A GLP-1/GLP-2 receptor dual agonist to treat NASH: Targeting the gut-liver axis and microbiome.

BACKGROUND AND AIMS: Currently there is no Food and Drug Administration-approved drug to treat NAFLD and NASH, the rates of which are increasing worldwide. Although NAFLD/NASH are highly complex and heterogeneous conditions, most pharmacotherapy pipelines focus on a single mechanistic target. Considering the importance of the gut-liver axis in their pathogenesis, we investigated the therapeutic effect of a long-acting dual agonist of glucagon-like peptide (GLP)-1 and GLP-2 receptors in mice with NAFLD/NASH. APPROACH AND RESULTS: C57BL/6J mice were fed a choline-deficient high-fat diet/high fructose and sucrose solution. After 16 weeks, mice were randomly allocated to receive vehicle, GLP1-Fc, GLP2-Fc, or GLP1/2-Fc fusion (GLP1/2-Fc) subcutaneously every 2 days for 4 weeks. Body weight was monitored, insulin/glucose tolerance tests were performed, feces were collected, and microbiome profiles were analyzed. Immobilized cell systems were used to evaluate direct peptide effect. Immunohistochemistry, quantitative PCR, immunoblot analysis, tunnel assay, and biochemical assays were performed to assess drug effects on inflammation, hepatic fibrosis, cell death, and intestinal structures. The mice had well-developed NASH phenotypes. GLP1/2-Fc reduced body weight, glucose levels, hepatic triglyceride levels, and cellular apoptosis. It improved liver fibrosis, insulin sensitivity, and intestinal tight junctions, and increased microvillus height, crypt depth, and goblet cells of intestine compared with a vehicle group. Similar effects of GLP1/2-Fc were found in in vitro cell systems. GLP1/2-Fc also changed microbiome profiles. We applied fecal microbiota transplantation (FMT) gain further insight into the mechanism of GLP1/2-Fc-mediated protection. We confirmed that FMT exerted an additive effect on GLP1-Fc group, including the body weight change, liver weight, hepatic fat accumulation, inflammation, and hepatic fibrosis. CONCLUSIONS: A long-acting dual agonist of GLP-1 and GLP-2 receptors is a promising therapeutic strategy to treat NAFLD/NASH.

Development of a machine learning-based fine-grained risk stratification system for thyroid nodules using predefined clinicoradiological features.

OBJECTIVE: We constructed and validated a machine learning-based malignancy risk estimation model using predefined clinicoradiological features, and evaluated its clinical utility for the management of thyroid nodules. METHODS: In total, 5708 benign (n = 4597) and malignant (n = 1111) thyroid nodules were collected from 5081 consecutive patients treated in 26 institutions. Seventeen experienced radiologists evaluated nodule characteristics on ultrasonographic images. Eight predictive models were used to stratify the thyroid nodules according to malignancy risk; model performance was assessed via nested 10-fold cross-validation. The best-performing algorithm was externally validated using data for 454 thyroid nodules from a tertiary hospital, then compared to the Thyroid Imaging Reporting and Data System (TIRADS)-based interpretations of radiologists (American College of Radiology, European and Korean TIRADS, and AACE/ACE/AME guidelines). RESULTS: The area under the receiver operating characteristic (AUROC) curves of the algorithms ranged from 0.773 to 0.862. The sensitivities, specificities, positive predictive values, and negative predictive values of the best-performing models were 74.1-76.6%, 80.9-83.4%, 49.2-51.9%, and 93.0-93.5%, respectively. For the external validation set, the ElasticNet values were 83.2%, 89.2%, 81.8%, and 90.1%, respectively. The corresponding TIRADS values were 66.5-85.0%, 61.3-80.8%, 45.9-72.1%, and 81.5-90.3%, respectively. The new model exhibited a significantly higher AUROC and specificity than did the TIRADS risk stratification, although its sensitivity was similar. CONCLUSION: We developed a reliable machine learning-based predictive model that demonstrated enhanced specificity when stratifying thyroid nodules according to malignancy risk. This system will contribute to improved personalized management of thyroid nodules. KEY POINTS: • The area under the receiver operating characteristic (AUROC) curve, sensitivity, and specificity of our model were 0.914, 83.2%, and 89.2%, respectively (derived using the validation dataset). • Compared to the TIRADS values, the AUROC and specificity are significantly higher, while the sensitivity is similar. • An interactive version of our AI algorithm is at http://tirads.cdss.co.kr .

