Biomedical potentials of alginate via physical, chemical, and biological modifications.

Alginate is a linear polysaccharide with a modifiable structure and abundant functional groups, offers immense potential for tailoring diverse alginate-based materials to meet the demands of biomedical applications. Given the advancements in modification techniques, it is significant to analyze and summarize the modification of alginate by physical, chemical and biological methods. These approaches provide plentiful information on the preparation, characterization and application of alginate-based materials. Physical modification generally involves blending and physical crosslinking, while chemical modification relies on chemical reactions, mainly including acylation, sulfation, phosphorylation, carbodiimide coupling, nucleophilic substitution, graft copolymerization, terminal modification, and degradation. Chemical modified alginate contains chemically crosslinked alginate, grafted alginate and oligo-alginate. Biological modification associated with various enzymes to realize the hydrolysis or grafting. These diverse modifications hold great promise in fully harnessing the potential of alginate for its burgeoning biomedical applications in the future. In summary, this review provides a comprehensive discussion and summary of different modification methods applied to improve the properties of alginate while expanding its biomedical potentials.

Ocular image-based deep learning for predicting refractive error: A systematic review.

Background: Uncorrected refractive error is a major cause of vision impairment worldwide and its increasing prevalent necessitates effective screening and management strategies. Meanwhile, deep learning, a subset of Artificial Intelligence, has significantly advanced ophthalmological diagnostics by automating tasks that required extensive clinical expertise. Although recent studies have investigated the use of deep learning models for refractive power detection through various imaging techniques, a comprehensive systematic review on this topic is has yet be done. This review aims to summarise and evaluate the performance of ocular image-based deep learning models in predicting refractive errors. Main text: We search on three databases (PubMed, Scopus, Web of Science) up till June 2023, focusing on deep learning applications in detecting refractive error from ocular images. We included studies that had reported refractive error outcomes, regardless of publication years. We systematically extracted and evaluated the continuous outcomes (sphere, SE, cylinder) and categorical outcomes (myopia), ground truth measurements, ocular imaging modalities, deep learning models, and performance metrics, adhering to PRISMA guidelines. Nine studies were identified and categorised into three groups: retinal photo-based (n â€‹= â€‹5), OCT-based (n â€‹= â€‹1), and external ocular photo-based (n â€‹= â€‹3).For high myopia prediction, retinal photo-based models achieved AUC between 0.91 and 0.98, sensitivity levels between 85.10% and 97.80%, and specificity levels between 76.40% and 94.50%. For continuous prediction, retinal photo-based models reported MAE ranging from 0.31D to 2.19D, and R 2 between 0.05 and 0.96. The OCT-based model achieved an AUC of 0.79-0.81, sensitivity of 82.30% and 87.20% and specificity of 61.70%-68.90%. For external ocular photo-based models, the AUC ranged from 0.91 to 0.99, sensitivity of 81.13%-84.00% and specificity of 74.00%-86.42%, MAE ranges from 0.07D to 0.18D and accuracy ranges from 81.60% to 96.70%. The reported papers collectively showed promising performances, in particular the retinal photo-based and external eye photo -based DL models. Conclusions: The integration of deep learning model and ocular imaging for refractive error detection appear promising. However, their real-world clinical utility in current screening workflow have yet been evaluated and would require thoughtful consideration in design and implementation.

Simvastatin alleviates glymphatic system damage via the VEGF-C/VEGFR3/PI3K-Akt pathway after experimental intracerebral hemorrhage.

Current clinical practice primarily relies on surgical intervention to remove hematomas in patients with intracerebral hemorrhage (ICH), given the lack of effective drug therapies. Previous research indicates that simvastatin (SIM) may enhance hematoma absorption and resolution in the acute phase of ICH, though the precise mechanisms remain unclear. Recent findings have highlighted the glymphatic system (GS) as a crucial component in intracranial cerebrospinal fluid circulation, playing a significant role in hematoma clearance post-ICH. This study investigates the link between SIM efficacy in hematoma resolution and the GS. Our experimental results show that SIM alleviates GS damage in ICH-induced rats, resulting in improved outcomes such as reduced brain edema, neuronal apoptosis, and degeneration. Further analysis reveals that SIM's effects are mediated through the VEGF-C/VEGFR3/PI3K-Akt pathway. This study advances our understanding of SIM's mechanism in promoting intracranial hematoma clearance and underscores the potential of targeting the GS for ICH treatment.

