Sleep deprivation adversely affects the digestive system. Multiple studies have suggested sleep deprivation and oxidative stress are closely related. Autophagy can be triggered by oxidative stress as a self-defense strategy to promote survival. In this study, we investigated the effects of sleep deprivation on liver functions, oxidative stress, and concomitant hepatocyte autophagy, as well as the associated pathways. Enzymatic and nonenzymatic biochemical markers in the serum were used to assess hepatic function and damage. To evaluate the occurrence of autophagy, expression of autophagy-related proteins was tested and autophagosomes were labeled. Additionally, methane dicarboxylic aldehyde (MDA), antioxidant enzymes, and the protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway were analyzed using chemical methods and a Western blot. Serum alanine transaminase, aspartate aminotransferase, and alkaline phosphatase increased in sleep-deprived rats. Total protein and albumin abundance was also abnormal. Sleep deprivation induced histopathological changes in the liver. The superoxide dismutase level decreased significantly in the liver of sleep-deprived rats. In contrast, the MDA content increased in the sleep deprivation group. Moreover, the microtubule-associated protein 1 light chain 3 beta (LC3B) II/I ratio and Beclin I content increased considerably in the sleep-deprived rats, while p62 levels decreased. Sleep deprivation apparently inhibited the AKT/mTOR signaling pathway. We conclude that sleep deprivation can induce oxidative stress and ultimately cause liver injury. Autophagy triggered by oxidative stress appears to be mediated by the AKT/mTOR pathway and plays a role in relieving oxidative stress caused by sleep deprivation.

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Purpose This study explored the feasibility of reducing the scan time of Patlak parametric imaging on the uEXPLORER. Methods A total of 65 patients (27 females and 38 males, age 56.1 ± 10.4) were recruited in this study. 18F fluorodeoxyglucose was injected, and its dose was adjusted by body weight (4.07 MBq/kg). Total‐body dynamic scanning was performed on the uEXPLORER total‐body Positron emission tomography/computed tomography (CT) scanner with a total scan time of 60 min from the injection. The image derived input function (IDIF) was obtained from the aortic arch. The voxelwise Patlak analysis was applied to generate the Ki images designated as GIDIF with different acquisition times (20–60, 30–60, 40‐60, and 44–60 min). The population‐based input function (PBIF) was constructed from the mean value of the IDIF from the population, and Ki images designated as GPBIF were generated using the PBIF. Nonlocalmeans (NLM) denoising was applied to the generated images to get two extra groups of (NLM‐designated) images: GIDIF+NLM and GPBIF+NLM. Two radiologists evaluated the overall image quality, noise, and lesion detectability of the Ki images from different groups. The 20–60 min scans in GIDIF were selected as the gold standard for each patient. We determined that image quality is at sufficient level if all the lesions can be recognized and meet the clinical criteria. Ki values in muscle and lesion were compared across different groups to evaluate the quantitative accuracy. Results The overall image quality, image noise, and lesion conspicuity were significantly better in long time series than short time series in all four groups (all p < 0.001). The Ki images in the GIDIF and GPBIF groups generated from 30‐min scans showed diagnostic value equivalent to the 40‐min scans of GIDIF. While the image quality of the 16‐min scans was poor, all lesions could still be detected. No significant difference was found between Ki values estimated with GIDIF and GPBIF in muscle and lesion regions (all p > 0.5). After applying the NLM filter, the coefficient of variation could be reduced on the order of (1%, 15%, 19%, and 37%) and (110%, 125%, 94%, and 69%) with four acquisition time schemes for lesion and muscle. The reduction percentage did not have a substantial difference in IDIF and PBIF group. The Ki images in the GIDIF+NLM and GPBIF+NLM groups generated from the 20‐min acquisitions showed acceptable quality. All lesions could be found on the NLM processed images of the 16‐min scans. No significant difference was found between Ki values produced with GIDIF+NLM and GPBIF+NLM in muscle and lesion regions(all p > 0.7). Conclusions The Ki images generated by the PBIF‐based Patlak model using a 20‐min dynamic scan with the NLM filter achieved a similar diagnostic efficiency to images with GIDIF from 40‐min dynamic data, and there is no significant difference between Ki images generated using IDIF or PBIF (p > 0.5).

