine concentration in the venous phase, and effective atomic number in the venous phase were independent predictors for histological grading. A nomogram was constructed to predict the risk of high-grade tumors in PDAC, with AUCs of 0.887 and 0.844 in the training and validation cohorts, respectively. The nomogram exhibited good calibration and was more beneficial than a single parameter in both cohorts. Pathological- and nomoscore-predicted high-grade PDACs were associated with poor OS (all p < 0.05). CONCLUSIONS: The nomogram, which combines DECT parameters and radiological features, can predict the histological grade and OS in patients with PDAC before surgery. KEY POINTS: Question Preoperative determination of histological grade in PDAC is crucial for guiding treatment, yet current methods are invasive and limited. Findings A DECT-based nomogram combining vascular invasion, normalized iodine concentration, and effective atomic number accurately predicts histological grade and OS in PDAC patients. Clinical relevance The DECT-based nomogram is a reliable, non-invasive tool for predicting histological grade and OS in PDAC. It provides essential information to guide personalized treatment strategies, potentially improving patient management and outcomes.

Chiral Pyclen-Based Heptadentate Chelates as Highly Stable MRI Contrast Agents.

In recent years, pyclen-based complexes have attracted a great deal of interest as magnetic resonance imaging (MRI) contrast agents (CAs) and luminescent materials, as well as radiopharmaceuticals. Remarkably, gadopiclenol, a Gd(III) bishydrated complex featuring a pyclen-based heptadentate ligand, received approval as a novel contrast agent for clinical MRI application in 2022. To maximize stability and efficiency, two novel chiral pyclen-based chelators and their complexes were developed in this study. Gd-X-PCTA-2 showed significant enhancements in both thermodynamic and kinetic stabilities compared to those of the achiral parent derivative Gd-PCTA. 1H NMRD profiles reveal that both chiral gadolinium complexes (Gd-X-PCTA-1 and Gd-X-PCTA-2) have a higher relaxivity than Gd-PCTA, while variable-temperature 17O NMR studies show that the two inner-sphere water molecules have distinct residence times τMa and τMb. Furthermore, in vivo imaging demonstrates that Gd-X-PCTA-2 enhances the signal in the heart and kidneys of the mice, and the chiral Gd complexes exhibit the ability to distinguish between tumors and normal tissues in a 4T1 mouse model more efficiently than that of the clinical agent gadobutrol. Biodistribution studies show that Gd-PCTA and Gd-X-PCTA-2 are primarily cleared by a renal pathway, with 24 h residues of Gd-X-PCTA-2 in the liver and kidney being lower than those of Gd-PCTA.

Efficacy and safety of ultrasound-guided percutaneous radiofrequency ablation for synovial hyperplasia.

PURPOSE: This study aimed to investigate the efficacy and safety of ultrasound-guided percutaneous radiofrequency ablation (RFA) for the treatment of synovial hyperplasia in the knee joints of antigen-induced arthritis (AIA) model rabbits. METHODS: Forty Japanese large-eared white rabbits were divided into AIA and control groups. After successful induction of the AIA model, the knee joints were randomly assigned to RFA and non-RFA groups. The RFA group underwent ultrasound-guided RFA to treat synovial hyperplasia in the knee joint. Dynamic observation of various detection indices was conducted to evaluate the safety and effectiveness of the RFA procedure. RESULTS: Successful synovial ablation was achieved in the RFA group, with no intraoperative or perioperative mortality. Postoperative the circumference of the knee joint reached a peak before decreasing in the third week after surgery. The incidence and diameter of postoperative skin ulcers were not significantly different compared to the non-RFA group (p > .05). Anatomical examination revealed an intact intermuscular fascia around the ablated area in the RFA group. The ablated synovial tissue initially presented as a white mass, which subsequently liquefied into a milky white viscous fluid. Gross articular cartilage was observed, along with liquefied necrosis of the synovium on pathological histology and infiltration of inflammatory cells in the surrounding soft tissue. CONCLUSION: The experimental results demonstrated that ultrasound-guided RFA of the knee in the treatment of synovial hyperplasia in AIA model animals was both effective and safe.

A multicenter study of cervical cancer using quantitative diffusion-weighted imaging.

