Precirrhotic Primary Biliary Cholangitis with Portal Hypertension: Bile Duct Injury Correlate.

Background/Aims: : The histological characteristics and natural history of precirrhotic primary biliary cholangitis (PBC) with portal hypertension (PH) are unclear. Our aim was to clarify the prevalence, risk factors, and histological characteristics of precirrhotic PBC patients with PH. Methods: : This retrospective study compared the clinical features, histological characteristics, and response to ursodeoxycholic acid (UDCA) between the PH and non-PH groups of precirrhotic PBC patients. Results: : Out of 165 precirrhotic PBC patients, 40 (24.2%) also had PH. According to histological stage 1, 2 and 3 disease, 5.3% (1/19), 17.3% (17/98), and 45.8% (22/48) of patients also had PH, respectively. Precirrhotic PBC with PH was significantly positively correlated with bile duct loss, degree of cytokeratin 7 positivity, and degree of fibrosis in the portal area, but significantly negatively correlated with lymphoid follicular aggregation. Compared to the non-PH group, patients in the PH group showed a higher prevalence of obliterative portal venopathy, incomplete septal fibrosis, portal tract abnormalities and non-zonal sinusoidal dilatation (p<0.05). In addition, patients with PH were more likely to present with symptoms of jaundice, ascites, epigastric discomfort, a poorer response to UDCA, and more decompensation events (p<0.05). High alkaline phosphatase levels, low white blood cell counts, high Mayo scores, and high FIB-4 index values were risk factors for precirrhotic PBC with PH. Conclusions: : Approximately 24.2% of precirrhotic PBC patients have PH, which is histologically related to the injury of bile ducts. High alkaline phosphatase levels, low white blood cell counts, high Mayo scores, and high FIB-4 index values are associated with increased risk of precirrhotic PBC with PH.

Right superior frontal gyrus: A potential neuroimaging biomarker for predicting short-term efficacy in schizophrenia.

Antipsychotic drug treatment for schizophrenia (SZ) can alter brain structure and function, but it is unclear if specific regional changes are associated with treatment outcome. Therefore, we examined the effects of antipsychotic drug treatment on regional grey matter (GM) density, white matter (WM) density, and functional connectivity (FC) as well as associations between regional changes and treatment efficacy. SZ patients (n = 163) and health controls (HCs) (n = 131) were examined by structural magnetic resonance imaging (sMRI) at baseline, and a subset of SZ patients (n = 77) were re-examined after 8 weeks of second-generation antipsychotic treatment to assess changes in regional GM and WM density. In addition, 88 SZ patients and 81 HCs were examined by resting-state functional MRI (rs-fMRI) at baseline and the patients were re-examined post-treatment to examine FC changes. The Positive and Negative Syndrome Scale (PANSS) and MATRICS Consensus Cognitive Battery (MCCB) were applied to measure psychiatric symptoms and cognitive impairments in SZ. SZ patients were then stratified into response and non-response groups according to PANSS score change (≥50 % decrease or <50 % decrease, respectively). The GM density of the right cingulate gyrus, WM density of the right superior frontal gyrus (SFG) plus 5 other WM tracts were reduced in the response group compared to the non-response group. The FC values between the right anterior cingulate and paracingulate gyrus and left thalamus were reduced in the entire SZ group (n = 88) after treatment, while FC between the right inferior temporal gyrus (ITG) and right medial superior frontal gyrus (SFGmed) was increased in the response group. There were no significant changes in regional FC among the non-response group after treatment and no correlations with symptom or cognition test scores. These findings suggest that the right SFG is a critical target of antipsychotic drugs and that WM density and FC alterations within this region could be used as potential indicators in predicting the treatment outcome of antipsychotics of SZ.

Human umbilical cord blood mesenchymal stem cells mediate microglia activation and improve anxiety-like behavior in MIA-induced offspring of schizophrenic rats.

