Honokiol ameliorates angiotensin II-induced cardiac hypertrophy by promoting dissociation of the Nur77-LKB1 complex and activating the AMPK pathway.

Pathological cardiac hypertrophy is a key contributor to heart failure, and the molecular mechanisms underlying honokiol (HNK)-mediated cardioprotection against this condition remain worth further exploring. This study aims to investigate the effect of HNK on angiotensin II (Ang II)-induced myocardial hypertrophy and elucidate the underlying mechanisms. Sprague-Dawley rats were exposed to Ang II infusion, followed by HNK or vehicle treatment for 4 weeks. Our results showed that HNK treatment protected against Ang II-induced myocardial hypertrophy, fibrosis and dysfunction in vivo and inhibited Ang II-induced hypertrophy in neonatal rat ventricular myocytes in vitro. Mechanistically, HNK suppressed the Ang II-induced Nur77 expression at the transcriptional level and promoted ubiquitination-mediated degradation of Nur77, leading to dissociation of the Nur77-LKB1 complex. This facilitated the translocation of LKB1 into the cytoplasm and activated the LKB1-AMPK pathway. Our findings suggest that HNK attenuates pathological remodelling and cardiac dysfunction induced by Ang II by promoting dissociation of the Nur77-LKB1 complex and subsequent activation of AMPK signalling. This study uncovers a novel role of HNK on the LKB1-AMPK pathway to protect against cardiac hypertrophy.

Targeting PDE4B (Phosphodiesterase-4 Subtype B) for Cardioprotection in Acute Myocardial Infarction via Neutrophils and Microcirculation.

BACKGROUND: Timely and complete restoration of blood flow is the most effective intervention for patients with acute myocardial infarction. However, the efficacy is limited by myocardial ischemia-reperfusion (MI/R) injury. PDE4 (phosphodiesterase-4) hydrolyzes intracellular cyclic adenosine monophosphate and it has 4 subtypes A-D. This study aimed to delineate the role of PDE4B (phosphodiesterase-4 subtype B) in MI/R injury. METHODS: Mice were subjected to 30-minute coronary artery ligation, followed by 24-hour reperfusion. Cardiac perfusion was assessed by laser Doppler flow. Vasomotor reactivities were determined in mouse and human coronary (micro-)arteries. RESULTS: Cardiac expression of PDE4B, but not other PDE4 subtypes, was increased in mice following reperfusion. PDE4B was detected primarily in endothelial and myeloid cells of mouse and human hearts. PDE4B deletion strikingly reduced infarct size and improved cardiac function 24-hour or 28-day after MI/R. PDE4B in bone marrow-derived cells promoted MI/R injury and vascular PDE4B further exaggerated this injury. Mechanistically, PDE4B mediated neutrophil-endothelial cell interaction and PKA (protein kinase A)-dependent expression of cell adhesion molecules, neutrophil cardiac infiltration, and release of proinflammatory cytokines. Meanwhile, PDE4B promoted coronary microcirculatory obstruction and vascular permeability in MI/R, without affecting flow restriction-induced thrombosis. PDE4B blockade increased flow-mediated vasodilatation and promoted endothelium-dependent dilatation of coronary arteries in a PKA- and nitric oxide-dependent manner. Furthermore, postischemia administration with piclamilast, a PDE4 pan-inhibitor, improved cardiac microcirculation, suppressed inflammation, and attenuated MI/R injury in mice. Incubation with sera from patients with acute myocardial infarction impaired acetylcholine-induced relaxations in human coronary microarteries, which was abolished by PDE4 inhibition. Similar protection against MI/R-related coronary injury was recapitulated in mice with PDE4B deletion or inhibition, but not with the pure vasodilator, sodium nitroprusside. CONCLUSIONS: PDE4B is critically involved in neutrophil inflammation and microvascular obstruction, leading to MI/R injury. Selective inhibition of PDE4B might protect cardiac function in patients with acute myocardial infarction designated for reperfusion therapy.

Multiparametric MRI-based fusion radiomics for predicting telomerase reverse transcriptase (TERT) promoter mutations and progression-free survival in glioblastoma: a multicentre study.

