DDT-Net: Dose-Agnostic Dual-Task Transfer Network for Simultaneous Low-Dose CT Denoising and Simulation.

Deep learning (DL) algorithms have achieved unprecedented success in low-dose CT (LDCT) imaging and are expected to be a new generation of CT reconstruction technology. However, most DL-based denoising models often lack the ability to generalize to unseen dose data. And they only learn the posterior distribution of latent normal-dose CT (NDCT) images conditioned on observed LDCT images in the traditional maximum a posteriori (MAP) framework, while ignoring the noise generation process of LDCT images. Moreover, most simulation tools for LDCT typically operate on proprietary projection data, which is generally not accessible without an established collaboration with CT manufacturers. To alleviate these issues, in this work, we propose a dose-agnostic dual-task transfer network, termed DDT-Net, for simultaneous LDCT denoising and simulation. Concretely, the dual-task learning module is constructed to integrate the LDCT denoising and simulation tasks into a unified optimization framework by learning the joint distribution of LDCT and NDCT data. We approximate the joint distribution of continuous dose level data by training DDT-Net with discrete dose data, which can be generalized to denoising and simulation of unseen dose data. In particular, the mixed-dose training strategy adopted by DDT-Net can promote the denoising performance of lower-dose data. The paired dataset simulated by DDT-Net can be used for data augmentation to further restore the tissue texture of LDCT images. Experimental results on synthetic data and clinical data show that the proposed DDT-Net outperforms competing methods in terms of denoising and generalization performance at unseen dose data, and it also provides a simulation tool that can quickly simulate realistic LDCT images at arbitrary dose levels.

The neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and neutrophil-to-high-density-lipoprotein ratio are correlated with the severity of Parkinson's disease.

Background: Inflammation plays a pivotal role in the pathogenesis of Parkinson's disease (PD). However, the correlation between peripheral inflammatory markers and the severity of PD remains unclear. Methods: The following items in plasma were collected for assessment among patients with PD (n = 303) and healthy controls (HCs; n = 303) were assessed for the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR) and neutrophil-to-high-density-lipoprotein ratio (NHR) in plasma, and neuropsychological assessments were performed for all patients with PD. Spearman rank or Pearson correlation was used to evaluate the correlation between the NLR, the LMR and the NHR and the severity of PD. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of the NLR, LMR and NHR for PD. Results: The plasma NLR and NHR were substantially higher in patients with PD than in HCs, while the plasma LMR was substantially lower. The plasma NLR was positively correlated with Hoehn and Yahr staging scale (H&Y), Unified Parkinson's Disease Rating Scale (UPDRS), UPDRS-I, UPDRS-II, and UPDRS-III scores. Conversely, it exhibited a negative relationship with Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Furthermore, the plasma NHR was positively correlated with H&Y, UPDRS, UPDRS-I, UPDRS-II and UPDRS-III scores. Moreover, negative associations were established between the plasma LMR and H&Y, UPDRS, UPDRS-I, UPDRS-II, and UPDRS-III scores. Finally, based on the ROC curve analysis, the NLR, LMR and NHR exhibited respectable PD discriminating power. Conclusion: Our research indicates that a higher NLR and NHR and a lower LMR may be relevant for assessing the severity of PD and appear to be promising disease-state biomarker candidates.

ALKBH5 protects against stroke by reducing endoplasmic reticulum stress-dependent inflammation injury via the STAT5/PERK/EIF2α/CHOP signaling pathway in an m6A-YTHDF1-dependent manner.

BACKGROUND: Endoplasmic reticulum (ER) stress causes neuroinflammation and neuronal apoptosis during ischemic stroke progression. This study has investigated the role of ALKBH5 in ER stress during ischemic stroke progression. METHODS: In vivo and in vitro models of ischemic stroke were established by middle cerebral artery occlusion (MCAO) and OGD/R treatment, respectively. Cerebral infarct size was detected using triphenyltetrazolium chloride staining (TTC), and pathological changes were examined using histological staining. The levels of inflammatory factors were analyzed using Enzyme-linked immunosorbent assay. Cell counting kit-8 assay and flow cytometry were used to measure cell viability and apoptosis, respectively. The global m6A level was detected using the commercial kit, and STAT5 mRNA m6A level was determined using methylated RNA binding protein immunoprecipitation (Me-RIP). ALKBH5, YTHDF1, and STAT5 interactions were analyzed using RIP and RNA pull-down assays. RESULTS: ALKBH5 was upregulated in MCAO animals and OGD/R cell models. ALKBH5 knockdown exacerbated ER stress, neuroinflammation, and neuronal apoptosis in brain tissues and neuronal cells. ALKBH5 inhibited STAT5 mRNA stability and expression in an m6A-YTHDF1-dependent manner. STAT5 promoted ER stress by activating the PERK/eIF2/CHOP signaling pathway. Furthermore, STAT5 knockdown reversed the effects of ALKBH5 knockdown on OGD/R-induced ER stress and neuroinflammation in HT22 cells. CONCLUSION: ALKBH5 knockdown exacerbated ischemic stroke by increasing ER stress-dependent neuroinflammation and neuronal apoptosis via the STAT5/PERK/EIF2α/CHOP signaling pathway in an m6A-YTHDF1-dependent manner.

