Macrophage membrane-reversibly camouflaged nanotherapeutics accelerate fracture healing by fostering MSCs recruitment and osteogenic differentiation.

The fracture healing outcome is largely dependent on the quantities as well as osteogenic differentiation capacities of mesenchymal stem cells (MSCs) at the lesion site. Herein, macrophage membrane (MM)-reversibly cloaked nanocomplexes (NCs) are engineered for the lesion-targeted and hierarchical co-delivery of short stromal derived factor-1α peptide (sSDF-1α) and Ckip-1 small interfering RNA (Ckip-1 siRNA, siCkip-1) to promote bone repair by concurrently fostering recruitment and osteogenic differentiation of endogenous MSCs. To construct the NCs, a membrane-penetrating α-helical polypeptide first assembles with siCkip-1, and the cationic NCs are sequentially coated with catalase and an outer shell of sSDF-1α-anchored MM. Due to MM-assisted inflammation homing, intravenously injected NCs could efficiently accumulate at the fractured femur, where catalase decomposes the local hydrogen peroxide to generate oxygen bubbles that drives the shedding of sSDF-1α-anchored MM in the extracellular compartment. The exposed, cationic inner core thus enables robust trans-membrane delivery into MSCs to induce Ckip-1 silencing. Consequently, sSDF-1α-guided MSCs recruitment cooperates with siCkip-1-mediated osteogenic differentiation to facilitate bone formation and accelerate bone fracture healing. This study provides an enlightened strategy for the hierarchical co-delivery of macromolecular drugs into different cellular compartments, and it also renders a promising modality for the management of fracture healing.

Molecular Analysis of Parthenogenetic Chimerism in a 46,XX/46,XY Patient with Idiopathic Oligoasthenoteratozoospermia.

INTRODUCTION: Parthenogenetic chimera is an extremely rare condition in human. Very few patients with parthenogenetic chimerism with XX/XY cells have been identified. CASE PRESENTATION: We report the clinical findings and molecular analysis of chimerism with a 46,XX/46,XY karyotype in a patient presenting idiopathic oligoasthenoteratozoospermia (OAT). To clarify the mechanism of chimera formation, short tandem repeat analysis using 21 loci was carried out. Quantitation of alleles in D6S1043, D12S391, fibrinogen alpha chain, and amelogenin revealed double paternal and one maternal genetic contribution to the patient, which is consistent with a parthenogenetic chimerism. The likely mechanism of chimerism formation was also discussed, followed by a literature review. CONCLUSION: This is the first documented case of parthenogenetic chimerism in an adult male with XX/XY cells presenting OAT. Improved cell sampling and more sensitive and specific detection methods are necessary to identify more patients with XX/XY chimerism for systematic studies on this condition in the future.

Research Progress on the Mechanism of Nanoparticles Crossing the Intestinal Epithelial Cell Membrane.

Improving the stability of drugs in the gastrointestinal tract and their penetration ability in the mucosal layer by implementing a nanoparticle delivery strategy is currently a research focus in the pharmaceutical field. However, for most drugs, nanoparticles failed in enhancing their oral absorption on a large scale (4 folds or above), which hinders their clinical application. Recently, several researchers have proved that the intestinal epithelial cell membrane crossing behaviors of nanoparticles deeply influenced their oral absorption, and relevant reviews were rare. In this paper, we systematically review the behaviors of nanoparticles in the intestinal epithelial cell membrane and mainly focus on their intracellular mechanism. The three key complex intracellular processes of nanoparticles are described: uptake by intestinal epithelial cells on the apical side, intracellular transport and basal side exocytosis. We believe that this review will help scientists understand the in vivo performance of nanoparticles in the intestinal epithelial cell membrane and assist in the design of novel strategies for further improving the bioavailability of nanoparticles.

Inflammatory Cell-Inspired Cascade Nanozyme Induces Intracellular Radical Storm for Enhanced Anticancer Therapy.