Current treatments for schizophrenia (SCZ) remain largely ineffective in one-third of patients. Recent studies using stem cell therapy show a close relationship between stem cell immunomodulatory function and neuroinflammation in SCZ. To better investigate the efficacy of stem cell therapy for SCZ, human umbilical cord blood mesenchymal stem cells (hUC-MSC) with powerful immunomodulatory effects were administered to rats via the tail vein (once a week for 5 consecutive weeks starting from the weaning period) using a maternal immune activation (MIA) rodent model. Open field, PPI, Western blotting, Q-PCR, and immunofluorescence were used to assess the biological effects of repeated tail vein injections of hUC-MSC in offspring rats following the MIA model of SCZ. The results indicated that offspring of MIA rats exhibited schizophrenia-like (SCZ-like) anxiety behavior, with observed microglial activation triggering neuroinflammation. Furthermore, levels of IBA1, HMGB1, and PSD95 were significantly up-regulated, while SYP was significantly down-regulated. It is suggested that hUCB-MSCs may act through HMGB1, Iba1, PSD95, and related pathway molecules to alleviate neuroinflammation and repair synaptic damage by regulating the activity state of microglia. Consequently, this could improve the abnormal behavior observed in MIA offspring rats.

Bacillus-derived consortium enhances Ginkgo biloba's health and resistance to Alternaria tenuissima.

BACKGROUND: Bacillus, as a plant-growth-promoting rhizobacteria, can enhance the resistance of plants to phytopathogens. In our study, Bacillus strains showing excellent biocontrol were screened and used to control ginkgo leaf blight (Alternaria tenuissima). RESULTS: Four biocontrol Bacillus strains-Bsa537, Bam337, Bso544, and Bsu503-were selected from 286 isolates based on their capacity to inhibit pathogens and promote plant growth. The four Bacillus strains significantly improved the resistance of ginkgo to leaf blight. This was especially the case when the four strains were used as a mixture, which contributed to a decrease in lesion area of >40%. Hence, a mixture of Bacillus strains was used to control ginkgo leaf blight in the field. Treatment efficiency varied from 30% to 100% (average 81.5%) and was higher than that of the control (-2% to -18%, average - 8.5%); the antioxidant capacity of the treated ginkgo was also stronger. In addition, ginkgo biomass increased as a result of treatment with the Bacillus mixture, including leaf weight, area, thickness, number of lateral roots and root weight. Furthermore, the Bacillus mixture improved the ginkgo rhizosphere soil by boosting the number of beneficial microorganisms, lowering the number of pathogens and hastening soil catabolism. CONCLUSION: The Bacillus mixture improved the health status of ginkgo by protecting it from pathogen attack, promoting its growth and improving the microorganism community in the rhizosphere. This work closes a technological gap in the biological control of ginkgo leaf blight, investigates application methods for compound Bacillus biofertilizers and establishes a framework for the popularity and commercialization of these products. © 2024 Society of Chemical Industry.

Thy1-ApoE4/C/EBPß double transgenic mice act as a sporadic model with Alzheimer's disease.

Early onset familial Alzheimer's disease (FAD) with APP, PS1/2 (presenilins) mutation accounts for only a small portion of AD cases, and most are late-onset sporadic. However, majority of AD mouse models are developed to mimic the genetic cause of human AD by overexpressing mutated forms of human APP, PS1/2, and/or Tau protein, though there is no Tau mutation in AD, and no single mouse model recapitulates all aspects of AD pathology. Here, we report Thy1-ApoE4/C/EBPß double transgenic mouse model that demonstrates key AD pathologies in an age-dependent manner in absence of any human APP or PS1/2 mutation. Using the clinical diagnosis criteria, we show that this mouse model exhibits tempo-spatial features in AD patient brains, including progressive cognitive decline associated with brain atrophy, which is accompanied with extensive neuronal degeneration. Remarkably, the mice display gradual Aß aggregation and neurofibrillary tangles formation in the brain validated by Aß PET and Tau PET. Moreover, the mice reveal widespread neuroinflammation as shown in AD brains. Hence, Thy1-ApoE4/C/EBPß mouse model acts as a sporadic AD mouse model, reconstituting the major AD pathologies.