PURPOSE: This study evaluated the performance of multiparametric magnetic resonance imaging (MRI)-based fusion radiomics models (MMFRs) to predict telomerase reverse transcriptase (TERT) promoter mutation status and progression-free survival (PFS) in glioblastoma patients. METHODS: We retrospectively analysed 208 glioblastoma patients from two hospitals. Quantitative imaging features were extracted from each patient's T1-weighted, T1-weighted contrast-enhanced, and T2-weighted preoperative images. Using a coarse-to-fine feature selection strategy, four radiomics signature models were constructed based on the three MRI sequences and their combination for TERT promoter mutation status and PFS; model performance was subsequently evaluated. Subgroup analyses were performed by the radiomics signature of TERT promoter mutation status and PFS to distinguish patients who could benefit from prolonged temozolomide chemotherapy cycles. RESULTS: TERT promoter mutation status was best predicted by MMFR, with an area under the curve (AUC) of 0.816 and 0.812 for the training and internal validation sets, respectively. The external test set also achieved stable and optimal prediction results (AUC, 0.823). MMFR better predicted patient PFS compared with the single-sequence radiomics signature in the test set (C-index, 0.643 vs 0.561 vs 0.620 vs 0.628). Subgroup analyses showed that more than six cycles of postoperative temozolomide chemotherapy were associated with improved PFS for patients in class 2 (high TERT promoter mutation and high survival rates; HR, 0.222; 95% CI, 0.054 - 0.923; p = 0.025). CONCLUSION: MMFR is an effective method to predict TERT promoter mutations and PFS in patients with glioblastoma. Moreover, subgroup analysis could differentiate patients who may benefit from prolonged TMZ chemotherapy cycles.

GLP-1 receptor agonist liraglutide alleviates kidney injury by regulating nuclear translocation of NRF2 in diabetic nephropathy.

Diabetic nephropathy (DN) is a severe renal disorder that arises as a complication of diabetes. Liraglutide, an analogue of a glucagon-like peptide 1 (GLP-1) receptor agonist, has been shown to decrease diabetes-caused renal damage. Nevertheless, the complete understanding of the roles and mechanism remains unclear. In our study, diabetic rat models were created through a single intraperitoneal injection of streptozotocin (STZ). The level of fasting blood glucose, 24-h urine protein, serum creatinine (Scr) and blood urea nitrogen (BUN) were assessed. Periodic acid-Schiff (PAS) staining was applied to examine the pathological changes in renal tissues. Reactive oxygen species (ROS) formation was measured via dichloro-dihydro-fluorescein diacetate (DCFH-DA) probes. Western blot was conducted to examine the levels of oxidative stress-related and extracellular matrix (ECM)-associated proteins. The nuclear translocation of NRF2 was investigated through immunofluorescence and Western blot assays. We demonstrated that liraglutide attenuated DN-induced oxidative stress and ECM deposition in vitro and in vivo. Liraglutide exerted a reno-protective effect by promoting nuclear translocation of NRF2 in mesangial cells. ML385, an NRF2 inhibitor, counteracted the beneficial impact of liraglutide.

The Effect of Tai Chi (Bafa Wubu) Training and Artificial Intelligence-Based Movement-Precision Feedback on the Mental and Physical Outcomes of Elderly.

(1) Background: This study aims to compare the effects of AI-based exercise feedback and standard training on the physical and mental health outcomes of older adults participating in a 4-week tai chi training program. (2) Methods: Participants were divided into three groups: an AI feedback group received real-time movement accuracy feedback based on AI and inertial measurement units (IMUs), a conventional feedback group received verbal feedback from supervisors, and a control group received no feedback. All groups trained three times per week for 8 weeks. Outcome measures, including movement accuracy, balance, grip strength, quality of life, and depression, were assessed before and after the training period. (3) Results: Compared to pre-training, all three groups showed significant improvements in movement accuracy, grip strength, quality of life, and depression. Only the AI feedback group showed significant improvements in balance. In terms of movement accuracy and balance, the AI feedback group showed significantly greater improvement compared to the conventional feedback group and the control group. (4) Conclusions: Providing real-time AI-based movement feedback during tai chi training offers greater health benefits for older adults compared to standard training without feedback.

