[Correlation between clinical phenotypes and genotypes among 46 children with SCN1A-related developmental epileptic encephalopathy].

OBJECTIVE: To explore the correlation between clinical phenotypes and genotypes among 46 children with SCN1A-related developmental epileptic encephalopathy (DEE). METHODS: Clinical data of 46 children with DEE and SCN1A variants identified at the Guangzhou Women and Children's Medical Center between January 2018 and June 2022 were collected. The children were grouped based on their age of onset, clinical manifestations, neurodevelopmental status, and results of genetic testing. The correlation between SCN1A genotypes and clinical phenotypes was analyzed. RESULTS: Among the 46 patients, 2 children (4.35%) had developed the symptoms before 3 months of age, 42 (91.30%) were between 3 to 9 months, and 2 cases (4.35%) were after 10 months. Two cases (4.35%) presented with epilepsy of infancy with migrating focal seizures (EIMFS), while 44 (95.7%) had presented with Dravet syndrome (DS), including 28 cases (63.6%) with focal onset (DS-F), 13 cases (29.5%) with myoclonic type (DS-M), 1 case (2.27%) with generalized type (DS-G), and 2 cases (4.55%) with status epilepticus type (DS-SE). Both of the two EIMFS children had severe developmental delay, and among the DS patients, 7 cases had normal development, while the remaining had developmental delay. A total of 44 variants were identified through genetic sequencing, which included 16 missense variants and 28 truncating variants. All EIMFS children had carried the c.677C>T (p.Thr226Met) missense variant. In the DS group, there was a significant difference in the age of onset between the missense variants group and the truncating variants group (P < 0.05). Missense variants were more common in D1 (7/15, 46.7%) and pore regions (8/15, 53.3%), while truncating variants were more common in D1 (12/28, 42.9%). Children with variants outside the pore region were more likely to develop myoclonic seizures. CONCLUSION: The clinical phenotypes of DEE are diverse. There is a difference in the age of onset between individuals with truncating and missense variants in the SCN1A gene. Missense variants outside the pore region are associated with a higher incidence of myoclonic seizures.

Clinical effects of atorvastatin combined with conbercept in the treatment of patients with macular edema secondary to retinal vein occlusion and carotid plaque: study protocol for a prospective randomized controlled trial.

INTRODUCTION: Intravitreal injections of anti-vascular endothelial growth factor (anti-VEGF) drugs have been widely used in patients with macular edema (ME) secondary to retinal vein occlusion (RVO); however, recurrence is a major concern. This study aims to observe the clinical effects of atorvastatin and intravitreal therapy in the treatment of patients with branch or central RVO-ME and coexistent carotid plaques (CP). METHODS AND ANALYSIS: A prospective randomized controlled clinical trial will be conducted. Sixty-four patients diagnosed with branch or central RVO-ME and coexistent CP will be enrolled and randomly allocated in a 1:1 ratio to the control and experimental groups. The control group will be treated with intravitreal conbercept monthly for 3 months, followed by monthly evaluation and injection of pro re nata (PRN) for 12 months, while the experimental group will be treated with oral atorvastatin 20 mg daily combined with the control group treatment. If a drop of best-corrected visual acuity (BCVA) is more than five Early Treatment Diabetic Retinopathy Study (ETDRS) letters (one line) or an increment in central subfield thickness (CSFT) of 100 µm (or a 10% increment from the previous visit), intravitreal re-treatment will be performed. Outcome measurements include CSFT, BCVA, number of injections, and incidence of adverse events during the 12-month follow-up period. Differences between groups will be evaluated using Student's t-test, and comparisons between groups will be evaluated using repeated-measures analysis of variance. ETHICS AND DISSEMINATION: The study has been approved by the Institutional Review Board of Nanjing Lishui People's Hospital, Nanjing, China (approval number 2023KY0418-12, dated 18 April 2023), and has been registered on chictr.org.cn. Written informed consent will be collected from each patient and the results of this trial will be submitted to a peer-reviewed journal. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2300071359. Registered on 12 May 2023.

Multifaceted physiological and therapeutical impact of curcumin on hormone-related endocrine dysfunctions: A comprehensive review.

