Radiomics-based distinction of small (≤2 cm) hepatocellular carcinoma and precancerous lesions based on unenhanced MRI

AIM

To assess the feasibility of a radiomics model based on unenhanced magnetic resonance imaging (MRI) to differentiate small hepatocellular carcinoma (S-HCC) (≤2 cm) and pre-hepatocellular carcinoma (Pre-HCC).

MATERIALS AND METHODS

One hundred and fourteen histopathologically confirmed 114 hepatic nodules were analysed retrospectively. All patients had undergone MRI before surgery using a 3 T MRI system. Each nodule was segmented on unenhanced MRI sequences (T1-weighted imaging [T1] and T2WI with fat-suppression [FS-T2]). Radiomics features were extracted and the optimal features were selected using the least absolute shrinkage and selection operator (LASSO). The support vector machine (SVM) was used to establish the radiomics model. One abdominal radiologist performed the conventional qualitative analysis for classification of S-HCC and Pre-HCC. The diagnostic performances of the radiomics and radiologist models were evaluated using receiver operating characteristic (ROC) analysis.

RESULT

Radiomics features (n=1,223) were extracted from each sequence and the optimal features were selected from T1, FS-T2, and T1+FS-T2 to construct the radiomics models. The radiomics model based on T1+FS-T2 showed the best performance among the three models, with areas under the ROC curves (AUCs) of 0.95 (95 % confidence interval [CI], 0.875-0.986) and 0.942 (95 % CI, 0.775-0.985), accuracies of 86 % and 88.5 %, sensitivities of 94.12 % and 100 %, and specificities of 85.48 % and 85.19 %, respectively. The radiomics model on FS-T2 showed better performance on a single sequence than that of the T1-based model. The diagnostic performance for the radiomic model was significantly higher than that for the radiologist (AUC = 0.518, p<0.05).

CONCLUSION

This study suggested that a radiomics model based on unenhanced MRI may serve as a feasible and non-invasive tool to classify S-HCC and Pre-HCC.

Medical long-tailed learning for imbalanced data: Bibliometric analysis

BACKGROUND

In the last decade, long-tail learning has become a popular research focus in deep learning applications in medicine. However, no scientometric reports have provided a systematic overview of this scientific field. We utilized bibliometric techniques to identify and analyze the literature on long-tailed learning in deep learning applications in medicine and investigate research trends, core authors, and core journals. We expanded our understanding of the primary components and principal methodologies of long-tail learning research in the medical field.

METHODS

Web of Science was utilized to collect all articles on long-tailed learning in medicine published until December 2023. The suitability of all retrieved titles and abstracts was evaluated. For bibliometric analysis, all numerical data were extracted. CiteSpace was used to create clustered and visual knowledge graphs based on keywords.

RESULTS

A total of 579 articles met the evaluation criteria. Over the last decade, the annual number of publications and citation frequency both showed significant growth, following a power-law and exponential trend, respectively. Noteworthy contributors to this field include Husanbir Singh Pannu, Fadi Thabtah, and Talha Mahboob Alam, while leading journals such as IEEE ACCESS, COMPUTERS IN BIOLOGY AND MEDICINE, IEEE TRANSACTIONS ON MEDICAL IMAGING, and COMPUTERIZED MEDICAL IMAGING AND GRAPHICS have emerged as pivotal platforms for disseminating research in this area. The core of long-tailed learning research within the medical domain is encapsulated in six principal themes: deep learning for imbalanced data, model optimization, neural networks in image analysis, data imbalance in health records, CNN in diagnostics and risk assessment, and genetic information in disease mechanisms.

CONCLUSION

This study summarizes recent advancements in applying long-tail learning to deep learning in medicine through bibliometric analysis and visual knowledge graphs. It explains new trends, sources, core authors, journals, and research hotspots. Although this field has shown great promise in medical deep learning research, our findings will provide pertinent and valuable insights for future research and clinical practice.

[Expression of endosialin in human hypertrophic scars and its regulation on fibroblast phenotype]