Deep learning referral suggestion and tumour discrimination using explainable artificial intelligence applied to multiparametric MRI.

OBJECTIVES: An appropriate and fast clinical referral suggestion is important for intra-axial mass-like lesions (IMLLs) in the emergency setting. We aimed to apply an interpretable deep learning (DL) system to multiparametric MRI to obtain clinical referral suggestion for IMLLs, and to validate it in the setting of nontraumatic emergency neuroradiology. METHODS: A DL system was developed in 747 patients with IMLLs ranging 30 diseases who underwent pre- and post-contrast T1-weighted (T1CE), FLAIR, and diffusion-weighted imaging (DWI). A DL system that segments IMLLs, classifies tumourous conditions, and suggests clinical referral among surgery, systematic work-up, medical treatment, and conservative treatment, was developed. The system was validated in an independent cohort of 130 emergency patients, and performance in referral suggestion and tumour discrimination was compared with that of radiologists using receiver operating characteristics curve, precision-recall curve analysis, and confusion matrices. Multiparametric interpretable visualisation of high-relevance regions from layer-wise relevance propagation overlaid on contrast-enhanced T1WI and DWI was analysed. RESULTS: The DL system provided correct referral suggestions in 94 of 130 patients (72.3%) and performed comparably to radiologists (accuracy 72.6%, McNemar test; p = .942). For distinguishing tumours from non-tumourous conditions, the DL system (AUC, 0.90 and AUPRC, 0.94) performed similarly to human readers (AUC, 0.81~0.92, and AUPRC, 0.88~0.95). Solid portions of tumours showed a high overlap of relevance, but non-tumours did not (Dice coefficient 0.77 vs. 0.33, p < .001), demonstrating the DL's decision. CONCLUSIONS: Our DL system could appropriately triage patients using multiparametric MRI and provide interpretability through multiparametric heatmaps, and may thereby aid neuroradiologic diagnoses in emergency settings. CLINICAL RELEVANCE STATEMENT: Our AI triages patients with raw MRI images to clinical referral pathways in brain intra-axial mass-like lesions. We demonstrate that the decision is based on the relative relevance between contrast-enhanced T1-weighted and diffusion-weighted images, providing explainability across multiparametric MRI data. KEY POINTS: • A deep learning (DL) system using multiparametric MRI suggested clinical referral to patients with intra-axial mass-like lesions (IMLLs) similar to radiologists (accuracy 72.3% vs. 72.6%). • In the differentiation of tumourous and non-tumourous conditions, the DL system (AUC, 0.90) performed similar with radiologists (AUC, 0.81-0.92). • The DL's decision basis for differentiating tumours from non-tumours can be quantified using multiparametric heatmaps obtained via the layer-wise relevance propagation method.

Tumor habitat analysis by magnetic resonance imaging distinguishes tumor progression from radiation necrosis in brain metastases after stereotactic radiosurgery.

OBJECTIVES: The identification of viable tumor after stereotactic radiosurgery (SRS) is important for future targeted therapy. This study aimed to determine whether tumor habitat on structural and physiologic MRI can distinguish viable tumor from radiation necrosis of brain metastases after SRS. METHOD: Multiparametric contrast-enhanced T1- and T2-weighted imaging, apparent diffusion coefficient (ADC), and cerebral blood volume (CBV) were obtained from 52 patients with 69 metastases, showing enlarging enhancing masses after SRS. Voxel-wise clustering identified three structural MRI habitats (enhancing, solid low-enhancing, and nonviable) and three physiologic MRI habitats (hypervascular cellular, hypovascular cellular, and nonviable). Habitat-based predictors for viable tumor or radiation necrosis were identified by logistic regression. Performance was validated using the area under the curve (AUC) of the receiver operating characteristics curve in an independent dataset with 24 patients. RESULTS: None of the physiologic MRI habitats was indicative of viable tumor. Viable tumor was predicted by a high-volume fraction of solid low-enhancing habitat (low T2-weighted and low CE-T1-weighted values; odds ratio [OR] 1.74, p <.001) and a low-volume fraction of nonviable tissue habitat (high T2-weighted and low CE-T1-weighted values; OR 0.55, p <.001). Combined structural MRI habitats yielded good discriminatory ability in both development (AUC 0.85, 95% confidence interval [CI]: 0.77-0.94) and validation sets (AUC 0.86, 95% CI:0.70-0.99), outperforming single ADC (AUC 0.64) and CBV (AUC 0.58) values. The site of progression matched with the solid low-enhancing habitat (72%, 8/11). CONCLUSION: Solid low-enhancing and nonviable tissue habitats on structural MRI can help to localize viable tumor in patients with brain metastases after SRS. KEY POINTS: • Structural MRI habitats helped to differentiate viable tumor from radiation necrosis. • Solid low-enhancing habitat was most helpful to find viable tumor. • Providing spatial information, the site of progression matched with solid low-enhancing habitat.