BACKGROUND: Parameters from diffusion-weighted imaging (DWI) have been increasingly used as imaging biomarkers for the diagnosis and monitoring of treatment responses in cancer. The consistency of DWI measurements across different centers remains uncertain, which limits the widespread use of quantitative DWI in clinical settings. PURPOSE: To investigate the consistency of quantitative metrics derived from DWI between different scanners in a multicenter clinical setting. MATERIAL AND METHODS: A total of 193 patients with cervical cancer from four scanners (MRI1, MRI2, MRI3, and MRI4) at three centers were included in this retrospective study. DWI data were processed using the mono-exponential and intravoxel incoherent motion (IVIM) model, yielding the following parameters: apparent diffusion coefficient (ADC); true diffusion coefficient (D); pseudo-diffusion coefficient (D*); perfusion fraction (f); and the product of f and D* (fD*). Various parameters of cervical cancer obtained from different scanners were compared. RESULTS: The parameters D and ADC derived from MRI1 and MRI2 were significantly different from those derived from MRI3 or MRI4 (P <0.01 for all comparisons). However, there was no significant difference in cervical cancer perfusion parameters (D* and fD*) between the different scanners (P >0.05). The P values of comparisons of all DWI parameters (D, D*, fD*, and ADC) between MRI3 and MRI4 (same vendor in different centers) for cervical cancer were all >0.05, except for f (P = 0.05). CONCLUSION: Scanners of the same model by the same vendor can yield close measurements of the ADC and IVIM parameters. The perfusion parameters showed higher consistency among the different scanners.

Abnormalities in spontaneous brain activity and functional connectivity are associated with cognitive impairments in children with type 1 diabetes mellitus.

BACKGROUND: It remains unclear whether alterations in brain function occur in the early stage of pediatric type 1 diabetes mellitus(T1DM). We aimed to examine changes in spontaneous brain activity and functional connectivity (FC) in children with T1DM using resting-state functional magnetic resonance imaging (rs-fMRI), and to pinpoint potential links between neural changes and cognitive performance. METHODS: In this study, 22 T1DM children and 21 age-, sex-matched healthy controls underwent rs-fMRI. The amplitude of low frequency fluctuations (ALFF) and seed-based FC analysis were performed to examine changes in intrinsic brain activity and functional networks in T1DM children. Partial correlation analyses were utilized to explore the correlations between ALFF values and clinical parameters. RESULTS: The ALFF values were significantly lower in the lingual gyrus (LG) and higher in the left medial superior frontal gyrus (MSFG) in T1DM children compared to controls. Subsequent FC analysis indicated that the LG had decreased FC with bilateral inferior occipital gyrus, and the left MSFG had decreased FC with right precentral gyrus, right inferior parietal gyrus and right postcentral gyrus in children with T1DM. The ALFF values of LG were positively correlated with full-scale intelligence quotient and age at disease onset in T1DM children, while the ALFF values of left MSFG were positively correlated with working memory scores. CONCLUSION: Our findings revealed abnormal spontaneous activity and FC in brain regions related to visual, memory, default mode network, and sensorimotor network in the early stage of T1DM children, which may aid in further understanding the mechanisms underlying T1DM-associated cognitive dysfunction.

Development and Validation of a Combined MRI Radiomics, Imaging and Clinical Parameter-Based Machine Learning Model for Identifying Idiopathic Central Precocious Puberty in Girls.

BACKGROUND: Idiopathic central precocious puberty (ICPP) impairs child development, without early intervention. The current reference standard, the gonadotropin-releasing hormone stimulation test, is invasive which may hinder diagnosis and intervention. PURPOSE: To develop a model for accurate diagnosis of ICPP, by integrating pituitary MRI, carpal bone age, gonadal ultrasound, and basic clinical data. STUDY TYPE: Retrospective. POPULATION: A total of 492 girls with PP (185 with ICPP and 307 peripheral precocious puberty [PPP]) were randomly divided by reference standard into training (75%) and internal validation (25%) data. Fifty-one subjects (16 with ICPP, 35 with PPP) provided by another hospital as external validation. FIELD STRENGTH/SEQUENCE: T1-weighted (spin echo [SE], fast SE, cube) and T2-weighted (fast SE-fat suppression) imaging at 3.0 T or 1.5 T. ASSESSMENT: Radiomics features were extracted from pituitary MRI after manual segmentation. Carpal bone age, ovarian, follicle and uterine volumes and endometrium presence were assessed from radiographs and gonadal ultrasound. Four machine learning methods were developed: a pituitary MRI radiomics model, an integrated image model (with pituitary MRI, gonadal ultrasound and bone age), a basic clinical model (with age and sex hormone data), and an integrated multimodal model combining all features. STATISTICAL TESTS: Intraclass correlation coefficients were used to assess consistency of segmentation. Receiver operating characteristic (ROC) curves and the Delong tests were used to assess and compare the diagnostic performance of models. P < 0.05 was considered statistically significant. RESULTS: The area under of the ROC curve (AUC) of the pituitary MRI radiomics model, integrated image model, basic clinical model, and integrated multimodal model in the training data was 0.668, 0.809, 0.792, and 0.860. The integrated multimodal model had higher diagnostic efficacy (AUC of 0.862 and 0.866 for internal and external validation). CONCLUSION: The integrated multimodal model may have potential as an alternative clinical approach to diagnose ICPP. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Altered gray matter volume in children with newly diagnosed type 1 diabetes mellitus.