Differences in physicochemical properties of pectin extracted from pomelo peel with different extraction techniques.

In order to obtain high yield pomelo peel pectin with better physicochemical properties, four pectin extraction methods, including hot acid extraction (HAE), microwave-assisted extraction (MAE), ultrasound-assisted extraction, and enzymatic assisted extraction (EAE) were compared. MAE led to the highest pectin yield (20.43%), and the lowest pectin recovery was found for EAE (11.94%). The physicochemical properties of pomelo peel pectin obtained by different methods were also significantly different. Pectin samples obtained by MAE had the highest methoxyl content (8.35%), galacturonic acid content (71.36%), and showed a higher apparent viscosity, thermal and emulsion stability. The pectin extracted by EAE showed the highest total phenolic content (12.86%) and lowest particle size (843.69 nm), showing higher DPPH and ABTS scavenging activities than other extract methods. The pectin extracted by HAE had the highest particle size (966.12 nm) and degree of esterification (55.67%). However, Fourier-transform infrared spectroscopy showed that no significant difference occurred among the different methods in the chemical structure of the extracted pectin. This study provides a theoretical basis for the industrial production of pomelo peel pectin.

ALKBH5-mediated m6A modification of IL-11 drives macrophage-to-myofibroblast transition and pathological cardiac fibrosis in mice.

Cardiac macrophage contributes to the development of cardiac fibrosis, but factors that regulate cardiac macrophages transition and activation during this process remains elusive. Here we show, by single-cell transcriptomics, lineage tracing and parabiosis, that cardiac macrophages from circulating monocytes preferentially commit to macrophage-to-myofibroblast transition (MMT) under angiotensin II (Ang II)-induced hypertension, with accompanying increased expression of the RNA N6-methyladenosine demethylases, ALKBH5. Meanwhile, macrophage-specific knockout of ALKBH5 inhibits Ang II-induced MMT, and subsequently ameliorates cardiac fibrosis and dysfunction. Mechanistically, RNA immunoprecipitation sequencing identifies interlukin-11 (IL-11) mRNA as a target for ALKBH5-mediated m6A demethylation, leading to increased IL-11 mRNA stability and protein levels. By contrast, overexpression of IL11 in circulating macrophages reverses the phenotype in ALKBH5-deficient mice and macrophage. Lastly, targeted delivery of ALKBH5 or IL-11 receptor α (IL11RA1) siRNA to monocytes/macrophages attenuates MMT and cardiac fibrosis under hypertensive stress. Our results thus suggest that the ALKBH5/IL-11/IL11RA1/MMT axis alters cardiac macrophage and contributes to hypertensive cardiac fibrosis and dysfunction in mice, and thereby identify potential targets for cardiac fibrosis therapy in patients.

Serum S100B protein and white matter changes in schizophrenia before and after medication.

Schizophrenia patients have abnormalities in white matter (WM) integrity in brain regions. S100B has been shown to be a marker protein for glial cells. The atypical antipsychotics have neuroprotective effects on the brain. It is not clear whether antipsychotics can induce S100B changes and improve symptoms by protecting oligodendrocytes. To investigate WM and S100B changes and associations and determine the effect of quetiapine on WM and S100B in schizophrenia patients, we determined serum S100B levels with solid phase immunochromatography and fractional anisotropy（FA）values of 36 patients and 40 healthy controls. Patients exhibited significantly higher serum concentrations of S100B and decreased FA values in left postcentral，right superior frontal，right thalamus, and left inferior occipital gyrus, while higher in right temporal cortex WM compared with healthy controls. Following treatment with quetiapine, patients had decreased S100B and higher FA values in right cerebellum，right superior frontal，right thalamus, and left parietal cortex，and decreased FA values in right temporal cortex WM compared with pre-treatment values. Furthermore, S100B were negatively correlated with PANSS positive scores and positively correlated with FA values in the left postcentral cortex. In addition，the percentage change in FA values in the right temporal cortex was positively correlated with the percentage change in the S100B, percentage reduction in PANSS scores, and percentage reduction in PANSS-positive scores. Our findings demonstrated abnormalities in S100B and WM microstructure in patients with schizophrenia. These abnormalities may be partly reversed by quetiapine treatment.

