Orphan Nuclear Receptor ERRα Controls Macrophage Metabolic Signaling and A20 Expression to Negatively Regulate TLR-Induced Inflammation.

The orphan nuclear receptor estrogen-related receptor α (ERRα; NR3B1) is a key metabolic regulator, but its function in regulating inflammation remains largely unknown. Here, we demonstrate that ERRα negatively regulates Toll-like receptor (TLR)-induced inflammation by promoting Tnfaip3 transcription and fine-tuning of metabolic reprogramming in macrophages. ERRα-deficient (Esrra(-/-)) mice showed increased susceptibility to endotoxin-induced septic shock, leading to more severe pro-inflammatory responses than control mice. ERRα regulated macrophage inflammatory responses by directly binding the promoter region of Tnfaip3, a deubiquitinating enzyme in TLR signaling. In addition, Esrra(-/-) macrophages showed an increased glycolysis, but impaired mitochondrial respiratory function and biogenesis. Further, ERRα was required for the regulation of NF-κB signaling by controlling p65 acetylation via maintenance of NAD(+) levels and sirtuin 1 activation. These findings unravel a previously unappreciated role for ERRα as a negative regulator of TLR-induced inflammatory responses through inducing Tnfaip3 transcription and controlling the metabolic reprogramming.

Enzymatic extraction of anthocyanins from the pomace of aronia (Aronia melanocarpa).

Efficient extraction of natural pigments is a key focus in enhancing the utilization of by-products for applications in the food industry. In this study, an enzymatic extraction method using Pectinex Ultra SP-L, Pectinex XXL, Novoshape, and Celluclast was used to investigate natural pigment production from the pomace of aronia, a commercially important plant. The method's performance was monitored using high-performance liquid chromatography with diode-array detection by measuring total and individual anthocyanin levels. Pectinex XXL (0.5%) yielded the highest total anthocyanin extraction (2082.41 ± 85.69 mg/100 g) in the single enzyme treatment, followed by Pectinex Ultra SP-L (0.05%), Celluclast (0.01%), and Novoshape (0.1%). Combining Pectinex XXL (0.25%) with Celluclast (0.01%) increased the extraction ratio of total anthocyanins (2 323.04 ± 61.32 mg/100 g) by ∼50.7% compared with that obtained using the solvent extraction method. This study demonstrated an effective enzymatic extraction method for application in the food industry.

MMP-9 facilitates selective proteolysis of the histone H3 tail at genes necessary for proficient osteoclastogenesis.

Although limited proteolysis of the histone H3 N-terminal tail (H3NT) is frequently observed during mammalian differentiation, the specific genomic sites targeted for H3NT proteolysis and the functional significance of H3NT cleavage remain largely unknown. Here we report the first method to identify and examine H3NT-cleaved regions in mammals, called chromatin immunoprecipitation (ChIP) of acetylated chromatin (ChIPac). By applying ChIPac combined with deep sequencing (ChIPac-seq) to an established cell model of osteoclast differentiation, we discovered that H3NT proteolysis is selectively targeted near transcription start sites of a small group of genes and that most H3NT-cleaved genes displayed significant expression changes during osteoclastogenesis. We also discovered that the principal H3NT protease of osteoclastogenesis is matrix metalloproteinase 9 (MMP-9). In contrast to other known H3NT proteases, MMP-9 primarily cleaved H3K18-Q19 in vitro and in cells. Furthermore, our results support CBP/p300-mediated acetylation of H3K18 as a central regulator of MMP-9 H3NT protease activity both in vitro and at H3NT cleavage sites during osteoclastogenesis. Importantly, we found that abrogation of H3NT proteolysis impaired osteoclastogenic gene activation concomitant with defective osteoclast differentiation. Our collective results support the necessity of MMP-9-dependent H3NT proteolysis in regulating gene pathways required for proficient osteoclastogenesis.

The orphan nuclear receptor SHP acts as a negative regulator in inflammatory signaling triggered by Toll-like receptors.