BACKGROUND: Type 1 diabetes mellitus (T1DM) affects the development of cognitive function in children, which may be due to deficits in brain structures or functions. It is unclear whether children with T1DM experience alterations in the gray matter (GM) structure at the initial stages of the disease. This study investigated GM structure alterations in children with newly diagnosed T1DM. METHODS: Based on 3D T1-weighted MR images, we investigated the gray matter volume (GMV) of 35 newly diagnosed T1DM children and 35 age- and sex-matched healthy controls using voxel-based morphometry. The brain regions with significant differences in GMV between the newly diagnosed T1DM children and the controls were extracted and the correlation with clinical data was assessed. RESULTS: Compared with the control group, children with newly diagnosed T1DM had a lower GMV in the right inferior and middle temporal gyri, right lingual gyrus, and left superior frontal gyrus. In T1DM subjects, the GMV of the right middle temporal gyrus was positively correlated with IQ but was negatively correlated with HbA1c. CONCLUSIONS: Our findings provide compelling evidence that GM abnormalities occur during early disease stages in T1DM children, which may be a potential neurobiological mechanism underlying cognitive deficits. IMPACT: Using an efficient method to analyze gray matter changes in T1DM is very important. The anterior, posterior, and temporal brain regions are susceptible to T1DM in children. Recent glucose variability may affect regional gray matter volume in children with newly diagnosed T1DM. Structural changes were documented in the gray matter of the brain even at the early stages of the disease in children with T1DM.

Disruption of brain regional homogeneity and functional connectivity in male NAFLD: evidence from a pilot resting-state fMRI study.

BACKGROUND: The neurophysiological mechanisms underlying cognitive deficits in non-alcoholic fatty liver disease (NAFLD) remain unknown. Cognitive changes may be caused by brain alterations in neural activity and functional connectivity (FC). AIM: This study aims to investigate the alterations between spontaneous brain neural activity and FC in male NAFLD patients and the relationship of neural activity with cognitive performance. METHODS: In this prospective study, 33 male pre-cirrhosis NAFLD subjects and 20 male controls matched for age, education level, and body mass index. All participants underwent resting-state functional magnetic resonance imaging scans and neuropsychological examinations. Regional homogeneity (ReHo) analysis was used to investigate the brain function in NAFLD, and regions with significantly altered ReHo were selected as seeds for subsequent FC analysis. Partial correlation analysis was used to assess the relationships between altered ReHo measures and cognitive performance indicators. RESULTS: Compared with the controls, the NAFLD patients showed increased ReHo in the opercular part of the right inferior frontal gyrus (IFGoperc) and decreased ReHo in the right middle frontal gyrus (MFG) and left superior parietal gyrus (SPG). The subsequent FC analysis showed increased FC between these regions (right IFGoperc, right MFG, and left SPG) and nodes of the default mode network (DMN) (such as left supraMarginal, left median cingulate and paracingulate gyri, left precuneus, orbital part of left medial frontal gyrus, and bilateral posterior cingulate gyrus). In addition, significant positive correlations were observed between NAFLD patients' clock drawing test scores and altered ReHo in prefrontal cortices (right IFGoperc and right MFG). CONCLUSION: Before developing cirrhosis, NAFLD patients showed altered neural activity in several brain regions and altered FC between the salience network and DMN. These alterations could potentially be a compensatory mechanism to maintain cognitive function in pre-cirrhosis NAFLD patients.

MRI-based radiomics model for distinguishing Stage I endometrial carcinoma from endometrial polyp: a multicenter study.

