Advancing Alzheimer's research: Radiomics visualization of the default mode network in cerebral perfusion imaging.

OBJECTIVE: Alzheimer's disease, an irreversible neurological condition, demands timely diagnosis for effective clinical intervention. This study employs radiomics analysis to assess image features in default mode network cerebral perfusion imaging among individuals with cognitive impairment. METHODS: A radiomics analysis of cerebral perfusion imaging was conducted on 117 patients with cognitive impairment. They were divided into training and validation sets in a 7:3 ratio. Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest were employed to select and model image features, followed by logistic regression analysis of LASSO and Random Forest results. Diagnostic performance was assessed by calculating the area under the curve (AUC). RESULTS: In the training set, LASSO achieved AUC of 0.978, Random Forest had an AUC of 0.933. In the validation set, LASSO had AUC of 0.859, Random Forest had AUC of 0.986. By conducting Logistic Regression analysis in combination with LASSO and Random Forest, we identified a total of five radiomics features, with four related to morphology and one to textural features, originating from the medial prefrontal cortex and middle temporal gyrus. In the training set, Logistic Regression achieved AUC of 0.911, while in the validation set, it attained AUC of 0.925. CONCLUSION: The medial prefrontal cortex and middle temporal gyrus are the two brain regions within the default mode network that hold the highest significance for Alzheimer's disease diagnosis. Radiomics analysis contributes to the clinical assessment of Alzheimer's disease by delving into image data to extract deeper layers of information.

Diagnosis of thyroid disease using deep convolutional neural network models applied to thyroid scintigraphy images: a multicenter study.

Objectives: The aim of this study was to improve the diagnostic performance of nuclear medicine physicians using a deep convolutional neural network (DCNN) model and validate the results with two multicenter datasets for thyroid disease by analyzing clinical single-photon emission computed tomography (SPECT) image data. Methods: In this multicenter retrospective study, 3194 SPECT thyroid images were collected for model training (n=2067), internal validation (n=514) and external validation (n=613). First, four pretrained DCNN models (AlexNet, ShuffleNetV2, MobileNetV3 and ResNet-34) for were tested multiple medical image classification of thyroid disease types (i.e., Graves' disease, subacute thyroiditis, thyroid tumor and normal thyroid). The best performing model was then subjected to fivefold cross-validation to further assess its performance, and the diagnostic performance of this model was compared with that of junior and senior nuclear medicine physicians. Finally, class-specific attentional regions were visualized with attention heatmaps using gradient-weighted class activation mapping. Results: Each of the four pretrained neural networks attained an overall accuracy of more than 0.85 for the classification of SPECT thyroid images. The improved ResNet-34 model performed best, with an accuracy of 0.944. For the internal validation set, the ResNet-34 model showed higher accuracy (p < 0.001) when compared to that of the senior nuclear medicine physician, with an improvement of nearly 10%. Our model achieved an overall accuracy of 0.931 for the external dataset, a significantly higher accuracy than that of the senior physician (0.931 vs. 0.868, p < 0.001). Conclusion: The DCNN-based model performed well in terms of diagnosing thyroid scintillation images. The DCNN model showed higher sensitivity and greater specificity in identifying Graves' disease, subacute thyroiditis, and thyroid tumors compared to those of nuclear medicine physicians, illustrating the feasibility of deep learning models to improve the diagnostic efficiency for assisting clinicians.

Isolation of primary human liver cells from normal and nonalcoholic steatohepatitis livers.

Here, we present a protocol for isolating human hepatocytes and neural progenitor cells from normal and nonalcoholic steatohepatitis livers. We describe steps for perfusion for scaled-up liver cell isolation and optimization of chemical digestion to achieve maximal yield and cell viability. We then detail a liver cell cryopreservation and potential applications, such as the use of human liver cells as a tool to link experimental and translational research.

Imageological/Structural Study regarding the Improved Pharmacokinetics by 68Ga-Labeled PEGylated PSMA Multimer in Prostate Cancer.