Over the past five decades, Curcumin (Cur), derived from turmeric (Curcuma longa), has gained considerable attention for its potential therapeutic applications. Synthesizing insights from clinical trials conducted over the last 25 years, this review delves into diseases where Cur has demonstrated promise, offering a nuanced understanding of its pharmacokinetics, safety, and effectiveness. Focusing on specific examples, the impact of Cur on various human diseases is explored. Endocrine glands and associated signaling pathways are highlighted, elucidating how Cur influences cellular signaling. The article underscores molecular mechanisms such as hormone level alteration, receptor interaction, cytokine and adipokine expression inhibition, antioxidant enzyme activity, and modulation of transcription factors. Cur showcases diverse protective mechanisms against inflammation and oxidative damage by suppressing antiapoptotic genes and impeding tumor promotion. This comprehensive overview emphasizes the potential of Cur as a natural agent for countering aging and degenerative diseases, calling for further dedicated research in this realm.

PathoGraph: An Attention-Based Graph Neural Network Capable of Prognostication Based on CD276 Labelling of Malignant Glioma Cells.

Computerized methods have been developed that allow quantitative morphological analyses of whole slide images (WSIs), e.g., of immunohistochemical stains. The latter are attractive because they can provide high-resolution data on the distribution of proteins in tissue. However, many immunohistochemical results are complex because the protein of interest occurs in multiple locations (in different cells and also extracellularly). We have recently established an artificial intelligence framework, PathoFusion which utilises a bifocal convolutional neural network (BCNN) model for detecting and counting arbitrarily definable morphological structures. We have now complemented this model by adding an attention-based graph neural network (abGCN) for the advanced analysis and automated interpretation of such data. Classical convolutional neural network (CNN) models suffer from limitations when handling global information. In contrast, our abGCN is capable of creating a graph representation of cellular detail from entire WSIs. This abGCN method combines attention learning with visualisation techniques that pinpoint the location of informative cells and highlight cell-cell interactions. We have analysed cellular labelling for CD276, a protein of great interest in cancer immunology and a potential marker of malignant glioma cells/putative glioma stem cells (GSCs). We are especially interested in the relationship between CD276 expression and prognosis. The graphs permit predicting individual patient survival on the basis of GSC community features. Our experiments lay a foundation for the use of the BCNN-abGCN tool chain in automated diagnostic prognostication using immunohistochemically labelled histological slides, but the method is essentially generic and potentially a widely usable tool in medical research and AI based healthcare applications.

Impact of litter size on the hematological and iron status of gilts, sows and newborn piglets: a comparative study of domestic pigs and wild boars.

BACKGROUND: The critically low hepatic iron stores of newborn piglets are considered to be a major cause of neonatal iron deficiency in modern breeds of domestic pig (Sus domestica). The main factor believed to contribute to this phenomenon is large litter size, which has been an objective of selective breeding of pigs for decades. As consequence, iron transferred from the pregnant sow has to be distributed among a greater number of fetuses. RESULTS: Here, we investigated whether litter size influences red blood cell (RBC) indices and iron parameters in Polish Large White (PLW) piglets and gilts. Small and large litters were produced by the transfer of different numbers of embryos, derived from the same superovulated donor females, to recipient gilts. Piglets from large litters obtained following routine artificial insemination were also examined. Our results clearly demonstrated that varying the number of piglets in a litter did not affect the RBC and iron status of 1-day-old piglets, with all showing iron deficiency anemia. In contrast, gilts with small litters displayed higher RBC and iron parameters compared to mothers with large litters. A comparative analysis of the RBC status of wild boars (having less than half as many piglets per litter as domestic pigs) and PLW pigs, demonstrated higher RBC count, hemoglobin level and hematocrit value of both wild boar sows and piglets, even compared to small-litter PLW animals. CONCLUSIONS: These findings provide evidence that RBC and iron status in newborn PLW piglets are not primarily determined by litter size, and indicate the need to study the efficiency of iron transport across the placenta in domestic pig and wild boar females.

MBD-Net: Multi-Branch Dilated Convolutional Network With Cyst Discriminator for Renal Multi-Structure Segmentation.