MFS-DBF: A trustworthy multichannel feature sieve and decision boundary formulation system for Obstructive Sleep Apnea detection.

The fine identification of sleep apnea events is instrumental in Obstructive Sleep Apnea (OSA) diagnosis. The development of sleep apnea event detection algorithms based on polysomnography is becoming a research hotspot in medical signal processing. In this paper, we propose an Inverse-Projection based Visualization System (IPVS) for sleep apnea event detection algorithms. The IPVS consists of a feature dimensionality reduction module and a feature reconstruction module. First, features of blood oxygen saturation and nasal airflow are extracted and used as input data for event analysis. Then, visual analysis is conducted on the feature distribution for apnea events. Next, dimensionality reduction and reconstruction methods are combined to achieve the dynamic visualization of sleep apnea event feature sets and the visual analysis of classifier decision boundaries. Moreover, the decision-making consistency is explored for various sleep apnea event detection classifiers, which provides researchers and users with an intuitive understanding of the detection algorithm. We applied the IPVS to an OSA detection algorithm with an accuracy of 84% and a diagnostic accuracy of 92% on a publicly available dataset. The experimental results show that the consistency between our visualization results and prior medical knowledge provides strong evidence for the practicality of the proposed system. For clinical practice, the IPVS can guide users to focus on samples with higher uncertainty presented by the OSA detection algorithm, reducing the workload and improving the efficiency of clinical diagnosis, which in turn increases the value of trust.

Biomimetic nanomedicine cocktail enables selective cell targeting to enhance ovarian Cancer chemo- and immunotherapy.

Ovarian cancer is one of the deadliest cancers, and combined chemo- and immunotherapies are potential strategies to combat it. However, the anti-cancer efficacy of the combined therapies may be limited by the non-selective co-delivery of chemotherapy and immunotherapy. Herein, a combined chemo- and immunotherapy is designed to selectively target ovarian tumor (ID8) cells and dendritic cells (DCs) using ID8 cell membrane (IM) and bacterial outer membrane vesicles (OMVs), respectively. Doxorubicin (DOX) and Ovalbumin (OVA) peptide (OVA257-264) are chosen as model chemotherapy and immunotherapy agents, respectively. A DNA nanocube capable of easily loading DOX or OVA257-264 is chosen as the carrier. Firstly, the DNA nanocube is used to load DOX or OVA257-264 to prepare cube-DOX or cube-OVA. This nanocube was then encapsulated with IM to form IM@Cube-DOX and with OMV to form OMV@Cube-OVA. IM@Cube-DOX can be selectively taken up by ID8 cells, leading to effective cell killing, while OMV@Cube-OVA targets and activates DC2.4 cells in vitro. Both IM@Cube-DOX and OMV@Cube-OVA show increased accumulation at ID8 tumors in C57BL/6 mice. Combined IM@Cube-DOX + OMV@Cube-OVA therapy demonstrates better anti-tumor efficacy than non-selective delivery methods such as OMV@(Cube-DOX + Cube-OVA) or IM@(Cube-DOX + Cube-OVA) in ID8-OVA tumor-bearing mice. In conclusion, this study demonstrates a biomimetic delivery strategy that enables selective drug delivery to tumor cells and DCs, thereby enhancing the anti-tumor efficacy of combined chemo- and immunotherapy through the selective delivery strategy.

A novel real-time model for predicting acute kidney injury in critically ill patients within 12 hours.