PMSA (prostate-specific membrane antigen) is currently the most significant target for diagnosing and treating PCa (prostate cancer). Herein, we reported a series 68Ga/177Lu-labeled multimer PSMA tracer conjugating with PEG chain, including [68Ga]Ga-DOTA-(1P-PEG4), [68Ga]Ga-DOTA-(2P-PEG0), [68Ga]Ga-DOTA-(2P-PEG4), and [68Ga]Ga/[177Lu]Lu-DOTA-(2P-PEG4)2, which showed an advantage of a multivalent effect and PEGylation to achieve higher tumor accumulation and faster kidney clearance. To figure out how structural optimizations based on a PSMA multimer and PEGylation influence the probe's tumor-targeting ability, biodistribution, and metabolism, we examined PSMA molecular probes' affinities to PC-3 PIP (PSMA-highly-expressed PC-3 cell line), and conducted pharmacokinetics analysis, biodistribution detection, small animal PET/CT, and SPECT/CT imaging. The results showed that PEG4 and PSMA dimer optimizations enhanced the probes' tumor-targeting ability in PC-3 PIP tumor-bearing mice models. Compared with the PSMA monomer, the PEGylated PSMA dimer reduced the elimination half-life in the blood and increased uptake in the tumor, and the biodistribution results were consistent with PET/CT imaging results. [68Ga]Ga-DOTA-(2P-PEG4)2 exhibited higher tumor-to-organ ratios. When labeled by lutetium-177, relatively high accumulation of DOTA-(2P-PEG4)2 was still detected in PC-3 PIP tumor-bearing mice models after 48 h, indicating its prolonged tumor retention time. Given the superiority in imaging, simple synthetic processes, and structural stability, DOTA-(2P-PEG4)2 is expected to be a promising tumor-targeting diagnostic molecular probe in future clinical practice.

Aberrant iron distribution via hepatocyte-stellate cell axis drives liver lipogenesis and fibrosis.

Hepatocytes have important roles in liver iron homeostasis, abnormalities in which are tightly associated with liver steatosis and fibrosis. Here, we show that non-alcoholic fatty liver disease (NAFLD) and steatohepatitis (NASH) are characterized by iron-deficient hepatocytes and iron overload in hepatic stellate cells (HSCs). Iron deficiency enhances hepatocyte lipogenesis and insulin resistance through HIF2α-ATF4 signaling. Elevated secretion of iron-containing hepatocyte extracellular vesicles (EVs), which are normally cleared by Kupffer cells, accounts for hepatocyte iron deficiency and HSC iron overload in NAFLD/NASH livers. Iron accumulation results in overproduction of reactive oxygen species that promote HSC fibrogenic activation. Conversely, blocking hepatocyte EV secretion or depleting EV iron cargo restores liver iron homeostasis, concomitant with mitigation of NAFLD/NASH-associated liver steatosis and fibrosis. Taken together, these studies show that iron distribution disorders contribute to the development of liver metabolic diseases.

MiR-690 treatment causes decreased fibrosis and steatosis and restores specific Kupffer cell functions in NASH.

Nonalcoholic steatohepatitis (NASH) is a liver disease associated with significant morbidity. Kupffer cells (KCs) produce endogenous miR-690 and, via exosome secretion, shuttle this miRNA to other liver cells, such as hepatocytes, recruited hepatic macrophages (RHMs), and hepatic stellate cells (HSCs). miR-690 directly inhibits fibrogenesis in HSCs, inflammation in RHMs, and de novo lipogenesis in hepatocytes. When an miR-690 mimic is administered to NASH mice in vivo, all the features of the NASH phenotype are robustly inhibited. During the development of NASH, KCs become miR-690 deficient, and miR-690 levels are markedly lower in mouse and human NASH livers than in controls. KC-specific KO of miR-690 promotes NASH pathogenesis. A primary target of miR-690 is NADK mRNA, and NADK levels are inversely proportional to the cellular miR-690 content. These studies show that KCs play a central role in the etiology of NASH and raise the possibility that miR-690 could emerge as a therapeutic for this condition.

Selective PPARδ agonist seladelpar suppresses bile acid synthesis by reducing hepatocyte CYP7A1 via the fibroblast growth factor 21 signaling pathway.