Radiation-induced lung injury (RILI) frequently occurs in patients with thoracic malignancies. In response to radiation, alveolar epithelial cells (AEC) undergo epithelial-mesenchymal transition (EMT) and contribute to the pathogenesis of RILI. Insulin-like growth factor binding protein 7 (IGFBP7) is reported as a downstream mediator of transforming growth factor-β1 (TGF-β1) pathway, which plays a crucial role in radiationinduced EMT. In the present study, the levels of IGFBP7 and TGF-β1 were simultaneously increased in experimental RILI models and radiationtreated AEC (human pulmonary alveolar epithelial cells [HPAEpic]). The expression of IGFBP7 in radiation-treated HPAEpic cells was obviously inhibited by the specific inhibitor of TGF-β receptor antagonist SB431542 and TGF-β1 neutralizing antibody, and time-dependently enhanced by TGF-β1 treatment. Moreover, IGFBP7 knockdown significantly attenuated the effects of radiation on morphology change, cell migration, expression of EMT-related markers (E-cadherin, α-SMA, and Vimentin), and phosphorylation of extracellular-signal-regulated kinase (ERK). The effects of IGFBP7 overexpression on the expression of EMT-related markers were partially reversed by the ERK inhibitor PD98059. In conclusion, IGFBP7, was enhanced by TGF-β1, may be involved in radiation-induced EMT of AEC via the ERK signaling pathway, thus contributing to the pathogenesis of RILI.

In situ microfibrillar composites (PP/mPA66) of modified polyamide66 (mPA66) with polypropylene (PP) were prepared by using a “post‐compatibilization” technique. The mPA66 was firstly obtained by reactive extrusion of PA66 resin with a specially designed compatibilizer, which was then blended with PP through extrusion combined with a hot stretching and subsequently quenching process. The PP/mPA66 in situ microfibrillar composites were comparatively studied with simply blended samples of PP/PA66 that were prepared by blending PA66 and PP together with (or without) the same compatibilizer through extrusion. PA66‐g‐PP (and/or elastomers) graft copolymer formation in mPA66 was identified by dissolution test and infrared spectroscopy measurement, the compatibilizer is unevenly dispersed with large domains in PA66 as observed by scanning electron microscope (SEM). In PP/mPA66 composites, the in situ generated PA66 microfibrils have a rather nonuniform diameter distribution and a very rough surface. SEM observations for the fractured surface illustrated that PP/mPA66 composites have structural characteristics of stronger adhesion and moderate flexibility of the interface. Enhanced compatibilization between the PA66 microfibrils with the PP matrix resulted in improved mechanical properties of the PP/mPA66 composites. With optimized composition, the PP/mPA66 composite has notched Izod impact strength, flexural modulus, and tensile yield stress of 1.49, 1.16, and 0.99 times as those of the neat PP, respectively. Such enhanced mechanical properties balance and improved interface adhesion were not found in the simply blended samples of PP/PA66 with or without the specially designed compatibilizer. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013

Objectives To use magnetic resonance fingerprinting (MRF)-derived T1 and T2 values to differentiate gonadotroph from nongonadotroph pituitary macroadenomas based on the 2017 World Health Organization classification of pituitary adenomas. Methods A total of 57 patients with suspected pituitary macroadenomas were enrolled for analyses in this study between May 2018 and January 2020. Conventional magnetic resonance imaging (MRI) and MRF were performed in all patients before surgery using a 3-T MRI scanner. MRF-derived T1 and T2 values were compared between the gonadotroph and non-gonadotroph pituitary macroadenomas using a Mann-Whitney U test. The Knosp classification was used to evaluate cavernous sinus invasion by the adenomas. Receiver operating characteristic analyses were used to determine the diagnostic performance of T1 and T2 values. Results Quantitative T1 and T2 values yielded from MRF of gonadotroph pituitary macroadenomas were significantly higher than those of the non-gonadotroph pituitary macroadenomas (p < 0.001 and = 0.002, respectively). The AUC for the T2 value (0.888) was significantly greater than that for the T1 value (0.742) (p = 0.034). The AUC for combined T1 and T2 values was 0.885. Non-gonadotroph pituitary macroadenomas were more likely to invade the cavernous sinus than gonadotroph pituitary macroadenomas (55% vs 26%, p = 0.026). Conclusions MRF may help to preoperatively differentiate between gonadotroph and non-gonadotroph pituitary macroadenomas and may be useful in guiding the treatment of these adenomas. Key Points • Somatostatin receptor type 3 is the most abundant receptor subtype in gonadotroph pituitary adenomas.• Magnetic resonance fingerprinting may help to preoperatively differentiate between gonadotroph and non-gonadotroph pituitary macroadenomas. • Magnetic resonance fingerprinting shows potential for guiding the treatment of pituitary macroadenomas.