Objective: To explore the expression of endosialin, i.e., CD248 in human hypertrophic scars (HSs) and its regulatory effect on the phenotype of hypertrophic scar fibroblasts (HSFs). Methods: The method of experimental research was used. From March to May, 2023, 3 pediatric patients with HS were admitted to the Department of Burns and Cutaneous Surgery of the First Affiliated Hospital of Air Force Medical University, including 2 females and 1 male, aged one year ten months to two years. The HS tissue resected during the surgery and the remaining full-thickness skin graft, i.e., normal skin tissue after full-thickness skin grafting were collected from the aforementioned pediatric patients for subsequent experiments. Using the aforementioned two types of tissue, the histological structures were observed by hematoxylin-eosin staining, collagen distribution was observed by Masson staining, and the expression of CD248 was observed and measured by immunohistochemical staining. The primary HSFs were isolated from HS tissue using explant culture technique, and the 3rd to 5th passages of HSFs were used in subsequent experiments. According to the random number table, HSFs were divided into immunoglobulin G78 (IgG78)-treated group and IgG control group, which were treated with 200 nmol/L human CD248 monoclonal antibody IgG78 and human IgG control antibody for 24 h, respectively. The mRNA expressions of collagen type Ⅰ (Col Ⅰ) and α-smooth muscle actin (α-SMA) in HSFs were measured by real-time fluorescence quantitative reverse transcription polymerase chain reaction, the protein expressions of Col Ⅰ and α-SMA in HSFs were detected by Western blotting, and the intracellular location and protein expressions of Col Ⅰ and α-SMA were detected by immunofluorescence method. The number of samples in each experiment was 3. Data were statistically analyzed with paired sample t test and independent sample t test. Results: Compared with those in normal skin tissue, the epidermis and dermis in HS tissue were significantly thicker, with massive accumulation and disordered arrangement of collagen in the dermis. The expression of CD248 in HS tissue was significantly upregulated compared with that in normal skin tissue (t=5.29, P<0.05). At post treatment hour 24, the mRNA expressions of Col Ⅰ and α-SMA of HSFs in IgG78-treated group were 0.39±0.05 and 0.56±0.09, respectively, which were significantly lower than 1.00±0.07 and 1.00±0.08 in IgG control group, respectively (with t values of 11.87 and 6.49, respectively, P values all <0.05). The protein expressions of Col Ⅰ and α-SMA of HSFs in IgG78-treated group were 0.617±0.011 and 0.67±0.14, respectively, which were significantly lower than 1.259±0.052 and 1.23±0.16 in IgG control group, respectively (with t values of 20.92 and 4.52, respectively, P values all <0.05). At post treatment hour 24, immunofluorescence staining showed that Col Ⅰ and α-SMA mainly located in the cytoplasm of HSFs in the two groups, and the protein expressions of Col Ⅰ and α-SMA of HSFs in IgG78-treated group were obviously downregulated compared with those in IgG control group. Conclusions: The expression of CD248 is significantly upregulated in human HS. Targeted blockade of CD248 can significantly inhibit the collagen synthesis by HSFs and the transdifferentiation of HSFs into myofibroblasts.

MedGAN: An adaptive GAN approach for medical image generation

Generative adversarial networks (GANs) and their variants as an effective method for generating visually appealing images have shown great potential in different medical imaging applications during past decades. However, some issues remain insufficiently investigated: many models still suffer from model collapse, vanishing gradients, and convergence failure. Considering the fact that medical images differ from typical RGB images in terms of complexity and dimensionality, we propose an adaptive generative adversarial network, namely MedGAN, to mitigate these issues. Specifically, we first use Wasserstein loss as a convergence metric to measure the convergence degree of the generator and the discriminator. Then, we adaptively train MedGAN based on this metric. Finally, we generate medical images based on MedGAN and use them to build few-shot medical data learning models for disease classification and lesion localization. On demodicosis, blister, molluscum, and parakeratosis datasets, our experimental results verify the advantages of MedGAN in model convergence, training speed, and visual quality of generated samples. We believe this approach can be generalized to other medical applications and contribute to radiologists' efforts for disease diagnosis. The source code can be downloaded at https://github.com/geyao-c/MedGAN.

Medical Image Super-Resolution Based on Semantic Perception Transfer Learning

Medical images are an important basis for doctors to diagnose diseases, but some medical images have low resolution due to hardware technology and cost constraints. Super-resolution technology can reconstruct low-resolution medical images into high-resolution images and enhance the quality of low-resolution images, thus assisting doctors in diagnosing diseases. However, traditional super-resolution methods mainly learn the mapping relationships among modal pixels from low resolution to high resolution, lacking the learning of high-level semantic features, resulting in a lack of understanding and utilization of semantic information, such as reconstructed objects, object attributes, and spatial relationships between two objects. In this paper, we propose a medical image super-resolution method based on semantic perception transfer learning. First, we propose a novel semantic perception super-resolution method that empowers super-resolution models to perceive high-level semantics by transferring features of the image description generation network in natural language processing. Second, we construct a semantic feature extraction network and an image description generation network and comprehensively utilized image and text modal data to learn transferable, high-level semantic features. Third, we train an end-to-end, semantic perception super-resolution model by fusing dynamic perceptual convolution, a semantic extraction network, and distillation polarization self-attention. Experiments show that semantic perception transfer learning can effectively improve the quality of super-resolution reconstruction.

Efficacy and Safety of Probiotics in Geriatric Patients with Constipation: Systematic Review and Meta-Analysis

BACKGROUND

Probiotics may be an effective alternative to traditional drug therapy for constipation in the elderly.

OBJECTIVE

To assess the efficacy and safety of probiotics in managing constipation among the elderly.

METHODS

Eight databases were queried for randomized controlled trials (RCTs) investigating probiotics' efficacy in addressing constipation among the elderly until January 2023. The meta-analysis was conducted employing R software version 4.2.2. The Cochrane risk of bias tool was utilized to evaluate the risk of bias, and the GRADE approach was employed to assess the credibility of the evidence concerning the efficacy of probiotics in treating constipation in older individuals.

RESULTS

A total of six RCTs involving 444 patients were included. Two studies were rated as low risk of bias. The meta-analysis findings revealed that probiotics, when compared to a placebo, led to an increase in stool frequency (MD = 1.02,95% CI [0.21, 2.07], p<0.05, very low quality), the probiotic group exhibited a notable impact on ameliorating symptoms associated with constipation (OR = 11.28, 95%CI [7.21, 17.64], p < 0.05, very low quality), no significant disparities were observed in terms of efforts to evacuate, manual maneuvers, and the incidence of adverse events (p>0.05).

CONCLUSION

The available evidence indicates a degree of uncertainty, ranging from low-to-very low, suggesting the efficacy of probiotics in augmenting bowel frequency and ameliorating constipation-related symptoms among elderly patients with constipation. Nevertheless, given the quality of the studies included, it is advisable to conduct further well-designed investigations with substantial sample sizes to substantiate the findings of this study.