In surgery-based renal cancer treatment, one of the most essential tasks is the three-dimensional (3D) kidney parsing on computed tomography angiography (CTA) images. In this paper, we propose an end-to-end convolutional neural network-based framework to segment multiple renal structures, including kidneys, kidney tumors, arteries, and veins from arterial-phase CT images. Our method consists of two collaborative modules: First, we propose an encoding-decoding network, named Multi-Branch Dilated Convolutional Network (MBD-Net), consisting of residual, hybrid dilated convolutional, and reduced-dimensional convolutional structures, which improves the feature extraction ability with relatively fewer network parameters. Given that renal tumors and cysts have confusing geometric structures, we also design the Cyst Discriminator to effectively distinguish tumors from cysts without labeling information via gray-scale curves and radiographic features. We have quantitatively evaluated our approach on a publicly available dataset from MICCAI 2022 Kidney Parsing for Renal Cancer Treatment Challenge (KiPA2022), with mean Dice similarity coefficient (DSC) as 96.18%, 90.99%, 88.66% and 80.35% for the kidneys, kidney tumors, arteries, and veins respectively, winning the stable and top performance in the challenge.Clinical relevance-The proposed CNN-Based framework can automatically segment 3D kidneys, renal tumors, arteries, and veins for kidney parsing techniques, benefiting surgery-based renal cancer treatment.

MiR-597-5p inhibits carcinogenesis and macrophage recruitment in colitis-related colorectal cancer via reducing the expression of CXCL5.

Despite being the subject of multiple cancer studies, nothing is known about miR-597-5p's role in colitis-associated colorectal cancer (CAC). We intend to explore how miR-597-5p influences the growth and development of CAC. In order to construct a CAC model, mice were stimulated with azoxymethane (AOM)/dextran sulfate sodium (DSS). The in situ hybridization (ISH) and quantitative real-time polymerase chain reaction (qRT-PCR) was used for the detection of miR-597-5p expression. The protein expression of CXCL5 was determined by western blotting, immunohistochemistry and enzyme-linked immuno sorbent assay (ELISA). The histologic colitis score and hematoxylin and eosin (HE) staining were used to evaluate degree of damage to colonic tissues. The proportion of macrophages detected in colon tumors was also measured using flow cytometry. The transwell test was employed to assess macrophage migration. It was found that the miR-597-5p and its target CXCL5 had a negative correlation. MiR-597-5p expression was decreased, while CXCL5 expression was raised in CAC tissues. In AOM/DSS-induced mice, miR-597-5p deficiency in intestinal epithelial cells resulted in decreasing colon length as well as increasing tumor numbers and histologic colitis score, which was reversed by CXCL5 inhibition. MiR-597-5p deficiency facilitated macrophage recruitment in AOM/DSS-induced mice and promoted macrophage migration in vitro, which were reversed by CXCL5 inhibition. Deficiency of miR-597-5p aggravated macrophage recruitment and tumorigenesis in a mouse CAC model, suggesting that miR-597-5p agonists may have an anti-inflammatory therapeutic effect in inflammatory bowel diseases and reduce the risk of developing CAC.

Levetiracetam may be an unsuitable choice for patients with PRRT2-associated self-limited infantile epilepsy.

INTRODUCTION: Self-limited infantile epilepsy (SeLIE) is a benign epilepsy. Previous studies have shown that monotherapy with most antiseizure medications can effectively relieve seizures in patients with SeLIE, but the efficacy of levetiracetam has not been investigated. OBJECTIVE: This study aimed to investigate the efficacy of levetiracetam in the treatment of SeLIE patients with PRRT2 mutations. METHODS: The clinical data of 39 SeLIE patients (21 males and 18 females, aged 4.79 ± 1.60 months) with pathogenic variants in PRRT2 or 16p11.2 microdeletion were retrospectively analyzed. Based on the use of initial antiseizure medication (ASM), the patients were classified into two groups: Levetiracetam group (LEG) and Other ASMs group (OAG). The difference of efficacy between the two groups was compared. RESULTS: Among the 39 SeLIE patients, 16 were LEG (10 males and 6 females, aged 5.25 ± 2.07 months), with whom two obtained a seizure-free status (12.50%) and 14 ineffective or even deteriorated (87.50%). Among the 14 ineffective or deteriorated cases, 13 were seizure-controlled after replacing levetiracetam with other ASMs including topiramate, oxcarbazepine, lamotrigine, and valproate, and the remaining one finally achieved remission at age 3. Of the 39 patients, 23 were OAG (11 males and 12 females; aged 4.48 ± 1.12 months), of whom 22 achieved seizure remission, except for one patient who was ineffective with topiramate initially and relieved by oxcarbazepine instead. Although there were no significant differences in gender and age of onset between the two groups, the effective rate was significantly different (12.50% in LEG vs. 95.65% in OAG) (P < 0.01). CONCLUSION: The findings showed that patients with SeLIE caused by the PRRT2 mutations did not benefit from the use of levetiracetam, but could benefit from other ASMs.