Ezetimibe ameliorates lipid accumulation during adipogenesis by regulating the AMPK-mTORC1 pathway.

Adipogenesis, a critical process that converts adipocyte precursors into adipocytes, is considered a potential therapeutic target for the treatment of obesity. Ezetimibe, a drug approved by the United States Food and Drug Administration, is used for the treatment of hypercholesterolemia. Recently, it was reported to ameliorate high fat diet-induced dyslipidemia in mice and reduce lipid accumulation in hepatocytes through the activation of AMPK. However, the anti-adipogenic effects of ezetimibe and the underlying molecular mechanism have not yet been elucidated. Here, we found that ezetimibe reduced lipid accumulation via activating AMPK during the early phase of adipogenesis. We also observed that ezetimibe inhibited peroxisome proliferator-activated receptor γ, which is a major transcription factor of adipogenesis. Furthermore, ezetimibe-mediated AMPK activation reduced lipid accumulation by inhibiting mTORC1 signaling, leading to the downregulation of lipogenesis-related genes. Mitotic clonal expansion, required for adipogenesis, accelerates cell cycle progression and cell proliferation. We additionally observed that ezetimibe prevented the progression of mitotic clonal expansion by arresting the cell cycle at the G0/G1 phase, which was followed by the inhibition of cell proliferation. Collectively, ezetimibe-mediated inhibition of adipogenesis is dependent on the AMPK-mTORC1 pathway. Thus, we suggest that ezetimibe might be a promising drug for the treatment of obesity.

Diagnostic performance and interobserver agreement of the callosal angle and Evans' index in idiopathic normal pressure hydrocephalus: a systematic review and meta-analysis.

OBJECTIVE: To evaluate the diagnostic performance and interobserver agreement of the callosal angle and Evans' index in idiopathic normal pressure hydrocephalus (iNPH). METHODS: A systematic search of MEDLINE and EMBASE was performed to find studies assessing the diagnostic performance or interobserver agreement of the callosal angle and Evans' index in iNPH. Pooled sensitivity and specificity of the two radiologic indices were calculated. The area under the curve (AUC) was obtained based on a hierarchical summary receiver operating characteristic curve. The diagnostic performances of both radiologic indices were compared in subgroup analysis. To evaluate interobserver agreement, the pooled correlation coefficient was calculated. RESULTS: Ten original articles (874 patients) were included. The pooled sensitivity and specificity of the callosal angle in the diagnosis of iNPH were 91% (95% CI, 86-94%) and 93% (95% CI, 89-96%), respectively. The pooled sensitivity and specificity of Evans' index were 96% (95% CI, 47-100%) and 83% (95% CI, 77-88%), respectively. Subgroup analysis demonstrated a significant higher specificity of the callosal angle than that of Evans' index (p < 0.01). The AUC of the callosal angle and Evans' index were 0.97 (95% CI, 0.95-0.98) and 0.87 (95% CI, 0.84-0.90), respectively. The pooled correlation coefficients for the callosal angle and Evans' index were 0.92 (95% CI, 0.82-0.96) and 0.92 (95% CI, 0.83-0.97), respectively. CONCLUSIONS: Our meta-analysis demonstrated a high performance of the callosal angle in the diagnosis of iNPH. Evans' index showed reasonable diagnostic performance with high sensitivity but low specificity. Interobserver agreements were excellent in both radiologic indices. KEY POINTS: • Callosal angle showed high diagnostic performance in idiopathic normal pressure hydrocephalus. • Evans' index showed reasonable diagnostic performance with high sensitivity but low specificity. • Interobserver agreements were excellent in both callosal angle and Evans' index.