Tracing the Flu Symptom Progression via a Smart Face Mask.

Respiration and body temperature are largely influenced by the highly contagious influenza virus, which poses persistent global public health challenges. Here, we present a wireless all-in-one sensory face mask (WISE mask) made of ultrasensitive fibrous temperature sensors. The WISE mask shows exceptional thermosensitivity, excellent breathability, and wearing comfort. It offers highly sensitive body temperature monitoring and respiratory detection capabilities. Capitalizing on the advances in the Internet of Things and artificial intelligence, the WISE mask is further demonstrated by customized flexible circuitry, deep learning algorithms, and a user-friendly interface to continuously recognize the abnormalities of both the respiration and body temperature. The WISE mask represents a compelling approach to tracing flu symptom progression in a cost-effective and convenient manner, serving as a powerful solution for personalized health monitoring and point-of-care systems in the face of ongoing influenza-related public health concerns.

Peritumoral Radiomics for Identification of Telomerase Reverse Transcriptase Promoter Mutation in Patients With Glioblastoma Based on Preoperative MRI.

Purpose: To evaluate the value of intra- and peritumoral deep learning (DL) features based on multi-parametric magnetic resonance imaging (MRI) for identifying telomerase reverse transcriptase (TERT) promoter mutation in glioblastoma (GBM). Methods: In this study, we included 229 patients with GBM who underwent preoperative MRI in two hospitals between November 2016 and September 2022. We used four 2D Convolutional Neural Networks (GoogLeNet, DenseNet121, VGG16, and MobileNetV3-Large) to extract intra- and peritumoral DL features. The Mann-Whitney U test, Pearson correlation analysis, least absolute shrinkage and selection operator, and logistic regression analysis were used for feature selection and construction of DL radiomics (DLR) signatures in different regions. These multi-parametric and multi-region signatures were combined to identify TERT promoter mutation. The area under the receiver operating characteristic curve (AUC) was used to evaluate the effects of the signatures. Results: The signatures based on the DL features from the peritumoral regions with expansion distances of 2 mm, 8 mm, and 10 mm using the GoogLeNet architecture correlated with the optimal AUC values (test set: .823, .753, and .768) in the T2-weighted, T1-weighted contrast-enhanced, and T1-weighted images. Using the stacking fusion method, DLR with multi-parameter and multi-region fusion achieved the best discrimination with AUC values of .948 and .902 in the training and test sets, respectively. Conclusions: The radiomics model based on the fusion of multi-parameter MRI intra- and peritumoral DLR signatures may help to identify TERT promoter mutation in patients with GBM.

Risk factors and clinical characteristics of surgical site infections in athletes undergoing Achilles tendon repair surgery.

Achilles tendon ruptures are common in athletes, requiring surgical intervention. However, the risk of surgical site infections (SSIs) post-surgery poses significant challenges. This study aims to analyse the risk factors and microbial aetiology associated with SSIs in athletes undergoing Achilles tendon repair. A comprehensive retrospective analysis was conducted from May 2021 to July 2023. The study included 25 patients with SSIs (case group) and 50 patients without SSIs (control group) post Achilles tendon repair surgery. Inclusion criteria encompassed patients with medically confirmed Achilles tendon ruptures who underwent surgical repair. Exclusion criteria included prior tendon pathologies and significant chronic illnesses. Diagnostic criteria for SSIs involved symptoms like elevated body temperature and localized tenderness, along with laboratory confirmations such as positive microbiological cultures. The study utilized VITEK® 2 for bacterial identification and involved statistical analyses like univariate and multivariate logistic regression. The study identified Staphylococcus aureus as the primary pathogen in SSIs. Significant risk factors included lack of prophylactic antibiotic use, presence of diabetes, open wounds and prolonged surgery duration. Univariate analysis revealed stark contrasts in these factors between infected and non-infected groups, while multivariate analysis underscored their importance in SSI development. S. aureus emerged as the predominant pathogen in SSIs post Achilles tendon repair. Critical risk factors such as absence of prophylactic antibiotics, diabetes, open wounds and extended surgery duration play a vital role in SSIs. Addressing these factors is essential for better postoperative outcomes in Achilles tendon repair surgeries.

