Distinct Processing of lncRNAs Contributes to Non-conserved Functions in Stem Cells.

Long noncoding RNAs (lncRNAs) evolve more rapidly than mRNAs. Whether conserved lncRNAs undergo conserved processing, localization, and function remains unexplored. We report differing subcellular localization of lncRNAs in human and mouse embryonic stem cells (ESCs). A significantly higher fraction of lncRNAs is localized in the cytoplasm of hESCs than in mESCs. This turns out to be important for hESC pluripotency. FAST is a positionally conserved lncRNA but is not conserved in its processing and localization. In hESCs, cytoplasm-localized hFAST binds to the WD40 domain of the E3 ubiquitin ligase ß-TrCP and blocks its interaction with phosphorylated ß-catenin to prevent degradation, leading to activated WNT signaling, required for pluripotency. In contrast, mFast is nuclear retained in mESCs, and its processing is suppressed by the splicing factor PPIE, which is highly expressed in mESCs but not hESCs. These findings reveal that lncRNA processing and localization are previously under-appreciated contributors to the rapid evolution of function.

Gene regulation by long non-coding RNAs and its biological functions.

Evidence accumulated over the past decade shows that long non-coding RNAs (lncRNAs) are widely expressed and have key roles in gene regulation. Recent studies have begun to unravel how the biogenesis of lncRNAs is distinct from that of mRNAs and is linked with their specific subcellular localizations and functions. Depending on their localization and their specific interactions with DNA, RNA and proteins, lncRNAs can modulate chromatin function, regulate the assembly and function of membraneless nuclear bodies, alter the stability and translation of cytoplasmic mRNAs and interfere with signalling pathways. Many of these functions ultimately affect gene expression in diverse biological and physiopathological contexts, such as in neuronal disorders, immune responses and cancer. Tissue-specific and condition-specific expression patterns suggest that lncRNAs are potential biomarkers and provide a rationale to target them clinically. In this Review, we discuss the mechanisms of lncRNA biogenesis, localization and functions in transcriptional, post-transcriptional and other modes of gene regulation, and their potential therapeutic applications.

SLERT Regulates DDX21 Rings Associated with Pol I Transcription.

Dysregulated rRNA synthesis by RNA polymerase I (Pol I) is associated with uncontrolled cell proliferation. Here, we report a box H/ACA small nucleolar RNA (snoRNA)-ended long noncoding RNA (lncRNA) that enhances pre-rRNA transcription (SLERT). SLERT requires box H/ACA snoRNAs at both ends for its biogenesis and translocation to the nucleolus. Deletion of SLERT impairs pre-rRNA transcription and rRNA production, leading to decreased tumorigenesis. Mechanistically, SLERT interacts with DEAD-box RNA helicase DDX21 via a 143-nt non-snoRNA sequence. Super-resolution images reveal that DDX21 forms ring-shaped structures surrounding multiple Pol I complexes and suppresses pre-rRNA transcription. Binding by SLERT allosterically alters individual DDX21 molecules, loosens the DDX21 ring, and evicts DDX21 suppression on Pol I transcription. Together, our results reveal an important control of ribosome biogenesis by SLERT lncRNA and its regulatory role in DDX21 ring-shaped arrangements acting on Pol I complexes.

Mechanisms of Long Noncoding RNA Nuclear Retention.

Long noncoding RNAs (lncRNAs) are crucial regulators in diverse cellular contexts and biological processes. The subcellular localization of lncRNAs determines their modes of action. Compared to mRNAs, however, many mRNA-like lncRNAs are preferentially localized to the nucleus where they regulate chromatin organization, transcription, and different nuclear condensates. Recent studies have revealed the complex mechanisms that govern lncRNA nuclear retention. We review current understanding of how the transcription and processing of lncRNAs, motifs within lncRNAs, and trans-factors coordinately contribute to their nuclear retention in mammalian cells.

Impaired olfactory identification in dementia-free individuals is associated with the functional abnormality of the precuneus.