Programmed Death of Microglia in Alzheimer's Disease: Autophagy, Ferroptosis, and Pyroptosis

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, amyloid-β (Aβ) plaques and the formation of neurofibrillary tangles (NFTs) composed of hyperphosphorylated tau. Increasing evidence has demonstrated that the damage of cell plays an important role in AD. Cell death is a critical phenomenon for physiological functions, which promotes AD pathogenesis. Programmed cell death, including necroptosis, pyroptosis, autophagy, and ferroptosis, have been discovered that have unique biological functions and pathophysiological characteristics. Here, we review the available evidence detailing the mechanisms of programmed microglial death, including pyroptosis, autophagy, and ferroptosis. We also highlight the role of programmed death of microglia during the process of AD and focus on the connection between the disease and cell death.

Background selection schema on deep learning-based classification of dermatological disease

Skin diseases are one of the most common ailments affecting humans. Artificial intelligence based on deep learning can significantly improve the efficiency of identifying skin disorders and alleviate the scarcity of medical resources. However, the distribution of background information in dermatological datasets is imbalanced, causing generalized deep learning models to perform poorly in skin disease classification. We propose a deep learning schema that combines data preprocessing, data augmentation, and residual networks to study the influence of color-based background selection on a deep model's capacity to learn foreground lesion subject attributes in a skin disease classification problem. First, clinical photographs are annotated by dermatologists, and then the original background information is masked with unique colors to generate several subsets with distinct background colors. Sample-balanced training and test sets are generated using random over/undersampling and data augmentation techniques. Finally, the deep learning networks are independently trained on diverse subsets of backdrop colors to compare the performance of classifiers based on different background information. Extensive experiments demonstrate that color-based background information significantly affects the classification of skin diseases and that classifiers trained on the green subset achieve state-of-the-art performance for classifying black and red skin lesions.

Federated Learning Empowered Real-Time Medical Data Processing Method for Smart Healthcare

Computer-aided diagnosis (CAD) has always been an important research topic for applying artificial intelligence in smart healthcare. Sufficient medical data are one of the most critical factors in CAD research. However, medical data are usually obtained in chronological order and cannot be collected all at once, which poses difficulties for the application of deep learning technology in the medical field. The traditional batch learning method consumes considerable time and space resources for real-time medical data, and the incremental learning method often leads to catastrophic forgetting. To solve these problems, we propose a real-time medical data processing method based on federated learning. We divide the process into the model stage and the exemplar stage. In the model stage, we use the federated learning method to fuse the old and new models to mitigate the catastrophic forgetting problem of the new model. In the exemplar stage, we use the most representative exemplars selected from the old data to help the new model review the old knowledge, which further mitigates the catastrophic forgetting problem of the new model. We use this method to conduct experiments on a simulated medical real-time data stream. The experimental results show that our method can learn a disease diagnosis model from a continuous medical real-time data stream. As the amount of data increases, the performance of the disease diagnosis model continues to improve, and the catastrophic forgetting problem has been effectively mitigated. Compared with the traditional batch learning method, our method can significantly save time and space resources.

A new approach for contralateral C7 nerve transfer via retrospinal route

Anterior and posterior approaches exist for the treatment of spinal pathologies. Anatomically, the 7th cervical spinal nerve(C7)crosses the C6-C7 intervertebral foramen bilaterally, allowing contralateral prevertebral or posterior C7 nerve transfer to be used. The advantage of the posterior rather than the anterior spinal approach is that it does not require retraction of important blood vessels, nerves, or other structures. In this paper, we describe transfer of the contralateral C7 nerve using a posterior approach.

Male urethral diverticulum squamous cell carcinoma containing a calculus: a rare entity

Male urethral diverticula with calculi have a low incidence. It is extremely rare when the diverticulum accompanied with carcinoma. We report a case of diverticulum of the male urethra containing giant calculi which developed into squamous cell carcinoma. The patient initially presented with lower urinary tract symptoms and a hard, painless perineal mass. We believe that the process of diagnosis and treatment is of great significance in clinical practice.

[Efficacy and safety of paclitaxel liposomes compared to paclitaxel combined with platinum in concurrent chemoradiotherapy for unresectable cervical carcinoma: a Meta-analysis]

Objective: To explore the efficacy and safety of paclitaxel liposomes compared to paclitaxel with platinum in concurrent chemoradiotherapy for unresectable cervical carcinoma. Methods: SinoMed, CNKI, WanFang MED ONLINE, VIP, PubMed, MEDLINE, Cochrane Library, Embase and ClinicalTrials.gov were searched to collect the papers or clinical studies of paclitaxel liposomes and paclitaxel combined with platinum in concurrent chemoradiotherapy for unresectable cervical carcinoma from the inception to January 15th 2021 in Chinese and English. Two independent reviewers screened the literatures, extracted the data and assessed the bias of the included studies. Meta-analysis was performed using RevMan 5.4 and R software. Results: Totally 9 papers involving 666 patients with unresectable cervical carcinoma were included. The results of meta-analysis indicated that compared to paclitaxel combined with platinum in concurrent chemoradiotherapy for unresectable cervical carcinoma, paclitaxel liposomes combined with platinum exhibited superiority in near-term efficacy (complete response + partial response) [81.4%(272/334) vs 68.7%(228/332), RR=1.19; 95% CI: 1.09, 1.29, P=0.000 1]; substantially decreased the incidence rates of blood system disorders [myelosuppressio, 50.3%(168/334)vs 65.1%(216/332)], gastrointestinal disorders [34.4%(115/334) vs 55.1%(183/332)], alopecia [42.2%(94/223)vs 63.3%(140/221)], allergic reaction [11.6% (23/198)vs 27.6%(54/196), P≤0.000 1], peripheral neuritis [43.0%(52/121) vs 54.9%(67/122)], or joint and muscle pain [20.3%(16/79) vs 34.6%(28/81), P<0.050 0]. Conclusion: Compared to paclitaxel combined with platinum in concurrent chemoradiotherapy for unresectable cervical carcinoma, paclitaxel liposomes is superior in near-term efficacy, and exhibits better safety.