Deep Learning Radiomics for the Assessment of Telomerase Reverse Transcriptase Promoter Mutation Status in Patients With Glioblastoma Using Multiparametric MRI.

BACKGROUND: Studies have shown that magnetic resonance imaging (MRI)-based deep learning radiomics (DLR) has the potential to assess glioma grade; however, its role in predicting telomerase reverse transcriptase (TERT) promoter mutation status in patients with glioblastoma (GBM) remains unclear. PURPOSE: To evaluate the value of deep learning (DL) in multiparametric MRI-based radiomics in identifying TERT promoter mutations in patients with GBM preoperatively. STUDY TYPE: Retrospective. POPULATION: A total of 274 patients with isocitrate dehydrogenase-wildtype GBM were included in the study. The training and external validation cohorts included 156 (54.3 ± 12.7 years; 96 males) and 118 (54 .2 ± 13.4 years; 73 males) patients, respectively. FIELD STRENGTH/SEQUENCE: Axial contrast-enhanced T1-weighted spin-echo inversion recovery sequence (T1CE), T1-weighted spin-echo inversion recovery sequence (T1WI), and T2-weighted spin-echo inversion recovery sequence (T2WI) on 1.5-T and 3.0-T scanners were used in this study. ASSESSMENT: Overall tumor area regions (the tumor core and edema) were segmented, and the radiomics and DL features were extracted from preprocessed multiparameter preoperative brain MRI images-T1WI, T1CE, and T2WI. A model based on the DLR signature, clinical signature, and clinical DLR (CDLR) nomogram was developed and validated to identify TERT promoter mutation status. STATISTICAL TESTS: The Mann-Whitney U test, Pearson test, least absolute shrinkage and selection operator, and logistic regression analysis were applied for feature selection and construction of radiomics and DL signatures. Results were considered statistically significant at P-value <0.05. RESULTS: The DLR signature showed the best discriminative power for predicting TERT promoter mutations, yielding an AUC of 0.990 and 0.890 in the training and external validation cohorts, respectively. Furthermore, the DLR signature outperformed CDLR nomogram (P = 0.670) and significantly outperformed clinical models in the validation cohort. DATA CONCLUSION: The multiparameter MRI-based DLR signature exhibited a promising performance for the assessment of TERT promoter mutations in patients with GBM, which could provide information for individualized treatment. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures.

BACKGROUND: Studies have shown that deep-learning radiomics (DLR) could help differentiate glioblastoma (GBM) from solitary brain metastasis (SBM), but whether integrating demographic-MRI and DLR features can more accurately distinguish GBM from SBM remains uncertain. PURPOSE: To construct and validate a demographic-MRI deep-learning radiomics nomogram (DDLRN) integrating demographic-MRI and DLR signatures to differentiate GBM from SBM preoperatively. STUDY TYPE: Retrospective. POPULATION: Two hundred and thirty-five patients with GBM (N = 115) or SBM (N = 120), randomly divided into a training cohort (90 GBM and 98 SBM) and a validation cohort (25 GBM and 22 SBM). FIELD STRENGTH/SEQUENCE: Axial T2-weighted fast spin-echo sequence (T2WI), T2-weighted fluid-attenuated inversion recovery sequence (T2-FLAIR), and contrast-enhanced T1-weighted spin-echo sequence (CE-T1WI) using 1.5-T and 3.0-T scanners. ASSESSMENT: The demographic-MRI signature was constructed with seven imaging features ("pool sign," "irregular ring sign," "regular ring sign," "intratumoral vessel sign," the ratio of the area of peritumoral edema to the enhanced tumor, the ratio of the lesion area on T2-FLAIR to CE-T1WI, and the tumor location) and demographic factors (age and sex). Based on multiparametric MRI, radiomics and deep-learning (DL) models, DLR signature, and DDLRN were developed and validated. STATISTICAL TESTS: The Mann-Whitney U test, Pearson test, least absolute shrinkage and selection operator, and support vector machine algorithm were applied for feature selection and construction of radiomics and DL models. RESULTS: DDLRN showed the best performance in differentiating GBM from SBM with area under the curves (AUCs) of 0.999 and 0.947 in the training and validation cohorts, respectively. Additionally, the DLR signature (AUC = 0.938) outperformed the radiomics and DL models, and the demographic-MRI signature (AUC = 0.775) was comparable to the T2-FLAIR radiomics and DL models in the validation cohort (AUC = 0.762 and 0.749, respectively). DATA CONCLUSION: DDLRN integrating demographic-MRI and DLR signatures showed excellent performance in differentiating GBM from SBM. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