BACKGROUND: Patients with early endometrial carcinoma (EC) have a good prognosis, but it is difficult to distinguish from endometrial polyps (EPs). PURPOSE: To develop and assess magnetic resonance imaging (MRI)-based radiomics models for discriminating Stage I EC from EP in a multicenter setting. MATERIAL AND METHODS: Patients with Stage I EC (n = 202) and EP (n = 99) who underwent preoperative MRI scans were collected in three centers (seven devices). The images from devices 1-3 were utilized for training and validation, and the images from devices 4-7 were utilized for testing, leading to three models. They were evaluated by the area under the receiver operating characteristic curve (AUC) and metrics including accuracy, sensitivity, and specificity. Two radiologists evaluated the endometrial lesions and compared them with the three models. RESULTS: The AUCs of device 1, 2_ada, device 1, 3_ada, and device 2, 3_ada for discriminating Stage I EC from EP were 0.951, 0.912, and 0.896 for the training set, 0.755, 0.928, and 1.000 for the validation set, and 0.883, 0.956, and 0.878 for the external validation set, respectively. The specificity of the three models was higher, but the accuracy and sensitivity were lower than those of radiologists. CONCLUSION: Our MRI-based models showed good potential in differentiating Stage I EC from EP and had been validated in multiple centers. Their specificity was higher than that of radiologists and may be used for computer-aided diagnosis in the future to assist clinical diagnosis.

Neutrophil membrane-coated nanoparticles exhibit increased antimicrobial activities in an anti-microbial resistant K. pneumonia infection model.

OBJECTIVE: To investigate the efficacy and safety of neutrophil membrane-coated nanoparticles mediated KLA peptides (KLAKLAKKLAKLAK) and gentamicin in the targeted therapy of anti-microbial resistant Klebsiella pneumoniae (K. pneumonia) lung infection. METHODS: The characteristics of KLA-neutrophils nanoparticles (NNPs) are identified via dynamic light scattering (DLS), transmission electron microscope (TEM), SDS-PAGE, Western blot, quantitative flow cytometry (QFCM) and confocal microscopy. The safety of KLA-NNPs both in vitro and in vivo is evaluated by hemolysis test, platelet α granule membrane protein concentration, protein adsorption capacity, in vitro macrophage phagocytosis, weight change, liver function indicators, blood biochemical indicators, and pathological changes of vital organs in mice. The efficacy of KLA-NNPs is determined by time-kill assay, fluorescent label test, intracellular bacterial content, caspase-1 activity, survival rate, and HE staining both in vitro and in vivo. RESULTS: The prepared KLA-NNPs have a typical "core-shell" structure, uniform nanometer size, and retain the membrane proteins on the neutrophil membrane that achieve functional effects. In vitro safety analysis showed that KLA-NNPs have good blood compatibility and can inhibit macrophage phagocytosis in vitro. KLA-NNPs can effectively release KLA and significantly reduce intracellular bacteria and caspase-1 activity. In vivo safety analysis and efficacy analysis revealed that KLA-NNPs have good biocompatibility and could effectively improve the survival rate of mice. CONCLUSION: The prepared KLA-NNPs have good nano-medicine chemical and physical properties and safety. It can evade immune system clearance, achieve high-efficiency targeted aggregation and drug delivery to bacterial infection sites, and effectively inhibit the development of pneumonia induced by drug-resistant K. pneumonia.

Longitudinal unraveling: The impact of recombinant human growth hormone on spontaneous brain activity in children with short stature-A resting-state fMRI study.

Recombinant human growth hormone (rhGH) is an approved method to improve the growth and ameliorate behavioral issues in children with short stature. However, the data concerning the effects of rhGH treatment on spontaneous brain activity remains unclear. This study included 35 children with short stature, categorized into two groups: the treated group (n = 14) and the untreated group (n = 21). All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological assessments at baseline and at the end of a one-year follow-up. The rs-fMRI based amplitude of low frequency fluctuation (ALFF) analysis method was employed to assess spontaneous brain activity. Interaction effects between rhGH and time on ALFF were detected using a mixed-effects analysis. Additionally, Stepwise regression analysis was conducted to investigate the associations between ALFF values and significant clinical indicators. The treated group exhibited significant improvements in height, weight, insulin-like growth factor-1 (IGF-1) levels, insulin-like growth factor binding protein 3 (IGFBP-3) levels, and processing speed index (PSI) when reevaluated from baseline. The interaction effect of rhGH × time was evident in the right putamen (RPUT), where the ALFF value showed a significant increase following rhGH treatment, while also demonstrating a notable positive correlation with height. Moreover, The main effect of time was manifested as a significant decrease in the ALFF value of the left dorsolateral superior frontal gyrus (LSFG) within the untreated group during the follow-up period, concurrently displaying a positive correlation with age. In conclusion, rhGH treatment not only has a positive effect on the growth, cognition, and behavior of children with short stature, but also improves and normalizes spontaneous brain activity.