Efficacy and safety of platelet-rich plasma injections for the treatment of osteoarthritis: a systematic review and meta-analysis of randomized controlled trials.

Background: In recent years, platelet-rich plasma (PRP) injections for osteoarthritis (OA) have been widely promoted in clinical practice, but their effectiveness is controversial. Therefore, we conducted a meta-analysis of relevant randomized controlled trials (RCTs) to determine the efficacy and safety of PRP injections for the treatment of OA. Methods: We searched databases including Embase, Web of Science, Medline, PubMed, and the Cochrane Library for relevant studies. Two researchers (YQX and CG) performed literature screening, baseline data extraction, literature quality assessment, and heterogeneity analysis of RCTs from the retrieved studies. Based on the magnitude of heterogeneity I2, random-effects or fixed-effects models were selected for the meta-analysis. Results: We included 24 RCTs comprising 1344 patients with OA who met the inclusion criteria, with the main types of morbidity being knee osteoarthritis (KOA), hip osteoarthritis (HOA), ankle osteoarthritis (AOA), and temporomandibular joint osteoarthritis (TMJOA). Our results indicate that PRP injections were effective in improving Visual Analog Scale (VAS) pain scores in patients with KOA, HOA, and AOA compared to controls (AOA, MD = -1.15, CI = 95% [-1.74, -0.56], I2 = 40%, P < 0.05; KOA, MD = -1.03, CI = 95% [-1.16, -0.9], I2 = 87%, P < 0.05; TMJOA, MD = -1.35, CI = 95% [-1.74, -0.97], I2 = 92%, P < 0.05) but showed no significant efficacy in patients with HOA (MD = -0.27, CI = 95% [-0.8, 0.26], I2 = 56%, P>0.05). Compared to controls, PRP injections were effective in improving Knee Injury and Osteoarthritis Outcome Score (KOOS), including the patient's pain symptoms, activities of daily living (ADL), and adhesion symptomatology, but not for that of sports function (KOOS-pain, MD = 2.77, CI = 95% [0, 5.53], I2 = 0%, P < 0.05; KOOS-symptoms, MD = 3.73, CI = 95% [0.76, 6.71], I2 = 0%, P < 0.05; KOOS-ADL, MD = 3.61, CI = 95% [0.79, 6.43], I2 = 0%, P < 0.05; KOOS-QOL, MD = 4.66, CI = 95% [0.98, 8.35], I2 = 29%, P < 0.05, KOOS-sport, MD = 0.48, CI = 95% [-3.02, 3.98], I2 = 0%, P > 0.05). PRP injections were effective in improving Western Ontario and McMaster Universities Arthritis Index (WOMAC) scores, including pain, stiffness, and functional joint motion, in patients with OA compared with the control group (WOMAC-pain, MD = -1.08, CI = 95% [-1.62, -0.53], I2 = 87%, P < 0.05; WOMAC-stiffness, MD = -1.17, CI = 88% [-1.72, -0.63], I2 = 87%, P < 0.05; WOMAC-function, MD = -1.12, CI = 95% [-1.65, -0.58], I2 = 87%, P < 0.05). In addition, subgroup analysis showed that leukocyte-poor (LP) PRP injections were more effective than leukocyte-rich (LR) PRP injections in improving pain symptoms in patients with OA (VAS, LR-PRP, MD = -0.81, CI = 95% [-1.65, -0.03], I2 = 83%, P = 0.06 > 0.05; LP-PRP, MD = -1.62, CI = 95% [-2.36, -0.88], I2 = 92%, P < 0.05). A subgroup analysis based on injection sites showed that no statistical difference in efficacy between intra-articular (IA) combined with intra-osseous (IO) simultaneous PRP injections. IA PRP injections only improved VAS pain scores in patients with OA (IA+IO PRP injections, MD = -0.74, CI =95% [-1.29, -0.18], I2 = 61%, P < 0.05; IA PRP injections, MD = -1.43, CI = 95% [-2.18, -0.68], I2 = 87%, P < 0.05, test for subgroup differences, P > 0.05, I2 = 52.7%). Conclusion: PRP injection therapy can safely and effectively improve functional activity in patients with OA and produce positive analgesic effects in patients with KOA, TMJOA, and AOA. However, PRP injection therapy did not significantly reduce pain symptoms in patients with HOA. In addition, the analgesic effect of LP-PRP was greater than that of LR-PRP. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022362066.