[Genetic analysis of a child with developmental disorder and epilepsy due to a homozygous variant of PIGW gene].

OBJECTIVE: To explore the genetic basis for a child featuring global developmental disorder with epilepsy. METHODS: A child who had presented at Guangzhou Women and Children's Medical Center in July 2022 was selected as the study subject. Clinical data was collected. Potential variant was detected by whole exome sequencing (WES). Candidate variant was validated by Sanger sequencing and bioinformatic analysis. RESULTS: The child, a three-year-old ethnic Zhuang Chinese girl, had presented with global developmental disorder and epilepsy, for which rehabilitation therapy was ineffective. Genetic testing revealed that she has harbored a homozygous c.821T>C (p.Leu274Pro) missense variant of the PIGW gene, for which both of her parents and sister were heterozygous carriers. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variant was classified as variant of uncertain significance. CONCLUSION: The homozygous c.821T>C (p.Leu274Pro) variant of the PIGW gene probably underlay the onset of disease in this child. Above finding has enriched the mutational spectrum of the PIGW gene.

Unsupervised Local Discrimination for Medical Images.

Contrastive learning, which aims to capture general representation from unlabeled images to initialize the medical analysis models, has been proven effective in alleviating the high demand for expensive annotations. Current methods mainly focus on instance-wise comparisons to learn the global discriminative features, however, pretermitting the local details to distinguish tiny anatomical structures, lesions, and tissues. To address this challenge, in this paper, we propose a general unsupervised representation learning framework, named local discrimination (LD), to learn local discriminative features for medical images by closely embedding semantically similar pixels and identifying regions of similar structures across different images. Specifically, this model is equipped with an embedding module for pixel-wise embedding and a clustering module for generating segmentation. And these two modules are unified by optimizing our novel region discrimination loss function in a mutually beneficial mechanism, which enables our model to reflect structure information as well as measure pixel-wise and region-wise similarity. Furthermore, based on LD, we propose a center-sensitive one-shot landmark localization algorithm and a shape-guided cross-modality segmentation model to foster the generalizability of our model. When transferred to downstream tasks, the learned representation by our method shows a better generalization, outperforming representation from 18 state-of-the-art (SOTA) methods and winning 9 out of all 12 downstream tasks. Especially for the challenging lesion segmentation tasks, the proposed method achieves significantly better performance.

Necroptosis Mediates Muscle Protein Degradation in a Cachexia Model of Weanling Pig with Lipopolysaccharide Challenge.

Necroptosis, an actively researched form of programmed cell death closely related to the inflammatory response, is important in a variety of disorders and diseases. However, the relationship between necroptosis and muscle protein degradation in cachexia is rarely reported. This study aimed to elucidate whether necroptosis played a crucial role in muscle protein degradation in a cachexia model of weaned piglets induced by lipopolysaccharide (LPS). In Experiment 1, the piglets were intraperitoneally injected with LPS to construct the cachexia model, and sacrificed at different time points after LPS injection (1, 2, 4, 8, 12, and 24 h). In Experiment 2, necrostatin-1 (Nec-1), a necroptosis blocker, was pretreated in piglets before the injection of LPS to inhibit the occurrence of necroptosis. Blood and longissimus dorsi muscle samples were collected for further analysis. In the piglet model with LPS-induced cachexia, the morphological and ultrastructural damage, and the release of pro-inflammatory cytokines including tumor necrosis factor (TNF)-α, interleukin (IL)-1ß, and IL-6 were dynamically elicited in longissimus dorsi muscle. Further, protein concentration and protein/DNA ratio were dynamically decreased, and protein degradation signaling pathway, containing serine/threonine kinase (Akt), Forkhead box O (FOXO), muscular atrophy F-box (MAFbx), and muscle ring finger protein 1 (MuRF1), was dynamically activated in piglets after LPS challenge. Moreover, mRNA and protein expression of necroptosis signals including receptor-interacting protein kinase (RIP)1, RIP3, and mixed lineage kinase domain-like pseudokinase (MLKL), were time-independently upregulated. Subsequently, when Nec-1 was used to inhibit necroptosis, the morphological damage, the increase in expression of pro-inflammatory cytokines, the reduction in protein content and protein/DNA ratio, and the activation of the protein degradation signaling pathway were alleviated. These results provide the first evidence that necroptosis mediates muscle protein degradation in cachexia by LPS challenge.