OBJECTIVE: Olfactory dysfunction indicates a higher risk of developing dementia. However, the potential structural and functional changes are still largely unknown. METHODS: A total of 236 participants were enrolled, including 45 Alzheimer's disease (AD) individuals and 191dementia-free individuals. Detailed study methods, comprising neuropsychological assessment and olfactory identification test (University of Pennsylvania smell identification test, UPSIT), as well as structural and functional magnetic resonance imaging (MRI) were applied in this research. The dementia-free individuals were divided into two sub-groups based on olfactory score: dementia-free with olfactory dysfunction (DF-OD) sub-group and dementia-free without olfactory dysfunction (DF-NOD) sub-group. The results were analyzed for subsequent intergroup comparisons and correlations. The cognitive assessment was conducted again three years later. RESULTS: (i) At dementia-free stage, there was a positive correlation between olfactory score and cognitive function. (ii) In dementia-free group, the volume of crucial brain structures involved in olfactory recognition and processing (such as amygdala, entorhinal cortex and basal forebrain volumes) are positively associated with olfactory score. (iii) Compared to the DF-NOD group, the DF-OD group showed a significant reduction in olfactory network (ON) function. (iv) Compared to DF-NOD group, there were significant functional connectivity (FC) decline between PCun_L(R)_4_1 in the precuneus of posterior default mode network (pDMN) and the salience network (SN) in DF-OD group, and the FC values decreased with falling olfactory scores. Moreover, in DF-OD group, the noteworthy reduction in FC were observed between PCun_L(R)_4_1 and amygdala, which was a crucial component of ON. (v) The AD conversion rate of DF-OD was 29.41%, while the DF-NOD group was 12.50%. The structural and functional changes in the precuneus were also observed in AD and were more severe. CONCLUSIONS: In addition to the olfactory circuit, the precuneus is a critical structure in the odor identification process, whose abnormal function underlies the olfactory identification impairment of dementia-free individuals.

[Titin: structure, isoforms and functional regulation].

Titin, the largest known protein in the body expressed in three isoforms (N2A, N2BA and N2B), is essential for muscle structure, force generation, conduction and regulation. Since the 1950s, muscle contraction mechanisms have been explained by the sliding filament theory involving thin and thick muscle filaments, while the contribution of cytoskeleton in force generation and conduction was ignored. With the discovery of insoluble protein residues and large molecular weight proteins in muscle fibers, the third myofilament, titin, has been identified and attracted a lot of interests. The development of single molecule mechanics and gene sequencing technology further contributed to the extensive studies on the arrangement, structure, elastic properties and components of titin in sarcomere. Therefore, this paper reviews the structure, isforms classification, elastic function and regulatory factors of titin, to provide better understanding of titin.

Distortion correction of single-shot EPI enabled by deep-learning.

PURPOSE: A distortion correction method for single-shot EPI was proposed. Point-spread-function encoded EPI (PSF-EPI) images were used as the references to correct traditional EPI images based on deep neural network. THEORY AND METHODS: The PSF-EPI method can obtain distortion-free echo planar images. In this study, a 2D U-net based network was trained to achieve the distortion correction of single-shot EPI (SS-EPI) images, using PSF-EPI images as targets in the training stage. Anatomical T2W-TSE images were also fed into the network to improve the quality of the results. The applications in diffusion-weighted images were used as examples in this work. The network was trained on data acquired on healthy volunteers and tested on data of both healthy volunteers and patients. The corrected EPI images from the proposed method were also compared with those from field-mapping and top-up based distortion correction methods. RESULTS: Experimental results showed that the proposed method can correct for EPI distortions better than both the field-mapping and top-up based methods, and the results were close to the distortion-free images from PSF-EPI. Additionally, inclusion of T2W-TSE images helped improve distortion correction of the SS-EPI images without contaminating the output noticeably. The experiments with patients and different MRI platforms demonstrated the generalization feasibility of the proposed method preliminarily. CONCLUSION: Through the correction of diffusion-weighted images, the proposed deep-learning based method was demonstrated to have the feasibility to correct for the distortion of EPI images.

Repeatability and reproducibility of FreeSurfer, FSL-SIENAX and SPM brain volumetric measurements and the effect of lesion filling in multiple sclerosis.