The orphan nuclear receptor SHP (small heterodimer partner) is a transcriptional corepressor that regulates hepatic metabolic pathways. Here we identified a role for SHP as an intrinsic negative regulator of Toll-like receptor (TLR)-triggered inflammatory responses. SHP-deficient mice were more susceptible to endotoxin-induced sepsis. SHP had dual regulatory functions in a canonical transcription factor NF-κB signaling pathway, acting as both a repressor of transactivation of the NF-κB subunit p65 and an inhibitor of polyubiquitination of the adaptor TRAF6. SHP-mediated inhibition of signaling via the TLR was mimicked by macrophage-stimulating protein (MSP), a strong inducer of SHP expression, via an AMP-activated protein kinase-dependent signaling pathway. Our data identify a previously unrecognized role for SHP in the regulation of TLR signaling.

Diagnosis of Crohn's disease and ulcerative colitis using the microbiome.

BACKGROUND: Inflammatory bowel disease (IBD) is a multifactorial chronic inflammatory disease resulting from dysregulation of the mucosal immune response and gut microbiota. Crohn's disease (CD) and ulcerative colitis (UC) are difficult to distinguish, and differential diagnosis is essential for establishing a long-term treatment plan for patients. Furthermore, the abundance of mucosal bacteria is associated with the severity of the disease. This study aimed to differentiate and diagnose these two diseases using the microbiome and identify specific biomarkers associated with disease activity. RESULTS: Differences in the abundance and composition of the microbiome between IBD patients and healthy controls (HC) were observed. Compared to HC, the diversity of the gut microbiome in patients with IBD decreased; the diversity of the gut microbiome in patients with CD was significantly lower. Sixty-eight microbiota members (28 for CD and 40 for UC) associated with these diseases were identified. Additionally, as the disease progressed through different stages, the diversity of the bacteria decreased. The abundances of Alistipes shahii and Pseudodesulfovibrio aespoeensis were negatively correlated with the severity of CD, whereas the abundance of Polynucleobacter wianus was positively correlated. The severity of UC was negatively correlated with the abundance of A. shahii, Porphyromonas asaccharolytica and Akkermansia muciniphilla, while it was positively correlated with the abundance of Pantoea candidatus pantoea carbekii. A regularized logistic regression model was used for the differential diagnosis of the two diseases. The area under the curve (AUC) was used to examine the performance of the model. The model discriminated UC and CD at an AUC of 0.873 (train set), 0.778 (test set), and 0.633 (validation set) and an area under the precision-recall curve (PRAUC) of 0.888 (train set), 0.806 (test set), and 0.474 (validation set). CONCLUSIONS: Based on fecal whole-metagenome shotgun (WMS) sequencing, CD and UC were diagnosed using a machine-learning predictive model. Microbiome biomarkers associated with disease activity (UC and CD) are also proposed.

Multi-task deep learning-based radiomic nomogram for prognostic prediction in locoregionally advanced nasopharyngeal carcinoma.

PURPOSE: Prognostic prediction is crucial to guide individual treatment for locoregionally advanced nasopharyngeal carcinoma (LA-NPC) patients. Recently, multi-task deep learning was explored for joint prognostic prediction and tumor segmentation in various cancers, resulting in promising performance. This study aims to evaluate the clinical value of multi-task deep learning for prognostic prediction in LA-NPC patients. METHODS: A total of 886 LA-NPC patients acquired from two medical centers were enrolled including clinical data, [18F]FDG PET/CT images, and follow-up of progression-free survival (PFS). We adopted a deep multi-task survival model (DeepMTS) to jointly perform prognostic prediction (DeepMTS-Score) and tumor segmentation from FDG-PET/CT images. The DeepMTS-derived segmentation masks were leveraged to extract handcrafted radiomics features, which were also used for prognostic prediction (AutoRadio-Score). Finally, we developed a multi-task deep learning-based radiomic (MTDLR) nomogram by integrating DeepMTS-Score, AutoRadio-Score, and clinical data. Harrell's concordance indices (C-index) and time-independent receiver operating characteristic (ROC) analysis were used to evaluate the discriminative ability of the proposed MTDLR nomogram. For patient stratification, the PFS rates of high- and low-risk patients were calculated using Kaplan-Meier method and compared with the observed PFS probability. RESULTS: Our MTDLR nomogram achieved C-index of 0.818 (95% confidence interval (CI): 0.785-0.851), 0.752 (95% CI: 0.638-0.865), and 0.717 (95% CI: 0.641-0.793) and area under curve (AUC) of 0.859 (95% CI: 0.822-0.895), 0.769 (95% CI: 0.642-0.896), and 0.730 (95% CI: 0.634-0.826) in the training, internal validation, and external validation cohorts, which showed a statistically significant improvement over conventional radiomic nomograms. Our nomogram also divided patients into significantly different high- and low-risk groups. CONCLUSION: Our study demonstrated that MTDLR nomogram can perform reliable and accurate prognostic prediction in LA-NPC patients, and also enabled better patient stratification, which could facilitate personalized treatment planning.