Diagnostic performance of loss of nigral hyperintensity on susceptibility-weighted imaging in parkinsonism: an updated meta-analysis.

OBJECTIVES: To evaluate diagnostic performance of loss of nigral hyperintensity on SWI in differentiating idiopathic Parkinson's disease (IPD) or primary parkinsonism (including IPD and Parkinson-plus syndrome) from healthy/disease controls. METHODS: MEDLINE/PubMed and EMBASE databases were searched to identify original articles investigating the diagnostic performance of loss of nigral hyperintensity for differentiating IPD or primary parkinsonism from healthy/disease control, up to April 3, 2020. Pooled sensitivity and specificity were calculated using a bivariate random-effects model. The proportion of nondiagnostic scan, inter- and intrareader agreement, and the proportion of concordance between clinical laterality and imaging asymmetry were also pooled. RESULTS: Nineteen articles covering 2125 patients (1097 with primary parkinsonism, 1028 healthy/disease controls) were included. For discrimination between IPD and healthy/disease controls, pooled sensitivity and specificity were 0.96 (95% CI, 0.91-0.98) and 0.95 (95% CI, 0.92-0.97). For discrimination between primary parkinsonism and healthy/disease controls, pooled sensitivity and specificity were 0.87 (95% CI, 0.75-0.94) and 0.93 (95% CI, 0.85-0.97). The pooled proportion of non-diagnostic scans on random-effects modeling was 4.2% (95% CI, 2.5-6.9%). The inter- and intrareader agreements were almost perfect, with the pooled coefficients being 0.84 (95% CI, 0.78-0.89) and 0.96 (95% CI, 0.89-0.99), respectively. The pooled proportion of concordant cases was 69.3% (95% CI, 58.4-78.4%). CONCLUSIONS: Loss of nigral hyperintensity on SWI can differentiate IPD or primary parkinsonism from a healthy/disease control group with high accuracy. However, the proportion of non-diagnostic scans is not negligible and must be taken into account. KEY POINTS: • For discrimination between idiopathic Parkinson's disease and healthy/disease controls, pooled sensitivity and specificity of loss of nigral hyperintensity were 0.96 and 0.95. • For discrimination between primary parkinsonism and healthy/disease controls, pooled sensitivity and specificity of loss of nigral hyperintensity were 0.87 and 0.93. • The pooled proportion of non-diagnostic scans on random-effects modeling was 4.2%.

Downregulation of α-Melanocyte-Stimulating Hormone-Induced Activation of the Pax3-MITF-Tyrosinase Axis by Sorghum Ethanolic Extract in B16F10 Melanoma Cells.

Ultraviolet irradiation-induced hyperpigmentation of the skin is associated with excessive melanin production in melanocytes. Tyrosinase (TYR) is a key enzyme catalyzing the rate-limiting step in melanogenesis. TYR expression is controlled by microphthalmia-associated transcription factor (MITF) expression. Sorghum is a cereal crop widely used in a variety of foods worldwide. Sorghum contains many bioactive compounds and is beneficial to human health. However, the effects of sorghum in anti-melanogenesis have not been well characterized. In this study, the biological activity of sorghum ethanolic extract (SEE) on α-melanocyte-stimulating hormone (α-MSH)-induced TYR expression was evaluated in B16F10 melanoma cells. SEE attenuated α-MSH-induced TYR gene promoter activity through the downregulation of the transcription factor MITF. We found that paired box gene 3 (Pax3) contributes to the maximal induction of MITF gene promoter activity. Further analysis demonstrated that SEE inhibited α-MSH-induced Pax3 expression. The collective results indicate that SEE attenuates α-MSH-induced TYR expression through the suppression of Pax3-mediated MITF gene promoter activity. Targeting the Pax3-MITF axis pathway could be considered a potential strategy to increase the efficacy of anti-melanogenesis.