Human neutrophil peptide 1 promotes immune sterilization in vivo by reducing the virulence of multidrug-resistant Klebsiella pneumoniae and increasing the ability of macrophages.

By studying the expression in patients and cell modeling in vitro, antimicrobial peptides for Klebsiella were screened. Killing curve and membrane permeability experiments are used to study the antibacterial effect of antimicrobial peptides in vitro. Cytotoxicity-related indicators including lipopolysaccharide (LPS), capsule polysaccharide (CPS), and outer membrane protein expression were measured. Intranasal inoculation of pneumoconiosis was used to construct a mouse infection model, and the survival rate and cytokine expression level were tested. Human neutrophil peptide 1 (HNP-1) showed a significant antibacterial effect, which improved the permeability of the outer membrane of K. pneumoniae. Moreover, HNP-1 decreased LPS, CPS content, and outer membrane proteins. K. pneumoniae infection decreased antimicrobial peptide, oxidative stress, and autophagy-related genes, while HNP-1 increased these genes. After coculture with macrophages, the endocytosis of macrophages is enhanced and the bacterial load is greater in the K. pneumoniae + peptide group. Besides, higher levels of pp38 and pp65 in the K. pneumoniae + peptide group. HNP-1 rescued the cytotoxicity induced by K. pneumoniae. The survival rate is significantly improved after K. pneumoniae is treated by HNP-1. All cytokines in the peptide group were significantly higher. HNP-1 promotes immune sterilization by reducing the virulence of multidrug-resistant K. pneumoniae and increasing the ability of macrophages.

A comparative study of four diffusion-weighted imaging models in the diagnosis of cervical cancer.

BACKGROUND: Most commonly used diffusion-weighted imaging (DWI) models include intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and mono-exponential model (MEM). Previous studies of the four models were inconsistent on which model was more effective in distinguishing cervical cancer from normal cervical tissue. PURPOSE: To assess the performance of four DWI models in characterizing cervical cancer and normal cervical tissue. MATERIAL AND METHODS: Forty-seven women with suspected cervical carcinoma underwent DWI using eight b-values before treatment. Imaging parameters, calculated using IVIM, SEM, DKI, and MEM, were compared between cervical cancer and normal cervical tissue. The diagnostic performance of the models was evaluated using independent t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curve analysis, and multivariate logistic regression analysis. RESULTS: All parameters except pseudo-diffusion coefficient (D*) differed significantly between cervical cancer and normal cervical tissue (P < 0.001). Through logistic regression analysis, all combined models showed a significant improvement in area under the ROC curve (AUC) compared to individual DWI parameters. The model with combined IVIM parameters had a larger AUC value compared to those of other combined models (P < 0.05). CONCLUSION: All four DWI models are useful for differentiating cervical cancer from normal cervical tissue and IVIM may be the optimal model.

Dissimilarity of functional connectivity uncovers the influence of participant's motion in functional magnetic resonance imaging studies.

Head motion is a major confounding factor impairing the quality of functional magnetic resonance imaging (fMRI) data. In particular, head motion can reduce analytical efficiency, and its effects are still present even after preprocessing. To examine the validity of motion removal and to evaluate the remaining effects of motion on the quality of the preprocessed fMRI data, a new metric of group quality control (QC), dissimilarity of functional connectivity, is introduced. Here, we investigate the association between head motion, represented by mean framewise displacement, and dissimilarity of functional connectivity by applying four preprocessing methods in two independent resting-state fMRI datasets: one consisting of healthy participants (N = 167) scanned in a 3T GE-Discovery 750 with longer TR (2.5 s), and the other of chronic back pain patients (N = 143) in a 3T Siemens Magnetom Prisma scanner with shorter TR (0.555 s). We found that dissimilarity of functional connectivity uncovers the influence of participant's motion, and this relationship is independent of population, scanner, and preprocessing method. The association between motion and dissimilarity of functional connectivity, and how the removal of high-motion participants affects this association, is a new strategy for group-level QC following preprocessing.