Serum alkaline phosphatase was independently associated with depression in patients with cerebrovascular disease.

Background and purpose: Blood markers have important value in the diagnosis of depressive disorders. Serum alkaline phosphatase (ALP) not only predicts stroke recurrence and poor functional prognosis in cerebrovascular disease (CVD) patients but also increases significantly in middle-aged women with depression. Thus, it has not been reported whether serum ALP is associated with the development of depression and/or vascular depression (VDe) in CVD patients. Methods: This was a cross-sectional study of 353 CVD patients (stroke patients, n = 291; cerebral small vessel disease (CSVD) patients, n = 62). Baseline demographic information, fasting blood markers (such as blood counts, liver function, kidney function and lipids), and brain CT/MRI scans were collected. CVD patients were divided into non-depression, suspected vascular depression (SVD), and positive vascular depression (PVD) groups according to their Hamilton Rating Scale for Depression (HAMD) scores. Univariate analysis of baseline data, blood markers, and the prevalence of lesions (> 1.5 cm) was performed. Subsequently, the diagnostic performance of the univariate and combined variables for SVD and PVD was analyzed using binary logistic regression. The diagnostic value of the multivariate model for VDe was analyzed by ordinal logistic regression. Results: (1) Serum ALP (p = 0.003) and hypersensitive C-reactive protein (hs-CRP, p = 0.001) concentrations increased as HAMD scores increased, and the prevalence of brain atrophy (p = 0.016) and lesions in the basal ganglia (p = 0.001) and parietal (p = 0.001), temporal (p = 0.002), and frontal lobes (p = 0.003) also increased, whereas the concentrations of hemoglobin (Hb, p = 0.003), cholinesterase (ChE, p = 0.001), and high-density lipoprotein cholesterol (HDL-C, p = 0.005) declined. Among these variables, hs-CRP (r = 0.218, p < 0.001) had a weak positively association with HAMD scores, and ChE (r = -0.226, p < 0.001) had a weak negative association. (2) The combination of Hb, hs-CRP, ChE, ALP, and HDL-C improved diagnostic performance for VDe [AUC = 0.775, 95% CI (0.706, 0.844), p < 0.001]. (3) Hb (OR = 0.986, p = 0.049), ChE (OR = 0.999, p = 0.020), ALP (OR = 1.017, p = 0.003), and basal ganglia lesions (OR = 2.197, p < 0.001) were important factors impacting VDe development. After adjusting for Hb, hs-CRP, ChE, HDL-C, lesions in the above mentioned four locations, sex, age and the prevalence of CSVD and brain atrophy, ALP [OR = 1.016, 95% CI (1.005, 1.027), p = 0.004] was independently associated with VDe. Conclusion: Hb, hs-CRP, ChE, ALP, and HDL-C concentrations are potential blood markers of depression in CVD patients and, when combined, may improve diagnostic performance for VDe. Serum ALP was independently associated with VDe in patients with CVD.

Effects of a vegetarian diet combined with aerobic exercise on glycemic control, insulin resistance, and body composition: a systematic review and meta-analysis.

BACKGROUND: Vegetarian diets and aerobic exercise are increasingly accepted as a common way to improve lifestyle. Several studies have shown that vegetarian diets combined with aerobic exercise interventions have a significant effect on preventing and reducing the risk of metabolic diseases. METHODS: A search of the PubMed, EBSCO, Embase, CENTRAL, and Web of Science databases was conducted for comparative studies of pre- and post-vegetarian diet adoption combined with aerobic exercise interventions on glycemic control and body composition. Qualitative reviews and meta-analyses of fixed and random effects were conducted to pool available data. The results were validated by sensitivity analysis. RESULTS: A total of 27 studies were selected for meta-analysis. Combining the studies included in the meta-analysis showed a mean difference for homeostasis model assessment of insulin resistance of - 0.75 (- 1.08 to - 0.42), fasting plasma glucose of - 0.27(- 0.30 to - 0.23), waist circumference of - 1.10 (- 5.06 to 2.86) and body mass index of - 0.70 (- 1.38 to - 0.01). CONCLUSION: In summary, our findings suggest that participants who adopted a vegetarian diet combined with aerobic exercise intervention had significantly lower fasting plasma glucose and insulin levels and improved body composition compared to preintervention participants. LEVEL OF EVIDENCE: Level I, systematic review and meta-analysis.