OBJECTIVES: To compare the cross-sectional robustness of commonly used volumetric software and effects of lesion filling in multiple sclerosis (MS). METHODS: Nine MS patients (six females; age 38±13 years, disease duration 7.3±5.2 years) were scanned twice with repositioning on three MRI scanners (Siemens Aera 1.5T, Avanto 1.5T, Trio 3.0T) the same day. Volumetric T1-weighted images were processed with FreeSurfer, FSL-SIENAX, SPM and SPM-CAT before and after 3D FLAIR lesion filling with LST. The whole-brain, grey matter (GM) and white matter (WM) volumes were calculated with and without normalisation to the intracranial volume or FSL-SIENAX scaling factor. Robustness was assessed using the coefficient of variation (CoV). RESULTS: Variability in volumetrics was lower within than between scanners (CoV 0.17-0.96% vs. 0.65-5.0%, p<0.001). All software provided similarly robust segmentations of the brain volume on the same scanner (CoV 0.17-0.28%, p=0.076). Normalisation improved inter-scanner reproducibility in FreeSurfer and SPM-based methods, but the FSL-SIENAX scaling factor did not improve robustness. Generally, SPM-based methods produced the most consistent volumetrics, while FreeSurfer was more robust for WM volumes on different scanners. FreeSurfer had more robust normalised brain and GM volumes on different scanners than FSL-SIENAX (p=0.004). MS lesion filling changed the output of FSL-SIENAX, SPM and SPM-CAT but not FreeSurfer. CONCLUSIONS: Consistent use of the same scanner is essential and normalisation to the intracranial volume is recommended for multiple scanners. Based on robustness, SPM-based methods are particularly suitable for cross-sectional volumetry. FreeSurfer poses a suitable alternative with WM segmentations less sensitive to MS lesions. KEY POINTS: • The same scanner should be used for brain volumetry. If different scanners are used, the intracranial volume normalisation improves the FreeSurfer and SPM robustness (but not the FSL scaling factor). • FreeSurfer, FSL and SPM all provide robust measures of the whole brain volume on the same MRI scanner. SPM-based methods overall provide the most robust segmentations (except white matter segmentations on different scanners where FreeSurfer is more robust). • MS lesion filling with Lesion Segmentation Toolbox changes the output of FSL-SIENAX and SPM. FreeSurfer output is not affected by MS lesion filling since it already takes white matter hypointensities into account and is therefore particularly suitable for MS brain volumetry.

Pharmacokinetics and tissue distribution of oroxin B in rats using a validated LC-MS/MS assay.

A highly sensitive LC-MS/MS method was developed to measure oroxin B in rat plasma and tissue homogenates. The analyte and IS were isolated from biological matrices by a simple protein precipitation followed by centrifugation. Detection was conducted by electrospray negative-ionization mass spectrometry in selected-reaction monitoring mode. The assay was linear in the concentration range 4.52-904 ng/mL with intra- and inter-day precision of <14.41%. It was successfully applied to the pharmacokinetics and tissue distribution studies of oroxin B after an intravenous dose of 1.0 mg/kg in rats. The results would be useful for further development of oroxin B.

Simultaneous determination of sesquiterpene lactones isoalantolactone and alantolactone isomers in rat plasma by liquid chromatography with tandem mass spectrometry: application to a pharmacokinetic study.

A selective, sensitive, and accurate LC-MS/MS method for the simultaneous determination of isoalantolactone and alantolactone in rat plasma has been developed using psoralen as the internal standard. LC-MS/MS analysis was carried out on a Triple Quadrupole mass spectrometer using positive ion ESI and the selected reaction monitoring mode. The assays were linear in the range of 7.5-750 ng/mL for isoalantolactone and 5.5-550 ng/mL for alantolactone. The average recoveries in plasma samples both were better than 85%. The intra- and inter-day precision and accuracy values were found to be within the assay variability criteria limits according to the US FDA guidelines. The method was successfully applied to pharmacokinetic studies of the two structural isomers after an intravenous injection of Inula helenium formulation to rats.

A joint model for lesion segmentation and classification of MS and NMOSD.