A synthetic chalcone derivative, 2-hydroxy-3',5,5'-trimethoxychalcone (DK-139), suppresses the TNFα-induced invasive capability of MDA-MB-231 human breast cancer cells by inhibiting NF-κB-mediated GROα expression.

2-Hydroxy-3',5,5'-trimenthoxyochalcone (DK-139) is a synthetic chalcone-derived compound. This study evaluated the biological activity of DK-139 on the inhibition of tumor metastasis. Growth-regulated oncogene-alpha (GROα) plays an important role in the progression of tumor development by stimulating angiogenesis and metastasis. In this study, DK-139 inhibited tumor necrosis factor alpha (TNFα)-induced GROα gene promoter activity by inhibiting of IκB kinase (IKK) in MDA-MB231 cells. In addition, DK-139 prevented the TNFα-induced cell migration, F-actin formation, and invasive capability of MDA-MB-231 cells. These findings suggest that DK-139 is a potential drug candidate for the inhibition of tumor cell locomotion and invasion via the suppression of NF-κB-mediated GROα expression.

PF-4708671, a specific inhibitor of p70 ribosomal S6 kinase 1, activates Nrf2 by promoting p62-dependent autophagic degradation of Keap1.

p70 ribosomal S6 kinase 1 (S6K1) is an important serine/threonine kinase and downstream target of the mechanistic target of rapamycin complex 1 (mTORC1) signaling pathway. PF-4708671 is a specific inhibitor of S6K1, and prevents S6K1-mediated phosphorylation of the S6 protein. PF-4708671 treatment often leads to apoptotic cell death. However, the protective mechanism against PF-4708671-induced cell death has not been elucidated. The nuclear factor erythroid 2-related factor 2 (Nrf2)-Kelch-like ECH-associated protein 1 (Keap1) pathway is essential for protecting cells against oxidative stress. p62, an adaptor protein in the autophagic process, enhances Nrf2 activation through the impairment of Keap1 activity. In this study, we showed that PF-4708671 induces autophagic Keap1 degradation-mediated Nrf2 activation in p62-dependent manner. Furthermore, p62-dependent Nrf2 activation plays a crucial role in protecting cells from PF-4708671-mediated apoptosis.

Fenofibrate activates Nrf2 through p62-dependent Keap1 degradation.

Peroxisome proliferator-activated receptor α (PPARα) activates the ß-oxidation of fatty acids in the liver. Fenofibrate is a potent agonist of PPARα and is used in the treatment of hyperlipidemia. Fenofibrate treatment often induces the production of intracellular reactive oxygen species (ROS), leading to cell death. The nuclear factor erythroid 2-related factor 2 (Nrf2)-Kelch-like ECH-associated protein 1 (Keap1) pathway is an essential component of the defense mechanism against oxidative stress. However, the molecular mechanism underlying the regulation of the Nrf2-Keap1 pathway in fenofibrate-induced cell death is not known. In this study, we demonstrated that fenofibrate induces Keap1 degradation and Nrf2 activation. This fenofibrate-mediated Keap1 degradation is partly dependent on autophagy. Furthermore, fenofibrate-induced Keap1 degradation followed by Nrf2 activation is mainly mediated by p62, which functions as an adaptor protein in the autophagic pathway. Consistent with these findings, ablation of p62 increased fenofibrate-mediated apoptotic cell death associated with ROS accumulation. These results strongly suggest that p62 plays a crucial role in preventing fenofibrate-induced cell death.

Concerted action of p62 and Nrf2 protects cells from palmitic acid-induced lipotoxicity.

Nonalcoholic fatty liver disease (NAFLD), frequently associated with obesity and diabetes mellitus, is caused by the accumulation of excess fatty acids within liver cells. Palmitic acid (PA), a common saturated fatty acid found in mammals, induces the generation of reactive oxygen species (ROS) and elicits apoptotic cell death, known as lipotoxicity. However, protective mechanisms against PA-induced lipotoxicity have not been elucidated. In this study, we aimed to clarify the role of p62, an adapter protein in the autophagic process, as well as the nuclear factor erythroid 2-related factor 2 (Nrf2)-Kelch-like ECH-associated protein 1 (Keap1) pathway, in protecting cells from PA-induced lipotoxicity. The Nrf2-Keap1 pathway is essential for the protection of cells from oxidative stress. p62 enhances its binding to Keap1 and leads to Nrf2 activation. Here, we show that PA potentiates Keap1 degradation and thereby activates the transcription of Nrf2 target genes partially through autophagy. Furthermore, this PA-mediated Keap1 degradation depends on p62. Correspondingly, a lack of p62 attenuates the PA-mediated Nrf2 activation and increases the susceptibility of cells to oxidative stress. These results indicate that p62 plays an important role in protecting cells against lipotoxicity through Keap1 degradation-mediated Nrf2 activation.