Manipulating intracellular levels of reactive oxygen and nitrogen species (RONS) is of great potential for cancer treatment. Inspired by the natural mechanism of a radical storm in inflammatory cells via activated and regulatable biocatalysis, the authors herein report a self-powered nanozyme that can enable RONS production in tumor cells via cascade reactions. The nanozymes are constructed via glucose oxidase (GOx)-templated inverse microemulsion polymerization from acrylamide, arginine-acrylamide, ferrocene-acrylate, and N,N'-bis(acryloyl)cystamine, followed by surface coating with hyaluronic acid. After targeted delivery into cancer cells, the nanozymes are dissociated by intracellular glutathione to release GOx, which decomposed glucose to generate gluconic acid and H2 O2 . Under such acidified conditions, H2 O2 efficiently oxidized pendant arginine residues to produce nitric oxide , transformed into a highly toxic hydroxyl radical and superoxide anion via ferrocene-mediated Fenton reaction and Haber-Weiss cycle, and simultaneously generated peroxynitrite anion via reaction between NO and ·O2 - , thus provoking the RONS radical storm to effectively eradicate A549 tumor cells both in vitro and in vivo. This nature-inspired enzyme-chemical dynamic therapy may provide a promising modality for anti-cancer treatment.

Risk factors and machine learning model for predicting hospitalization outcomes in geriatric patients with dementia.

Introduction: Geriatric patients with dementia incur higher healthcare costs and longer hospital stays than other geriatric patients. We aimed to identify risk factors for hospitalization outcomes that could be mitigated early to improve outcomes and impact overall quality of life. Methods: We identified risk factors, that is, demographics, hospital complications, pre-admission, and post-admission risk factors including medical history and comorbidities, affecting hospitalization outcomes determined by hospital stays and discharge dispositions. Over 150 clinical and demographic factors of 15,678 encounters (8407 patients) were retrieved from our institution's data warehouse. We further narrowed them down to twenty factors through feature selection engineering by using analysis of variance (ANOVA) and Glmnet. We developed an explainable machine-learning model to predict hospitalization outcomes among geriatric patients with dementia. Results: Our model is based on stacking ensemble learning and achieved accuracy of 95.6% and area under the curve (AUC) of 0.757. It outperformed prevalent methods of risk assessment for encounters of patients with Alzheimer's disease dementia (ADD) (4993), vascular dementia (VD) (4173), Parkinson's disease with dementia (PDD) (3735), and other unspecified dementias (OUD) (2777). Top identified hospitalization outcome risk factors, mostly from medical history, include encephalopathy, number of medical problems at admission, pressure ulcers, urinary tract infections, falls, admission source, age, race, anemia, etc., with several overlaps in multi-dementia groups. Discussion: Our model identified several predictive factors that can be modified or intervened so that efforts can be made to prevent recurrence or mitigate their adverse effects. Knowledge of the modifiable risk factors would help guide early interventions for patients at high risk for poor hospitalization outcome as defined by hospital stays longer than seven days, undesirable discharge disposition, or both. The interventions include starting specific protocols on modifiable risk factors like encephalopathy, falls, and infections, where non-existent or not routine, to improve hospitalization outcomes of geriatric patients with dementia. Highlights: A total 15,678 encounters of Geriatrics with dementia with a final 20 risk factors.Developed a predictive model for hospitalization outcomes for multi-dementia types.Risk factors for each type were identified including those amenable to interventions.Top factors are encephalopathy, pressure ulcers, urinary tract infection (UTI), falls, and admission source.With accuracy of 95.6%, our ensemble predictive model outperforms other models.

Image-to-image translation of label-free molecular vibrational images for a histopathological review using the UNet+/seg-cGAN model.

