NRP1 promotes osteo/odontogenic differentiation via shroom3 in dental pulp stem cells.

Neuropilin-1 (NRP1) is a single transmembrane glycoprotein involved in a variety of physiological events. However, the exact mechanisms by which NRP1 regulates dental pulp stem cells (DPSCs) to differentiate toward an osteo/odontogenic phenotype are poorly understood. Here, we determined the significantly increased expression of full-length NRP1 and glycosaminoglycan (GAG)-modified NRP1 during osteo/odontogenesis in DPSCs. NRP1 was confirmed to promote alkaline phosphatase (ALP) activity, mineralized nodule deposition, protein and mRNA expression of Runx2, DSPP and DMP1 in DPSCs via the loss-of-function and gain-of-function approaches. Further, a non-GAG-modified NRP1 mutant (NRP1 S612A) was generated and the suppression of osteo/odontogenic differentiation was observed in the NRP1 S612A overexpression cells. Knockdown of the adaptor protein shroom3 resulted in the inhibition of osteo/odontogenesis. The protein-protein interaction network, the protein-protein docking and confocal analyses indicated the interactions between NRP1 and shroom3. Furthermore, immunoprecipitation followed by western analysis confirmed the binding of NRP1 to shroom3, but overexpression of NRP1 S612A greatly influenced the recruitment of shroom3 by NRP1. These results provide strong evidence that NRP1 is a critical regulator for osteo/odontogenesis through interacting with shroom3. Moreover, our results indicate that NRP1 S612A attenuates osteo/odontogenesis, suggesting that GAG modification is essential for NRP1 in DPSCs.

Downregulation of lncRNA EPB41L4A-AS1 promotes gastric cancer cell proliferation, migration and invasion.

BACKGROUND: The incidence of gastric cancer ranks the first among digestive tract tumors in China. However, there are no specific symptoms in the early stage of the tumor and the diagnosis process is complex, so more effective detection methods are very needed. In this study, a novel long noncoding RNA (lncRNA) was introduced as a diagnostic biomarker for gastric cancer, which brought new thinking to the exploration of its pathological mechanism and clinical prediction. METHODS: The level of lncRNA EPB41L4A-AS1 (EPB41L4A-AS1) in gastric cancer serum and cells was verified via real-time quantitative polymerase chain reaction (RT-qPCR). Receiver operating characteristic (ROC) curve was performed based on the EPB41L4A-AS1 level, and the diagnostic possibility of EPB41L4A-AS was analyzed. The chi-square test evaluated the correlation between EPB41L4A-AS expression and clinical information. The cells were cultured and transfected in vitro, and the mediations of abnormal EPB41L4A-AS level on the viability and motility of gastric cancer cells were verified through cell counting kit-8 (CCK-8) and Transwell assay. Furthermore, luciferase activity assay was performed to confirm the sponge molecule microRNA-17-5p (miR-17-5p) of EPB41L4A-AS1. RESULTS: EPB41L4A-AS1 was decreased in gastric cancer, and low EPB41L4A-AS1 level indicated resultful diagnostic value. Overexpression of EPB41L4A-AS1 inhibited the activity of gastric cancer cells, while knockdown of EPB41L4A-AS1 promoted tumor deterioration. EPB41L4A-AS1 directly targeted and regulated the expression ofmiR-17-5p. CONCLUSION: This study elaborated that EPB41L4A-AS1 is lowly expressed in gastric cancer. Silencing EPB41L4A-AS1 was beneficial to cell proliferation, migration, and invasion. EPB41L4A-AS1 provides a new possibility for the diagnosis of gastric cancer patients by targeting miR-17-5p.

Circ_0082374 Promotes the Tumorigenesis and Suppresses Ferroptosis in Non-small Cell Lung Cancer by Up-Regulating GPX4 Through Sequestering miR-491-5p.