Peroxisome proliferator-activated receptor delta (PPARδ) agonists have been shown to exert beneficial effects in liver disease and reduce total bile acid levels. The mechanism(s) whereby PPARδ agonism reduces bile acid levels are, however, unknown, and therefore the aim of the present study was to investigate the molecular pathways responsible for reducing bile acid synthesis in hepatocytes, following treatment with the selective PPARδ agonist, seladelpar. We show that administration of seladelpar to WT mice repressed the liver expression of cholesterol 7 alpha-hydroxylase (Cyp7a1), the rate-limiting enzyme for bile acid synthesis, and decreased plasma 7α-hydroxy-4-cholesten-3-one (C4), a freely diffusible metabolite downstream of Cyp7a1. In primary mouse hepatocytes, seladelpar significantly reduced the expression of Cyp7a1 independent of the nuclear bile acid receptor, Farnesoid X receptor. In addition, seladelpar upregulated fibroblast growth factor 21 (Fgf21) in mouse liver, serum, and in cultured hepatocytes. We demonstrate that recombinant Fgf21 protein activated the c-Jun N-terminal kinase (JNK) signaling pathway and repressed Cyp7a1 gene expression in primary hepatocytes. The suppressive effect of seladelpar on Cyp7a1 expression was blocked by a JNK inhibitor as well as in the absence of Fgf21, indicating that Fgf21 plays an indispensable role in PPARδ-mediated downregulation of Cyp7a1. Finally, reduction of CYP7A1 expression by seladelpar was confirmed in primary human hepatocytes. In conclusion, we show that seladelpar reduces bile acid synthesis via an FGF21-dependent mechanism that signals at least partially through JNK to repress CYP7A1.

Combined intermittent and sustained hypoxia is a novel and deleterious cardio-metabolic phenotype.

STUDY OBJECTIVES: Chronic obstructive pulmonary disease and obstructive sleep apnea overlap syndrome is associated with excess mortality, and outcomes are related to the degree of hypoxemia. People at high altitudes are susceptible to periodic breathing, and hypoxia at altitude is associated with cardio-metabolic dysfunction. Hypoxemia in these scenarios may be described as superimposed sustained hypoxia (SH) plus intermittent hypoxia (IH), or overlap hypoxia (OH), the effects of which have not been investigated. We aimed to characterize the cardio-metabolic consequences of OH in mice. METHODS: C57BL/6J mice were subjected to either SH (FiO2 = 0.10), IH (FiO2 = 0.21 for 12 h, and FiO2 oscillating between 0.21 and 0.06, 60 times/hour, for 12 h), OH (FiO2 = 0.13 for 12 h, and FiO2 oscillating between 0.13 and 0.06, 60 times/hour, for 12 h), or room air (RA), n = 8/group. Blood pressure and intraperitoneal glucose tolerance test were measured serially, and right ventricular systolic pressure (RVSP) was assessed. RESULTS: Systolic blood pressure transiently increased in IH and OH relative to SH and RA. RVSP did not increase in IH, but increased in SH and OH by 52% (p < .001) and 20% (p = .001). Glucose disposal worsened in IH and improved in SH, with no change in OH. Serum low- and very-low-density lipoproteins increased in OH and SH, but not in IH. Hepatic oxidative stress increased in all hypoxic groups, with the highest increase in OH. CONCLUSIONS: OH may represent a unique and deleterious cardio-metabolic stimulus, causing systemic and pulmonary hypertension, and without protective metabolic effects characteristic of SH.

[Effects of bisphenol-A on blastocyst development and implantation].

OBJECTIVE: To determine the effects of bisphenol-A (BPA) on blastocyst development and implantation. METHODS: According to completely randomized grouping method, 90 pregnant mice were divided into 100, 300, and 600 mg/(kg·d)BPA groups and control group. BPA-treated pregnant mice were orally administered with BPA at concentrations of 100, 300 and 600 mg/(kg·d) from day 0.5 to day 3.5 of their pregnancy. Blastocyst implantation and development were studied. RESULTS: In the 300 mg/(kg·d) BPA group, the number of implantation sites and implantation rate were significantly decreased. In the 600 mg/(kg·d) group, no implantation sites were observed among pregnant mice and BPA inhibited embryo implantation. Blastocyst development on day 4 was examined, and findings showed that the development rate and total numbers of blastocysts in BPA treatment groups had no significant difference from the control group. However, BPA at 300 and 600 mg/(kg·d) significantly reduced blastocyst hatching rate and dramatically increased the number of blastocyst apoptotic cells when compared with those in the control group. CONCLUSION: BPA at a high concentration damages the blastocyst development before implantation and inhibits embryo implantation.