Translating images generated by label-free microscopy imaging, such as Coherent Anti-Stokes Raman Scattering (CARS), into more familiar clinical presentations of histopathological images will help the adoption of real-time, spectrally resolved label-free imaging in clinical diagnosis. Generative adversarial networks (GAN) have made great progress in image generation and translation, but have been criticized for lacking precision. In particular, GAN has often misinterpreted image information and identified incorrect content categories during image translation of microscopy scans. To alleviate this problem, we developed a new Pix2pix GAN model that simultaneously learns classifying contents in the images from a segmentation dataset during the image translation training. Our model integrates UNet+ with seg-cGAN, conditional generative adversarial networks with partial regularization of segmentation. Technical innovations of the UNet+/seg-cGAN model include: (1) replacing UNet with UNet+ as the Pix2pix cGAN's generator to enhance pattern extraction and richness of the gradient, and (2) applying the partial regularization strategy to train a part of the generator network as the segmentation sub-model on a separate segmentation dataset, thus enabling the model to identify correct content categories during image translation. The quality of histopathological-like images generated based on label-free CARS images has been improved significantly.

Artificial intelligence-augmented, label-free molecular imaging method for tissue identification, cancer diagnosis, and cancer margin detection.

Label-free high-resolution molecular and cellular imaging strategies for intraoperative use are much needed, but not yet available. To fill this void, we developed an artificial intelligence-augmented molecular vibrational imaging method that integrates label-free and subcellular-resolution coherent anti-stokes Raman scattering (CARS) imaging with real-time quantitative image analysis via deep learning (artificial intelligence-augmented CARS or iCARS). The aim of this study was to evaluate the capability of the iCARS system to identify and differentiate the parathyroid gland and recurrent laryngeal nerve (RLN) from surrounding tissues and detect cancer margins. This goal was successfully met.

Retrospective study of deep learning to reduce noise in non-contrast head CT images.

PURPOSE: Presented herein is a novel CT denoising method uses a skip residual encoder-decoder framework with group convolutions and a novel loss function to improve the subjective and objective image quality for improved disease detection in patients with acute ischemic stroke (AIS). MATERIALS AND METHODS: In this retrospective study, confirmed AIS patients with full-dose NCCT head scans were randomly selected from a stroke registry between 2016 and 2020. 325 patients (67 ± 15 years, 176 men) were included. 18 patients each with 4-7 NCCTs performed within 5-day timeframe (83 total scans) were used for model training; 307 patients each with 1-4 NCCTs performed within 5-day timeframe (380 total scans) were used for hold-out testing. In the training group, a mean CT was created from the patient's co-registered scans for each input CT to train a rotation-reflection equivariant U-Net with skip and residual connections, as well as a group convolutional neural network (SRED-GCNN) using a custom loss function to remove image noise. Denoising performance was compared to the standard Block-matching and 3D filtering (BM3D) method and RED-CNN quantitatively and visually. Signal-to-noise ratio (SNR) and contrast-to-noise (CNR) were measured in manually drawn regions-of-interest in grey matter (GM), white matter (WM) and deep grey matter (DG). Visual comparison and impact on spatial resolution were assessed through phantom images. RESULTS: SRED-GCNN reduced the original CT image noise significantly better than BM3D, with SNR improvements in GM, WM, and DG by 2.47x, 2.83x, and 2.64x respectively and CNR improvements in DG/WM and GM/WM by 2.30x and 2.16x respectively. Compared to the proposed SRED-GCNN, RED-CNN reduces noise effectively though the results are visibly blurred. Scans denoised by the SRED-GCNN are shown to be visually clearer with preserved anatomy. CONCLUSION: The proposed SRED-GCNN model significantly reduces image noise and improves signal-to-noise and contrast-to-noise ratios in 380 unseen head NCCT cases.

The effect of platelet G proteins on platelet extravasation and tumor growth in the murine model of ovarian cancer.