Circular RNAs (circRNAs) have been identified to be dysregulated in non-small cell lung cancer (NSCLC) and implicated in the progression of this cancer. Here, this work aimed to investigate the role and mechanism of circ_0082374 on NSCLC progression. Levels of circ_0082374, miR-491-5p, GPX4 (glutathione peroxidase 4) and epithelial-mesenchymal transition (EMT)-related proteins were examined by quantitative real-time PCR or western blotting, respectively. Cell proliferation and metastasis were detected using cell counting kit-8, colony formation, EdU, transwell, and Scratch assays. Cell ferroptosis was evaluated by measuring cell survival after the treatment of different ferroptosis inducers or inhibitors, as well as the accumulation of intracellular reactive oxygen species (ROS), ferrous iron (Fe2+) and malondialdehyde (MDA). The binding between miR-491-5p and circ_0082374 or GPX4 was confirmed using dual-luciferase reporter and RNA pull-down assays. In vivo experiments were conducted using murine xenograft assay and immunohistochemistry. Circ_0082374 was a stable circRNA with high expression in NSCLC tissues and cells. Functionally, circ_0082374 silencing suppressed NSCLC cell proliferation and metastasis. Moreover, its down-regulation enhanced ferroptosis by decreasing iron and lipid peroxidation accumulation. Mechanistically, circ_0082374 could indirectly up-regulate GPX4 expression via miR-491-5p, indicating the circ_0082374/miR-491-5p/GPX4 competitive endogenous RNAs (ceRNA) network. Rescue experiments demonstrated that the miR-491-5p/GPX4 axis mediated the regulatory effects of circ_0082374 exerted on NSCLC cells. Moreover, knockdown of circ_0082374 impeded NSCLC growth and EMT via regulating miR-491-5p and GPX4. Circ_0082374 silencing could suppress NSCLC cell proliferation, metastasis and induce ferroptosis through miR-491-5p/GPX4 axis, suggesting a novel therapeutic approach for NSCLC patients.

Thiazolidinedione enhances the efficacy of anti-PD-1 monoclonal antibody in murine melanoma.

Several clinical studies observed a surprising beneficial effect of obesity on enhancing immunotherapy responsiveness in patients with melanoma, highlighting an as-yet insufficiently understood relationship between metabolism and immunogenicity. Here, we demonstrate that the thiazolidinedione (TZD) rosiglitazone, a drug commonly used to treat diabetes by sequestering fatty acids in metabolically inert subcutaneous adipose tissue, improved sensitivity to anti-programmed cell death protein 1 (PD-1) treatment in YUMMER1.7 tumor-bearing mice, an initially immunotherapy-sensitive murine melanoma model. We observed a transition from high to intermediate PD-1 expression in tumor-infiltrating CD8+ T cells. Moreover, TZD inhibited PD-1 expression in mouse and human T cells treated in vitro. In addition to its direct impact on immune cells, TZD also decreased circulating insulin concentrations, while insulin induced T cell exhaustion in culture. In TZD-treated mice, we observed higher fatty acid concentrations in the tumor microenvironment, with fatty acids protecting against exhaustion in culture. Together, these data are consistent with an indirect mechanism of TZD inhibiting T cell exhaustion. Finally, we analyzed imaging data from patients with melanoma before and after anti-PD-1 treatment, confirming the beneficial effect of increased subcutaneous fat on anti-PD-1 responsiveness in patients. We also found that the expression of peroxisome proliferator-activated receptor gamma (PPARγ), the canonical activator of lipid uptake and adipogenesis activated by TZD, correlated with overall survival time. Taken together, these data identify a new adjuvant to enhance immunotherapy efficacy in YUMMER1.7 melanoma mice, and discover a new metabolism-based prognostic marker in human melanoma.NEW & NOTEWORTHY Zhang et al. demonstrate that the diabetes drug rosiglitazone improves the efficacy of immunotherapy in mouse melanoma. This effect is both direct and indirect: TZD directly reduces PD-1 expression in CD8+ T cells (i.e., reduces exhaustion), and indirectly reduces exhaustion by lowering insulin levels and increasing local fat. Finally, they demonstrate that hallmarks of TZD action (such as PPARγ expression and subcutaneous fat content) correlate with improved immunotherapy efficacy in humans with melanoma.

Expression and metabolism profiles of CVT associated with inflammatory responses and oxygen carrier ability in the brain.