Decrypting biocontrol functions and application modes by genomes data of three Trichoderma Strains/Species.

Trichoderma is an excellent biocontrol agent, but most Trichoderma genomes remained at the scaffold level, which greatly limits the research of biocontrol mechanism. Here, we reported the chromosome-level genome of Trichoderma harzianum CGMCC20739 (Tha739), T. asperellum CGMCC11653 (Tas653) and T. atroviride CGMCC40488 (Tat488), they were assembled into 7 chromosomes, genome size were 40 Mb (10,611 genes), 37.3 Mb (10,102 genes) and 36.3 Mb (9,896 genes), respectively. The positive selected genes of three strains were associated to response to stimulus, signaling transduction, immune system and localization. Furthermore, the number of transcription factors in Tha739, Tas653 and Tat488 strains had significant difference, which may contribute to the differential biocontrol function and stress tolerance. The genes related to signal transduction and gene clusters related to antimicrobial compounds in Tha739 were more than those in Tas653 and Tat488, which showed Tha739 may keenly sense other fungi and quickly secret antimicrobial compounds to inhibit other fungi. Tha739 also contained more genes associated to detoxification, antioxidant and nutrition utilization, indicating it had higher stress-tolerance to hostile environments. And the substrate for synthesizing IAA in Tha739 was mainly 3-indole acetonitrile and indole acetaldehyde, but in Tat488, it was indole-3-acetamide, moreover, Tha739 secreted more phosphatase and phytase and was more related to soil phosphorus metabolism, Tat488 secreted more urease and was more related to soil nitrogen metabolism. These candidate genes related to biocontrol function and stress-tolerance laid foundations for construction of functional strains. All above proved the difference in biocontrol function of Tha739, Tas653 and Tat488 strains, however, the defects in individual strains could be compensated for through Trichoderma-biome during the commercial application process of biocontrol Trichoderma strains.

Digital spatial profiling of segmental outflow regions in trabecular meshwork reveals a role for ADAM15.

In this study we used a spatial transcriptomics approach to identify genes specifically associated with either high or low outflow regions in the trabecular meshwork (TM) that could potentially affect aqueous humor outflow in vivo. High and low outflow regions were identified and isolated from organ cultured human anterior segments perfused with fluorescently-labeled 200 nm FluoSpheres. The NanoString GeoMx Digital Spatial Profiler (DSP) platform was then used to identified genes in the paraffin embedded tissue sections from within those regions. These transcriptome analyses revealed that 16 genes were statistically upregulated in high outflow regions and 57 genes were statistically downregulated in high outflow regions when compared to low outflow regions. Gene ontology enrichment analysis indicated that the top three biological categories of these differentially expressed genes were ECM/cell adhesion, signal transduction, and transcription. The ECM/cell adhesion genes that showed the largest differential expression (Log2FC ±1.5) were ADAM15, BGN, LDB3, and CRKL. ADAM15, which is a metalloproteinase that can bind integrins, was upregulated in high outflow regions, while the proteoglycan BGN and two genes associated with integrin signaling (LDB3, and CRKL) were downregulated. Immunolabeling studies supported the differential expression of ADAM15 and showed that it was specifically upregulated in high outflow regions along the inner wall of Schlemm's canal and in the juxtacanalicular (JCT) region of the TM. In addition to these genes, the studies showed that genes for decorin, a small leucine-rich proteoglycan, and the α8 integrin subunit were enriched in high outflow regions. These studies identify several novel genes that could be involved in segmental outflow, thus demonstrating that digital spatial profiling could be a useful approach for understanding segmental flow through the TM. Furthermore, this study suggests that changes in the expression of genes involved in regulating the activity and/or organization of the ECM and integrins in the TM are likely to be key players in segmental outflow.