We and other investigators have shown that platelets promote metastasis and the growth of tumors. Our rationale for conducting this study is that platelets' prometastatic and progrowth effects depend on a close encounter between platelets and cancer cells. This interaction occurs inside blood vessels with circulating tumor cells and outside blood vessels with cancer cells residing in the tumor parenchyma. Our hypothesis was that platelet extravasation is required for the effect of platelets on tumor growth. Platelets respond to environmental stimuli by activation of G protein-coupled receptors on their surface. We investigated the impact of various platelet G proteins on the growth of ovarian cancer tumors and platelet extravasation. We used mice with platelet-specific deficiency of Gαi2 (Gi), Gα13 (G13), or Gαq (Gq) in a syngeneic ovarian cancer model. We measured the total weight of tumor nodules resected from tumor-bearing mice. We developed methods for automated whole-slide image acquisition and unbiased computerized image analysis to quantify extravasated platelets. We compared the number of platelets inside tumor nodules of platelet G protein-deficient tumor-bearing mice. We found that deficiency of Gi and G13, but not Gq, in platelets resulted in smaller tumors compared with those in corresponding littermates. Deficiency of Gi and G13 in platelets reduced the number of extravasated platelets by >90%, but deficiency of Gq did not reduce the number of extravasated platelets significantly. The lack of Gi or G13 in platelets reduced platelet extravasation into the tumor and tumor growth.

Deep learning powers cancer diagnosis in digital pathology.

Technological innovation has accelerated the pathological diagnostic process for cancer, especially in digitizing histopathology slides and incorporating deep learning-based approaches to mine the subvisual morphometric phenotypes for improving pathology diagnosis. In this perspective paper, we provide an overview on major deep learning approaches for digital pathology and discuss challenges and opportunities of such approaches to aid cancer diagnosis in digital pathology. In particular, the emerging graph neural network may further improve the performance and interpretability of deep learning in digital pathology.

Clinical and transcriptional signatures of human CD204 reveal an applicable marker for the protumor phenotype of tumor-associated macrophages in breast cancer.

BACKGROUND: Tumor-associated macrophages in human breast cancer are poorly understood. Specific tumor-associated macrophage-related molecular mechanisms among different intrinsic molecular subtypes remain unclear. Here, we have identified and explored the roles of the tumor-associated macrophages novel marker: CD204 in different subtypes of breast cancer. RESULTS: CD204 was upregulated in four subtypes of breast cancer, and this was associated with poor survival outcomes. CD204 could promote tumor cell proliferation, migration, and invasion and was involved in immune system-related pathways among all subtypes. Special pathways in each subtype were also found. High CD204 mRNA expressions were associated with high proportions of protumor immune cell populations, and most immunoinhibitors positive correlated with CD204 expression in all subtypes. CONCLUSIONS: These findings contribute to a better understanding and managing the protumor phenotype of tumor-associated macrophages in different subtypes of breast cancer. METHODS: The expression of CD204 and its clinical outcome were analyzed. The roles of CD204 in the regulation of tumor cell proliferation, migration, and invasion were studied. Potential pathways influenced by CD204 were displayed. Immune cell infiltration in different CD204 mRNA expression status and correlations between CD204 and immunoinhibitors were also analyzed.

Analysis of miRNA-mRNA network reveals miR-140-5p as a suppressor of breast cancer glycolysis via targeting GLUT1.

Aim: Aerobic glycolysis is characteristic of breast cancer. Comprehensive expression profiles of key proteins, their prognosis and detailed relationships between miRNAs and mRNAs remain unclear. Materials & methods: Oncomine database, Kaplan-Meier overall survival and miRNA-mRNA network analysis were performed. A key miRNA was identified and explored in vitro and in vivo. Results & conclusion: Eleven key glycolytic proteins were found with higher expression and poor prognosis: GLUT1, SLC2A5, HK1, PFKP, ALDOA, TPI1, GAPDH, PGK1, ENO1, GOT1 and GOT2. Seven miRNAs were predicted targeting 11 key glycolytic proteins: miR-140-5p, miR-3064-5p, miR-152-3p, miR-449b-5p, miR-449a, miR-194-5p and miR-34a-5p. Among them, miR-140-5p was found to be downregulated in breast cancer and directly targeted GLUT1, resulting in an antiglycolytic and antiproliferative effect.

Circular RNA circASS1 is downregulated in breast cancer cells MDA-MB-231 and suppressed invasion and migration.