CT-based Radiogenomics Framework for COVID-19 Using ACE2 Imaging Representations.

Coronavirus disease 2019 (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus 2 which enters the body via the angiotensin-converting enzyme 2 (ACE2) and altering its gene expression. Altered ACE2 plays a crucial role in the pathogenesis of COVID-19. Gene expression profiling, however, is invasive and costly, and is not routinely performed. In contrast, medical imaging such as computed tomography (CT) captures imaging features that depict abnormalities, and it is widely available. Computerized quantification of image features has enabled 'radiogenomics', a research discipline that identifies image features that are associated with molecular characteristics. Radiogenomics between ACE2 and COVID-19 has yet to be done primarily due to the lack of ACE2 expression data among COVID-19 patients. Similar to COVID-19, patients with lung adenocarcinoma (LUAD) exhibit altered ACE2 expression and, LUAD data are abundant. We present a radiogenomics framework to derive image features (ACE2-RGF) associated with ACE2 expression data from LUAD. The ACE2-RGF was then used as a surrogate biomarker for ACE2 expression. We adopted conventional feature selection techniques including ElasticNet and LASSO. Our results show that: i) the ACE2-RGF encoded a distinct collection of image features when compared to conventional techniques, ii) the ACE2-RGF can classify COVID-19 from normal subjects with a comparable performance to conventional feature selection techniques with an AUC of 0.92, iii) ACE2-RGF can effectively identify patients with critical illness with an AUC of 0.85. These findings provide unique insights for automated COVID-19 analysis and future research.

GDF15 Promotes Cell Growth, Migration, and Invasion in Gastric Cancer by Inducing STAT3 Activation.

Growth differentiation factor 15 (GDF15) has been reported to play an important role in cancer and is secreted and involved in the progression of various cancers, including ovarian cancer, prostate cancer, and thyroid cancer. Nevertheless, the functional mechanism of GDF15 in gastric cancer is still unclear. Immunohistochemical staining was performed to estimate the expression of GDF15 in 178 gastric cancer tissues. The biological role and action mechanism of GDF15 were investigated by examining the effect of GDF15 knockdown in AGS and SNU216 gastric cancer cells. Here, we report that the high expression of GDF15 was associated with invasion depth (p = 0.002), nodal involvement (p = 0.003), stage III/IV (p = 0.01), lymphatic invasion (p = 0.05), and tumor size (p = 0.049), which are related to poor survival in gastric cancer patients. GDF15 knockdown induced G0/G1 cell cycle arrest and remarkably inhibited cell proliferation and reduced cell motility, migration, and invasion compared to the control. GDF15 knockdown inhibited the epithelial-mesenchymal transition by regulating the STAT3 phosphorylation signaling pathways. Taken together, our results indicate that GDF15 expression is associated with aggressive gastric cancer by promoting STAT3 phosphorylation, suggesting that the GDF15-STAT3 signaling axis is a potential therapeutic target against gastric cancer progression.

Benchmarking for biomedical natural language processing tasks with a domain specific ALBERT.

BACKGROUND: The abundance of biomedical text data coupled with advances in natural language processing (NLP) is resulting in novel biomedical NLP (BioNLP) applications. These NLP applications, or tasks, are reliant on the availability of domain-specific language models (LMs) that are trained on a massive amount of data. Most of the existing domain-specific LMs adopted bidirectional encoder representations from transformers (BERT) architecture which has limitations, and their generalizability is unproven as there is an absence of baseline results among common BioNLP tasks. RESULTS: We present 8 variants of BioALBERT, a domain-specific adaptation of a lite bidirectional encoder representations from transformers (ALBERT), trained on biomedical (PubMed and PubMed Central) and clinical (MIMIC-III) corpora and fine-tuned for 6 different tasks across 20 benchmark datasets. Experiments show that a large variant of BioALBERT trained on PubMed outperforms the state-of-the-art on named-entity recognition (+ 11.09% BLURB score improvement), relation extraction (+ 0.80% BLURB score), sentence similarity (+ 1.05% BLURB score), document classification (+ 0.62% F1-score), and question answering (+ 2.83% BLURB score). It represents a new state-of-the-art in 5 out of 6 benchmark BioNLP tasks. CONCLUSIONS: The large variant of BioALBERT trained on PubMed achieved a higher BLURB score than previous state-of-the-art models on 5 of the 6 benchmark BioNLP tasks. Depending on the task, 5 different variants of BioALBERT outperformed previous state-of-the-art models on 17 of the 20 benchmark datasets, showing that our model is robust and generalizable in the common BioNLP tasks. We have made BioALBERT freely available which will help the BioNLP community avoid computational cost of training and establish a new set of baselines for future efforts across a broad range of BioNLP tasks.