Introduction: Multiple sclerosis (MS) and neuromyelitis optic spectrum disorder (NMOSD) are mimic autoimmune diseases of the central nervous system with a very high disability rate. Their clinical symptoms and imaging findings are similar, making it difficult to diagnose and differentiate. Existing research typically employs the T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) MRI imaging technique to focus on a single task in MS and NMOSD lesion segmentation or disease classification, while ignoring the collaboration between the tasks. Methods: To make full use of the correlation between lesion segmentation and disease classification tasks of MS and NMOSD, so as to improve the accuracy and speed of the recognition and diagnosis of MS and NMOSD, a joint model is proposed in this study. The joint model primarily comprises three components: an information-sharing subnetwork, a lesion segmentation subnetwork, and a disease classification subnetwork. Among them, the information-sharing subnetwork adopts a dualbranch structure composed of a convolution module and a Swin Transformer module to extract local and global features, respectively. These features are then input into the lesion segmentation subnetwork and disease classification subnetwork to obtain results for both tasks simultaneously. In addition, to further enhance the mutual guidance between the tasks, this study proposes two information interaction methods: a lesion guidance module and a crosstask loss function. Furthermore, the lesion location maps provide interpretability for the diagnosis process of the deep learning model. Results: The joint model achieved a Dice similarity coefficient (DSC) of 74.87% on the lesion segmentation task and accuracy (ACC) of 92.36% on the disease classification task, demonstrating its superior performance. By setting up ablation experiments, the effectiveness of information sharing and interaction between tasks is verified. Discussion: The results show that the joint model can effectively improve the performance of the two tasks.

2.5D transfer deep learning model for segmentation of contrast-enhancing lesions on brain magnetic resonance imaging of multiple sclerosis and neuromyelitis optica spectrum disorder.

Background: Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are the two mimic autoimmune diseases of the central nervous system, which are rare in East Asia. Quantitative detection of contrast-enhancing lesions (CELs) on contrast-enhancing T1-weighted magnetic resonance (MR) images is of great significance for assessing the disease activity of MS and NMOSD. However, it is challenging to develop automatic segmentation algorithms due to the lack of data. In this work, we present an automatic segmentation model of CELs based on Fully Convolutional with Attention DenseNet (FCA-DenseNet) and transfer learning strategy to address the challenge of CEL quantification in small-scale datasets. Methods: A transfer learning approach was employed in this study, whereby pretraining was conducted using 77 MS subjects from the open access datasets (MICCAI 2016, MICCAI 2017, ISBI 2015) for white matter hyperintensity segmentation, followed by fine-tuning using 24 MS and NMOSD subjects from the local dataset for CEL segmentation. The proposed FCA-DenseNet combined the Fully Convolutional DenseNet and Convolutional Block Attention Module in order to improve the learning capability. A 2.5D data slicing strategy was used to process complex 3D MR images. U-Net, ResUNet, TransUNet, and Attention-UNet are used as comparison models to FCA-DenseNet. Dice similarity coefficient (DSC), positive predictive value (PPV), true positive rate (TPR), and volume difference (VD) are used as evaluation metrics to evaluate the performances of different models. Results: FCA-DenseNet outperforms all other models in terms of all evaluation metrics, with a DSC of 0.661±0.187, PPV of 0.719±0.201, TPR of 0.680±0.254, and VD of 0.388±0.334. Transfer learning strategy has achieved success in building segmentation models on a small-scale local dataset where traditional deep learning approaches fail to train effectively. Conclusions: The improved FCA-DenseNet, combined with transfer learning strategy and 2.5D data slicing strategy, has successfully addressed the challenges in constructing deep learning models on small-scale datasets, making it conducive to clinical quantification of brain CELs and diagnosis of MS and NMOSD.

Dual Semi-Supervised Learning for Classification of Alzheimer's Disease and Mild Cognitive Impairment Based on Neuropsychological Data.