ß2AR against myocarditis-lipid deposition depends on estrogenic environment in stress.

Cardiac lipid accumulation and inflammation have been linked to stress. There is mounting evidence that estrogen reduces lipid deposition and has anti-inflammatory properties; however, the exact mechanism is unknown. Recent studies showed that NLRP3 inflammasome is a key trigger of cardiac inflammation, and it is also involved in the progression of metabolic diseases. This study investigated the crucial role of the NLRP3 inflammasome in lipid accumulation during stress and the regulatory mechanism of estrogen in this process. Stress models were established by isoproterenol treatments in mice and H9c2 cells. With 5 mM isoproterenol, NLRP3 inflammasome activation was observed earlier at 0.5 h than that of lipid accumulation at 1 h in H9c2 cells. At 1 h after stress, the isoproterenol concentration required for NLRP3 inflammasome activation was lower compared to the concentration required for lipid deposition in mice myocardia and H9c2 cells; the former required 210 mg/kg or 10 µM for activation while the latter required 280 mg/kg or 5 mM. Knocking out or inhibiting NLRP3 inflammasome reduced myocardial lipid accumulation caused by stress in the mice myocardia and H9c2 cells. Estrogen downregulated NLRP3 inflammasome and reduced lipid accumulation in cardiomyocytes during stress. Finally, the anti-inflammatory and lipid-lowering effect of estrogen disappeared in ß2ARKO mice and H9c2 cells pre-treated with ICI118,551. In conclusion, the upregulation of NLRP3 inflammasome induced by stress led to myocardial lipid accumulation, and ß2AR downregulated NLRP3 inflammasome thereby reducing lipid accumulation which was dependent on the estrogenic environment.

Learning CT projection denoising from adjacent views.

BACKGROUND: Many learning-based low-dose (LD) computed tomography (CT) imaging methods require large paired full- and low-dose datasets for training, which are usually unavailable in clinic. Whereas models trained on simulated data often face the generalization problem on real clinical data. PURPOSE: To develop an unsupervised learning technique to acquire clean CT projection from its adjacent LD projections. METHODS: Given a sequential LD projection set, the method extracts out the middle projection as the target and treats the rest ones as the input. The model is trained with the mean absolute error with proposed inter-view gradient constraint term, which helps to suppress outliers and preserve edges in the denoised projection. The simulated low-dose CT grand challenge dataset and a real physical torso phantom dataset were employed for experiment. The peak signal to noise ratio (PSNR) and structural similarity index measure (SSIM) were calculated for quantitative evaluation. RESULTS: In experiments with both the simulated and real datasets, visual comparisons reveal that the proposed method obtained images superior to unsupervised and supervised methods working in both image and projection domain. For numerical comparison, our method obtains larger SSIMs than other unsupervised methods at quarter and eighth dose levels. As for PSNR, our method obtains larger value at eighth dose whereas smaller value at quarter dose. The supervised models obtain better numerical results than all unsupervised models on simulated datasets. CONCLUSION: The proposed method can reduce the noise in CT projections effectively, making it an attractive tool for practical LDCT pre-processing.

Effects of central-peripheral FMS on urinary retention after spinal cord injury: a pilot randomized controlled trial protocol.