AIM: The study aimed to investigate the role of circular RNA circASS1 in breast cancer cells. MATERIALS & METHODS: Circular RNAs microarray expression profile were analyzed in MCF-7, MDA-MB-231, and qRT-PCR and western blotting were used to quantify expression of circASS1 and its parental gene ASS1. Wound healing, migration and invasion assay were performed. Luciferase assay system was used to detect harbored miRNA. RESULTS: CircASS1 in MDA-MB-231 is downregulated comparing to MCF-7, and overexpression of circASS1 could suppress invasion and migration. While silence, it could promote invasion and migration. MiR-4443 functioning as a tumor promoter gene could be captured by circASS1. ASS1 is upregulated in loss-of-function experiments, while downregulated in gain-of-function experiments. CONCLUSION: CircASS1 suppresses invasion and migration capacity of breast cancer cells and harbored miR-4443.

[Familial Y chromosome microdeletion with pericentric inversion of chromosome 19].

OBJECTIVE: To investigate the familial cytomolecular genetics of an infertile male. METHODS: We analyzed the clinical phenotypes and karyotypes of three males from the family of an infertile man, detected the sequence-tagged sites (STS) in the AZF deletions of the Y chromosome by multiplex polymerase chain reaction (PCR), and identified the target genes by multiplex ligation-dependent probe amplification (MLPA). RESULTS: The karyotypes of the proband and his brother were 46, XY, inv (19) (p13.3q13.1) and that of his father was 46, XY. The three males were all carriers of AZFc deletion of the Y chromosome, and all found with the same reduction of the gene copy number in the AZFb and AZFc regions. CONCLUSIONS: Combined use of karyotype analysis, Y chromosome STS PCR, and MLPA revealed the genetic causes of the male infertile family.

Circular RNA hsa_circ_0072995 promotes breast cancer cell migration and invasion through sponge for miR-30c-2-3p.

AIM: To study the role of hsa_circ_0072995 in regulating the invasion and migration of breast cancer cells. MATERIALS & METHODS: Hsa_circ_0072995 expression was confirmed by quantitative real-time PCR; evaluating the migration and invasion of breast cancer cells through transwell assay; predicating circRNA/microRNAs interaction using the miRanda and RNAhybrid software; identifying the relationship between hsa_circ_0072995 and miR-30c-2-3p by luciferase activity assay; detecting the location of hsa_circ_0072995 by Fluorescence in situ hybridization assay. RESULTS: Hsa_circ_0072995 was significantly upregulated in MDA-MB-231 cells compared with MCF-7 cells. Hsa_circ_0072995 regulated the invasion and migration of breast cancer cells. Hsa_circ_0072995 existed in the nucleus and cytoplasm, and the proportion of the two was roughly equal. Hsa_circ_0072995 bound to miR-30c-2-3p. Overexpression of miR-30c-2-3p inhibited breast cancer cells migration and invasion. Low expression of miR-30c-2-3p was correlated with poor overall survival by The Cancer Genome Atlas database. CONCLUSION: Hsa_circ_0072995 may be a novel biomarker for breast cancer, and may function in metastasis of breast cancer.

The regulatory roles of lncRNAs in the process of breast cancer invasion and metastasis.

Breast cancer (BC) is the most common cancer and principal cause of death among females worldwide. Invasion and metastasis are major causes which influence the survival and prognosis of BC. Therefore, to understand the molecule mechanism underlying invasion and metastasis is paramount for developing strategies to improve survival and prognosis in BC patients. Recent studies have reported that long non-coding RNAs (lncRNAs) play critical roles in the regulation of BC invasion and metastasis through a variety of molecule mechanisms that endow cells with an aggressive phenotype. In this article, we focused on the function of lncRNAs on BC invasion and metastasis through participating in epithelial-to-mesenchymal transition, strengthening cancer stem cells generation, serving as competing endogenous lncRNAs, influencing multiple signaling pathways as well as regulating expressions of invasion-metastasis related factors, including cells adhesion molecules, extracellular matrix, and matrix metallo-proteinases. The published work described has provided a better understanding of the mechanisms underpinning the contribution of lncRNAs to BC invasion and metastasis, which may lay the foundation for the development of new strategies to prevent BC invasion and metastasis.