Learning CT-free attenuation-corrected total-body PET images through deep learning.

OBJECTIVES: Total-body PET/CT scanners with long axial fields of view have enabled unprecedented image quality and quantitative accuracy. However, the ionizing radiation from CT is a major issue in PET imaging, which is more evident with reduced radiopharmaceutical doses in total-body PET/CT. Therefore, we attempted to generate CT-free attenuation-corrected (CTF-AC) total-body PET images through deep learning. METHODS: Based on total-body PET data from 122 subjects (29 females and 93 males), a well-established cycle-consistent generative adversarial network (Cycle-GAN) was employed to generate CTF-AC total-body PET images directly while introducing site structures as prior information. Statistical analyses, including Pearson correlation coefficient (PCC) and t-tests, were utilized for the correlation measurements. RESULTS: The generated CTF-AC total-body PET images closely resembled real AC PET images, showing reduced noise and good contrast in different tissue structures. The obtained peak signal-to-noise ratio and structural similarity index measure values were 36.92 ± 5.49 dB (p < 0.01) and 0.980 ± 0.041 (p < 0.01), respectively. Furthermore, the standardized uptake value (SUV) distribution was consistent with that of real AC PET images. CONCLUSION: Our approach could directly generate CTF-AC total-body PET images, greatly reducing the radiation risk to patients from redundant anatomical examinations. Moreover, the model was validated based on a multidose-level NAC-AC PET dataset, demonstrating the potential of our method for low-dose PET attenuation correction. In future work, we will attempt to validate the proposed method with total-body PET/CT systems in more clinical practices. CLINICAL RELEVANCE STATEMENT: The ionizing radiation from CT is a major issue in PET imaging, which is more evident with reduced radiopharmaceutical doses in total-body PET/CT. Our CT-free PET attenuation correction method would be beneficial for a wide range of patient populations, especially for pediatric examinations and patients who need multiple scans or who require long-term follow-up. KEY POINTS: • CT is the main source of radiation in PET/CT imaging, especially for total-body PET/CT devices, and reduced radiopharmaceutical doses make the radiation burden from CT more obvious. • The CT-free PET attenuation correction method would be beneficial for patients who need multiple scans or long-term follow-up by reducing additional radiation from redundant anatomical examinations. • The proposed method could directly generate CT-free attenuation-corrected (CTF-AC) total-body PET images, which is beneficial for PET/MRI or PET-only devices lacking CT image poses.

Genome-wide association study implicates lipid pathway dysfunction in antipsychotic-induced weight gain: multi-ancestry validation.

Antipsychotic-induced weight gain (AIWG) is a common side effect of antipsychotic medication and may contribute to diabetes and coronary heart disease. To expand the unclear genetic mechanism underlying AIWG, we conducted a two-stage genome-wide association study in Han Chinese patients with schizophrenia. The study included a discovery cohort of 1936 patients and a validation cohort of 534 patients, with an additional 630 multi-ancestry patients from the CATIE study for external validation. We applied Mendelian randomization (MR) analysis to investigate the relationship between AIWG and antipsychotic-induced lipid changes. Our results identified two novel genome-wide significant loci associated with AIWG: rs10422861 in PEPD (P = 1.373 × 10-9) and rs3824417 in PTPRD (P = 3.348 × 10-9) in Chinese Han samples. The association of rs10422861 was validated in the European samples. Fine-mapping and functional annotation revealed that PEPD and PTPRD are potentially causal genes for AIWG, with their proteins being prospective therapeutic targets. Colocalization analysis suggested that AIWG and type 2 diabetes (T2D) shared a causal variant in PEPD. Polygenic risk scores (PRSs) for AIWG and T2D significantly predicted AIWG in multi-ancestry samples. Furthermore, MR revealed a risky causal effect of genetically predicted changes in low-density lipoprotein cholesterol (P = 7.58 × 10-4) and triglycerides (P = 2.06 × 10-3) caused by acute-phase of antipsychotic treatment on AIWG, which had not been previously reported. Our model, incorporating antipsychotic-induced lipid changes, PRSs, and clinical predictors, significantly predicted BMI percentage change after 6-month antipsychotic treatment (AUC = 0.79, R2 = 0.332). Our results highlight that the mechanism of AIWG involves lipid pathway dysfunction and may share a genetic basis with T2D through PEPD. Overall, this study provides new insights into the pathogenesis of AIWG and contributes to personalized treatment of schizophrenia.