A novel MRI feature, the cut green pepper sign, can help differentiate a suprasellar pilocytic astrocytoma from an adamantinomatous craniopharyngioma.

OBJECTIVE: There are no specific magnetic resonance imaging (MRI) features that distinguish pilocytic astrocytoma (PA) from adamantinomatous craniopharyngioma (ACP). In this study we compared the frequency of a novel enhancement characteristic on MRI (called the cut green pepper sign) in PA and ACP. METHODS: Consecutive patients with PA (n = 24) and ACP (n = 36) in the suprasellar region were included in the analysis. The cut green pepper sign was evaluated on post-contrast T1WI images independently by 2 neuroradiologists who were unaware of the pathologic diagnosis. The frequency of cut green pepper sign in PA and ACP was compared with Fisher's exact test. RESULTS: The cut green pepper sign was identified in 50% (12/24) of patients with PA, and 5.6% (2/36) with ACP. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the cut green pepper sign for diagnosing PA were 50%, 94.4%, 85.7% and 73.9%, respectively. There was a statistically significant difference in the age of patients with PA with and without the cut green pepper sign (12.3 ± 9.2 years vs. 5.5 ± 4.4 years, p = 0.035). CONCLUSION: The novel cut green pepper sign can help distinguish suprasellar PA from ACP on MRI.

Accuracy and clinical relevance of an automated, algorithm-based analysis of facial signs from selfie images of women in the United States of various ages, ancestries and phototypes: A cross-sectional observational study.

BACKGROUND: Real-life validation is necessary to ensure our artificial intelligence (AI) skin diagnostic tool is inclusive across a diverse and representative US population of various ages, ancestries and skin phototypes. OBJECTIVES: To explore the relevance and accuracy of an automated, algorithm-based analysis of facial signs in representative women of different ancestries, ages and phototypes, living in the same country. METHODS: In a cross-sectional study of selfie images of 1041 US women, algorithm-based analyses of seven facial signs were automatically graded by an AI-based algorithm and by 50 US dermatologists of various profiles (age, gender, ancestry, geographical location). For automated analysis and dermatologist assessment, the same referential skin atlas was used to standardize the grading scales. The average values and their variability were compared with respect to age, ancestry and phototype. RESULTS: For five signs, the grading obtained by the automated system were strongly correlated with dermatologists' assessments (r ≥ 0.75); cheek skin pores were moderately correlated (r = 0.63) and pigmentation signs, especially for the darkest skin tones, were weakly correlated (r = 0.40) to the dermatologist assessments. Age and ancestry had no effect on the correlations. In many cases, the automated system performed better than the dermatologist-assessed clinical grading due to 0.3-0.5 grading unit differences among the dermatologist panel that were not related to any individual characteristic (e.g. gender, age, ancestry, location). The use of phototypes, as discontinuous categorical variables, is likely a limiting factor in the assessments of grading, whether obtained by automated analysis or clinical assessment of the images. CONCLUSIONS: The AI-based automatic procedure is accurate and clinically relevant for analysing facial signs in a diverse and inclusive population of US women, as confirmed by a diverse panel of dermatologists, although skin tone requires further improvement.