BACKGROUND: A major challenge in prevention and early treatment of acute kidney injury (AKI) is the lack of high-performance predictors in critically ill patients. Therefore, we innovatively constructed U-AKIpredTM for predicting AKI in critically ill patients within 12 h of panel measurement. METHODS: The prospective cohort study included 680 patients in the training set and 249 patients in the validation set. After performing inclusion and exclusion criteria, 417 patients were enrolled in the training set and 164 patients were enrolled in the validation set finally. AKI was diagnosed by Kidney Disease Improving Global Outcomes (KDIGO) criteria. RESULTS: Twelve urinary kidney injury biomarkers (mALB, IgG, TRF, α1MG, NAG, NGAL, KIM-1, L-FABP, TIMP2, IGFBP7, CAF22 and IL-18) exhibited good predictive performance for AKI within 12 h in critically ill patients. U-AKIpredTM, combined with three crucial biomarkers (α1MG, L-FABP and IGFBP7) by multivariate logistic regression analysis, exhibited better predictive performance for AKI in critically ill patients within 12 h than the other twelve kidney injury biomarkers. The area under the curve (AUC) of the U-AKIpredTM, as a predictor of AKI within 12 h, was 0.802 (95% CI: 0.771-0.833, P < 0.001) in the training set and 0.844 (95% CI: 0.792-0.896, P < 0.001) in validation cohort. A nomogram based on the results of the training and validation sets of U-AKIpredTM was developed which showed optimal predictive performance for AKI. The fitting effect and prediction accuracy of U-AKIpredTM was evaluated by multiple statistical indicators. To provide a more flexible predictive tool, the dynamic nomogram (https://www.xsmartanalysis.com/model/U-AKIpredTM) was constructed using a web-calculator. Decision curve analysis (DCA) and a clinical impact curve were used to reveal that U-AKIpredTM with the three crucial biomarkers had a higher net benefit than these twelve kidney injury biomarkers respectively. The net reclassification index (NRI) and integrated discrimination index (IDI) were used to improve the significant risk reclassification of AKI compared with the 12 kidney injury biomarkers. The predictive efficiency of U-AKIpredTM was better than the NephroCheck® when testing for AKI and severe AKI. CONCLUSION: U-AKIpredTM is an excellent predictive model of AKI in critically ill patients within 12 h and would assist clinicians in identifying those at high risk of AKI.

Changes in meat quality, metabolites and microorganisms of mutton during cold chain storage.

During the cold chain storage process, changes in metabolites and microorganisms are highly likely to lead to changes in meat quality. To elucidate the changes in the composition of metabolites and microbiota during cold chain storage of mutton, this study utilized untargeted metabolome and 5R 16S rRNA sequencing analyses to investigate the changes in the longissimus dorsi under different cold chain temperatures (4 °C and -20 °C). With the extension of cold chain storage time, the meat color darkened and the content of C18:2n-6, C20:3n-6, and C23:0 were significantly increased in mutton. In this study, nine metabolites, including 1,2-Dioleoyl-sn-glycero-3-phosphoethanolamine, alanylphenylala-nine, indole-3-acrylic acid and the others, were significantly altered during cold chain storage. The abundance of the dominant microorganisms, including Brachymonas, Aeromonas, Corynebacterium and Steroidobacter, was significantly altered. Furthermore, a high correlation was observed between the different metabolites and microorganisms. These findings provide an in-depth understanding of the effects of different cold chain storage temperatures and times on the quality of mutton.

Targeting PAX8 sensitizes ovarian cancer cells to ferroptosis by inhibiting glutathione synthesis.