Effect of sedated colonoscopy with different cost coverage on improving compliance with colorectal cancer screening in China.

Background: Colorectal cancer is the third most common cancer worldwide. Colonoscopy is the gold standard for colorectal cancer screening. However, the colonoscopy participation rate in China is much lower than that in Europe and the United States. As only non-sedated colonoscopies are offered in colorectal cancer screening programs in China, the absence of sedation may contribute to this gap. Methods: To explore the effect of free and partially participant-paid sedated colonoscopy on improving colorectal screening participation, we conducted a cross-sectional study under the framework of the Cancer Screening Program in Urban China in Xuzhou from May 2017 to December 2020. The Quanshan district was set as the control group and provided free non-sedated colonoscopy, the Yunlong district was set as a partial cost coverage group and offered partially participant-paid sedated colonoscopy, and the Gulou district was set as the full cost coverage group and offered free sedation colonoscopies. Multivariate logistic regression was used for multivariate analysis of colonoscopy participation and colorectal lesion detection rates between the groups. Results: From May 2017 to May 2020, 81,358 participants were recruited and completed questionnaire, 7,868 subjects who met high-risk conditions for CRC were invited to undergo colonoscopy. The colonoscopy participation rates in the control group, partially cost coverage, and full cost coverage groups were 17.33% (594/3,428), 25.66% (542/2,112), and 34.41% (801/2,328), respectively. Subjects in the partial and full cost coverage groups had 1.66-fold (95% CI: 1.48-1.86) and 2.49-fold (95% CI: 2.23-2.76) increased rates compared with those in the control group. The adjusted PARs for the partially and the full cost coverage group was 9.08 (95% CI: 6.88-11.28) and 18.97 (95% CI: 16.51-21.42), respectively. The detection rates of CAN in the control, partial-cost coverage, and full-cost coverage groups were 3.54% (21/594), 2.95% (16/542), and 5.12% (41/801), respectively. There were no significant differences in the detection rates between the group. However, sedated colonoscopy increases costs. Conclusion: Sedated colonoscopy increased colonoscopy participation rates in both the partial and full cost-covered groups. A partial cost coverage strategy may be a good way to increase colorectal cancer participation rates and quickly establish a colorectal cancer screening strategy in underfunded areas.

Freeze-dried powder of daylily bud improves bromocriptine-induced lactation disorder in rats via JAK2/STAT5 pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Milk deficiency is a prevalent problem in the world. Daylily (Hemerocallis citrina Borani), called the Chinese mother flower, is a traditional vegetable and is believed to possess a galactagogue effect in China. Flavonoids and phenols are considered as the active ingredients of daylily to promote lactation and improve depression. AIM OF THE STUDY: The aim of this study was to investigate the prolactin effects of freeze-dried powder of flower buds of H. citrina Baroni in rat and its action mechanisms. MATERIALS AND METHODS: The chemical constituents of flower buds of H. citrina Baroni treated by different drying techniques were analyzed by ultrahigh pressure liquid chromatography-mass spectrometry. Sprague-Dawley (SD) rat model induced by bromocriptine was used to evaluate the effect of freeze-dried powder of daylily buds on promoting lactation. Network pharmacology method, ELISA, qPCR, and Western blot were used to clarify the action mechanisms. RESULTS: We detected 657 compounds in daylily buds. The relative contents of total flavonoids and phenols in freeze-dried samples were higher than those in dried ones. Bromocriptine, as a dopamine receptor agonist, can significantly inhibit prolactin in rats. Daylily buds can restore the levels of prolactin, progesterone and estradiol depressed by bromocriptine, effectively improve the milk production of the rat, and promote the repair of rat mammary gland tissue. We analyzed the relationship between the chemical components of daylily buds and the genes related to lactation with network pharmacology method, revealing that flavonoids and phenols may be the active components that promoted milk production via JAK2/STAT5 pathway, which was confirmed by the results of qPCR and Western blot. Daylily buds can increase the mRNA expression of PRLR, CSN2, LALBA and FASN and the protein expression of PRLR, JAK2 and STAT5. CONCLUSION: Daylily buds can improve the insufficient lactation of rats induced by bromocriptine through PRLR/JAK2/STAT5 pathway, and the freeze-dried processing method may better retain the active components of flavonoids and phenols that promote milk in daylily.

A comparative study of structural parameters for spiral groove bearing in centrifugal rotary blood pump.