AIM: As the main type of stroke, the incidence of cerebral venous thrombosis (CVT) has been rising. However, the comprehensive mechanisms behind it remain unclear. Thus, the multi-omics study is required to investigate the mechanism after CVT and elucidate the characteristic pathology of venous stroke and arterial stroke. METHODS: Adult rats were subjected to CVT and MCAO models. Whole-transcriptome sequencing (RNA-seq) and untargeted metabolomics analysis were performed to construct the transcriptome and metabolism profiles of rat brains after CVT and also MCAO. The difference analysis, functional annotation, and enrichment analysis were also performed. RESULTS: Through RNA-seq analysis, differentially expressed genes (DEGs) were screened. 174 CVT specific genes including Il1a, Ccl9, Cxxl6, Tnfrsf14, etc., were detected. The hemoglobin genes, including both Hba and Hbb, were significantly downregulated after CVT, compared both to the MCAO and Sham groups. Metabolism analysis showed that CVT had higher heterogeneity of metabolism compared to MCAO. Metabolites including N-stearoyltyrosine, 5-methoxy-3-indoleaceate, Afegostat, pipecolic acid, etc. were specially regulated in CVT. Through the immune infiltration analysis, it was found that CVT had a higher immune response, with the abundance of certain types of immune cells increased, especially T helper cells. It was important to find the prevalence of the activation of inflammatory chemokine, cytokine, NOD-like pathway, and neutrophil extracellular trap. CONCLUSION: We explored and analyzed the gene expression and metabolomic characteristics of CVT, revealed the specific inflammatory reaction mechanism of CVT and found the markers in transcriptome and metabolism levels. It points out the direction for CVT early diagnosis and treatment.

90Y SPECT scatter estimation and voxel dosimetry in radioembolization using a unified deep learning framework.

PURPOSE: 90Y SPECT-based dosimetry following radioembolization (RE) in liver malignancies is challenging due to the inherent scatter and the poor spatial resolution of bremsstrahlung SPECT. This study explores a deep-learning-based absorbed dose-rate estimation method for 90Y that mitigates the impact of poor SPECT image quality on dosimetry and the accuracy-efficiency trade-off of Monte Carlo (MC)-based scatter estimation and voxel dosimetry methods. METHODS: Our unified framework consists of three stages: convolutional neural network (CNN)-based bremsstrahlung scatter estimation, SPECT reconstruction with scatter correction (SC) and absorbed dose-rate map generation with a residual learning network (DblurDoseNet). The input to the framework is the measured SPECT projections and CT, and the output is the absorbed dose-rate map. For training and testing under realistic conditions, we generated a series of virtual patient phantom activity/density maps from post-therapy images of patients treated with 90Y-RE at our clinic. To train the scatter estimation network, we use the scatter projections for phantoms generated from MC simulation as the ground truth (GT). To train the dosimetry network, we use MC dose-rate maps generated directly from the activity/density maps of phantoms as the GT (Phantom + MC Dose). We compared performance of our framework (SPECT w/CNN SC + DblurDoseNet) and MC dosimetry (SPECT w/CNN SC + MC Dose) using normalized root mean square error (NRMSE) and normalized mean absolute error (NMAE) relative to GT. RESULTS: When testing on virtual patient phantoms, our CNN predicted scatter projections had NRMSE of 4.0% ± 0.7% on average. For the SPECT reconstruction with CNN SC, we observed a significant improvement on NRMSE (9.2% ± 1.7%), compared to reconstructions with no SC (149.5% ± 31.2%). In terms of virtual patient dose-rate estimation, SPECT w/CNN SC + DblurDoseNet had a NMAE of 8.6% ± 5.7% and 5.4% ± 4.8% in lesions and healthy livers, respectively; compared to 24.0% ± 6.1% and 17.7% ± 2.1% for SPECT w/CNN SC + MC Dose. In patient dose-rate maps, though no GT was available, we observed sharper lesion boundaries and increased lesion-to-background ratios with our framework. For a typical patient data set, the trained networks took ~ 1 s to generate the scatter estimate and ~ 20 s to generate the dose-rate map (matrix size: 512 × 512 × 194) on a single GPU (NVIDIA V100). CONCLUSION: Our deep learning framework, trained using true activity/density maps, has the potential to outperform non-learning voxel dosimetry methods such as MC that are dependent on SPECT image quality. Across comprehensive testing and evaluations on multiple targeted lesions and healthy livers in virtual patients, our proposed deep learning framework demonstrated higher (66% on average in terms of NMAE) estimation accuracy than the current "gold-standard" MC method. The enhanced computing speed with our framework without sacrificing accuracy is highly relevant for clinical dosimetry following 90Y-RE.

SBP1 promotes tumorigenesis of thyroid cancer through TXN/NIS pathway.