Ovarian cancer is a malignant tumor originating from the ovary, characterized by its high mortality rate and propensity for recurrence. In some patients, especially those with recurrent cancer, conventional treatments such as surgical resection or standard chemotherapy yield suboptimal results. Consequently, there is an urgent need for novel anti-cancer therapeutic strategies. Ferroptosis is a distinct form of cell death separate from apoptosis. Ferroptosis inducers have demonstrated promising potential in the treatment of ovarian cancer, with evidence indicating their ability to enhance ovarian cancer cell sensitivity to cisplatin. However, resistance of cancer cells to ferroptosis still remains an inevitable challenge. Here, we analyzed genome-scale CRISPR-Cas9 loss-of function screens and identified PAX8 as a ferroptosis resistance protein in ovarian cancer. We identified PAX8 as a susceptibility gene in GPX4-dependent ovarian cancer. Depletion of PAX8 rendered GPX4-dependent ovarian cancer cells significantly more sensitive to GPX4 inhibitors. Additionally, we found that PAX8 inhibited ferroptosis in ovarian cancer cells. Combined treatment with a PAX8 inhibitor and RSL3 suppressed ovarian cancer cell growth, induced ferroptosis, and was validated in a xenograft mouse model. Further exploration of the molecular mechanisms underlying PAX8 inhibition of ferroptosis mutations revealed upregulation of glutamate-cysteine ligase catalytic subunit (GCLC) expression. GCLC mediated the ferroptosis resistance induced by PAX8 in ovarian cancer. In conclusion, our study underscores the pivotal role of PAX8 as a therapeutic target in GPX4-dependent ovarian cancer. The combination of PAX8 inhibitors such as losartan and captopril with ferroptosis inducers represents a promising new approach for ovarian cancer therapy.

Galectin-3 impairs calcium transients and ß-cell function.

In diabetes, macrophages and inflammation are increased in the islets, along with ß-cell dysfunction. Here, we demonstrate that galectin-3 (Gal3), mainly produced and secreted by macrophages, is elevated in islets from both high-fat diet (HFD)-fed and diabetic db/db mice. Gal3 acutely reduces glucose-stimulated insulin secretion (GSIS) in ß-cell lines and primary islets in mice and humans. Importantly, Gal3 binds to calcium voltage-gated channel auxiliary subunit gamma 1 (CACNG1) and inhibits calcium influx via the cytomembrane and subsequent GSIS. ß-Cell CACNG1 deficiency phenocopies Gal3 treatment. Inhibition of Gal3 through either genetic or pharmacologic loss of function improves GSIS and glucose homeostasis in both HFD-fed and db/db mice. All animal findings are applicable to male mice. Here we show a role of Gal3 in pancreatic ß-cell dysfunction, and Gal3 could be a therapeutic target for the treatment of type 2 diabetes.

The effects of Shaoma Zhijing granules and its main components on Tourette syndrome.

BACKGROUND: Tourette syndrome (TS) represents a neurodevelopmental disorder characterized by an uncertain etiology and influencing factors. Frequently, it co-occurs with conditions such as attention deficit hyperactivity disorder, obsessive-compulsive disorder, and sleep disturbances, which have garnered substantial attention from the research community in recent years. Clinical trials have demonstrated that Shaoma Zhijing Granules (SMZJG, 5-ling granule, also known as TSupport or T92 under U.S. development), a traditional Chinese medicine compound, is an effective treatment for TS. PURPOSE: To conduct scientometric analysis on developing trends, research countries and institutions, current status, hot spots of TS and discuss the underlying mechanisms of SMZJG and its main components on TS. The aim is to provide valuable reference for ongoing clinical and basic research on TS and SMZJG. STUDY DESIGN & METHODS: Using Tourette syndrome, SMZJG and its main components along with their synonyms as keywords, we conducted a comprehensive search across major scientific databases including the Web of Science Core Collection, PubMed and China National Knowledge Infrastructure (CNKI) databases. A total of 5952 references and 99 patents were obtained. Among these, 5039 articles and reviews, as well as 54 patents were analyzed by Citespace and VOSviewer software. RESULTS: The available evidence indicates that the SMZJG's components likely exert their mechanisms in treating TS by regulating the dopaminergic pathway system, neurotransmitter imbalances, reducing neuroinflammation, promoting the repair of nerve damage and improving sleep disorders. CONCLUSION: This comprehensive analysis lays the foundation for an extensive exploration of the feasibility and clinical applications of SMZJG in TS treatment.

Tumor-associated macrophage subtypes on cancer immunity along with prognostic analysis and SPP1-mediated interactions between tumor cells and macrophages.