Background: Urinary retention is a common complication of spinal cord injury (SCI), which can seriously affect the quality of life of patients. Function magnetic stimulation (FMS) has been widely used in the recovery of neurological function in various diseases, but its application in urinary retention after SCI remains unclear. Therefore, we would like to conduct a pilot randomized controlled trial (RCT) to observe the feasible effect of FMS on urinary retention after SCI, to explore its mechanism of action. Method/design: This is a single-center pilot RCT, which 60 patients with urinary retention after SCI will be selected, numbered in chronological order of hospitalization, and randomly divided into 4 groups using the random number table method, Groups A (control group), Group B, Group C, and Group D; Each group will receive the same conventional rehabilitation treatment. The whole intervention period 2 weeks and will be evaluated before and after treatment to collect data on residual bladder volume, functional near-infrared spectroscopy (fNIRS), changes in voiding condition, changes in surface electromyography (SEMG) values of pelvic floor muscle and quality of life scores (QoL). Study hypothesis: We hypothesized that FMS for the treatment of urinary retention after SCI would have a significant clinical feasible effect;and that peripheral combined with central FMS would be more effective than single-site FMS for the treatment of urinary retention after SCI. Objective: (1) To illustrate the clinical effectiveness of FMS in the treatment of urinary retention after SCI and to provide a new treatment modality for the patients; (2) Comparison of the differences in the efficacy of central and peripheral single FMS and combined central and peripheral FMS in the treatment of urinary retention after SCI; (3) To explore the central control mechanisms of bladder function recovery after SCI in conjunction with changes in fNIRS. Trial registration: This study has been ethically approved by the Scientific and Ethics Committee of the First Affiliated Hospital of Gannan Medical university with approval number (LLSC-2022112401). It has been registered with the China Clinical Trials Registry with the registration number: ChiCTR2200067143.

Bone marrow stromal cells attenuate oxygen and glucose deprivation followed by re­oxygenation­induced brain microvascular endothelial cell injury.

Ischemic stroke is a severe threat to the health of older individuals. Bone marrow mesenchymal stem cells (BMSCs) have been implicated in ischemic stroke. Urokinase­type plasminogen activator (uPA) and its specific receptor (uPAR) are associated with the pathological process of ischemic stroke. However, the relationship between BMSCs and uPA/uPAR in ischemic stroke remains unclear. For simulating the occurrence of an ischemic stroke in vitro, human cerebral microvascular endothelial cells (HBMECs) were subjected to oxygen and glucose deprivation followed by re­oxygenation (OGD/R) and were then cocultured with BMSCs. 3,4,5­dimethylthiazol­2,5­diphenyltetrazolium bromide and bromodeoxyuridine staining were used for measuring cell viability and proliferation. Flow cytometry was performed for assessing cell apoptosis. Endothelial cell tube formation was determined using angiogenesis assays. Alterations in the protein and gene expression in HBMECs were evaluated using western blot analysis and quantitative reverse transcription­polymerase chain reaction, respectively. OGD/R considerably inhibited the viability and proliferation of HBMECs by inducing apoptosis, which was reversed by BMSCs. Consistently, OGD/R­induced inhibition of angiogenesis was attenuated by BMSCs. In addition, BMSCs could protect HBMECs against OGD/R­induced injury by positively regulating the uPA/uPAR/stromal cell­derived factor­1α (SDF­1α)/C­X­C chemokine receptor type 4 (CXCR4) pathway, and uPA/uPAR could mediate the SDF­1α/CXCR4 pathway in OGD/R­treated HBMECs. Therefore, this study provides novel strategies to investigate the specific role of BMSCs in ameliorating OGD/R­induced vascular endothelial cell injury.

Erythrocytes Are an Independent Protective Factor for Vascular Cognitive Impairment in Patients With Severe White Matter Hyperintensities.

Background and Purpose: Hemoglobin is one of the main proteins in erythrocytes. There are significant correlations between low hemoglobin and white matter hyperintensities (WMH) and cognitive impairment. This study explored whether erythrocytopenia has predictive value for vascular cognitive impairment (VCI) in patients with WMH. Method: We conducted a cross-sectional study of 302 patients, including 62 with cerebral small vessel disease and 240 with stroke. Basic demographic data and fasting blood were collected. First, all patients were divided into normal cognition (NC), mild VCI (mVCI), and severe VCI (sVCI) groups (subgroups later) based on cognitive behavior scores. Second, all patients were divided into mild WMH (mWMH) and severe WMH (sWMH) groups based on Fazekas scores. The differences in blood markers between different groups or subgroups with different cognitive levels were analyzed by univariate analysis. Then, binary logistic regression was used to analyze the diagnostic value of erythrocyte counts for VCI in the sWMH group, and ordinal logistic regression was used to analyze the predictive value of multiple variables for different cognitive levels. Results: Univariate analysis showed that erythrocytes, hemoglobin, high-sensitivity C-reactive protein, retinol binding protein and prealbumin were potential blood markers for different cognitive levels in sWMH patients. Among them, erythrocytopenia has good predictive value for the diagnosis of mVCI (AUC = 0.685, P = 0.008) or sVCI (AUC = 0.699, P = 0.003) in patients with sWMH. Multivariate joint analysis showed that erythrocytes were an independent protective factor reducing the occurrence of VCI in patients with sWMH (OR = 0.633, P = 0.045). Even after adjusting for age, there was still a significant difference (P = 0.047). Conclusion: Erythrocytes are an independent protective factor for VCI in patients with sWMH. Promoting hematopoietic function may have potential value for prevention of cognitive decline in patients with cerebrovascular disease.