Artificial Intelligence Model Assisting Thyroid Nodule Diagnosis and Management: A Multicenter Diagnostic Study.

CONTEXT: It is not clear how to integrate artificial intelligence (AI)-based models into diagnostic workflows. OBJECTIVE: To develop and validate a deep-learning-based AI model (AI-Thyroid) for thyroid cancer diagnosis, and to explore how this improves diagnostic performance. METHODS: The system was trained using 19 711 images of 6163 patients in a tertiary hospital (Ajou University Medical Center; AUMC). It was validated using 11 185 images of 4820 patients in 24 hospitals (test set 1) and 4490 images of 2367 patients in AUMC (test set 2). The clinical implications were determined by comparing the findings of six physicians with different levels of experience (group 1: 4 trainees, and group 2: 2 faculty radiologists) before and after AI-Thyroid assistance. RESULTS: The area under the receiver operating characteristic (AUROC) curve of AI-Thyroid was 0.939. The AUROC, sensitivity, and specificity were 0.922, 87.0%, and 81.5% for test set 1 and 0.938, 89.9%, and 81.6% for test set 2. The AUROCs of AI-Thyroid did not differ significantly according to the prevalence of malignancies (>15.0% vs ≤15.0%, P = .226). In the simulated scenario, AI-Thyroid assistance changed the AUROC, sensitivity, and specificity from 0.854 to 0.945, from 84.2% to 92.7%, and from 72.9% to 86.6% (all P < .001) in group 1, and from 0.914 to 0.939 (P = .022), from 78.6% to 85.5% (P = .053) and from 91.9% to 92.5% (P = .683) in group 2. The interobserver agreement improved from moderate to substantial in both groups. CONCLUSION: AI-Thyroid can improve diagnostic performance and interobserver agreement in thyroid cancer diagnosis, especially in less-experienced physicians.

Diabetic sensory neuropathy and insulin resistance are induced by loss of UCHL1 in Drosophila.

Diabetic sensory neuropathy (DSN) is one of the most common complications of type 2 diabetes (T2D), however the molecular mechanistic association between T2D and DSN remains elusive. Here we identify ubiquitin C-terminal hydrolase L1 (UCHL1), a deubiquitinase highly expressed in neurons, as a key molecule underlying T2D and DSN. Genetic ablation of UCHL1 leads to neuronal insulin resistance and T2D-related symptoms in Drosophila. Furthermore, loss of UCHL1 induces DSN-like phenotypes, including numbness to external noxious stimuli and axonal degeneration of sensory neurons in flies' legs. Conversely, UCHL1 overexpression improves DSN-like defects of T2D model flies. UCHL1 governs insulin signaling by deubiquitinating insulin receptor substrate 1 (IRS1) and antagonizes an E3 ligase of IRS1, Cullin 1 (CUL1). Consistent with these results, genetic and pharmacological suppression of CUL1 activity rescues T2D- and DSN-associated phenotypes. Therefore, our findings suggest a complete set of genetic factors explaining T2D and DSN, together with potential remedies for the diseases.

Methods for Improving the Germination of Rhodotypos scandens (Thunb.) Makino Seeds through Endocarp Removal.