BACKGROUND: As the tissue with the highest selenium content in the body, the occurrence and development of thyroid cancer are closely related to selenium and selenoproteins. Selenium-binding protein 1 (SBP1) has been repeatedly implicated in several cancers, but its role and molecular mechanisms in thyroid cancer remains largely undefined. METHODS: The expression of SBP1, sodium/iodide symporter (NIS) and thioredoxin (TXN) were analyzed in clinical samples and cell lines. Cell counting kit-8 (CCK-8) and tube formation assays were used to analyze the cell viability and tube formation of cells. Immunofluorescence was used to determine the expression of the NIS. Co-immunoprecipitation (Co-IP) assay was carried out to verify the interaction of SBP1 with TXN. The mouse xenograft experiment was performed to investigate the growth of thyroid cancer cells with SBP1 knockdown in vivo. RESULTS: SBP1 was significantly increased in human thyroid cancer tissues and cells, especially in anaplastic thyroid cancer. Overexpression of SBP1 promoted FTC-133 cell proliferation, and the culture supernatant of SBP1-overexpression FTC-133 cells promoted tube formation of human retinal microvascular endothelial cells. Knockdown of SBP1, however, inhibited cell proliferation and tube formation. Furthermore, overexpression of SBP1 inhibited cellular differentiation of differentiated thyroid cancer cell line FTC-133, as indicated by decreased expression of thyroid stimulating hormone receptors, thyroglobulin and NIS. Knockdown of SBP1, however, promoted differentiation of BHT101 cells, an anaplastic thyroid cancer cell line. Notably, TXN, a negative regulator of NIS, was found to be significantly upregulated in human thyroid cancer tissues, and it was positively regulated by SBP1. Co-IP assay implied a direct interaction of SBP1 with TXN. Additionally, TXN overexpression reversed the effect of SBP1 knockdown on BHT101 cell viability, tube formation and cell differentiation. An in vivo study found that knockdown of SBP1 promoted the expression of thyroid stimulating hormone receptors, thyroglobulin and NIS, as well as inhibited the growth and progression of thyroid cancer tumors. CONCLUSION: SBP1 promoted tumorigenesis and dedifferentiation of thyroid cancer through positively regulating TXN.

Dichloroacetate as a novel pharmaceutical treatment for cancer-related fatigue in melanoma.

Cancer-related fatigue (CRF) is one of the most common complications in patients with multiple cancer types and severely affects patients' quality of life. However, there have only been single symptom-relieving adjuvant therapies but no effective pharmaceutical treatment for the CRF syndrome. Dichloroacetate (DCA), a small molecule inhibitor of pyruvate dehydrogenase kinase, has been tested as a potential therapy to slow tumor growth, based largely on its effects in vitro to halt cell division. We found that although DCA did not affect rates of tumor growth or the efficacy of standard cancer treatment (immunotherapy and chemotherapy) in two murine cancer models, DCA preserved physical function in mice with late-stage tumors by reducing circulating lactate concentrations. In vivo liquid chromatography-mass spectrometry/mass spectrometry studies suggest that DCA treatment may preserve membrane potential, postpone proteolysis, and relieve oxidative stress in muscles of tumor-bearing mice. In all, this study provides evidence for DCA as a novel pharmaceutical treatment to maintain physical function and motivation in murine models of CRF.NEW & NOTEWORTHY We identify a new metabolic target for cancer-related fatigue, dichloroacetate (DCA). They demonstrate that in mice, DCA preserves physical function and protects against the detrimental effects of cancer treatment by reducing cancer-induced increases in circulating lactate. As DCA is already FDA approved for another indication, these results could be rapidly translated to clinical trials for this condition for which no pharmaceutical therapies exist beyond symptom management.

Efficacy and safety of trastuzumab deruxtecan in the treatment of HER2-low/positive advanced breast cancer: a single-arm meta-analysis.