The miR-15b-5p/PDK4 axis regulates osteosarcoma proliferation through modulation of the Warburg effect.

Blocking aerobic glycolysis has been proposed as an attractive therapeutic strategy for impairing the proliferation of cancer cells. However, the underlying mechanisms are poorly understood. Here, we show that miR-15b-5p was downregulated in osteosarcoma (OS) and that lower expression of miR-15b-5p promoted proliferation and contributed to the Warburg effect in OS cells. Mechanistically, miR-15b-5p acted as a tumor suppressor in OS by directly targeting pyruvate dehydrogenase kinase-4 and inhibiting its expression. These results reveal a previously unknown function of miR-15b-5p in OS, which is associated with metabolic alterations that promote cancer progression. miR-15b-5p may play an essential role in the molecular therapy of patients with OS.

The progress of circular RNAs in various tumors.

Circular RNAs (circRNAs), a novel type of non-coding RNAs, presented as covalently closed continuous loops. Recent researches had found that circRNAs could function as microRNA sponges, regulators of gene transcription and encoding proteins. They were relatively stable and expressed widely in cytoplasm, which played important roles in carcinogenesis of cancers, such as esophageal cancer, gastric cancer, colorectal cancer, hepatocarcinoma, bladder cancer, glioma, breast cancer, osteosarcoma and so on. Furthermore, they were involved in many biological functions, like cell proliferation, drug resistance, cell cycle, invasion and metastasis. Therefore, the further studies were meaningful on the mechanism of cancers and circRNAs. In the review, we will summarize the current biogenesis of circRNAs and the roles of them in various cancers, which might be a novel biomarker and therapeutic avenue.

Cytokine-mediated therapeutic resistance in breast cancer.

Therapeutic resistance leading to tumor relapse is a major challenge in breast cancer (BCa) treatment. Numerous factors involved in multiple mechanisms promote the development of tumor chemo/radio-resistance. Cytokines/chemokines are important inflammatory factors and highly related to tumorigenesis, metastasis and tumors responses to treatment. A large number of studies have demonstrated that the network of cytokines activates multiple cell signaling pathways to promote tumor cell survival, proliferation, invasion, and migration. Particularly in BCa, cytokines-enhanced the epithelial-mesenchymal transition (EMT) process plays a pivotal role in the progression of metastatic phenotypes and resistance to the traditional chemo/radio-therapy. Virtually, therapeutic resistance is not entirely determined by tumor cell intrinsic characteristics but also dependent upon synchronized effects by numerous of local microenvironmental factors. Emerging evidence highlighted that exosomes secreted from various types of cells promote intercellular communication by transferring bioactive molecules including miRNAs and cytokines, suggesting that exosomes are essential for sustentation of tumor progression and therapeutic resistance within the tumor microenvironment. In this review, we discuss the mechanisms by which cytokines promote therapeutic resistance of BCa and suggest a potential approach for improving BCa therapeutics by inhibition of exosome function.

SLIT2/ROBO1 axis contributes to the Warburg effect in osteosarcoma through activation of SRC/ERK/c-MYC/PFKFB2 pathway.

Cellular metabolic reprogramming is the main characteristic of cancer cells and identification of targets using this metabolic pattern is extremely important to treat cancers, such as osteosarcoma (OS). In this study, SLIT2 and ROBO1 were upregulated in OS, and higher expression of ROBO1 was associated with worse overall survival rate. Furthermore, in vitro and in vivo experiments demonstrated that the SLIT2/ROBO1 axis promotes proliferation, inhibits apoptosis, and contributes to the Warburg effect in OS cells. Mechanistically, the SLIT2/ROBO1 axis exerted cancer-promoting effects on OS via activation of the SRC/ERK/c-MYC/PFKFB2 pathway. Taken together, the findings reveal a previously unappreciated function of SLIT2/ROBO1 signaling in OS, which is intertwined with metabolic alterations that promote cancer progression. Targeting the SLIT2/ROBO1 axis may be a potential therapeutic approach for patients with OS.