Non-invasive quantification of the brain [18F]FDG-PET using inferred blood input function learned from total-body data with physical constraint.

Full quantification of brain PET requires the blood input function (IF), which is traditionally achieved through an invasive and time-consuming arterial catheter procedure, making it unfeasible for clinical routine. This study presents a deep learning based method to estimate the input function (DLIF) for a dynamic brain FDG scan. A long short-term memory combined with a fully connected network was used. The dataset for training was generated from 85 total-body dynamic scans obtained on a uEXPLORER scanner. Time-activity curves from 8 brain regions and the carotid served as the input of the model, and labelled IF was generated from the ascending aorta defined on CT image. We emphasize the goodness-of-fitting of kinetic modeling as an additional physical loss to reduce the bias and the need for large training samples. DLIF was evaluated together with existing methods in terms of RMSE, area under the curve, regional and parametric image quantifications. The results revealed that the proposed model can generate IFs that closer to the reference ones in terms of shape and amplitude compared with the IFs generated using existing methods. All regional kinetic parameters calculated using DLIF agreed with reference values, with the correlation coefficient being 0.961 (0.913) and relative bias being 1.68±8.74% (0.37±4.93%) for Ki (K1). In terms of the visual appearance and quantification, parametric images were also highly identical to the reference images. In conclusion, our experiments indicate that a trained model can infer an image-derived IF from dynamic brain PET data, which enables subsequent reliable kinetic modeling.

Profiling IOP-responsive genes in anterior and posterior ocular tissues in the rat CEI glaucoma model.

Purpose: The rat Controlled Elevation of Intraocular pressure (CEI) model allows study of in vivo responses to defined intraocular pressures (IOP). In this study, we use Nanostring technology to investigate in vivo IOP-related gene responses in the trabecular meshwork (TM) and optic nerve head (ONH) simultaneously from the same animals. Methods: Male and female rats (N=35) were subject to CEI for 8-hours at pressures simulating mean, daytime normotensive rat IOP (CEI-20), or 2.5x IOP (CEI-50). Naïve animals, receiving no anesthesia or surgical interventions, served as controls. Immediately after CEI, TM and ONH tissues were dissected, RNA isolated, and samples were analyzed with a Nanostring panel containing 770 genes. Post-processing, raw count data were uploaded to Rosalind® for differential gene expression analyses. Results: For the TM, 45 IOP-related genes were significant in the "CEI-50 vs. CEI-20" and "CEI-50 vs. naïve" comparisons, with 15 genes common to both comparisons. Bioinformatics analysis identified Notch and TGFß pathways to be the most up- and down-regulated KEGG pathways, respectively. For ONH, 22 significantly regulated genes were identified in the "CEI-50 vs. naïve" comparison. Pathway analysis identified 'defense response' and 'immune response' as two significantly upregulated biological process pathways. Conclusions: This study demonstrates the ability to assay IOP-responsive genes in both TM and ONH tissues simultaneously. In the TM, downregulation of TGFß pathway genes suggest that TM responses may prevent TGFß-induced extracellular matrix synthesis. For ONH, the initial response to elevated IOP may be protective, with astrocytes playing a key role in these gene responses.

Reducing pediatric total-body PET/CT imaging scan time with multimodal artificial intelligence technology.