Identification of Potential Lead Compounds Targeting Novel Druggable Cavity of SARS-CoV-2 Spike Trimer by Molecular Dynamics Simulations.

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become an urgent public health problem. Spike (S) protein mediates the fusion between the virus and the host cell membranes, consequently emerging as an important target of drug design. The lack of comparisons of in situ full-length S homotrimer structures in different states hinders understanding the structures and revealing the function, thereby limiting the discovery and development of therapeutic agents. Here, the steady-state structures of the in situ full-length S trimer in closed and open states (Sclosed and Sopen) were modeled with the constraints of density maps, associated with the analysis of the dynamic structural differences. Subsequently, we identified various regions with structure and property differences as potential binding pockets for ligands that promote the formation of inactive trimeric protein complexes. By using virtual screening strategy and a newly defined druggable cavity, five ligands were screened with potential bioactivities. Then molecular dynamic (MD) simulations were performed on apo protein structures and ligand bound complexes to reveal the conformational changes upon ligand binding. Our simulation results revealed that sulforaphane (SFN), which has the best binding affinity, could inhibit the conformational changes of S homotrimer that would occur during the viral membrane fusion. Our results could aid in the understanding of the regulation mechanism of S trimer aggregation and the structure-activity relationship, facilitating the development of potential antiviral agents.

Risk factors for surgical site infections following open reduction and internal fixation in patients with tibial plateau fractures.

This retrospective cohort study aimed to identify the risk factors associated with postoperative wound infections in patients undergoing open reduction and internal fixation for tibial plateau fractures. The study was conducted between January 2019 and December 2022, with stringent inclusion and exclusion criteria. Data were collected from the Electronic Health Record system, including demographic information, lifestyle habits, comorbid conditions and surgical variables like preoperative American Society of Anesthesiologists (ASA) scores. The IBM Statistical Package for the Social Sciences, version 27.0, was utilized for rigorous statistical analyses. Univariate analysis identified several factors, such as body mass index (BMI), smoking status and diabetes mellitus, as significant predictors of postoperative wound infection. Multivariate logistic regression revealed that BMI, type of fracture (open vs. closed), surgery duration exceeding 150 min, preoperative albumin levels below 35 g/L and preoperative ASA score of 3 or higher were significant independent risk factors (p < 0.05). Patients with open fractures, preoperative malnutrition, elevated preoperative ASA scores and a history of smoking are at a heightened risk of developing postoperative wound infections. Timely preoperative evaluation of these risk factors is crucial for minimizing the risk of surgical site infections and optimizing clinical management.

Objective and automatic grading system of facial signs from selfie pictures of South African women: Characterization of changes with age and sun-exposures.

OBJECTIVE: To evaluate the capacity of the automatic detection system to accurately grade, from smartphones' selfie pictures, the severity of fifteen facial signs in South African women and their changes related to age and sun-exposure habits. METHODS: A two-steps approach was conducted based on self-taken selfie images. At first, to assess on 306 South African women (20-69 years) enrolled in Pretoria area (25.74°S, 28.22°E), age changes on fifteen facial signs measured by an artificial intelligence (AI)-based automatic grading system previously validated by experts/dermatologists. Second, as these South African panelists were recruited according to their usual behavior toward sun-exposure, that is, nonsun-phobic (NSP, N = 151) and sun-phobic (SP, N = 155) and through their regular and early use of a photo-protective product, to characterize the facial photo-damages. RESULTS: (1) The automatic scores showed significant changes with age, by decade, of sagging and wrinkles/texture (p < 0.05) after 20 and 30 years, respectively. Pigmentation cluster scores presented no significant changes with age whereas cheek skin pores enlarged at a low extent with two plateaus at thirties and fifties. (2) After 60 years, a significantly increased severity of wrinkles/texture and sagging was observed in NSP versus SP women (p < 0.05). A trend of an increased pigmentation of the eye contour (p = 0.06) was observed after 50 years. CONCLUSION: This work illustrates specific impacts of aging and sun-exposures on facial signs of South African women, when compared to previous experiments conducted in Europe or East Asia. Results significantly confirm the importance of sun-avoidance coupled with photo-protective measures to avoid long-term skin damages. In inclusive epidemiological studies that aim at investigating large human panels in very different contexts, the AI-based system offers a fast, affordable and confidential approach in the detection and quantification of facial signs and their dependency with ages, environments, and lifestyles.