Alleviative effects of foraging exercise on depressive-like behaviors in chronic mild stress-induced ischemic rat model.

BACKGROUND: Poststroke depression (PSD) is a common complication that seriously affects the functional recovery and prognosis of an individual. As some patients with PSD fail to respond to drug therapy, it is urgent to find a viable alternative treatment. METHODS: An active exercise program known as foraging exercise (FE), using food as bait, was designed. First, focal ischemia and chronic unpredictable mild stress (CUMS) were used to establish a PSD model in rats. FE was then performed for 4 weeks. Body weight and behavioral assessments were conducted at the end of the 4th and 8th weeks. RESULTS: After 8 weeks, the results revealed that, compared with the PSD group, the behavioral scores of the rats in the PSD/FE group were significantly improved, the expression of Iba-1 in the affected frontal lobe and striatum was decreased, and serum levels of IL-6 and the IL-6/IL-10 ratio were downregulated. However, the ratio of residual brain volume in rats that had experienced CUMS was significantly less than that in the stroke group. CONCLUSION: FE can alleviate the behavioral scores of PSD rats, and its mechanism may be related to a modulation of the immune-inflammation response of microglia. Furthermore, chronic, persistent stress may increase the volume of cerebral infarction after stroke.

[Identification of mouse lines with HA-tagged prostaglandin receptors].

Prostaglandins are a class of poly-unsaturated fatty acids-derived bioactive lipids with important physiological function by binding to specific receptors. Prostaglandin receptors lack specific antibodies, which greatly impedes the research on our understanding of the signaling of prostaglandins. The aim of this study was to identify nine mouse lines with amino terminal (-NH2, -N) HA-tagged prostaglandin receptors by using the combination of artificial sperm and CRISPR-Cas9 technology. The guide RNA expression plasmid and labeled targeting vector plasmids were transferred into "artificial sperm cells". The "artificial sperm cells" containing labeled proteins were selected and injected into mouse oocytes, and implanted into pseudopregnant mice to obtain labeled mice. The genomic DNA of the prostaglandin receptor tagged mice was extracted, and the genotypes of mice were detected by PCR method. We also isolated mouse peritoneal macrophages to verify the protein expression of HA-labeled prostaglandin receptor by Western blot. Specific DNA bands were amplified in prostaglandin receptor labeled mice, and specific HA protein bands were detected in macrophage proteins, which was not detected in wild type mice. In summary, we successfully constructed 9 mouse lines with HA-tagged prostaglandin receptors, providing a powerful tool for further study of the pathophysiological functions of prostaglandin signaling both in vivo and in vitro.

Tumor Immune Microenvironment and Its Related miRNAs in Tumor Progression.

MiRNA is a type of small non-coding RNA, by regulating downstream gene expression that affects the progression of multiple diseases, especially cancer. MiRNA can participate in the biological processes of tumor, including proliferation, invasion and escape, and exhibit tumor enhancement or inhibition. The tumor immune microenvironment contains numerous immune cells. These cells include lymphocytes with tumor suppressor effects such as CD8+ T cells and natural killer cells, as well as some tumor-promoting cells with immunosuppressive functions, such as regulatory T cells and myeloid-derived suppressor cells. MiRNA can affect the tumor immune microenvironment by regulating the function of immune cells, which in turn modulates the progression of tumor cells. Investigating the role of miRNA in regulating the tumor immune microenvironment will help elucidate the specific mechanisms of interaction between immune cells and tumor cells, and may facilitate the use of miRNA as a predictor of immune disorders in tumor progression. This review summarizes the multifarious roles of miRNA in tumor progression through regulation of the tumor immune microenvironment, and provides guidance for the development of miRNA drugs to treat tumors and for the use of miRNA as an auxiliary means in tumor immunotherapy.

Learning to Reconstruct CT Images From the VVBP-Tensor.