In this work, the hydrodynamic characteristics of spiral groove bearing in centrifugal rotary blood pump is investigated for the cases with different structural parameters. The simulation model is proposed based on the CFD technology and the effectiveness of simulation model is demonstrated by the published data. Then, the pressure, load carrying capacity and friction torque are calculated and the characteristics of pressure distribution are analyzed. It is found that the structural parameters of spiral groove would lead to the complex pressure distribution of blood film and the load carrying capacity also changes at the same time. Moreover, the deep analysis of structural characteristics for spiral groove bearing is conducted based on the orthogonal design method, which could improve the computational efficiency of hydrodynamic behavior of spiral groove bearing. And, the mapping relationship between structural parameter and hydrodynamic performance of bearing preferably is also illustrated.

Preoperative 18F-FDG PET/CT radiomics analysis for predicting HER2 expression and prognosis in gastric cancer.

Background: We aimed to establish and validate 2 machine learning models using 18F-flurodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiomic features to predict human epidermal growth factor receptor 2 (HER2) expression and prognosis in gastric cancer (GC) patients. Methods: We retrospectively enrolled 90 patients diagnosed with GC, including their clinical information and the 18F-FDG PET/CT images. Patients were allocated to a training cohort of 72 patients and an independent validation cohort (IVC) of 18 patients. There were 2,100 radiomic features extracted from the 18F-FDG PET/CT scans. A sequential combination of multivariate and univariate feature selection was applied, including sequential forward selection and a redundancy-based analysis. The justification of the model performance was conducted by cross-validation analysis on the training set and an independent validation analysis. Results: The machine learning models were developed using a balanced bagging approach for HER2 expression prediction and prognosis prediction, which differentiated HER2 positive expression from negative expression in the IVC with an area under the receiver operating characteristic curve (AUC) of 0.72, sensitivity of 0.85, and specificity of 0.80. The IVC for prognosis prediction achieved an AUC of 0.75, sensitivity of 0.82, and specificity of 0.71. We also conducted a reasonable interpretation for the selected features in each classification task from multiple aspects, including normalized feature importance analysis and statistical correlation analysis with the clinical features that were defaulted to be effective. Conclusions: 18F-FDG PET/CT radiomics analysis with a machine learning model provides a quantitative, efficient, and objective mechanism for predicting HER2 expression and prognosis in GC patients.

Compact Convolutional Neural Network with Multi-Headed Attention Mechanism for Seizure Prediction.

Epilepsy is a neurological disorder related to frequent seizures. Automatic seizure prediction is crucial for the prevention and treatment of epilepsy. In this paper, we propose a novel model for seizure prediction that incorporates a convolutional neural network (CNN) with multi-head attention mechanism. In this model, the shallow CNN automatically captures the EEG features, and the multi-headed attention focuses on discriminating the effective information among these features for identifying pre-ictal EEG segments. Compared with current CNN models for seizure prediction, the embedded multi-headed attention empowers the shallow CNN to be more flexible, and enables improvement of the training efficiency. Hence, this compact model is more resistant to being trapped in overfitting. The proposed method was evaluated over the scalp EEG data from the two publicly available epileptic EEG databases, and achieved outperforming values of event-level sensitivity, false prediction rate (FPR), and epoch-level F1. Furthermore, our method achieved the stable length of seizure prediction time that was between 14 and 15 min. The experimental comparisons showed that our method outperformed other prediction methods in terms of prediction and generalization performance.

Effects of plasma-derived exosomes from the normal and thin Bactrian camels on hepatocellular carcinoma and their differences at transcriptome and proteomics levels.