Tumor-associated macrophages (TAM) subtypes have been shown to impact cancer prognosis and resistance to immunotherapy. However, there is still a lack of systematic investigation into their molecular characteristics and clinical relevance in different cancer types. Single-cell RNA sequencing data from three different tumor types were used to cluster and type macrophages. Functional analysis and communication of TAM subpopulations were performed by Gene Ontology-Biological Process and CellChat respectively. Differential expression of characteristic genes in subpopulations was calculated using zscore as well as edgeR and Wilcoxon rank sum tests, and subsequently gene enrichment analysis of characteristic genes and anti-PD-1 resistance was performed by the REACTOME database. We revealed the heterogeneity of TAM, and identified eleven subtypes and their impact on prognosis. These subtypes expressed different molecular functions respectively, such as being involved in T cell activation, apoptosis and differentiation, or regulating viral bioprocesses or responses to viruses. The SPP1 pathway was identified as a critical mediator of communication between TAM subpopulations, as well as between TAM and epithelial cells. Macrophages with high expression of SPP1 resulted in poorer survival. By in vitro study, we showed SPP1 mediated the interactions between TAM clusters and between TAM and tumor cells. SPP1 promoted the tumor-promoting ability of TAM, and increased PDL1 expression and stemness of tumor cells. Inhibition of SPP1 attenuated N-cadherin and ß-catenin expression and the activation of AKT and STAT3 pathway in tumor cells. Additionally, we found that several subpopulations could decrease the sensitivity of anti-PD-1 therapy in melanoma. SPP1 signal was a critical pathway of communication between macrophage subtypes. Some specific macrophage subtypes were associated with immunotherapy resistance and prognosis in some cancer types.

Photobiomodulation therapy moderates cancer cachexia-associated muscle wasting through activating PI3K/AKT/FoxO3a pathway.

Cancer cachexia-associated muscle wasting as a multifactorial wasting syndrome, is an important factor affecting the long-term survival rate of tumor patients. Photobiomodulation therapy (PBMT) has emerged as a promising tool to cure and prevent many diseases. However, the effect of PBMT on skeletal muscle atrophy during cancer progression has not been fully demonstrated yet. Here, we found PBMT alleviated the atrophy of myotube diameter induced by cancer cells in vitro, and prevented cancer-associated muscle atrophy in mice bearing tumor. Mechanistically, the alleviation of muscle wasting by PBMT was found to be involved in inhibiting E3 ubiquitin ligases MAFbx and MuRF-1. In addition, transcriptomic analysis using RNA-seq and GSEA revealed that PI3K/AKT pathway might be involved in PBMT-prevented muscle cachexia. Next, we showed the protective effect of PBMT against muscle cachexia was totally blocked by AKT inhibitor in vitro and in vivo. Moreover, PBMT-activated AKT promoted FoxO3a phosphorylation and thus inhibiting the nucleus entry of FoxO3a. Lastly, in cisplatin-treated muscle cachexia model, PBMT had also been shown to ameliorate muscle atrophy through enhancing PI3K/AKT pathway to suppress MAFbx and MuRF-1 expression. These novel findings revealed that PBMT could be a promising therapeutic approach in treating muscle cachexia induced by cancer.

Trimethylamine N-oxide impairs ß-cell function and glucose tolerance.

ß-Cell dysfunction and ß-cell loss are hallmarks of type 2 diabetes (T2D). Here, we found that trimethylamine N-oxide (TMAO) at a similar concentration to that found in diabetes could directly decrease glucose-stimulated insulin secretion (GSIS) in MIN6 cells and primary islets from mice or humans. Elevation of TMAO levels impairs GSIS, ß-cell proportion, and glucose tolerance in male C57BL/6 J mice. TMAO inhibits calcium transients through NLRP3 inflammasome-related cytokines and induced Serca2 loss, and a Serca2 agonist reversed the effect of TMAO on ß-cell function in vitro and in vivo. Additionally, long-term TMAO exposure promotes ß-cell ER stress, dedifferentiation, and apoptosis and inhibits ß-cell transcriptional identity. Inhibition of TMAO production improves ß-cell GSIS, ß-cell proportion, and glucose tolerance in both male db/db and choline diet-fed mice. These observations identify a role for TMAO in ß-cell dysfunction and maintenance, and inhibition of TMAO could be an approach for the treatment of T2D.