Clinical applications of machine learning in predicting 3D shapes of the human body: a systematic review.

BACKGROUND: Predicting morphological changes to anatomical structures from 3D shapes such as blood vessels or appearance of the face is a growing interest to clinicians. Machine learning (ML) has had great success driving predictions in 2D, however, methods suitable for 3D shapes are unclear and the use cases unknown. OBJECTIVE AND METHODS: This systematic review aims to identify the clinical implementation of 3D shape prediction and ML workflows. Ovid-MEDLINE, Embase, Scopus and Web of Science were searched until 28th March 2022. RESULTS: 13,754 articles were identified, with 12 studies meeting final inclusion criteria. These studies involved prediction of the face, head, aorta, forearm, and breast, with most aiming to visualize shape changes after surgical interventions. ML algorithms identified were regressions (67%), artificial neural networks (25%), and principal component analysis (8%). Meta-analysis was not feasible due to the heterogeneity of the outcomes. CONCLUSION: 3D shape prediction is a nascent but growing area of research in medicine. This review revealed the feasibility of predicting 3D shapes using ML clinically, which could play an important role for clinician-patient visualization and communication. However, all studies were early phase and there were inconsistent language and reporting. Future work could develop guidelines for publication and promote open sharing of source code.

Enhancing medical image registration via appearance adjustment networks.

Deformable image registration is fundamental for many medical image analyses. A key obstacle for accurate image registration lies in image appearance variations such as the variations in texture, intensities, and noise. These variations are readily apparent in medical images, especially in brain images where registration is frequently used. Recently, deep learning-based registration methods (DLRs), using deep neural networks, have shown computational efficiency that is several orders of magnitude faster than traditional optimization-based registration methods (ORs). DLRs rely on a globally optimized network that is trained with a set of training samples to achieve faster registration. DLRs tend, however, to disregard the target-pair-specific optimization inherent in ORs and thus have degraded adaptability to variations in testing samples. This limitation is severe for registering medical images with large appearance variations, especially since few existing DLRs explicitly take into account appearance variations. In this study, we propose an Appearance Adjustment Network (AAN) to enhance the adaptability of DLRs to appearance variations. Our AAN, when integrated into a DLR, provides appearance transformations to reduce the appearance variations during registration. In addition, we propose an anatomy-constrained loss function through which our AAN generates anatomy-preserving transformations. Our AAN has been purposely designed to be readily inserted into a wide range of DLRs and can be trained cooperatively in an unsupervised and end-to-end manner. We evaluated our AAN with three state-of-the-art DLRs - Voxelmorph (VM), Diffeomorphic Voxelmorph (DifVM), and Laplacian Pyramid Image Registration Network (LapIRN) - on three well-established public datasets of 3D brain magnetic resonance imaging (MRI) - IBSR18, Mindboggle101, and LPBA40. The results show that our AAN consistently improved existing DLRs and outperformed state-of-the-art ORs on registration accuracy, while adding a fractional computational load to existing DLRs.

VprBP has intrinsic kinase activity targeting histone H2A and represses gene transcription.

Histone modifications play important roles in the regulation of gene expression and chromatin organization. VprBP has been implicated in transcriptionally silent chromatin formation and cell-cycle regulation, but the molecular basis underlying such effects remains unclear. Here we report that VprBP possesses an intrinsic protein kinase activity and is capable of phosphorylating histone H2A on threonine 120 (H2AT120p) in a nucleosomal context. VprBP is localized to a large set of tumor suppressor genes and blocks their transcription, in a manner that is dependent on its kinase activity toward H2AT120. The functional significance of VprBP-mediated H2AT120p is further underscored by the fact that RNAi knockdown and small-molecule inhibition of VprBP reactivate growth regulatory genes and impede tumor growth. Our findings establish VprBP as a major kinase responsible for H2AT120p in cancer cells and suggest that VprBP inhibition could be a new strategy for the development of anticancer therapeutics.