Background: Hepatocellular carcinoma (HCC) is a common malignant primary tumor. Bactrian camels have high economic and social values, but their potential medical value has not been studied. This study aimed to investigate the effects of Bactrian camel plasma-derived exosomes on HCC. Methods: Plasma was obtained from thin and normal Bactrian camels, and used to isolate exosomes by ultracentrifugation. The exosomes were then characterized by transmission electron microscopy and Nano particle tracking analyzer. In vivo imaging of nude mice and hematoxylin eosin (HE) staining of liver tissues were used to explore the effects of the exosomes on tumor growth. Finally, the differences of the two exosomes were further analyzed using small RNA sequencing and proteomics. Results: In vivo imaging and HE staining showed that no significant differences were found in fluorescence value and liver tissue morphology between the control mice and the mice treated with the exosomes from thin Bactrian camels; while the fluorescence value and the live histology changes were alleviated in the mice with the exosomes from normal Bactrian camels. After sequencing and proteomic analysis, 40 differentially expressed miRNAs (DE-miRNAs, 15 down-regulated and 25 up-regulated) and 172 differentially expressed proteins (DEPs, 77 up-regulated and 95 down-regulated) were identified in the plasma-derived exosomes from normal Bactrian camels. These identified DE-miRNAs and DEPs were significantly enriched in many signaling pathways. Conclusions: Normal Bactrian camel plasma-derived exosomes may inhibit the growth of HCC cells through regulating pathways of Ras, Ras-Association Proximate 1 (Rap1), phosphoinositide 3-kinase-protein kinase B (PI3K-Akt), mitogen-activated protein kinase (MAPK), adenosine monophosphate-activated protein kinase (AMPK), and canonical Wnt signaling pathways.

AMNet: Adaptive multi-level network for deformable registration of 3D brain MR images.

Three-dimensional (3D) deformable image registration is a fundamental technique in medical image analysis tasks. Although it has been extensively investigated, current deep-learning-based registration models may face the challenges posed by deformations with various degrees of complexity. This paper proposes an adaptive multi-level registration network (AMNet) to retain the continuity of the deformation field and to achieve high-performance registration for 3D brain MR images. First, we design a lightweight registration network with an adaptive growth strategy to learn deformation field from multi-level wavelet sub-bands, which facilitates both global and local optimization and achieves registration with high performance. Second, our AMNet is designed for image-wise registration, which adapts the local importance of a region in accordance with the complexity degrees of its deformation, and thereafter improves the registration efficiency and maintains the continuity of the deformation field. Experimental results from five publicly-available brain MR datasets and a synthetic brain MR dataset show that our method achieves superior performance against state-of-the-art medical image registration approaches.

Multi-task deep learning for medical image computing and analysis: A review.

The renaissance of deep learning has provided promising solutions to various tasks. While conventional deep learning models are constructed for a single specific task, multi-task deep learning (MTDL) that is capable to simultaneously accomplish at least two tasks has attracted research attention. MTDL is a joint learning paradigm that harnesses the inherent correlation of multiple related tasks to achieve reciprocal benefits in improving performance, enhancing generalizability, and reducing the overall computational cost. This review focuses on the advanced applications of MTDL for medical image computing and analysis. We first summarize four popular MTDL network architectures (i.e., cascaded, parallel, interacted, and hybrid). Then, we review the representative MTDL-based networks for eight application areas, including the brain, eye, chest, cardiac, abdomen, musculoskeletal, pathology, and other human body regions. While MTDL-based medical image processing has been flourishing and demonstrating outstanding performance in many tasks, in the meanwhile, there are performance gaps in some tasks, and accordingly we perceive the open challenges and the perspective trends. For instance, in the 2018 Ischemic Stroke Lesion Segmentation challenge, the reported top dice score of 0.51 and top recall of 0.55 achieved by the cascaded MTDL model indicate further research efforts in high demand to escalate the performance of current models.

A novel model of subretinal edema induced by DL-alpha aminoadipic acid.

In this study we described a new model of subretinal edema induced by single intraocular injection of DL-alpha-aminoadipic acid (DLAAA) that can be employed to study the mechanism of retinal edema and test the efficacy or potential toxicity of treatments. The progression of subretinal edema was evaluated by fundus photography, fluorescein angiography and optical coherence tomography for up to 4 weeks following DLAAA injection. The VEGF, IL-6, TNF-α, Occludin, ZO-1, AQP4, Kir4.1, GFAP and GS levels were examined in DLAAA models by immunostaining, immumohistochemical staining and Western blot. Additionally, bulk RNA-seq was used to detect the mechanism involved in DLAAA-induced retinal Müller cellular injuries. In vivo and vitro assays were further conducted to confirm the sequencing results. Subretinal edema was successfully induced by DLAAA in New Zealand White rabbits (1.29 mg/eye) and C57BL/6 mice (50 or 100 µg/eye). Our results demonstrated that the disruption of blood-retinal-barrier, including vascular hyperpermeability, inflammation, and Müller cell dysfunction of fluid clearance, was involved in subretinal edema formation in the model. Bulk RNA-seq and in vitro studies indicated the activation of p38 MAPK signaling pathway in DLAAA models. This DLAAA-induced subretinal edema model can be used for mechanistic studies or drug screening.