Deep learning (DL) is bringing a big movement in the field of computed tomography (CT) imaging. In general, DL for CT imaging can be applied by processing the projection or the image data with trained deep neural networks (DNNs), unrolling the iterative reconstruction as a DNN for training, or training a well-designed DNN to directly reconstruct the image from the projection. In all of these applications, the whole or part of the DNNs work in the projection or image domain alone or in combination. In this study, instead of focusing on the projection or image, we train DNNs to reconstruct CT images from the view-by-view backprojection tensor (VVBP-Tensor). The VVBP-Tensor is the 3D data before summation in backprojection. It contains structures of the scanned object after applying a sorting operation. Unlike the image or projection that provides compressed information due to the integration/summation step in forward or back projection, the VVBP-Tensor provides lossless information for processing, allowing the trained DNNs to preserve fine details of the image. We develop a learning strategy by inputting slices of the VVBP-Tensor as feature maps and outputting the image. Such strategy can be viewed as a generalization of the summation step in conventional filtered backprojection reconstruction. Numerous experiments reveal that the proposed VVBP-Tensor domain learning framework obtains significant improvement over the image, projection, and hybrid projection-image domain learning frameworks. We hope the VVBP-Tensor domain learning framework could inspire algorithm development for DL-based CT imaging.

Downsampled Imaging Geometric Modeling for Accurate CT Reconstruction via Deep Learning.

X-ray computed tomography (CT) is widely used clinically to diagnose a variety of diseases by reconstructing the tomographic images of a living subject using penetrating X-rays. For accurate CT image reconstruction, a precise imaging geometric model for the radiation attenuation process is usually required to solve the inversion problem of CT scanning, which encodes the subject into a set of intermediate representations in different angular positions. Here, we show that accurate CT image reconstruction can be subsequently achieved by downsampled imaging geometric modeling via deep-learning techniques. Specifically, we first propose a downsampled imaging geometric modeling approach for the data acquisition process and then incorporate it into a hierarchical neural network, which simultaneously combines both geometric modeling knowledge of the CT imaging system and prior knowledge gained from a data-driven training process for accurate CT image reconstruction. The proposed neural network is denoted as DSigNet, i.e., downsampled-imaging-geometry-based network for CT image reconstruction. We demonstrate the feasibility of the proposed DSigNet for accurate CT image reconstruction with clinical patient data. In addition to improving the CT image quality, the proposed DSigNet might help reduce the computational complexity and accelerate the reconstruction speed for modern CT imaging systems.

Quantifying Axial Spine Images Using Object-Specific Bi-Path Network.

Automatic estimation of indices from medical images is the main goal of computer-aided quantification (CADq), which speeds up diagnosis and lightens the workload of radiologists. Deep learning technique is a good choice for implementing CADq. Usually, to acquire high-accuracy quantification, specific network architecture needs to be designed for a given CADq task. In this study, considering that the target organs are the intervertebral disc and the dural sac, we propose an object-specific bi-path network (OSBP-Net) for axial spine image quantification. Each path of the OSBP-Net comprises a shallow feature extraction layer (SFE) and a deep feature extraction sub-network (DFE). The SFEs use different convolution strides because the two target organs have different anatomical sizes. The DFEs use average pooling for downsampling based on the observation that the target organs have lower intensity than the background. In addition, an inter-path dissimilarity constraint is proposed and applied to the output of the SFEs, taking into account that the activated regions in the feature maps of two paths should be different theoretically. An inter-index correlation regularization is introduced and applied to the output of the DFEs based on the observation that the diameter and area of the same object express an approximately linear relation. The prediction results of OSBP-Net are compared to several state-of-the-art machine learning-based CADq methods. The comparison reveals that the proposed methods precede other competing methods extensively, indicating its great potential for spine CADq.

X-ray microtomosynthesis of unstained pathology tissue samples.