Supporting patients to be involved in decisions about their health and care: Development of a best practice health literacy App for Australian adults living with Chronic Kidney Disease.

ISSUE ADDRESSED: Inadequate health literacy is common in those with chronic kidney disease (CKD), especially among culturally and linguistically diverse groups. Patient information for people with CKD, including those with kidney failure requiring dialysis, is often written beyond their literacy level, and many CKD-related apps are not accurate or evidence based. These represent important barriers to health care decision-making and equity in access to health care. METHODS: We developed a cross-platform application (the "SUCCESS app") to support Australian adults with kidney failure requiring dialysis to actively participate in self-management and decision-making. App content was informed by health literacy theory which recognises the importance of reducing the complexity of health information as well as equipping consumers with the skills necessary to access, understand and act on this information. The development team comprised members of diverse backgrounds and expertise, including nursing, allied health, psychology, epidemiology, nephrology and IT, as well as consumer representatives. RESULTS: Content areas included diet, fluids, medicine, physical activity, emotional well-being and supportive care, chosen as they represent important decision points in the CKD trajectory. To support functional health literacy, a four-step process to simplify written content was used including calculating readability statistics, applying the Patient Education Materials Assessment Tool, supplementing written information with video and audio content, and incorporating micro-learning and interactive quizzes. To develop communicative and critical health literacy skills, question prompt lists and evidence-based volitional help sheets were included in each module to support question-asking and behaviour change. We also developed animated skills training related to communication, shared decision-making and critical appraisal of health information. CONCLUSIONS: This is the first health literacy informed app developed to promote active patient participation in CKD management and decision-making. Ongoing evaluation of the SUCCESS app through analysis of quantitative and qualitative data will provide valuable insights into the feasibility of implementing the app with dialysis patients, and the impact of the intervention of psychosocial and clinical outcomes. SO WHAT?: Digital health solutions have been found to improve self-management for chronic conditions, and could optimise the use of health care services and patient outcomes.

Role of remodeling and spacing factor 1 in histone H2A ubiquitination-mediated gene silencing.

Posttranslational histone modifications play important roles in regulating chromatin-based nuclear processes. Histone H2AK119 ubiquitination (H2Aub) is a prevalent modification and has been primarily linked to gene silencing. However, the underlying mechanism remains largely obscure. Here we report the identification of RSF1 (remodeling and spacing factor 1), a subunit of the RSF complex, as a H2Aub binding protein, which mediates the gene-silencing function of this histone modification. RSF1 associates specifically with H2Aub, but not H2Bub nucleosomes, through a previously uncharacterized and obligatory region designated as ubiquitinated H2A binding domain. In human and mouse cells, genes regulated by RSF1 overlap significantly with those controlled by RNF2/Ring1B, the subunit of Polycomb repressive complex 1 (PRC1) which catalyzes the ubiquitination of H2AK119. About 82% of H2Aub-enriched genes, including the classic PRC1 target Hox genes, are bound by RSF1 around their transcription start sites. Depletion of H2Aub levels by Ring1B knockout results in a significant reduction of RSF1 binding. In contrast, RSF1 knockout does not affect RNF2/Ring1B or H2Aub levels but leads to derepression of H2Aub target genes, accompanied by changes in H2Aub chromatin organization and release of linker histone H1. The action of RSF1 in H2Aub-mediated gene silencing is further demonstrated by chromatin-based in vitro transcription. Finally, RSF1 and Ring1 act cooperatively to regulate mesodermal cell specification and gastrulation during Xenopus early embryonic development. Taken together, these data identify RSF1 as a H2Aub reader that contributes to H2Aub-mediated gene silencing by maintaining a stable nucleosome pattern at promoter regions.

Telehealth for Noncritical Patients With Chronic Diseases During the COVID-19 Pandemic.