Deep learning has shown impressive diagnostic abilities in Alzheimer's disease (AD) research in recent years. However, although neuropsychological tests play a crucial role in screening AD and mild cognitive impairment (MCI), there is still a lack of deep learning algorithms only using such basic diagnostic methods. This paper proposes a novel semi-supervised method using neuropsychological test scores and scarce labeled data, which introduces difference regularization and consistency regularization with pseudo-labeling. A total of 188 AD, 402 MCI, and 229 normal controls (NC) were enrolled in the study from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We first chose the 15 features most associated with the diagnostic outcome by feature selection among the seven neuropsychological tests. Next, we proposed a dual semi-supervised learning (DSSL) framework that uses two encoders to learn two different feature vectors. The diagnosed 60 and 120 subjects were randomly selected as training labels for the model. The experimental results show that DSSL achieves the best accuracy and stability in classifying AD, MCI, and NC (85.47% accuracy for 60 labels and 88.40% accuracy for 120 labels) compared to other semi-supervised methods. DSSL is an excellent semi-supervised method to provide clinical insight for physicians to diagnose AD and MCI.

Local Brain Network Alterations and Olfactory Impairment in Alzheimer's Disease: An fMRI and Graph-Based Study.

Alzheimer's disease (AD) is associated with the abnormal connection of functional networks. Olfactory impairment occurs in early AD; therefore, exploring alterations in olfactory-related regions is useful for early AD diagnosis. We combined the graph theory of local brain network topology with olfactory performance to analyze the differences in AD brain network characteristics. A total of 23 patients with AD and 18 normal controls were recruited for resting-state functional magnetic resonance imaging (fMRI), clinical neuropsychological examinations and the University of Pennsylvania Smell Identification Test (UPSIT). Between-group differences in the topological properties of the local network were compared. Pearson correlations were explored based on differential brain regions and olfactory performance. Statistical analysis revealed a correlation of the degree of cognitive impairment with olfactory recognition function. Local node topological properties were significantly altered in many local brain regions in the AD group. The nodal clustering coefficients of the bilateral temporal pole: middle temporal gyrus (TPOmid), degree centrality of the left insula (INS.L), degree centrality of the right middle temporal gyrus (MTG.R), and betweenness centrality of the left middle temporal gyrus (MTG.L) were related to olfactory performance. Alterations in local topological properties combined with the olfactory impairment can allow early identification of abnormal olfactory-related regions, facilitating early AD screening.

Clinical characteristics of late-onset neuromyelitis optica spectrum disorder.

BACKGROUND: Anti-aquaporin-4 (AQP-4) immunoglobulin G (IgG) is a major autoimmune antibody that contributes to the pathogenesis of neuromyelitis optica spectrum disorder (NMOSD). NMOSD often presents as disability, severe sensory impairment, and sleep disorders, which can cause anxiety and depression and further affect the quality of life. The age of onset is a key factor influencing the prognosis of NMOSD. However, this result was based on studies involving only anti-aquaporin-4 (AQP4) immunoglobulin G (IgG)-seropositive NMOSD patients or studies using the 2006 NMOSD diagnosis criteria. Therefore, further study of the age of onset of NMOSD is valuable. This study aimed to describe the clinical and magnetic resonance imaging (MRI) differences between early-onset neuromyelitis optica spectrum disorder (EO-NMOSD) and late-onset (LO)-NMOSD patients. METHODS: Fifty patients were enrolled, their anti-AQP4-IgG titers were measured, and brain and spinal cord MRIs were obtained. Additionally, several questionnaires related to disease severity, anxiety, depression, cognition, sleep, pain, and fatigue were collected. RESULTS: Higher AQP4-IgG seropositivity, higher AQP4-IgG titer, frequency of thoracic myelitis, and white matter hyperintensities (WMH), as well as greater severity of disability, greater severity of sleep disorders, higher anxiety, poorer cognitive function, and higher clinical dementia rating (CDR)-community affairs scores were observed in late-onset (LO)-NMOSD patients than those in early-onset (EO)-NMOSD. AQP4-IgG titer positively correlated with age, annual relapse rate, Expanded Disability Status Scale (EDSS) sensory scores, Activity of Daily Living Scale (ADL) scores, and Pittsburgh Sleep Quality Index (PSQI) scores. The EDSS-sensory scores positively correlated with age, relapse time, Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, PSQI, ADL, and CDR. WMH was positively correlated with age, EDSS-sensory scores, PSQI scores, and CDR scores and negatively correlated with the California Verbal Learning Test scores. CONCLUSION: LO-NMOSD patients have worse prognoses than those of EO-NMOSD patients. Higher AQP4-IgG titers, more WMHs, thoracic myelitis, and severe sensory symptoms are associated with cognition, depression, anxiety, and sleep disorders.