Influence of the hypothalamus-pituitary-gonadal axis reactivation and pubertal hormones on gray matter volume in early pubertal girls.

OBJECTIVE: Puberty is a sensitive period of brain development accompany with pubertal hormones fluctuation. However, the underlying mechanisms of the impact of hypothalamus-pituitary-gonadal (HPG) axis reactivation and associated elevated pubertal hormones on brain structure are still unclear. Here, we investigated the brain structure differences between girls with and without HPG axis reactivation and the influence of pubertal hormones on these brain regions. METHODS: 126 girls aged 8-9.5 years underwent a gonadotropin-releasing hormone (GnRH) stimulation test to identify the HPG axis status and categorized into HPG+ group (n = 80) and HPG- group (n = 46). T1-weighted gradient echo three dimensional MRI was performed using a 3.0-Tesla scanner to assess the difference in GMV between the two groups. Correlation analyses were conducted to explore the relations between the brain regions showing significant GMV differences and serum hormone concentrations. RESULT: The HPG+ group showed significantly higher GMV in the bilateral lingual gyrus and lower GMV within the right orbital inferior frontal gyrus compare to the HPG - group. Furthermore, GMV in the right orbital inferior frontal gyrus was positively associated with plasma concentrations of follicle stimulating hormone (FSH) in HPG+ group. CONCLUSION: The present study suggests that the reactivated HPG axis could affects regional structural brain changes in early pubertal girls. FSH production play an important role in bilateral lingual gyrus, which are involved in vision processing, semantic processing and emotional expression.

Strategic white matter injury associated with long-term information processing speed deficits in mild traumatic brain injury.

Deficits in information processing speed (IPS) are among the earliest and most prominent cognitive manifestations in mild traumatic brain injury (mTBI). We investigated the impact of white matter fiber location on IPS outcome in an individual basis assessment. A total of 112 acute mild TBI with all CT negative underwent brain DTI and blood sampling for inflammation cytokines within 7 days postinjury and 72 age- and sex matched healthy controls with same assessments were enrolled. IPS outcome was assessed by the trail making test at 6-12 month postinjury in mild TBI. Fractional anisotropy (FA) features were extracted using a novel lesion-load analytical strategy to capture spatially heterogeneous white matter injuries and minimize implicit assumptions of uniform injury across diverse clinical presentations. Acute mild TBI exhibited a general pattern of increased and decreased FA in specific white matter tracts. The power of acute FA measures to identify patients developing IPS deficits with 92% accuracy and further improved to 96% accuracy by adding inflammation cytokines. The classifiers predicted individual's IPS and working memory ratings (r = .74 and .80, respectively, p < .001). The thalamo-cortical circuits and commissural tracts projecting or connecting frontal regions became important predictors. This prognostic model was also verified by an independent replicate sample. Our findings highlighted damage to frontal interhemispheric and thalamic projection fiber tracts harboring frontal-subcortical neuronal circuits as a predictor for processing speed performance in mild TBI.

Plasma CRP level is positively associated with the severity of COVID-19.

AIMS: The coronavirus disease 2019 (COVID-19) is characterized as highly contagious and deadly; however there is no credible and convenient biomarker to predict the severity of the disease. The aim of the present study was to estimate whether the CRP level is able to act as a marker in indicating the severity of COVID-19. METHODS: Patients who complained cough or chest pain with or without fever were enrolled after laboratory confirmed of SARS-CoV-2 viral nucleic acid via qRT-PCR. Chest computed tomography (CT) was then performed to classify the patients into mild, moderate and severe pneumonia groups according to the interim management guideline. Then linear regression models were applied to analyze the association between c-reactive protein (CRP) levels and severity of COVID-19 pneumonia. RESULTS: When compared to mild pneumonia, the adjusted-Odds Ratio were 11.46, p = 0.029 and 23.40, p = 0.025 in moderate and severe pneumonia, respectively. The area under receiver operation curve was 0.898 (95% CI 0.835, 0.962, p < 0.001). Higher plasma CRP level indicated severe COVID-19 pneumonia and longer inpatients duration. CONCLUSIONS: The level of plasma CRP was positively correlated to the severity of COVID-19 pneumonia. Our findings could assist to discern patients of moderate to severe COVID-19 pneumonia from the mild ones. Our findings may be useful as an earlier indicator for severe illness and help physicians to stratify patients for intense care unit transfer.