Realistic medical image super-resolution with pyramidal feature multi-distillation networks for intelligent healthcare systems

There are two key requirements for medical lesion image super-resolution reconstruction in intelligent healthcare systems: clarity and reality. Because only clear and real super-resolution medical images can effectively help doctors observe the lesions of the disease. The existing super-resolution methods based on pixel space optimization often lack high-frequency details which result in blurred detail features and unclear visual perception. Also, the super-resolution methods based on feature space optimization usually have artifacts or structural deformation in the generated image. This paper proposes a novel pyramidal feature multi-distillation network for super-resolution reconstruction of medical images in intelligent healthcare systems. Firstly, we design a multi-distillation block that combines pyramidal convolution and shallow residual block. Secondly, we construct a two-branch super-resolution network to optimize the visual perception quality of the super-resolution branch by fusing the information of the gradient map branch. Finally, we combine contextual loss and L1 loss in the gradient map branch to optimize the quality of visual perception and design the information entropy contrast-aware channel attention to give different weights to the feature map. Besides, we use an arbitrary scale upsampler to achieve super-resolution reconstruction at any scale factor. The experimental results show that the proposed super-resolution reconstruction method achieves superior performance compared to other methods in this work.

A predictive model for the severity of COVID-19 in elderly patients

Elderly patients with coronavirus disease 2019 (COVID-19) are more likely to develop severe or critical pneumonia, with a high fatality rate. To date, there is no model to predict the severity of COVID-19 in elderly patients. In this study, patients who maintained a non-severe condition and patients who progressed to severe or critical COVID-19 during hospitalization were assigned to the non-severe and severe groups, respectively. Based on the admission data of these two groups in the training cohort, albumin (odds ratio [OR] = 0.871, 95% confidence interval [CI]: 0.809 - 0.937, P < 0.001), d-dimer (OR = 1.289, 95% CI: 1.042 - 1.594, P = 0.019) and onset to hospitalization time (OR = 0.935, 95% CI: 0.895 - 0.977, P = 0.003) were identified as significant predictors for the severity of COVID-19 in elderly patients. By combining these predictors, an effective risk nomogram was established for accurate individualized assessment of the severity of COVID-19 in elderly patients. The concordance index of the nomogram was 0.800 in the training cohort and 0.774 in the validation cohort. The calibration curve demonstrated excellent consistency between the prediction of our nomogram and the observed curve. Decision curve analysis further showed that our nomogram conferred significantly high clinical net benefit. Collectively, our nomogram will facilitate early appropriate supportive care and better use of medical resources and finally reduce the poor outcomes of elderly COVID-19 patients.

Mutation Analysis of Pre-mRNA Splicing Genes PRPF31, PRPF8, and SNRNP200 in Chinese Families with Autosomal Dominant Retinitis Pigmentosa

BACKGROUND

To screen variants in pre-mRNA Splicing genes in 95 Chinese autosomal dominant retinitis pigmentosa (adRP) families.

METHODS

Clinical examination and pedigree analysis were performed. Targeted exome sequencing (TES) and / or Sanger sequencing were performed to detect the variants in genes of Splicing factors and conduct intra-familiar segregation analysis with DNA available. In silico analysis was performed to predict pathogenicity of variants in protein level and in vitro splicing assays were performed to compare splicing variants with their corresponding wildtype about their splicing effect.

RESULTS

In this study, total nine different variants were identified in PRPF31, SNRNP200, and PRPF8 respectively, including six PRPF31 variants [five novel variants 322+1G>A, c.527+2T>G, c.590T>C(p.Leu197Pro), c.1035_1036insGC (p.Pro346Argfs X18), and c.1224dupG (p.Gln409AlafsX66) plus one reported variant c.1060C>T (p.Arg354X)], a recurrent PRPF8 variant c.6930G>T (p.Arg2310Ser), two SNRNP200 variants [one heterozygous and homozygous SNRNP200 recurrent variant c.3260G>A (p.Ser1087Leu), and a reported heterozygous c.2042G>A(p.Arg681His)]. In family 20009, incomplete penetrance was observed. A novel PRPF31 missense variant c.590T>C (p.Leu197Pro) was predicted to be pathogenic in protein level via in silico analysis and in vitro splicing assay demonstrated that two novel splicing PRPF31 variants c.322+1G>A and c.527+2T>G affect splicing compared with the wildtype.

CONCLUSIONS

In our studies, RP-causing variants of pre-mRNA Splicing genes (PRPF31, PRPF8 and SNRNP200) were identified in nine of the ninety-five adRP families respectively, which extend the spectra of RP variant and phenotype. And we provide the first example that SNRNP200-related RP can be caused by both heterozygous and homozygous variants of this gene.