OBJECTIVES: This study aims to decrease the scan time and enhance image quality in pediatric total-body PET imaging by utilizing multimodal artificial intelligence techniques. METHODS: A total of 270 pediatric patients who underwent total-body PET/CT scans with a uEXPLORER at the Sun Yat-sen University Cancer Center were retrospectively enrolled. 18F-fluorodeoxyglucose (18F-FDG) was administered at a dose of 3.7 MBq/kg with an acquisition time of 600 s. Short-term scan PET images (acquired within 6, 15, 30, 60 and 150 s) were obtained by truncating the list-mode data. A three-dimensional (3D) neural network was developed with a residual network as the basic structure, fusing low-dose CT images as prior information, which were fed to the network at different scales. The short-term PET images and low-dose CT images were processed by the multimodal 3D network to generate full-length, high-dose PET images. The nonlocal means method and the same 3D network without the fused CT information were used as reference methods. The performance of the network model was evaluated by quantitative and qualitative analyses. RESULTS: Multimodal artificial intelligence techniques can significantly improve PET image quality. When fused with prior CT information, the anatomical information of the images was enhanced, and 60 s of scan data produced images of quality comparable to that of the full-time data. CONCLUSION: Multimodal artificial intelligence techniques can effectively improve the quality of pediatric total-body PET/CT images acquired using ultrashort scan times. This has the potential to decrease the use of sedation, enhance guardian confidence, and reduce the probability of motion artifacts.

The role of dynamic, static, and delayed total-body PET imaging in the detection and differential diagnosis of oncological lesions.

OBJECTIVES: Commercialized total-body PET scanners can provide high-quality images due to its ultra-high sensitivity. We compared the dynamic, regular static, and delayed 18F-fluorodeoxyglucose (FDG) scans to detect lesions in oncologic patients on a total-body PET/CT scanner. MATERIALS & METHODS: In all, 45 patients were scanned continuously for the first 60 min, followed by a delayed acquisition. FDG metabolic rate was calculated from dynamic data using full compartmental modeling, whereas regular static and delayed SUV images were obtained approximately 60- and 145-min post-injection, respectively. The retention index was computed from static and delayed measures for all lesions. Pearson's correlation and Kruskal-Wallis tests were used to compare parameters. RESULTS: The number of lesions was largely identical between the three protocols, except MRFDG and delayed images on total-body PET only detected 4 and 2 more lesions, respectively (85 total). FDG metabolic rate (MRFDG) image-derived contrast-to-noise ratio and target-to-background ratio were significantly higher than those from static standardized uptake value (SUV) images (P < 0.01), but this is not the case for the delayed images (P > 0.05). Dynamic protocol did not significantly differentiate between benign and malignant lesions just like regular SUV, delayed SUV, and retention index. CONCLUSION: The potential quantitative advantages of dynamic imaging may not improve lesion detection and differential diagnosis significantly on a total-body PET/CT scanner. The same conclusion applied to delayed imaging. This suggested the added benefits of complex imaging protocols must be weighed against the complex implementation in the future. CLINICAL RELEVANCE: Total-body PET/CT was known to significantly improve the PET image quality due to its ultra-high sensitivity. However, whether the dynamic and delay imaging on total-body scanner could show additional clinical benefits is largely unknown. Head-to-head comparison between two protocols is relevant to oncological management.

Levels of neuronal pentraxin 2 in plasma is associated with cognitive function in patients with schizophrenia.

RATIONALE: The precise diagnosis and treatment of cognitive impairment remains a major challenge in the field of schizophrenia (SCZ) research. Synaptic dysfunction and loss are thought to be closely related to the occurrence and development of SCZ and may be involved in cognitive dysfunction. OBJECTIVES: The purpose of this study was to investigate whether neuronal pentraxins (NPTXs) plays a role in the etiology of SCZ and provide evidence of its possible therapeutic value a new target for drug development. METHODS: We recruited 275 participants, of whom 148 were SCZ from psychiatric hospital and 127 healthy control (HC) subjects from communities. Plasma concentrations of NPTXs were measured in HC and SCZ at baseline and after 8 weeks of antipsychotic treatment. The MATRICS Cognitive Consensus Battery was used to evaluate cognitive function. Furthermore, the brain is parcellated into 246 subregions using the Brainnetome atlas, and we extracted regional white matter volumes from magnetic resonance images of the SCZ groups. RESULTS: Plasma NPTX2 levels were significantly lower in SCZ compared with HC subjects, but were significantly raised in SCZ after 8 weeks of antipsychotic treatment compared to baseline. In addition, baseline plasma NPTX2 levels were positively correlated with cognitive performance. CONCLUSIONS: These findings indicate that NPTX2 may reveal novel aspects of disease etiology and act as a promising target for new drug development.