Background: Clinical trials have shown that the use of trastuzumab deruxtecan (DS-8201) alone is expected to provide novel therapeutic options for HER2-low/positive patients. Nevertheless, there are some variations in the efficacy of trial results, with potential risks at the safety level. Most DS-8201 trials in HER2 advanced breast cancer (ABC) have been conducted in the form of small-sample nonrandomized controlled studies, resulting in a lack of validated indicators to evaluate the efficacy and safety of DS-8201. Thus, this meta-analysis aimed to pool the results of various trials of DS-8201 alone to explore the efficacy and safety of DS-8201 in patients with HER2-low/positive advanced breast cancer. Methods: Relevant studies were searched in seven databases, including Embase, PubMed, Web of Science, Cochrane Library, CNKI, VIP database and WanFang data, to collect single-arm studies on DS-8201 for HER2-low/positive ABC. MINORS was adopted for quality assessment and STATA 16.0 for data analysis. Results: Ten studies involving 1,108 patients were included in this meta-analysis. As for the tumor response rate, the pooled ORR and DCR of all studies reached 57% (95% CI: 47%-67%) and 92% (95% CI: 89%-96%) respectively, and the pooled ORRs of the HER2-low expression group and the HER2-positive expression group were 46% (95% CI: 35%-56%) and 64% (95% CI: 54%-74%). Only the low expression group achieved median survival time, with a pooled median PFS and median OS of 9.24 (95% CI: 7.54-10.94) months and 23.87 (95% CI: 21.56-26.17) months, respectively. The most common treatment-related adverse events from DS-8201 were nausea (all grades: 62%; ≥ grade III: 5%), fatigue (all grade: 44%; ≥ grade III: 6%), and alopecia (all grades: 38%; ≥ grade III: 0.5%). Drug-related interstitial lung disease or pneumonitis occurred in 13% of the 1,108 patients, with only a 1% incidence of AE ≥ grade III. Conclusion: The present study suggests that DS-8201 is effective and safe in the treatment of ABC with low or positive HER2 expression, providing additional relevant information for its clinical application. However, further strengthening of the pairs is needed, as well as more clinical studies to support individualized treatment. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023390316.

The role and intervention of mitochondrial metabolism in osteoarthritis.

Osteoarthritis (OA), a prevalent degenerative joint disease, affects a substantial global population. Despite the elusive etiology of OA, recent investigations have implicated mitochondrial dysfunction as a significant factor in disease pathogenesis. Mitochondria, pivotal cellular organelles accountable for energy production, exert essential roles in cellular metabolism. Hence, mitochondrial dysfunction can exert broad-ranging effects on various cellular processes implicated in OA development. This comprehensive review aims to provide an overview of the metabolic alterations occurring in OA and elucidate the diverse mechanisms through which mitochondrial dysfunction can contribute to OA pathogenesis. These mechanisms encompass heightened oxidative stress and inflammation, perturbed chondrocyte metabolism, and compromised autophagy. Furthermore, this review will explore potential interventions targeting mitochondrial metabolism as means to impede or decelerate the progression of OA. In summary, this review offers a comprehensive understanding of the involvement of mitochondrial metabolism in OA and underscores prospective intervention strategies.

Tissue-specific reprogramming of glutamine metabolism maintains tolerance to sepsis.

Reprogramming metabolism is of great therapeutic interest for reducing morbidity and mortality during sepsis-induced critical illness. Disappointing results from randomized controlled trials targeting glutamine and antioxidant metabolism in patients with sepsis have begged a deeper understanding of the tissue-specific metabolic response to sepsis. The current study sought to fill this gap. We analyzed skeletal muscle transcriptomics of critically ill patients, versus elective surgical controls, which revealed reduced expression of genes involved in mitochondrial metabolism and electron transport, with increases in glutathione cycling, glutamine, branched chain, and aromatic amino acid transport. We then performed untargeted metabolomics and 13C isotope tracing to analyze systemic and tissue specific metabolic phenotyping in a murine polymicrobial sepsis model. We found an increased number of correlations between the metabolomes of liver, kidney, and spleen, with loss of correlations between the heart and quadriceps and all other organs, pointing to a shared metabolic signature within vital abdominal organs, and unique metabolic signatures for muscles during sepsis. A lowered GSH:GSSG and elevated AMP:ATP ratio in the liver underlie the significant upregulation of isotopically labeled glutamine's contribution to TCA cycle anaplerosis and glutamine-derived glutathione biosynthesis; meanwhile, the skeletal muscle and spleen were the only organs where glutamine's contribution to the TCA cycle was significantly suppressed. These results highlight tissue-specific mitochondrial reprogramming to support liver energetic demands and antioxidant synthesis, rather than global mitochondrial dysfunction, as a metabolic consequence of sepsis.

CircPDS5B Reduction Improves Angiogenesis Following Ischemic Stroke by Regulating MicroRNA-223-3p/NOTCH2 Axis.