Two case reports and a systematic review of the literature on adult cerebral cortical encephalitis with anti-myelin oligodendrocyte glycoprotein antibody.

Background and purpose: Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) has gained recognition in recent years as an immune-mediated inflammatory demyelinating disease of the central nervous system. The clinical features and prognosis of MOGAD adult cerebral cortical encephalitis (adult CCE) have not been fully elucidated. This study aims to further characterize the clinical symptoms, magnetic resonance imaging (MRI) findings, and prognosis of CCE with anti-MOG antibody. Methods: We present two adult cases of CCE with anti-MOG antibody and summarize the clinical symptoms, magnetic resonance imaging (MRI) findings, and prognosis of this phenotype as per a completed systematic review of the literature. Results: We found a total of 39 cases of MOGAD adult CCE (36% females; average age of onset of 29 years). Among them, 85% had seizure, 82% had headache, 64% had cortical symptoms, 64% had fever, 54% had changes of consciousness, and 38% had ocular symptoms. All cases demonstrated cerebral cortical T2 fluid-attenuated inversion recovery (FLAIR) lesions on MRI. Of the 25 patients (with seizure or not) who had EEG reports, 76% of patients showed abnormal EEG. Cerebrospinal fluid (CSF) white blood cell count of 90% of patients and CSF total protein of 67% of patients were elevated. In 16 patients with available CSF cytology data, 11 (69%) had abnormal cytology findings with monocytic predominance. In the 15 cases for which MOG antibody IgG was tested in both serum and CSF, 14 (93%) demonstrated a higher positive MOG IgG titer in serum than CSF. The majority of patients were treated with immunosuppressive therapy (97% corticosteroids, 15% mycophenolate mofetil, 13% IVIg, 5% azathioprine, and 5% other). The majority of patients had a favorable prognosis after treatment, as exemplified by improved clinical symptoms and imaging. Two patients relapsed. Conclusions: The clinical presentation and prognosis of adult CCE remain less understood in comparison to more common MOGAD phenotypes. It is important to consider MOGAD as an underlying etiology for adult CCE, as early detection and immunotherapy may improve outcomes.

Effect of Tai Chi combined with Kinesio taping on posture control of football players with FAI: protocol for a randomized controlled trial.

BACKGROUND: Functional ankle instability (FAI) of college football players is an important risk factor affecting their training and competition. Physical therapy and appropriate sports intervention can improve the stability of FAI patients. Previous studies have shown that Tai Chi (TC) and Kinesio taping (KT) can improve the posture control ability of FAI patients. However, whether Tai Chi combined with Kinesio taping effect patch can be used as an effective exercise for rehabilitation of college football players with FAI is not yet proven. METHODS/DESIGN: Fifty-three FAI college football players were randomly assigned to 3 groups: TC+KT (n = 20); TC+KTp (placebo Kinesio taping, KTp, placebo) (n = 17), and KT (n = 16). The TC+KT group received TC and KT functional correction technical intervention, the TC+KTp group received TC and placebo KT technical intervention, and the KT group received KT functional correction technical intervention. Each of the three groups received 30 min each time, 3 times a week, for a total of 6 weeks of intervention training. Star Excursion Balance Test (SEBT) and UniPedal Stance Test (UST) at baseline (before), 4 weeks after intervention (middle), and 6 weeks after intervention (after) and Toe Touch Test (TTT) were evaluated. DISCUSSION: For the first time in this trial, the impact will be evaluated. If the results are the same as expected, they will provide evidence that Tai Chi combined with Kinesio taping sticking intervention can promote the posture control of college football players with FAI. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR1900027253 . Registered on 6 November 2019.

[Effects of alternate-day modified fasting combined exercise on fat reducing and the FNDC5/Irisin-UCP1 pathway].