Background: The choice of surgical treatment for meningiomas is affected by the subtype and clinical characteristics. Therefore, an accurate preoperative diagnosis is essential. Current magnetic resonance imaging (MRI) technology is unable to distinguish between meningioma subtypes. In the present study, we compared and evaluated the utility of conventional MRI, magnetic resonance fingerprinting (MRF), and diffusion-weighted imaging (DWI) in differentiating World Health Organization grade I transitional and fibrous meningiomas from meningothelial meningiomas.Methods: Forty-six patients with pathologically confirmed meningiomas (15 meningothelial, 18 transitional, and 13 fibrous) were enrolled in the present study. All patients underwent conventional MRI, MRF, and DWI scans before surgery using a 3T scanner. The Jonckheere-Terpstra test was used to analyze differences in the signal and enhancement characteristics of the three groups from T 1 -weighted imaging (T1WI) and T 2 -weighted imaging (T2WI). To investigate the difference in quantitative T1 and T2 values derived from MRF and apparent diffusion coefficient (ADC) values between the three groups using the Kruskal-Wallis test, regions of interest (ROIs) were manually drawn on the parenchymal portion of the tumors; P<0.017 was considered statistically significant after Bonferroni correction for multiple comparison.The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performances of the different parameters.Results: Meningothelial meningiomas had significantly higher T1 and T2 values than transitional and fibrous meningiomas (all P<0.017). ROC analysis results revealed that the combination of T1 and T2 values had the largest area under the curve (AUC). The AUC for the combination of T1 and T2 values was 0.826 between meningothelial and transitional meningiomas, and the AUC for the combination of T1 and T2 values between meningothelial and fibrous meningiomas was 0.903. No significant differences were found in the T1 and T2 values between transitional and fibrous meningiomas. There were also no statistically significant differences in the conventional MRI (including T1WI, T2WI, and contrast-enhanced T1WI) and ADC values between the three meningioma subtypes (all P>0.05).Conclusions: MRF may provide more quantitative information than either conventional MRI or DWI for differentiating transitional and fibrous meningiomas from meningothelial meningiomas. T1 and T2 values derived from MRF may distinguish transitional and fibrous meningiomas from meningothelial meningiomas, and the combination of T1 and T2 values provides the highest diagnostic efficacy.

Although paclitaxel is a promising frontline chemotherapy agent for various malignancies, the clinical applications have been restricted by side effects, drug resistance, and cancer metastasis. The combination of paclitaxel and other agents could be the promising strategies against malignant tumor, which enhances the antitumor effect through synergistic effects, reduces required drug concentrations, and also suppresses tumorigenesis in multiple ways. In this study, we found that luteolin, a natural flavonoid compound, combined with low-dose paclitaxel synergistically regulated the proliferation, migration, epithelial-mesenchymal transition (EMT), and apoptosis of esophageal cancer cells in vitro, as well as synergistically inhibited tumor growth without obvious toxicity in vivo. The molecular mechanism of inhibiting cell migration and EMT processes may be related to the inhibition of SIRT1, and the mechanism of apoptosis induction is associated with the reactive oxygen species (ROS)/c-Jun N-terminal kinase (JNK) pathway-mediated activation of mitochondrial apoptotic pathway.