Pulmonary administration of tetrandrine loaded Zinc-Alginate nanogels attenuates pulmonary fibrosis in rats.

Pulmonary fibrosis is a chronic and progressive disease, current systemic administration is not fully effective with many side effects, such as gastrointestinal and liver injury. The pulmonary delivery system for pulmonary fibrosis may contribute to maximize therapeutic benefit. Natural compounds might have prominence as potential drug candidates, but the low bioavailabilities affect their clinical use. Tetrandrine is a natural alkaloid with good anti-inflammatory, antifibrogenetic and antioxidant effects, and it is used as a clinical therapeutic drug for the treatment of silicosis in China. In the present study, we explore a new strategy of pulmonary delivery system to improve low solubility and pesticide effect of tetrandrine. Tetrandrine was loaded into alginate nanogels by reverse microemulsion method. The release behavior of tetrandrine reached zero-order kinetics release and the maximum free radical clearance rates reached up to 90%. The pulmonary fibrosis rats were treated with tetrandrine nanogels by using ultrasonic atomizing inhalation. Tetrandrine nanogels decreased the development and progression of fibrosis by reducing inflammation response and bating the deposition of extra cellular matrix. In conclusion, ultrasonic atomizing inhalation of tetrandrine nanogels provided a new therapeutic strategy for pulmonary fibrosis.

Differences in intestinal motility during different sleep stages based on long-term bowel sounds.

BACKGROUND AND OBJECTIVES: This study focused on changes in intestinal motility during different sleep stages based on long-term bowel sounds. METHODS: A modified higher order statistics algorithm was devised to identify the effective bowel sound segments. Next, characteristic values (CVs) were extracted from each bowel sound segment, which included 4 time-domain, 4 frequency-domain and 2 nonlinear CVs. The statistical analysis of these CVs corresponding to the different sleep stages could be used to evaluate the changes in intestinal motility during sleep. RESULTS: A total of 6865.81 min of data were recorded from 14 participants, including both polysomnographic data and bowel sound data which were recorded simultaneously from each participant. The average accuracy, sensitivity and specificity of the modified higher order statistics detector were 96.46 ± 2.60%, 97.24 ± 2.99% and 94.13 ± 4.37%. In addition, 217088 segments of effective bowel sound corresponding to different sleep stages were identified using the modified detector. Most of the CVs were statistically different during different sleep stages ([Formula: see text]). Furthermore, the bowel sounds were low in frequency based on frequency-domain CVs, high in energy based on time-domain CVs and low in complexity base on nonlinear CVs during deep sleep, which was consistent with the state of the EEG signals during deep sleep. CONCLUSIONS: The intestinal motility varies by different sleep stages based on long-term bowel sounds using the modified higher order statistics detector. The study indicates that the long-term bowel sounds can well reflect intestinal motility during sleep. This study also demonstrates that it is technically feasible to simultaneously record intestinal motility and sleep state throughout the night. This offers great potential for future studies investigating intestinal motility during sleep and related clinical applications.

Enhanced antidepressant effects of BDNF-quercetin alginate nanogels for depression therapy.