Background and Objectives: Ischemic stroke (IS) is responsible for major causes of global death and disability, for which promoting angiogenesis is a promising therapeutic strategy. This study analyzed circular RNA PDS5B (circPDS5B) and its related mechanisms in angiogenesis in IS. Methods: In the permanent middle cerebral artery occlusion (pMCAO) mouse model, circPDS5B, microRNA (miR)-223-3p, and NOTCH2 levels were checked. By testing neurologic function, neuronal apoptosis, and expression of angiogenesis-related proteins in pMCAO mice, the protective effects of circPDS5B knockdown were probed. In human brain microvascular endothelial cells (HBMECs) under oxygen-glucose deprivation (OGD) conditions, the effects of circPDS5B, miR-223-3p, and NOTCH2 on angiogenesis were studied by measuring cellular activities. Results: The increase of circPDS5B and NOTCH2 expression and the decrease of miR-223-3p expression were examined in pMCAO mice. Reducing circPDS5B expression indicated protection against neurologic dysfunction, apoptosis, and angiogenesis impairment. For circPDS5B-depleted or miR-223-3p-restored HBMECs under OGD treatment, angiogenesis was promoted. MiR-223-3p inhibition-associated reduction of angiogenesis could be counteracted by knocking down NOTCH2. CircPDS5B depletion-induced angiogenesis in OGD-conditioned HBMECs was repressed after overexpressing NOTCH2. Discussion: In IS, the expression of circPDS5B was upregulated, and miR-223-3p inhibited HBMECs activity and promoted NOTCH2 expression, thus promoting IS. CircPDS5B reduction improves angiogenesis following ischemic stroke by regulating microRNA-223-3p/NOTCH2 axis.

[Regulation mechanism of resveratrol on odontogenic differentiation of human dental pulp stem cells].

PURPOSE: To investigate whether resveratrol promotes odontogenic differentiation of human dental pulp stem cells(DPSCs) by up-regulating the expression of silent information regulator 1 (SIRT1) and activating ß-catenin signaling pathway. METHODS: Different concentrations of resveratrol(0, 10, 15, 20 and 50 µmol/L) were used to treat DPSCs for 7 days and 14 days, and cell proliferative activity was detected by CCK-8. After odontogenic differentiation induced by 15 µmol/L resveratrol for 7 days, alkaline phosphatase(ALP) staining was performed and real-time quantitative reverse transcription PCR(qRT-PCR) was used to detect the mRNA expression of Runt-related transcription factor 2 (Runx2), dentin sialophosphoprotein(DSPP) and dentin matrix protein-1(DMP-1) in DPSCs. Western blot was used to detect the expression of SIRT1 in DPSCs on a specific day (0, 3rd, 5th, 7th and 14th) after differentiation induction. Western blot was also used to detect the expression of SIRT1 and activated ß-catenin during odontogenic differentiation of DPSCs treated by 15 µmol/L resveratrol for 7 days. The experimental data was analyzed with GraphPad Prism 9 software package. RESULTS: 15 µmol/L resveratrol had no significant effect on proliferation of DPSCs on the 7th and 14th day; 15 µmol/L resveratrol promoted odontogenic differentiation of DPSCs and up-regulated mRNA expression of RUNX2, DSPP, and DMP-1 in DPSCs; the expression of SIRT1 was the highest on the 7th day during odontogenic differentiation induction. Resveratrol resulted in the increasing protein expressions of SIRT1 and activated ß-catenin when DPSCs was induced to odontogenic differentiation for 7 days. CONCLUSIONS: Resveratrol promotes odontogenic differentiation of human DPSCs by up-regulating the expression of SIRT1 protein and activating ß-catenin signaling pathway.

Gene and protein expression and metabolic flux analysis reveals metabolic scaling in liver ex vivo and in vivo.

Metabolic scaling, the inverse correlation of metabolic rates to body mass, has been appreciated for more than 80 years. Studies of metabolic scaling have largely been restricted to mathematical modeling of caloric intake and oxygen consumption, and mostly rely on computational modeling. The possibility that other metabolic processes scale with body size has not been comprehensively studied. To address this gap in knowledge, we employed a systems approach including transcriptomics, proteomics, and measurement of in vitro and in vivo metabolic fluxes. Gene expression in livers of five species spanning a 30,000-fold range in mass revealed differential expression according to body mass of genes related to cytosolic and mitochondrial metabolic processes, and to detoxication of oxidative damage. To determine whether flux through key metabolic pathways is ordered inversely to body size, we applied stable isotope tracer methodology to study multiple cellular compartments, tissues, and species. Comparing C57BL/6 J mice with Sprague-Dawley rats, we demonstrate that while ordering of metabolic fluxes is not observed in in vitro cell-autonomous settings, it is present in liver slices and in vivo. Together, these data reveal that metabolic scaling extends beyond oxygen consumption to other aspects of metabolism, and is regulated at the level of gene and protein expression, enzyme activity, and substrate supply.