Toll-like receptors and inflammation in metabolic neuropathy; a role in early versus late disease?

Neuropathy is a common, morbid complication of the metabolic syndrome, prediabetes, and diabetes. Recent studies have indicated a potential role for the immune system in the development of neuropathy. In particular, toll-like receptors (TLR) 2 and 4 have been linked to metabolic dysfunction, and blocking TLR4 is proposed as a treatment for neuropathic pain. In the current study, we investigated the role of the immune system, particularly TLRs 2 and 4, in the pathogenesis and progression of neuropathy. Sural or sciatic nerve gene expression arrays from humans and murine neuropathy models of prediabetes and diabetes were first analyzed to identify differentially expressed TLR2- and TLR4-associated genes within the KEGG (Kyoto Encyclopedia of Genes and Genomes) database. We observed that genes associated with TLRs 2 and 4, particularly lipopolysaccharide binding protein (LPB) and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit beta (PIK3CB), were dysregulated across species and across multiple murine models of prediabetic and diabetic neuropathy. To further understand the role of these pathways in vivo, TLR 2 and 4 global knockout mice placed on a 60% high fat diet (HFD-TLR2/4^-/-) were compared with wild type (WT) mice on a high fat diet (HFD-WT) and WT controls on a standard diet (CON). Mice then underwent metabolic, neuropathic, and immunological phenotyping at two time points to assess the impact of TLR signaling on neuropathy and immunity during metabolic dysfunction over time. We found that HFD-TLR2/4^-/- and HFD-WT mice weighed more than CON mice but did not have increased fasting blood glucose levels. Despite normal blood glucose levels, HFD-TLR2/4^-/- mice eventually developed neuropathy at the later time point (28 wks of age) but were somewhat protected from neuropathy at the early time point (16 wks of age) as measured by shorter hind paw withdraw latencies. This is in contrast to HFD-WT mice which developed neuropathy within 11 wks of being placed on a high fat diet and were neuropathic by all measures at both the early and late time points. Finally, we immunophenotyped all three mouse groups at the later time point and found differences in the number of peripheral blood Ly6C-myeloid cells as well as F4/80+ expression. These results indicate that TLR signaling influences early development of neuropathy in sensory neurons, potentially via immune modulation and recruitment.

Knockdown of Tripartite Motif Containing 28 suppresses the migration, invasion and epithelial-mesenchymal transition in ovarian carcinoma cells through down-regulation of Wnt/β-catenin signaling pathway

Tripartite motif containing 28 (TRIM28) is a transcriptional corepressor of Kruppel-associated box zinc finger protein, which has been reported to participate in carcinogenesis. Nonetheless, whether TRIM28 plays a role in the metastasis of ovarian carcinoma (OC) is unclear and requires further investigation. In this study, two OC cell lines (A2780 and OVCAR-3) with stable low expression of TRIM28 were established via RNA interference. We found that the migratory and invasive ability of TRIM28-silenced OC cells significantly decreased. The expression and activity of matrix metallopeptidase (MMP)-2 and MMP-9 in these OC cells were inhibited. The TRIM28 shRNA also suppressed the epithelial-mesenchymal transition (EMT) of OC cells as evidenced by the up-regulated E-cadherin and the downregulated Vimentin and N-cadherin. Additionally, the Wnt/β-catenin signaling pathway was suppressed in TRIM28-silenced OC cells: the activity of β-catenin was inhibited, the expression of total and nuclear β-catenin, Axin 2, T-cell factor 1 (TCF1) and lymphoid enhancer binding factor 1 (LEF1) were decreased, whereas the phosphorylation of β-catenin at Ser33/37 was enhanced. Further, re-expression of active β-catenin in TRIM28-silenced OC cells partly restored their metastasis in vitro. Taken together, our study demonstrates a contributory role of TRIM28 in OC metastasis in vitro, suggesting TRIM28 as a novel therapeutic target for this malignant tumor.

Abnormal RNA stability in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) share key features, including accumulation of the RNA-binding protein TDP-43. TDP-43 regulates RNA homeostasis, but it remains unclear whether RNA stability is affected in these disorders. We use Bru-seq and BruChase-seq to assess genome-wide RNA stability in ALS patient-derived cells, demonstrating profound destabilization of ribosomal and mitochondrial transcripts. This pattern is recapitulated by TDP-43 overexpression, suggesting a primary role for TDP-43 in RNA destabilization, and in postmortem samples from ALS and FTD patients. Proteomics and functional studies illustrate corresponding reductions in mitochondrial components and compensatory increases in protein synthesis. Collectively, these observations suggest that TDP-43 deposition leads to targeted RNA instability in ALS and FTD, and may ultimately cause cell death by disrupting energy production and protein synthesis pathways.