BACKGROUND: Brain-derived neurotrophic factor (BDNF) with neuronic development and function is a promising therapeutic agent for treating depressive disorder, according to the neurotrophin hypothesis. However, the delivery of BDNF into the brain is not easy as these large protein molecules cannot efficiently cross the blood-brain barrier (BBB) and easily suffer oxidative damage in vivo. Therefore, the quercetin-based alginate nanogels (quercetin nanogels) loaded with BDNF have been developed, which could efficiently bypass the BBB via the nose-to-brain pathway and protect BDNF from oxidative damage, providing an effective route for the therapy of depressive disorders by intranasal delivery. RESULTS: Quercetin nanogels exhibited uniform size distribution, excellent biocompatibility, and potent antioxidant and anti-inflammatory activities. Quercetin nanogels in the thermosensitive gel achieved sustained and controlled release of BDNF with non-Fick's diffusion, exhibited rapid brain distribution, and achieved nearly 50-fold enhanced bioavailability compared to oral quercetin. Quercetin nanogels as a therapeutic drug delivery carrier exerted antidepressant effects on reserpine-induced rats, effectively delivered BDNF to reverse despair behavior in stress-induced mice, and exhibited antidepressant effects on chronic mild unpredictable stimulation (CUMS) rats. These antidepressant effects of BDNF-Quercetin nanogels for CUMS rats are associated with the regulation of the glutamatergic system, PI3K-Akt, and BDNF-TrkB signaling pathway. CONCLUSIONS: In this study, we provide a promising strategy for brain delivery of BDNF for treating depressive disorders, effectively achieved through combining quercetin nanogels and intranasal administration.

Identification of five novel variants of ADAR1 in dyschromatosis symmetrica hereditaria by next-generation sequencing.

Background: Dyschromatosis symmetrica hereditaria (DSH) is a rare autosomal dominant inherited pigmentary dermatosis characterized by a mixture of hyperpigmented and hypopigmented freckles on the dorsal aspect of the distal extremities. To date, pathogenic mutations causing DSH have been identified in the adenosine deaminase acting on RNA1 gene (ADAR1), which is mapped to chromosome 1q21. Objective: The present study aimed to investigate the underlying pathological mechanism in 14 patients with DSH from five unrelated Chinese families. Next-generation sequencing (NGS) and direct sequencing were performed on a proband with DSH to identify causative mutations. All coding, adjacent intronic, and 5'- and 3'-untranslated regions of ADAR1 were screened, and variants were identified. Result: These mutations consisted of three missense mutations (NM_001025107: c.716G>A, NM_001111.5: c.3384G>C, and NM_001111.5: c.3385T>G), one nonsense mutation (NM_001111.5:c.511G>T), and one splice-site mutation (NM_001111.5: c.2080-1G>T) located in exon 2, exon 14, and the adjacent intronic region according to recommended Human Genome Variation Society (HGVS) nomenclature. Moreover, using polymerase chain reaction and Sanger sequencing, we identified five novel ADAR1 variants, which can be predicted to be pathogenic by in silico genome sequence analysis. Among the mutations, the missense mutations had no significant effect on the spatial structure of the protein, while the stop codon introduced by the nonsense mutation truncated the protein. Conclusion: Our results highlighted that the advent of NGS has facilitated high-throughput screening for the identification of disease-causing mutations with high accuracy, stability, and specificity. Five novel genetic mutations were found in five unrelated families, thereby extending the pathogenic mutational spectrum of ADAR1 in DSH and providing new insights into this complex genetic disorder.

Assessing the predictability of the H3K27M status in diffuse glioma patients using frequency importance analysis on chemical exchange saturation transfer MRI.

BACKGROUND AND OBJECTIVES: In diffuse glioma patients, Lys-27-Met mutations in histone 3 genes (H3K27M) are associated with an aggravated prognosis and further decreased overall survival. By using frequency importance analysis on chemical exchange saturation transfer (CEST) MRI, this study aimed to assess the predictability of the H3K27M status in diffuse glioma patients. METHODS: Twenty-two patients diagnosed with diffuse glioma, with a known H3K27M status, were included in the present study. All patients underwent CEST MRI scans. The previously proposed frequency importance analysis was performed to determine the relative contribution of the amide and aliphatic protons for the differentiation between normal tissues and tumors. For this comparison, the conventional MTRasym analysis of amide protons at 3.5 ppm, i.e., the amide proton transfer-weighted (APTw) signal, was employed. Statistical analysis was performed using the Mann-Whitney U test, and the receiver operating characteristic (ROC) and area under the curve (AUC) analyses. RESULTS: The mean and 90th percentile of the ΔAPTw intensities, amide and aliphatic frequency importance values revealed statistically significant differences between the wildtype and the H3K27M-altered patient groups (p < 0.05). For the prediction of the H3K27M status, amide frequency importance achieved highest AUCs of 0.97, with a specificity of 0.93. In contrast, the ΔAPTw intensities and aliphatic frequency importance showed relatively lower AUCs (<0.35) in predicting the H3K27M status. CONCLUSIONS: Amide frequency importance exhibited satisfactory performance in the prediction of the H3K27M status. As such, it may be considered as a non-invasive MRI biomarker for the diagnosis of diffuse gliomas.