Nanoconfining solution-processed organic semiconductors for emerging optoelectronics.

Solution-processable organic materials for emerging electronics can generally be divided into two classes of semiconductors, organic small molecules and polymers. The theoretical thermodynamic limits of device performance are largely determined by the molecular structure of these compounds, and advances in synthetic routes have led to significant progress in charge mobilities and light conversion and light emission efficiencies over the past several decades. Still, the uncontrolled formation of out-of-equilibrium film microstructures and unfavorable polymorphs during rapid solution processing remains a critical bottleneck facing the commercialization of these materials. This tutorial review provides an overview of the use of nanoconfining scaffolds to impose order onto solution-processed semiconducting films to overcome this limitation. For organic semiconducting small molecules and polymers, which typically exhibit strong crystal growth and charge transport anisotropy along different crystallographic directions, nanoconfining crystallization within nanopores and nanogrooves can preferentially orient the fast charge transport direction of crystals with the direction of current flow in devices. Nanoconfinement can also stabilize high-performance metastable polymorphs by shifting their relative Gibbs free energies via increasing the surface area-to-volume ratio. Promisingly, such nanoconfinement-induced improvements in film and crystal structures have been demonstrated to enhance the performance and stability of emerging optoelectronics that will enable large-scale manufacturing of flexible, lightweight displays and solar cells.

Dapagliflozin: a sodium-glucose cotransporter 2 inhibitor, attenuates angiotensin II-induced cardiac fibrotic remodeling by regulating TGFß1/Smad signaling.

BACKGROUND: Cardiac remodeling is one of the major risk factors for heart failure. In patients with type 2 diabetes, sodium-glucose cotransporter 2 (SGLT2) inhibitors reduce the risk of the first hospitalization for heart failure, possibly through glucose-independent mechanisms in part, but the underlying mechanisms remain largely unknown. This study aimed to shed light on the efficacy of dapagliflozin in reducing cardiac remodeling and potential mechanisms. METHODS: Sprague-Dawley (SD) rats, induced by chronic infusion of Angiotensin II (Ang II) at a dose of 520 ng/kg per minute for 4 weeks with ALZET® mini-osmotic pumps, were treated with either SGLT2 inhibitor dapagliflozin (DAPA) or vehicle alone. Echocardiography was performed to determine cardiac structure and function. Cardiac fibroblasts (CFs) were treated with Ang II (1 µM) with or without the indicated concentration (0.5, 1, 10 µM) of DAPA. The protein levels of collagen and TGF-ß1/Smad signaling were measured along with body weight, and blood biochemical indexes. RESULTS: DAPA pretreatment resulted in the amelioration of left ventricular dysfunction in Ang II-infused SD rats without affecting blood glucose and blood pressure. Myocardial hypertrophy, fibrosis and increased collagen synthesis caused by Ang II infusion were significantly inhibited by DAPA pretreatment. In vitro, DAPA inhibit the Ang II-induced collagen production of CFs. Immunoblot with heart tissue homogenates from chronic Ang II-infused rats revealed that DAPA inhibited the activation of TGF-ß1/Smads signaling. CONCLUSION: DAPA ameliorates Ang II-induced cardiac remodeling by regulating the TGF-ß1/Smad signaling in a non-glucose-lowering dependent manner.

Cardiovascular Biology of Prostanoids and Drug Discovery.