Rhodotypos scandens (Thunb.) Makino is known to have a seed dispersal that is thick and stony (endocarp + seeds) and has potential as a landscaping tree seed. In several Rosaceae species, seeds are covered with a hard endocarp, making the internal seeds water-impermeable and germination difficult. Here, we analyzed the morphoanatomical traits and germination properties of R. scandens seeds. To identify ideal seed propagation conditions, we immersed R. scandens seeds in sulfuric acid for varying durations and subjected them to phytohormone (gibberellic acid A3 and fluridone) and a cold stratification (CS) (5 °C) treatment after endocarp removal (ER). The R. scandens stony seeds did not increase in mass by ≥25.0%. Following ER, the seed mass increased by ≥50.0% with water absorption when compared to the initial dry mass. Seed surfaces showed damage and cracks through scarification after 1 h of immersion in sulfuric acid, failing to germinate. A combination of ER, phytohormone treatment, and CS improved seed germination compared to ER alone (26.0 ± 5.3%). Overall, R. scandens seeds showed a dispersal with a hard endocarp from the parent plant, and a pre-treatment with ER, phytohormones, and CS was required for effective seed propagation.

Radiofrequency Ablation for the Treatment of Benign Thyroid Nodules: 10-Year Experience.

Background: Longer follow-up after radiofrequency ablation (RFA) of benign thyroid nodules is needed to understand regrowth and other causes of delayed surgery and long-term complications. Methods: This retrospective study included consecutive patients treated with RFA for symptomatic benign nonfunctioning thyroid nodules between March 2007 and December 2010. RFA was performed according to the standard protocol. We followed up patients at 1, 6, and 12 months, then yearly, until August 2022, and calculated the volume reduction ratio (VRR) at each follow-up. We assessed the incidence of regrowth according to three published criteria, delayed surgery, and complications. The Kaplan-Meier method was used to evaluate the cumulative incidence of regrowth, and univariable and multivariable Cox regression analyses were performed to identify risk factors for regrowth. Results: This study included 421 patients (mean age, 47 ± 13 years; 372 women) with 456 nodules (mean volume, 21 ± 23 mL). The median follow-up period was 90 months (interquartile range, 24-143 months). The mean VRR was 81% at 2 years, 90% at 5 years, and 94% at ≥10 years. Overall regrowth was noted in 12% (53/456) of nodules and was treated with repeat RFA (n = 33) or surgery (n = 4) or left under observation (n = 16). Thyroid nodules with ≥20 mL initial volume had significantly higher risk of regrowth compared with nodules with <10 mL initial volume (hazard ratio, 2.315 [95% confidence interval, 1.183-4.530]; p = 0.014 on multivariable Cox regression analysis). Delayed surgery was performed in 6% (26/421) of patients because of regrowth and/or persistent symptoms (n = 4) or newly detected thyroid tumors (n = 22), one benign and 21 malignant. The overall complication rate was 2.4% (10/421), with no procedure-related deaths or long-term complications. Conclusion: RFA is safe and effective for treating benign thyroid nodules, with a high VRR at long-term follow-up. Regular follow-up after initial success is warranted because of the possibility of regrowth of ablated nodules and the need for delayed surgery in some patients.

Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study.

OBJECTIVES: To assess whether a deep learning-based system (DLS) with black-blood imaging for brain metastasis (BM) improves the diagnostic workflow in a multi-center setting. MATERIALS AND METHODS: In this retrospective study, a DLS was developed in 101 patients and validated on 264 consecutive patients (with lung cancer) having newly developed BM from two tertiary university hospitals, which performed black-blood imaging between January 2020 and April 2021. Four neuroradiologists independently evaluated BM either with segmented masks and BM counts provided (with DLS) or not provided (without DLS) on a clinical trial imaging management system (CTIMS). To assess reading reproducibility, BM count agreement between the readers and the reference standard were calculated using limits of agreement (LoA). Readers' workload was assessed with reading time, which was automatically measured on CTIMS, and were compared between with and without DLS using linear mixed models considering the imaging center. RESULTS: In the validation cohort, the detection sensitivity and positive predictive value of the DLS were 90.2% (95% confidence interval [CI]: 88.1-92.2) and 88.2% (95% CI: 85.7-90.4), respectively. The difference between the readers and the reference counts was larger without DLS (LoA: -0.281, 95% CI: -2.888, 2.325) than with DLS (LoA: -0.163, 95% CI: -2.692, 2.367). The reading time was reduced from mean 66.9 s (interquartile range: 43.2-90.6) to 57.3 s (interquartile range: 33.6-81.0) (P <.001) in the with DLS group, regardless of the imaging center. CONCLUSION: Deep learning-based BM detection and counting with black-blood imaging improved reproducibility and reduced reading time, on multi-center validation.