OBJECTIVE: The effects of Alternate-day modified fasting combined exercise on fat mass, muscle mass, and serum Irisin, FNDC5 and UCP1 proteins were investigated in rats with 4 weeks of aerobic exercise and modified alternate-day fasting intervention. METHODS: Thirty-two healthy 8-week-old SPF male SD rats were randomly divided into control group, exercise group, alternate-day modified fasting and alternate-day modified fasting combined with exercise group, 8 rats in each group. The exercise group performed treadmill exercise with moderate exercise intensity(60 min/d,5 d/w), the alternate-day modified fasting group alternated between fasting and free feeding every other day, and fed 25% basal energy feed on fasting days, and the alternate-day modified fasting combined exercise group received two combined interventions. After 4 weeks of intervention, the body fat rate of rats was measured by apical blood sampling and abdominal aortic blood sampling, and the serum was preserved and centrifuged, and the wet weights of bilateral gastrocnemius, bilateral perirenal fat and brown fat at the scapula were weighed, and samples were collected for paraffin sectioning and HE staining, and the cell areas were counted; serum Irisin levels were measured by ELISA, and FNDC5 protein expression in gastrocnemius and UCP1 protein expression in adipose tissue were detected by Western blot. RESULTS: After 4 weeks of intervention, compared with the Con group, energy intake, body weight and body fat were decreased significantly in the Exer, ADMF and ADMF-Exer groups (P＜0.05), the wet weight/body weight and adipocyte area of white fat were reduced significantly (P＜0.01), and there was no significant difference in scapular fat wet weight/body weight (P＞0.05). Compared with the Con group, the gastrocnemius wet weight/body weight in the ADMF group was reduced significantly (P＜0.05), while that in the ADMF-Exer group was increased significantly (P＜0.05), the muscle cross-sectional areas in the Exer group and the ADMF-Exer group were increased (P＜0.05), and the content of gastrocnemius FNDC5 protein, serum Irisin level and expression of adipose UCP1 protein in the ADMF-Exer group were increased significantly (P＜0.05). After 4 weeks of intervention, energy intake was reduced significantly in both ADMF and ADMF-Exer groups (P＜0.01) and body weight of ADMF-Exer group was decreased (P＜0.05) compared with the Exer group. Compared with the Exer group, there were no significant differences in body fat content, white fat wet weight/body weight and scapular fat wet weight/body weight between ADMF group and ADMF-Exer group (P＞0.05), and adipocyte area in ADMF-Exer group was reduced significantly (P＜0.05). Compared with the Exer group, the gastrocnemius muscle wet weight/body weight was reduced significantly in the ADMF group (P＜0.05), and the expression of FNDC5 protein, serum Irisin and adipose UCP1 protein in the ADMF-Exer group were increased significantly compared with the Exer group (P＜0.05). CONCLUSION: Alternate-day modified fasting combined with exercise intervention can effectively control body weight and reduce body fat in rats, and the mechanism may be through the FNDC5/Irisin-UCP1 pathway to induce browning of white adipose tissue and increase thermogenesis of brown fat.

Energy Transfer Assisted Fast X-ray Detection in Direct/Indirect Hybrid Perovskite Wafer.

Metal halide perovskite scintillators encounter unprecedented opportunities in indirect ionizing radiation detection due to their high quantum yields. However, the long scintillation lifetime of microseconds upon irradiation, known as the afterglow phenomenon, obviously limits their fast development. Here, a new type of hybrid X-ray detector wafer combining direct methylamine lead iodide (MAPbI3 ) semiconductor and indirect zero-dimensional cesium copper iodide (Cs3 Cu2 I5 ) scintillator through low-cost fast tableting processes is reported. Due to the fast energy transfer from Cs3 Cu2 I5 to MAPbI3 , the device response time to X-rays is dramatically reduced by nearly 30 times to 36.6 ns, which enables fast X-ray detection capability by a large area detector arrays within 1 s. Moreover, Cs3 Cu2 I5 exists at the grain boundaries of MAPbI3 crystals, and blocks the paths of mobile ions of perovskite, leading to the lowest detectable dose rate of hybrid X-ray detector is thus reduced by 1.5 times compared with control MAPbI3 direct-type semiconductor, and 10 times compared with the Cs3 Cu2 I5 indirect-type scintillator. The direct/indirect hybrid wafer also exhibits improved operation stability at ambient conditions without any encapsulation. This new kind of hybrid X-ray detectors provides strong competitiveness by combining the advantages of both direct perovskite semiconductors and indirect perovskite scintillators for next-generation products.