During the recent coronavirus disease (COVID-19) pandemic, telehealth has received greater attention due to its role in reducing hospital visits from patients with COVID-19 or other conditions, while supporting home isolation in patients with mild symptoms. The needs of patients with chronic diseases tend to be overlooked during the pandemic. With reduced opportunities for routine clinic visits, these patients are adopting various telehealth services such as video consultation and remote monitoring. We advocate for more innovative designs to be considered to enhance patients' feelings of "copresence"-a sense of connection with another interactant via digital technology-with their health care providers during this time. The copresence-enhanced design has been shown to reduce patients' anxiety and increase their confidence in managing their chronic disease condition. It has the potential to reduce the patient's need to reach out to their health care provider during a time when health care resources are being stretched.

Therapeutic Potential of Gamma-Irradiated Resveratrol in Ulcerative Colitis via the Anti-Inflammatory Activity and Differentiation of Tolerogenic Dendritic Cells.

BACKGROUND/AIMS: New therapeutic strategies and the development of treatments against inflammatory bowel disease (IBD) require the initiation of immune tolerance and inhibition of excessive inflammation. Resveratrol, a polyphenolic compound, is a powerful immunosuppressor, but it can lead to apoptotic death of normal cells at high concentrations. When we induced a structural modification of resveratrol by gamma irradiation, we were able to investigate the potential tolerogenic and anti-inflammatory effect of a new radiolysis product (named γ-Res) during dendritic cell (DC) activation/differentiation. METHODS: The potential tolerogenic and anti-inflammatory effect of γ-Res were investigated by cytokine secretion, surface molecule expression, antigen uptake ability, antigen presenting ability, signaling pathway, and mixed lymphocyte reaction (MLR) assay using enzyme-linked immunosorbent assay (ELISA), western blot and flow cytometry. RESULTS: LPS-activated DCs treated with γ-Res exhibited alterations in their mature and functional statuses including a strongly inhibited cytokine production, surface molecule expression, antigen-presenting ability, and activated DC-induced T cell proliferation/activation. In addition, the DCs generated by the γ-Res treatment during DC differentiation induced a decreased surface molecule expression and increased IL-10 production without altering the levels of TNF-α and IL-12p70, thereby promoting the inhibition of T cell proliferation/activation and the induction of regulatory T cells via interaction with DCs in vitro. Furthermore, in the in vivo DSS-induced colitis model, γ-Res treatment conferred protective immunity with a decrease in IFN-γ+CD4+ and IL-17A+CD4+ T cells and imparted protection by reducing the disease activity and histological disease score and increasing the survival rate in dextran sulfate sodium (DSS)-induced colitis in mice. CONCLUSION: Thus, our results suggest that γ-Res may be an excellent candidate for use in IBD treatment.

Clinical significance of atypical protein kinase C (PKCι and PKCζ) and its relationship with yes-associated protein in lung adenocarcinoma.

BACKGROUND: Protein kinase C iota (PKCι) and protein kinase C zeta (PKCζ) are two atypical protein kinase (aPKC) enzymes that contribute to cell proliferation and cancer development. The Hippo/YAP pathway is commonly disrupted and upregulated in cancers. Herein, the expression patterns and clinical relevance of PKCι and PKCζ are evaluated in relation to YAP, a downstream effector of Hippo, in lung adenocarcinoma (LAC). The protein and mRNA expression levels of PKCι, PKCζ, YAP, and their phosphorylated forms, namely p-PKCι, p-PKCζ and p-YAP, are evaluated in relation to clinicopathological factors, including patient survival. METHODS: A total of 200 primary LAC tissue samples were examined by immunohistochemistry for PKCι, p-PKCι, PKCζ, p-PKCζ, YAP, and p-YAP protein expression. Sixty pairs of LAC and non-neoplastic lung tissue samples were assessed for PRKCI, PRKCZ, and YAP mRNA levels. PKCι, p-PKCι, PKCζ, and p-PKCζ protein expression were evaluated by Western blot analysis in the PC9 and PC9/GR LAC cell lines with YAP modulation. RESULTS: LAC demonstrated cytoplasmic PKCι, p-PKCι, PKCζ, and p-PKCζ immunostaining patterns. Positive aPKC protein expressions were related with poor patient survival. Especially, increased p-PKCι protein expression was significantly correlated with higher pathological stage and shortened overall survival. YAP overexpression contributes phosphorylation of PKCι and PKCζ protein expression in the LAC cell line. CONCLUSIONS: PKCι and PKCζ are related to YAP in LAC. PKCι and PKCζ play distinct roles in LAC; specifically, p-PKCι overexpression is suggested to underlie factors that indicate a poor prognosis.