COMPASS: a formal framework and aggregate dataset for generalized surgical procedure modeling.

PURPOSE: We propose a formal framework for the modeling and segmentation of minimally invasive surgical tasks using a unified set of motion primitives (MPs) to enable more objective labeling and the aggregation of different datasets. METHODS: We model dry-lab surgical tasks as finite state machines, representing how the execution of MPs as the basic surgical actions results in the change of surgical context, which characterizes the physical interactions among tools and objects in the surgical environment. We develop methods for labeling surgical context based on video data and for automatic translation of context to MP labels. We then use our framework to create the COntext and Motion Primitive Aggregate Surgical Set (COMPASS), including six dry-lab surgical tasks from three publicly available datasets (JIGSAWS, DESK, and ROSMA), with kinematic and video data and context and MP labels. RESULTS: Our context labeling method achieves near-perfect agreement between consensus labels from crowd-sourcing and expert surgeons. Segmentation of tasks to MPs results in the creation of the COMPASS dataset that nearly triples the amount of data for modeling and analysis and enables the generation of separate transcripts for the left and right tools. CONCLUSION: The proposed framework results in high quality labeling of surgical data based on context and fine-grained MPs. Modeling surgical tasks with MPs enables the aggregation of different datasets and the separate analysis of left and right hands for bimanual coordination assessment. Our formal framework and aggregate dataset can support the development of explainable and multi-granularity models for improved surgical process analysis, skill assessment, error detection, and autonomy.

FGF-21 Conducts a Liver-Brain-Kidney Axis to Promote Renal Cell Carcinoma.

Metabolic homeostasis is one of the most exquisitely tuned systems in mammalian physiology. Metabolic homeostasis requires multiple redundant systems to cooperate to maintain blood glucose concentrations in a narrow range, despite a multitude of physiological and pathophysiological pressures. Cancer is one of the canonical pathophysiological settings in which metabolism plays a key role. In this study, we utilized REnal Gluconeogenesis Analytical Leads (REGAL), a liquid chromatography-mass spectrometry/mass spectrometry-based stable isotope tracer method that we developed to show that in conditions of metabolic stress, the fasting hepatokine fibroblast growth factor-21 (FGF-21)1,2 coordinates a liver-brain-kidney axis to promote renal gluconeogenesis. FGF-21 promotes renal gluconeogenesis by enhancing ß2 adrenergic receptor (Adrb2)-driven, adipose triglyceride lipase (ATGL)-mediated intrarenal lipolysis. Further, we show that this liver-brain-kidney axis promotes gluconeogenesis in the renal parenchyma in mice and humans with renal cell carcinoma (RCC). This increased gluconeogenesis is, in turn, associated with accelerated RCC progression. We identify Adrb2 blockade as a new class of therapy for RCC in mice, with confirmatory data in human patients. In summary, these data reveal a new metabolic function of FGF-21 in driving renal gluconeogenesis, and demonstrate that inhibition of renal gluconeogenesis by FGF-21 antagonism deserves attention as a new therapeutic approach to RCC.

Physics-Guided Deep Scatter Estimation by Weak Supervision for Quantitative SPECT.

Accurate scatter estimation is important in quantitative SPECT for improving image contrast and accuracy. With a large number of photon histories, Monte-Carlo (MC) simulation can yield accurate scatter estimation, but is computationally expensive. Recent deep learning-based approaches can yield accurate scatter estimates quickly, yet full MC simulation is still required to generate scatter estimates as ground truth labels for all training data. Here we propose a physics-guided weakly supervised training framework for fast and accurate scatter estimation in quantitative SPECT by using a 100× shorter MC simulation as weak labels and enhancing them with deep neural networks. Our weakly supervised approach also allows quick fine-tuning of the trained network to any new test data for further improved performance with an additional short MC simulation (weak label) for patient-specific scatter modelling. Our method was trained with 18 XCAT phantoms with diverse anatomies / activities and then was evaluated on 6 XCAT phantoms, 4 realistic virtual patient phantoms, 1 torso phantom and 3 clinical scans from 2 patients for 177Lu SPECT with single / dual photopeaks (113, 208 keV). Our proposed weakly supervised method yielded comparable performance to the supervised counterpart in phantom experiments, but with significantly reduced computation in labeling. Our proposed method with patient-specific fine-tuning achieved more accurate scatter estimates than the supervised method in clinical scans. Our method with physics-guided weak supervision enables accurate deep scatter estimation in quantitative SPECT, while requiring much lower computation in labeling, enabling patient-specific fine-tuning capability in testing.