In pathology protocols, a tissue block, such as one containing a mouse brain or a biopsy sample from a patient, can produce several hundred thin sections. Substantial time may be required to analyse all sections. In cases of uncertainty regarding which sections to focus on, noninvasive scout imaging of intact blocks can help in guiding the pathology procedure. The scouting step is ideally done in a time window of minutes without special sample preparation that may interfere with the pathology procedures. The challenge is to obtain some visibility of unstained tissue structures at sub-10 µm resolution. We explored a novel x-ray tomosynthesis method as a way to maximise contrast-to-noise ratio, a determinant of tissue visibility. It provided a z-stack of thousands of images at 7.3 µm resolution (10% contrast, half-period of 68.5 line pairs/mm), in scans of 5-15 minutes. When compared with micro-CT scans, the straight-line tomosynthesis scan did not need to rotate the sample, which allowed flat samples, such as paraffin blocks, to be kept as close as possible to the x-ray source. Thus, given the same hardware, scan time and resolution, this mode maximised the photon flux density through the sample, which helped in maximising the contrast-to-noise ratio. The tradeoff of tomosynthesis is incomplete 3D information. The microtomosynthesis scanner has scanned 110 unstained human and animal tissue samples as part of their respective pathology protocols. In all cases, the z-stack of images showed tissue structures that guided sectioning or provided correlative structural information. We describe six examples that presented different levels of visibility of soft tissue structures. Additionally, in a set of coronary artery samples from an HIV patient donor, microtomosynthesis made a new discovery of isolated focal calcification in the internal elastic lamina of coronary wall, which was the onset of medial calcific sclerosis in the arteries.

A microscopy version of the imaging method for 3D luggage screening has been adapted to image unstained pathology samples. Pathology tests of tissue samples are used for clinical diagnosis and for biomedical research. The tissue samples are often embedded in paraffin blocks and sectioned into many thin slices, which are then stained with the appropriate agents for light microscopy. Since each tissue block can produce several hundred thin sections, much time and labour is required to analyse all sections. Noninvasive scout imaging of intact blocks can help in guiding the pathology procedure. The scouting step is ideally done in a time window of minutes without special sample preparation that may interfere with the pathology procedures. The challenge is to obtain some visibility of unstained tissue structures at sufficient resolution. X-ray imaging is a promising tool to meet the challenge since x-rays can penetrate thick samples that are opaque to visible light. With x-ray imaging, a determinant of tissue visibility is the flux density of photons that illuminate the sample. We explored a novel x-ray tomosynthesis method as a way to maximise this factor. It provided a stack of thousands of cross-sectional images at 7.3 µm resolution (half-period of 68.5 line pairs/mm) in scans of 5-15 minutes. When compared with micro-CT scans (a widely used laboratory technology), this method did not need to rotate the sample, which allowed flat samples such as paraffin blocks to be kept as close as possible to the x-ray source. Thus, given the same hardware, scan time and resolution, this method maximised the photon flux density through the sample, which helped in improving the visibility of unstained tissue under x-ray. The tradeoff of the method is incomplete 3D information. Over 100 unstained human and animal tissue samples have been scanned with this method as part of their respective pathology protocols. In all cases, the stack of cross-sectional images showed tissue structures that guided pathology analysis or provided correlative structural information. We describe six examples that presented different levels of tissue visibility. Additionally, in a set of coronary artery samples from an HIV patient donor, microtomosynthesis made a new discovery of isolated focal calcification in the internal elastic lamina of coronary wall, which was the onset of medial calcific sclerosis in the arteries.

Vitrimer-Like Shape Memory Polymers: Characterization and Applications in Reshaping and Manufacturing.

The shape memory effect (SME) refers to the ability of a material to recover its original shape, but only in the presence of a right stimulus. Most polymers, either thermo-plastic or thermoset, can have the SME, although the actual shape memory performance varies according to the exact material and how the material is processed. Vitrimer, which is between thermoset and thermo-plastic, is featured by the reversible cross-linking. Vitrimer-like shape memory polymers (SMPs) combine the vitrimer-like behavior (associated with dissociative covalent adaptable networks) and SME, and can be utilized to achieve many novel functions that are difficult to be realized by conventional polymers. In the first part of this paper, a commercial polymer is used to demonstrate how to characterize the vitrimer-like behavior based on the heating-responsive SME. In the second part, a series of cases are presented to reveal the potential applications of vitrimer-like SMPs and their composites. It is concluded that the vitrimer-like feature not only enables many new ways in reshaping polymers, but also can bring forward new approaches in manufacturing, such as, rapid 3D printing in solid state on space/air/sea missions.

Thermo-Responsive Shape Memory Effect and Conversion of Porous Structure in a Polyvinyl Chloride Foam.

In this paper, a thermo-responsive shape memory effect in a polyvinyl chloride thermoset foam is characterized. Excellent shape recovery performance is observed in foam samples programmed both at room temperature and above their transition temperature. The conversion of porous structures in the foam from closed-cell to open-cell after a shape memory effect cycle is revealed via a series of specially designed oil-dripping experiments and optical images of the micro pores. Programming the strain higher than 20% results in an apparent increase in open-cell level, whereas programming temperatures have almost no influence.