PINK1 and Parkin regulate IP3R-mediated ER calcium release.

Although defects in intracellular calcium homeostasis are known to play a role in the pathogenesis of Parkinson's disease (PD), the underlying molecular mechanisms remain unclear. Here, we show that loss of PTEN-induced kinase 1 (PINK1) and Parkin leads to dysregulation of inositol 1,4,5-trisphosphate receptor (IP3R) activity, robustly increasing ER calcium release. In addition, we identify that CDGSH iron sulfur domain 1 (CISD1, also known as mitoNEET) functions downstream of Parkin to directly control IP3R. Both genetic and pharmacologic suppression of CISD1 and its Drosophila homolog CISD (also known as Dosmit) restore the increased ER calcium release in PINK1 and Parkin null mammalian cells and flies, respectively, demonstrating the evolutionarily conserved regulatory mechanism of intracellular calcium homeostasis by the PINK1-Parkin pathway. More importantly, suppression of CISD in PINK1 and Parkin null flies rescues PD-related phenotypes including defective locomotor activity and dopaminergic neuronal degeneration. Based on these data, we propose that the regulation of ER calcium release by PINK1 and Parkin through CISD1 and IP3R is a feasible target for treating PD pathogenesis.

Novel Cu(II) complexes as DNA-destabilizing agents and their DNA nuclease activity.

Here, we report a series of four novel Cu complexes, namely 2-(piperidin-1-ylmethyl)quinoline copper(II) nitrate, [LACu(NO3)2] (Cu1), 4-(quinolin-2-ylmethyl)morpholine copper(II) nitrate, [LBCu(NO3)2] (Cu2), 4-(quinolin-2-ylmethyl)morpholine copper(II) chloride, [LBCuCl2] (Cu3), and 2-(piperidin-1-ylmethyl)pyridine copper(II) chloride, [LCCu(µ-Cl)Cl]2 (Cu4). X-ray diffraction studies revealed that the geometry around the Cu(II) center could be best described as distorted octahedral in Cu1 and Cu2, whereas Cu3 and Cu4 showed distorted tetrahedral and square pyramidal geometries, respectively. DNA binding studies showed that Cu complexes Cu1-3 containing quinoline interacted via minor groove binding, whereas the Cu4 complex containing pyridine interacted via intercalation. All Cu complexes containing quinoline and pyridine caused destabilization of DNA at specific homogeneous G-C regions. The Cu1-3 complexes as groove binders destabilized the DNA structure much more than the Cu4 complex as an intercalator. Regarding groove binders, the Cu2 complex containing quinoline and morpholine caused the highest distortion and destabilization of the DNA structure, leading to high DNA cleavage efficiency.

Contrast-enhanced CT-based Radiomics for the Differentiation of Anaplastic or Poorly Differentiated Thyroid Carcinoma from Differentiated Thyroid Carcinoma: A Pilot Study.

Differential diagnosis of anaplastic thyroid carcinoma/poorly differentiated thyroid carcinoma (ATC/PDTC) from differentiated thyroid carcinoma (DTC) is crucial in patients with large thyroid malignancies. This study creates a predictive model using radiomics feature analysis to differentiate ATC/PDTC from DTC. We compared the clinicoradiological characteristics and radiomics features extracted from a volume of interest on contrast-enhanced computed tomography (CT) between the groups. Estimations of variable importance were performed via modeling using the random forest quantile classifier. The diagnostic performance of the model with radiomics features alone had the area under the receiver operating characteristic (AUROC) curve value of 0.883. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were 81.7%, 93.3%, 97.7%, 64.5%, and 84.6%, respectively, for the differential diagnosis of ATC/PDTC and DTC. The model with both radiomics and clinicoradiological information showed the AUROC of 0.908, with sensitivity, specificity, PPV, NPV, and accuracy of 82.9%, 97.6%, 99.2%, 67.1%, and 86.5% respectively. Distant metastasis, moment, shape, age, and gray-level size zone matrix features were the most useful factors for differential diagnosis. Therefore, we concluded that a radiomics approach based on contrast-enhanced CT features can potentially differentiate ATC/PDTC from DTC in patients with large thyroid malignancies.