Training End-to-End Unrolled Iterative Neural Networks for SPECT Image Reconstruction.

Training end-to-end unrolled iterative neural networks for SPECT image reconstruction requires a memory-efficient forward-backward projector for efficient backpropagation. This paper describes an open-source, high performance Julia implementation of a SPECT forward-backward projector that supports memory-efficient backpropagation with an exact adjoint. Our Julia projector uses only ~5% of the memory of an existing Matlab-based projector. We compare unrolling a CNN-regularized expectation-maximization (EM) algorithm with end-to-end training using our Julia projector with other training methods such as gradient truncation (ignoring gradients involving the projector) and sequential training, using XCAT phantoms and virtual patient (VP) phantoms generated from SIMIND Monte Carlo (MC) simulations. Simulation results with two different radionuclides (90Y and 177Lu) show that: 1) For 177Lu XCAT phantoms and 90Y VP phantoms, training unrolled EM algorithm in end-to-end fashion with our Julia projector yields the best reconstruction quality compared to other training methods and OSEM, both qualitatively and quantitatively. For VP phantoms with 177Lu radionuclide, the reconstructed images using end-to-end training are in higher quality than using sequential training and OSEM, but are comparable with using gradient truncation. We also find there exists a trade-off between computational cost and reconstruction accuracy for different training methods. End-to-end training has the highest accuracy because the correct gradient is used in backpropagation; sequential training yields worse reconstruction accuracy, but is significantly faster and uses much less memory.

Effect of oxidation at an elevated temperature on the evolution of phases, microstructure, and properties of the oxide films formed on the surface of TiZr.

This study examined the evolution of the microstructure, microhardness, corrosion resistance, and selective leaching properties of oxide films formed on the surface of a Ti-50Zr (%) alloy during heat treatment at 600 °C for various time intervals. According to our experimental results, the growth and evolution of oxide films can be divided into three stages. In stage I (heat treatment for less than 2 min), ZrO2 was first formed on the surface of the TiZr alloy, which slightly improved its corrosion resistance. In stage II (heat treatment for 2-10 min), the initially generated ZrO2 is gradually transformed into ZrTiO4 from the top to the bottom of the surface layer. The formation of ZrTiO4 significantly improves the microhardness and corrosion resistance of the alloy. In stage III (heat treatment for more than 10 min), microcracks appeared and propagated on the surface of the ZrTiO4 film, deteriorating the surface properties of the alloy. The ZrTiO4 began to peel off after heat treatment for more than 60 min. The untreated and heat-treated TiZr alloys exhibited excellent selective leaching properties in Ringer's solution, whereas a trace amount of suspended ZrTiO4 oxide particles formed in the solution after soaking the 60 min heat-treated TiZr alloy for 120 days. Surface modification of the TiZr alloy by generating an intact ZrTiO4 oxide film effectively improved its microhardness and corrosion resistance; however, oxidation should be performed appropriately to obtain materials with optimal properties for biomedical applications.

OrbitNet-A fully automated orbit multi-organ segmentation model based on transformer in CT images.

The delineation of orbital organs is a vital step in orbital diseases diagnosis and preoperative planning. However, an accurate multi-organ segmentation is still a clinical problem which suffers from two limitations. First, the contrast of soft tissue is relatively low. It usually cannot clearly show the boundaries of organs. Second, the optic nerve and the rectus muscle are difficult to distinguish because they are spatially adjacent and have similar geometry. To address these challenges, we propose the OrbitNet model to automatically segment orbital organs in CT images. Specifically, we present a global feature extraction module based on the transformer architecture called FocusTrans encoder, which enhance the ability to extract boundary features. To make the network focus on the extraction of edge features in the optic nerve and rectus muscle, the SA block is used to replace the convolution block in the decoding stage. In addition, we use the structural similarity measure (SSIM) loss as a part of the hybrid loss function to learn the edge differences of the organs better. OrbitNet has been trained and tested on the CT dataset collected by the Eye Hospital of Wenzhou Medical University. The experimental results show that our proposed model achieved superior results. The average Dice Similarity Coefficient (DSC) is 83.9%, the value of average 95% Hausdorff Distance (HD95) is 1.62 mm, and the value of average Symmetric Surface Distance (ASSD) is 0.47 mm. Our model also has good performance on the MICCAI 2015 challenge dataset.