Prostanoids are a group of bioactive lipids that are synthesized de novo from membrane phospholipid-released arachidonic acid and have diverse functions in normal physiology and disease. NSAIDs (non-steroidal anti-inflammatory drugs), which are among the most commonly used medications, ameliorate pain, fever, and inflammation by inhibiting COX (cyclooxygenase), which is the rate-limiting enzyme in the biosynthetic cascade of prostanoids. The use of NSAIDs selective for COX-2 inhibition increases the risk of a thrombotic event (eg, myocardial infarction and stroke). All NSAIDs are associated with an increased risk of heart failure. Substantial variation in clinical responses to aspirin exists and is associated with cardiovascular risk. Limited clinical studies suggest the involvement of prostanoids in vascular restenosis in patients who received angioplasty intervention. mPGES (microsomal PG [prostaglandin] E synthase)-1, an alternative target downstream of COX, has the potential to be therapeutically targeted for inflammatory disease, with diminished thrombotic risk relative to selective COX-2 inhibitors. mPGES-1-derived PGE2 critically regulates microcirculation via its receptor EP (receptor for prostanoid E) 4. This review summarizes the actions and associated mechanisms for modulating the biosynthesis of prostanoids in thrombosis, vascular remodeling, and ischemic heart disease as well as their therapeutic relevance.

Comparing the self-perceived effects of a facial anti-aging product to those automatically detected from selfie images of Chinese women of different ages and cities.

OBJECTIVE: To assess the agreement, after 1-month application of a popular and efficient anti-aging product, between self-perceived facial signs of aging and those detected and graded by an automatic A.I-based system, using smartphones' selfie images. MATERIAL AND METHODS: Of 1065 Chinese women, aged 18-60 years, from eight different Chinese cities were recruited. They were asked to apply daily, for 1 month, a referential anti-aging product onto their whole face. Selfie images were taken by all subjects at D0 and D28 and sent to our facilities for being analyzed through 10 different facial signs. At D28 , all subjects were asked to fill a questionnaire on the status of their faces, through six general statements. RESULTS: A global agreement between both approaches is reached, particularly among women older than 40 years where the severity of facial signs is already more pronounced or among younger women who present at least facial signs scored above one grading units. This limit becomes, therefore, a prerequisite in the recruitment of Chinese subjects in the case of anti-aging applied studies and possible automatically based on automatic grading system. When respecting such conditions, the positive effects of the product on most facial signs can be demonstrated after 28 days of successive applications. CONCLUSION: Such methodological approach paves the road in fulfilling the need of consumers of a better transparency in the claims of an anti-aging product.

Japanese experiment of a complete and objective automatic grading system of facial signs from selfie pictures: Validation with dermatologists and characterization of changes due to age and sun exposures.

OBJECTIVE: To evaluate the capacity of the automatic detection system to accurately grade, from smartphones' selfie pictures, the severity of ten facial signs in Japanese women and their changes due to age and sun exposures. METHODS: A three-step approach was conducted, based on self-taken selfie images. At first, to check on 310 Japanese women (18-69 years) enrolled in the northerner Hokkaido area (latitude 43.2°N), how, on ten facial signs, the A.I-based automatic grading system may correlate with dermatological assessments, taken as reference. Second, to assess and compare age changes in 310 Japanese and 112 Korean women. Third, as these Japanese panelists were recruited according to their usual behavior toward sun exposure, that is, non-sun-phobic (NSP, N = 114) and sun-phobic (SP, N = 196), and through their regular and early use of a photo-protective product, to characterize the facial photo-damages. RESULTS: (a) On the ten facial signs, detected automatically, nine were found significantly (P < .0001) highly correlated with the evaluations made by three Japanese dermatologists (Wrinkles: r = .75; Sagging: r = .80; Pigmentation: r = .75). (b) The automatic scores showed significant changes with age, by decade, of Wrinkles/Texture, Pigmentation, and Ptosis/Sagging (P < .05). (c) After 45 years, a significantly increased severity of Wrinkles/Texture and Pigmentation was observed in NSP vs. SP women (P < .05). A trend of an increased Ptosis/Sagging (P = .09) was observed. CONCLUSION: This work illustrates, for the first time through investigations conducted at home, some impacts of aging and sun exposures on facial signs of Japanese women. Results significantly confirm the importance of sun avoidance coupled with photo-protective measures. In epidemiological studies, the AI-based system offers a fast, affordable, and confidential approach in detection and quantification of facial signs and their dependence with ages, environments and lifestyles.