PPAR-α Activation Mediates Innate Host Defense through Induction of TFEB and Lipid Catabolism.

The role of peroxisome proliferator-activated receptor α (PPAR-α) in innate host defense is largely unknown. In this study, we show that PPAR-α is essential for antimycobacterial responses via activation of transcription factor EB (TFEB) transcription and inhibition of lipid body formation. PPAR-α deficiency resulted in an increased bacterial load and exaggerated inflammatory responses during mycobacterial infection. PPAR-α agonists promoted autophagy, lysosomal biogenesis, phagosomal maturation, and antimicrobial defense against Mycobacterium tuberculosis or M. bovis bacillus Calmette-Guérin. PPAR-α agonists regulated multiple genes involved in autophagy and lysosomal biogenesis, including Lamp2, Rab7, and Tfeb in bone marrow-derived macrophages. Silencing of TFEB reduced phagosomal maturation and antimicrobial responses, but increased macrophage inflammatory responses during mycobacterial infection. Moreover, PPAR-α activation promoted lipid catabolism and fatty acid ß-oxidation in macrophages during mycobacterial infection. Taken together, our data indicate that PPAR-α mediates antimicrobial responses to mycobacterial infection by inducing TFEB and lipid catabolism.

Parathyroid carcinoma arising from auto-transplanted parathyroid tissue after Total Parathyroidectomy in chronic kidney disease patient: a case report.

BACKGROUND: Secondary hyperparathyroidism is a common complication in patients with chronic kidney disease that requires vigilant treatment due to its high mortality rate. Pharmacologic therapy is recommended as an initial treatment; if there is no response, a total parathyroidectomy is performed. In some cases, surgery is accompanied by auto-transplantation of parathyroid tissue. CASE PRESENTATION: The patient was diagnosed with chronic kidney disease and received a kidney transplant. However, due to rejection of the transplanted kidney, medical nephrectomy was carried out and routine hemodialysis was initiated and observed. At this time, secondary hyperparathyroidism with elevated parathyroid hormone and hyperphosphatemia developed and pharmacologic treatment was applied. However, there was no response to pharmacologic treatment; therefore, total parathyroidectomy with auto-transplantation was performed. Eight years after surgery, a growing mass was observed in the transplantation site, accompanied by an elevation of parathyroid hormone. A complete resection of the mass was performed, and the patient was diagnosed with parathyroid carcinoma. Additional adjuvant radiation therapy was ordered, and the patient is being monitored. CONCLUSIONS: This is a rare but remarkable case of parathyroid carcinoma arising from auto-transplanted parathyroid tissue after total parathyroidectomy in a patient with secondary hyperparathyroidism. We suggest caution should be taken when choosing to auto- transplant parathyroid tissue and that careful postoperative observation should be performed.

Tetracycline Analogs Inhibit Osteoclast Differentiation by Suppressing MMP-9-Mediated Histone H3 Cleavage.

Osteoporosis is a common disorder of bone remodeling, caused by the imbalance between bone resorption by osteoclasts and bone formation by osteoblasts. Recently, we reported that matrix metalloproteinase-9 (MMP-9)-dependent histone H3 proteolysis is a key event for proficient osteoclast formation. Although it has been reported that several MMP-9 inhibitors, such as tetracycline and its derivatives, show an inhibitory effect on osteoclastogenesis, the molecular mechanisms for this are not fully understood. Here we show that tetracycline analogs, especially tigecycline and minocycline, inhibit osteoclast formation by blocking MMP-9-mediated histone H3 tail cleavage. Our molecular docking approach found that tigecycline and minocycline are the most potent inhibitors of MMP-9. We also observed that both inhibitors significantly inhibited H3 tail cleavage by MMP-9 in vitro. These compounds inhibited receptor activator of nuclear factor kappaB ligand (RANKL)-induced osteoclast formation by blocking the NFATc1 signaling pathway. Furthermore, MMP-9-mediated H3 tail cleavage during osteoclast differentiation was selectively blocked by these compounds. Treatment with both tigecycline and minocycline rescued the osteoporotic phenotype induced by prednisolone in a zebrafish osteoporosis model. Our findings demonstrate that the tetracycline analogs suppress osteoclastogenesis via MMP-9-mediated H3 tail cleavage, and suggest that MMP-9 inhibition could offer a new strategy for the treatment of glucocorticoid-induced osteoporosis.