Endotoxin Removal from Albumin and Saline Solutions

Microporous membranes have been developed which can remove endotoxins selectively from electrolyte and albumin solutions by regioselective adsorption in the membrane matrix and outside surface of the membrane. The membranes were prepared in the form of hollow fibre membranes in a continuous process. By varying the membrane preparation parameters, different pore sizes and adsorption capacities could be realized, thus broadening applications for biological purification. Dynamic adsorption capacities for endotoxin from albumin and saline solution were determined and were found to be in the range of 0.2 and 0.1 μg endotoxin/g membrane, respectively, suggesting different adsorption mechanisms. (Int J Artif Organs 2007; 30: 589–93)

[Analysis of contrast echocardiography for detecting right to left shunt in adults with patent foramen ovale]

Objective: To analyze the contrast echocardiography for detecting right to left shunt in adults with patent foramen ovale(PFO), and study the relationship between PFO and cryptogenic stroke. Methods: Clinical data of forty-six adults patients with PFO diagnosed by transesophageal echocardiography(TEE)from March, 2012 to March, 2017 were retrospectively collected, and the patients were divided to 3 groups according to the direction and brightness of the color Doppler shunts: obvious left-to-right shunt (OLRS, group A), weak left-to-right shunt(WLRS, group B), bi-directional shunt(BDS, group C). A right-to-left shunt (RLS) scale was calculated using the method of 10 ml hand-operated saline for contrast echocardiography. Results: There were seventeen cases in group A, four cases (23.5%) showed RLS at level 1, and thirteen cases (76.5%) showed no RLS; there were twenty cases in group B, and all cases (100%) showed RLS, with five cases (25%) at level 1 and fifteen cases (75%) at level 2-3; there were nine cases in group C, and all cases (100%) showed RLS, with two cases (22.2%) at level 1 and seven cases (77.8%) at level 2-3. Anteroposterior diameter of left atrium of patients with no RLS (4.8 cm±0.6 cm) was significantly larger than that of patients with RLS in contrast echocardiography (3.6 cm±0.5 cm)(P=0.000). Conclusions: OLRS of adults with patent foramen ovale and with larger left atrium have less RLS than WLRS and DLRS with normal left atrium in contrast echocardiography.The possibility of paradoxical embolism in WLRS and DLRS is higher than that in OLRS, which should be taken seriously in clinical practice.

Effect of selective serotonin reuptake inhibitors on expression of 5-HT1AR and neurotransmitters in rats with vascular dementia

5-hydroxytryptamine receptor 1A (5-HT1AR) is closely associated with cognitive functions. Selective serotonin reuptake inhibitors (SSRIs) can protect individuals from brain damage following ischemia/hypoxia. To investigate the function of SSRIs in vascular dementia (VD), we established a rat model of VD, and observed the effect of SSRIs on the expression of 5-HT1AR mRNA and neurotransmitters. Male SD rats (6 months) were randomly assigned into sham, model, and SSRI groups (N = 30). VD was achieved by permanent ligation of the bilateral common carotid artery. Escitalopram, a highly selective 5-HT reabsorption inhibitor, was ip injected into the rats for three consecutive weeks. The Morris water-maze was used to test learning and memory. H&E staining for neuronal injury was conducted on cortical and hippocampal tissues. HPLC was used to determine the levels of dopamine (DA), 5-HT, and norepinephrine (NE). RT-PCR was used to determine expression of 5-HT1AR mRNA. As compared to control rats, model animals demonstrated elongated escape latency, lower platform crossing times, and significant injuries to hippocampal CA1 neurons. This was accompanied by reductions in DA, 5-HT, and NE levels in hippocampal tissues, as well as reduced cortical 5-HT and decreased 5-HT1AR mRNA expression (P < 0.05). Escitalopram treatments reduced escape latency, elevated platform crossing times, improved CA1 neuronal damage, increased DA and 5-HT levels in hippocampal and cortical neurons, as well as elevated expression of 5-HT1AR mRNA (P < 0.05). Therefore, SSRIs may improve cognitive dysfunction of VD rats, possibly by stimulating expression of neurotransmitters and protecting neurons.

Methicillin-Resistant Staphylococcus Aureus infection exacerbates NSCLC cell metastasis by up-regulating TLR4/MyD88 pathway

Methicillin-resistant Staphylococcus aureus (MRSA) infection is a major public health problem worldwide, which brings to a more great threat for cancer patients. It's necessary to give attentions to lung cancer combined with MRSA. This study mainly focuses on the influences of MRSA on lung cancer cells (A549). We first found that MRSA infection can enhance metastasis ability of A549 cell and increase matrix metalloproteinase (MMP2 and MMP9) expressions in MRSA-infected A549 cell. Toll-like receptors (TLRs) have been reported to play an important role in tumor cell initiation and migration, and regulate the expression of MMPs in tumors. Our further research indicates that Toll-like receptor 4 (TLR4)/molecules myeloid differentiation factor 88 (MyD88) signaling was up-regulated in MRSA-infected A549 cell. After silencing TLR4 or MyD88 gene, the enhanced metastasis ability of A549 cell by MRSA was decreased significantly; Also, MMP2 and MMP9 expression increase was reversed. In conclusion, MRSA infection can enhance NSCLC cell metastasis by up-regulating TLR4/MyD88 signaling.

Secure and Cost-Effective Distributed Aggregation for Mobile Sensor Networks

Secure data aggregation (SDA) schemes are widely used in distributed applications, such as mobile sensor networks, to reduce communication cost, prolong the network life cycle and provide security. However, most SDA are only suited for a single type of statistics (i.e., summation-based or comparison-based statistics) and are not applicable to obtaining multiple statistic results. Most SDA are also inefficient for dynamic networks. This paper presents multi-functional secure data aggregation (MFSDA), in which the mapping step and coding step are introduced to provide value-preserving and order-preserving and, later, to enable arbitrary statistics support in the same query. MFSDA is suited for dynamic networks because these active nodes can be counted directly from aggregation data. The proposed scheme is tolerant to many types of attacks. The network load of the proposed scheme is balanced, and no significant bottleneck exists. The MFSDA includes two versions: MFSDA-I and MFSDA-II. The first one can obtain accurate results, while the second one is a more generalized version that can significantly reduce network traffic at the expense of less accuracy loss.