The suppression of cervical cancer ferroptosis by macrophages: The attenuation of ALOX15 in cancer cells by macrophages-derived exosomes.

Induction of cancer cell ferroptosis has been proposed as a potential treatment in several cancer types. Tumor-associated macrophages (TAMs) play a key role in promoting tumor malignant progression and therapy resistance. However, the roles and mechanisms of TAMs in regulating tumor ferroptosis is still unexplored and remains enigmatic. This study shows ferroptosis inducers has shown therapeutic outcomes in cervical cancer in vitro and in vivo. TAMs have been found to suppress cervical cancer cells ferroptosis. Mechanistically, macrophage-derived miRNA-660-5p packaged into exosomes are transported into cancer cells. In cancer cells, miRNA-660-5p attenuates ALOX15 expression to inhibit ferroptosis. Moreover, the upregulation of miRNA-660-5p in macrophages depends on autocrine IL4/IL13-activated STAT6 pathway. Importantly, in clinical cervical cancer cases, ALOX15 is negatively associated with macrophages infiltration, which also raises the possibility that macrophages reduce ALOX15 levels in cervical cancer. Moreover, both univariate and multivariate Cox analyses show ALOX15 expression is independent prognostic factor and positively associated with good prognosis in cervical cancer. Altogether, this study reveals the potential utility of targeting TAMs in ferroptosis-based treatment and ALOX15 as prognosis indicators for cervical cancer.

Leucyl and Cystinyl Aminopeptidase as a Prognostic-Related Biomarker in OV Correlating with Immune Infiltrates.

Background: It was indicated that tumor intrinsic heterogeneity and the tumor microenvironment (TME) of ovarian cancer (OV) influence immunotherapy efficacy and patient outcomes. Leucyl and cystinyl aminopeptidase (LNPEP) encodes a zinc-dependent aminopeptidase, which has been proved to participant in the vesicle-mediated transport and class I MHC mediated antigen processing and presentation. However, the function of LNPEP in TME of OV and its potential molecular mechanisms have not been determined. Therefore, we aimed to investigate a prognostic biomarker which may be helpful in identifying TME heterogeneity of ovarian cancer. Methods: In this study, bioinformatics databases were used to explore the expression profile and immune infiltration of LNPEP. Bioinformatics analyses of survival data and interactors of LNPEP were conducted to predict the prognostic value of LNPEP in OV. The protein levels of LNPEP were validated by Western blot and immunohistochemistry. Results: Based on the TCGA data, our data displayed that the mRNA expression of LNPEP was markedly down-regulated in ovarian cancer than that in para-cancer tissues, contrary to the protein level. Importantly, high LNPEP expression was associated with poor prognosis in patients with OV. Furthermore, Cox regression analysis showed that LNPEP was an independent prognostic factor in OV. GO and KEGG pathway analyses indicated the co-expressed genes of LNPEP were mainly related to a variety of immune-related pathways, including Th1 and Th2 cell differentiation, Th17 cell differentiation, and immunoregulatory interaction. Our data also demonstrated that the expression of LNPEP was strongly correlated with immune infiltration levels, immunomodulators, chemokines and chemokine receptors. Conclusion: In our study, we identified and established a prognostic signature of immune-related LNPEP in OV, which will be of great value in predicting the prognosis of clinical trials and may become a new therapeutic target for immunological research and potential prognostic biomarker in OV.