Clinical characteristics and prognosis of non-APAP drug-induced acute liver failure: a large multicenter cohort study.

BACKGROUND: There is growing recognition of natural history, complications, and outcomes of patients who develop non-acetaminophen (APAP) drug-induced acute liver failure (ALF). To clarify high-risk factors and develop a nomogram model to predict transplant-free survival (TFS) in patients with non-APAP drug-induced ALF. METHODS: Patients with non-APAP drug-induced ALF from 5 participating centers were retrospectively analyzed. The primary endpoint was 21-day TFS. Total sample size was 482 patients. RESULTS: Regarding causative agents, the most common implicated drugs were herbal and dietary supplements (HDS) (57.0%). The hepatocellular type (R ≥ 5) was the main liver injury pattern (69.0%). International normalized ratio, hepatic encephalopathy grades, the use of vasopressor, N-acetylcysteine, or artificial liver support system were associated with TFS and incorporated to construct a nomogram model (drug-induced acute liver failure-5, DIALF-5). The AUROC of DIALF-5 for 7-day, 21-day, 60-day, and 90-day TFS in the internal cohort were 0.886, 0.915, 0.920, and 0.912, respectively. Moreover, the AUROC of DIALF-5 for 21-day TFS had the highest AUROC, which was significantly higher than 0.725 of MELD and 0.519 of KCC (p < 0.05), numerically higher than 0.905 of ALFSG-PI but without statistical difference (p > 0.05). These results were successfully validated in the external cohort (147 patients). CONCLUSIONS: Based on easily identifiable clinical data, the novel DIALF-5 model was developed to predict transplant-free survival in non-APAP drug-induced ALF, which was superior to KCC, MELD and had a similar prediction performance to ALFSG-PI but is more convenient, which can directly calculate TFS at multiple time points.

Development and validation of a noninvasive prediction model of autoimmune hepatitis in patients with liver diseases.

BACKGROUND AND AIMS: There is no golden standard for the diagnosis of autoimmune hepatitis which still dependent on liver biopsy currently. So, we developed a noninvasive prediction model to help optimize the diagnosis of autoimmune hepatitis. METHODS: From January 2017 to December 2019, 1739 patients who had undergone liver biopsy were seen in the second hospital of Nanjing, of which 128 were here for consultation. Clinical, laboratory, and histologic data were obtained retrospectively. Multivariable logistic regression analysis was employed to create a nomogram model that predicting the risk of autoimmune hepatitis. Internal and external validation was both performed to evaluate the model. RESULTS: A total of 1288 patients with liver biopsy were enrolled (1184 from the second hospital of Nanjing, the remaining 104 from other centers). After the univariate and multivariate logistic regression analysis, nine variables including ALT, IgG, ALP/AST, ALB, ANA, AMA, HBsAg, age, and gender were selected to establish the noninvasive prediction model. The nomogram model exhibits good prediction in diagnosing autoimmune hepatitis with AUROC of 0.967 (95% CI: 0.776-0.891) in internal validation and 0.835 (95% CI: 0.752-0.919) in external validation. CONCLUSIONS: ALT, IgG, ALP/AST, ALB, ANA, AMA, HBsAg, age, and gender are predictive factors for the diagnosis of autoimmune hepatitis in patients with unexplained liver diseases. The predictive nomogram model built by the nine predictors achieved good prediction for diagnosing autoimmune hepatitis.