Flavonoids intake and risk of prostate cancer: a meta-analysis of observational studies

The aim of the study was to assess the association between total flavonoids/flavonoid subclasses intake and prostate cancer risk. Several databases were searched to select eligible studies with predefined criteria. Risk ratios (RRs) with 95% confidence intervals (CIs) were used as the effect size. Publication bias and sensitivity analysis were performed. A total of five studies including four prospective cohort studies and one case-control study were included in the meta-analysis. The pooled result demonstrated a significantly increased risk of prostate cancer with higher intake of total flavonoids (RR = 1.12, 95% CI: 1.02-1.23, P = 0.013). However, sensitivity analysis indicated that there lacked a significant association after removing the study of Wang et al. (RR = 1.17, 95% CI: 0.94-1.46). Subgroup analysis stratified by flavonoids subclasses found that higher intake of anthocyanidins and flavan-3-ols were significantly associated with increased prostate cancer risk (RR = 1.12, 95% CI: 1.03-1.21, P = 0.011; RR = 1.21, 95% CI: 1.10-1.32, P < 0.001). Sensitivity analysis also indicated that after removing Wang's study, no significant association between anthocyanidins intake and prostate cancer risk was detected (RR = 1.22, 95% CI: 0.97-1.54). In conclusion, higher intake of flavonoids may not be associated with prostate cancer risk.

Benzylation of heterocyclic N-oxides via direct oxidative cross-dehydrogenative coupling with toluene derivatives

A novel cross-dehydrogenative coupling (CDC) of heterocyclic N-oxides with toluene derivatives has been disclosed.

Influence of suppression of CapG gene expression by siRNA on the growth and metastasis of human prostate cancer cells

This study investigated CapG gene expression in prostate cancer cell lines; in addition, we explored the effects of CapG suppression on DU145 cell growth, and the underlying mechanism with which CapG affects DU145 cell growth and invasiveness. The expression of CapG and 18 related genes in DU145 cells was analyzed by flow cytometry, quantitative polymerase chain reaction (qPCR), CCK8 assay, western blot, and the trans-well assay. DU145 cells were transfected with designed small interfering RNA (siRNA). CapG expression was quantified by qPCR and western blot. DU145 cell proliferation and invasiveness was analyzed using the CCK8, flow cytometric, and trans-well assays. CapG, TMPRSS1, EGFR, ETS-1, ERBB2, AKT, Cyclin D1, P21, Bcl-2, and Bak1 gene and Bcl-2, Cyclin D1, and CapG protein expressions were significantly lower in the siRNA group compared to the negative control group (P < 0.05). The proliferation of CapG siRNA DU145 cells was lower than that of the two control groups, 48 h after transfection. The cell inhibition rate was 24.5, 35.4, and 16,5% at 24, 48, and 72 h, respectively. The growth curve indicated that CapG siRNA DU145 cells showed a significantly slower proliferation rate (P < 0.05). The trans-well assay showed a significant decrease in the migratory and invasive capacities of DU145 cells in the siRNA group (P < 0.05). The suppression of CapG expression caused a significant decrease in the proliferation, invasiveness, and metastasis of DU145 cells. The mechanism with which CapG, with other oncogenes, influences cancer cell cycle remains to be elucidated.

Dual-faced SH3BGRL: oncogenic in mice, tumor suppressive in humans

Despite abundant data supporting c-Src as a metastasis-promoting oncogene, activating mutations of c-Src are rare. This suggests that trans-interacting proteins may have a critical role in regulating c-Src activation. Here, we first report the discovery of Src homology 3 (SH3) domain-binding glutamic acid-rich-like protein (SH3BGRL), a novel c-Src activator in mice. Ectopic expression of murine SH3BGRL (mSH3BGRL) strongly promoted both tumor cell invasion and lung metastasis. Molecularly, mSH3BGRL specifically bound the inactive form of c-Src phosphorylated at Tyr527, promoting Tyr416 phosphorylation of c-Src and subsequent FAK-mediated activation of ERK and AKT signaling pathways. Targeting endogenous c-Src alone was sufficient to abolish mSH3BGRL-induced cancer metastasis in vivo. Unexpectedly, human SH3BGRL (hSH3BGRL) in turn suppressed tumorigenesis and metastasis in nature. We attempted site-specific reversion of hSH3BGRL amino-acid sequence to mSH3BGRL and found V108A substitution sufficient to restore SH3BGRL function as a c-Src activator and metastasis promoter. Notably, the somatic mutation R76C of hSH3BGRL can similarly act as hSH3BGRL-V108A and mSH3BGRL in tumorigenesis and metastasis. Our results uncover an evolutionarily controversial role of SH3BGRL in driving tumor metastasis through c-Src activation, and suggests that hSH3BGRL mutation status could be relevant to cancer diagnosis and therapy.

Novel mutations in GJB6 and GJB2 in Clouston syndrome

Clouston syndrome (CS; also termed hidrotic ectodermal dysplasia) is a rare autosomal dominant genetic skin disorder, characterized by alopecia, nail dystrophy, and palmoplantar hyperkeratosis. Mutations in the GJB6 gene, which encodes the gap junction protein connexin 30, have been shown to cause this disorder. To date, four mutations of GJB6 have been found in patients with CS: G11R, V37E, D50N and A88V. Mutations in GJA1 (V41L) and GJB2 (R127H) are also related to CS. We found a novel missense mutation, N14S, in GJB6 and the previously identified F191L mutation in GJB2 (Cx26) in a proband with CS in a Han Chinese pedigree; these mutations were not found in 200 ethnically matched nonconsanguineous Han Chinese controls.

REpeated AutoLogous Infusions of STem cells In Cirrhosis (REALISTIC): a multicentre, phase II, open-label, randomised controlled trial of repeated autologous infusions of granulocyte colony-stimulating factor (GCSF) mobilised CD133+ bone marrow stem cells in patients with cirrhosis. A study protocol for a randomised controlled trial

INTRODUCTION

Liver disease mortality and morbidity are rapidly rising and liver transplantation is limited by organ availability. Small scale human studies have shown that stem cell therapy is safe and feasible and has suggested clinical benefit. No published studies have yet examined the effect of stem cell therapy in a randomised controlled trial and evaluated the effect of repeated therapy.

METHODS AND ANALYSIS

Patients with liver cirrhosis will be randomised to one of three trial groups: group 1: Control group, Standard conservative management; group 2 treatment: granulocyte colony-stimulating factor (G-CSF; lenograstim) 15 µg/kg body weight daily on days 1-5; group 3 treatment: G-CSF 15 µg/kg body weight daily on days 1-5 followed by leukapheresis, isolation and aliquoting of CD133+ cells. Patients will receive an infusion of freshly isolated CD133+ cells immediately and frozen doses at days 30 and 60 via peripheral vein (0.2×10(6) cells/kg for each of the three doses). Primary objective is to demonstrate an improvement in the severity of liver disease over 3 months using either G-CSF alone or G-CSF followed by repeated infusions of haematopoietic stem cells compared with standard conservative management. The trial is powered to answer two hypotheses of each treatment compared to control but not powered to detect smaller expected differences between the two treatment groups. As such, the overall α=0.05 for the trial is split equally between the two hypotheses. Conventionally, to detect a relevant standardised effect size of 0.8 point reduction in Model for End-stage Liver Disease score using two-sided α=0.05(overall α=0.1 split equally between the two hypotheses) and 80% power requires 27 participants to be randomised per group (81 participants in total).

ETHICS AND DISSEMINATION

The trial is registered at Current Controlled Trials on 18 November 2009 (ISRCTN number 91288089, EuDRACT number 2009-010335-41). The findings of this trial will be disseminated to patients and through peer-reviewed publications and international presentations.

Improvement of l-citrulline production in Corynebacterium glutamicum by ornithine acetyltransferase

In this study, Corynebacterium glutamicum ATCC 13032 was engineered to produce l-citrulline through a metabolic engineering strategy. To prevent the flux away from l-citrulline and to increase the expression levels of genes involved in the citrulline biosynthesis pathway, the argininosuccinate synthase gene (argG) and the repressor gene (argR) were inactivated. The engineered C. glutamicum ATCC 13032 ∆argG ∆argR (CIT 2) produced higher amounts of l-citrulline (5.43 g/L) compared to the wildtype strain (0.15 g/L). To determine new strategies for further enhancement of l-citrulline production, the effect of l-citrulline on ornithine acetyltransferase (EC 2.3.1.35; OATase; ArgJ) was first investigated. Citrulline was determined to inhibit Ornithine acetyltransferase; for 50 % inhibition, citrulline concentration was 30 mM. The argJ gene from C. glutamicum ATCC 13032 was cloned, and the recombinant shuttle plasmid pXMJ19-argJ was constructed and expressed in C. glutamicum ATCC 13032 ∆argG ∆argR (CIT 2). Overexpression of the argJ gene exhibited increased OAT activity and resulted in a positive effect on citrulline production (8.51 g/L). These results indicate that OAT plays a vital role during l-citrulline production in C. glutamicum.

Abdominal subcutaneous adipose tissue insulin resistance and lipolysis in patients with non-alcoholic steatohepatitis

BACKGROUND

Systemic insulin resistance (IR) is a primary feature in non-alcoholic steatohepatitis (NASH), however, there remain limited data on tissue-specific insulin sensitivity in vivo.

METHODS

We examined tissue-specific (adipose, muscle and liver) insulin sensitivity and inflammation in 16 European Caucasian patients with biopsy-confirmed NASH and in 15 healthy controls. All underwent a two-step hyperinsulinaemic euglycaemic clamp incorporating stable isotope measurements of carbohydrate and lipid metabolism with concomitant subcutaneous adipose tissue (SAT) microdialysis.

RESULTS

Hepatic and muscle insulin sensitivity were decreased in patients with NASH compared with controls, as demonstrated by reduced suppression of hepatic glucose production and glucose disposal (Gd) rates following insulin infusion. In addition, rates of lipolysis were higher in NASH patients with impaired insulin-mediated suppression of free fatty acid levels. At a tissue specific level, abdominal SAT in patients with NASH was severely insulin resistant, requiring >sixfold more insulin to cause ½-maximal suppression of glycerol release when compared with healthy controls. Furthermore, patients with NASH had significantly higher circulating levels of pro-inflammatory adipocytokines than controls.

CONCLUSION

NASH patients have profound IR in the liver, muscle and in particular adipose tissues. This study represents the first in vivo description of dysfunctional SAT in patients with NASH.