The individual difference of motor imagery ability evoked by visual stimulus and its personality manifestation.

Motor imagery has been commonly studied as a means of motor rehabilitation but, the individual differences limit its practical application. Visually evoked motor imagery has been widely highlighted by researchers because of its vivid stimulus. However, this modality is still not applicable to all persons. In this study, we studied the different performances of the visually evoked motor imagery between subjects and tried to explore the personality manifestation which can result in this performance. We found that conscientiousness and openness have negative connections with the performance of visually evoked motor imagery. To compare with spontaneous motor imagery, the visually evoked motor imagery reflects less personality difference between subjects with good and bad performances on motor imagery. This indicate that visually stimulus may increase the pervasive application of motor imagery. This study may provide benefits to predict the rehabilitation effect and to rapidly select the suitable motor rehabilitation methods.

SENP3 attenuates foam cell formation by deSUMOylating NLRP3 in macrophages stimulated with ox-LDL.

SUMO-specific protease 3 (SENP3) participates in the removal of SUMOylation and maintains the balance of the SUMO system, which ensures normal functioning of substrates and cellular activities. In the present study, we found that SENP3 expression was significantly reduced in ox-LDL-stimulated macrophages. SENP3 overexpression suppressed and SENP3 knockdown promoted macrophage foam cell formation. Moreover, SENP3 inhibited cholesterol uptake, CD36 expression, and NOD-like receptor thermal protein domain-associated protein 3 (NLRP3) inflammasome activation in ox-LDL-stimulated macrophages. Ox-LDL-stimulated NLRP3 SUMOylation was reduced by SENP3. Blocking NLRP3 SUMOylation inhibited foam cell formation and NLRP3 inflammasome activation. Thus, this study revealed that SENP3 inhibits macrophage foam cell formation by deSUMOylating NLRP3 and regulating NLRP3 inflammasome activation, which may provide a potentially innovative approach to treatment of atherosclerosis.

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.

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.

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.

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.

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.

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.

Self-Patterning Tetrathiafulvalene Crystalline Films.

Tetrathiafulvalene (TTF) crystals grown from the melt are organized as spherulites in which helicoidal fibrils growing radially from the nucleation center twist in concert with one another. Alternating bright and dark concentric bands are apparent when films are viewed between crossed polarizers, indicating an alternating pattern of crystallographic faces exposed at the film surface. Band-dependent reorganization of the TTF crystals was observed during exposure to methanol vapor. Crystalline growth appears on bright bands at the expense of the dark bands. After a 24 h period of exposure to methanol vapor, the original spherulites were completely restructured, and the films comprise isolated, concentric circles of crystallites whose orientations are determined by the initial TTF crystal fibril orientation. While the surface of these outgrowths appears faceted and smooth, cross-sectional SEM images revealed a semiporous inner structure, suggesting solvent-vapor-induced recrystallization. Collectively, these results show that crystal twisting can be used to rhythmically redistribute material. Crystal twisting is a common and often controllable phenomenon independent of molecular or crystal structure and therefore offers a generalizable path to spontaneous pattern formation in a wide range of materials.

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.

Assessment of functional prognosis of anterior cruciate ligament reconstruction in athletes based on a body shape index.

BACKGROUND: A healthy body shape is essential to maintain athletes' sports level. At present, little is known about the effect of athletes' body shape on anterior cruciate ligament reconstruction (ACLR). Moreover, the relationship between body shape and variables such as knee joint function after operation and return to the field has not been well studied. AIM: To verify the relationship between a body shape index (ABSI) and the functional prognosis of the knee after ACLR in athletes with ACL injuries. METHODS: We reviewed 76 athletes with unilateral ACL ruptures who underwent ACLR surgery in the First Hospital of Shanxi Medical University between 2017 and 2020, with a follow-up period of more than 24 mo. First, all populations were divided into a High-ABSI group (ABSI > 0.835, n = 38) and a Low-ABSI group (ABSI < 0.835, n = 38) based on the arithmetic median (0.835) of ABSI values. The primary exposure factor was ABSI, and the outcome indicators were knee function scores as well as postoperative complications. The correlation between ABSI and postoperative knee function scores and postoperative complications after ACLR were analyzed using multifactorial logistic regression. RESULTS: The preoperative knee function scores of the two groups were similar. The surgery and postoperative rehabilitation exercises, range of motion (ROM) compliance rate, Lysholm score, and Knee Injury and Osteoarthritis Outcome Score of the two groups gradually increased, whereas the quadriceps atrophy index gradually decreased. The knee function scores were higher in the Low-ABSI group than in the High-ABSI group at the 24-mo postoperative follow-up (P < 0.05). In multifactorial logistic regression, ABSI was a risk factor of low knee joint function score after surgery, specifically low ROM scores (odds ratio [OR] = 1.31, 95% confidence interval [CI] [1.10-1.44]; P < 0.001), low quadriceps atrophy index (OR = 1.11, 95%CI [0.97-1.29]; P < 0.05), low Lysholm scores (OR = 2.34, 95%CI [1.78-2.94]; P < 0.001), low symptoms (OR = 1.14, 95%CI [1.02-1.34]; P < 0.05), low activity of daily living (OR = 1.34, 95%CI [1.18-1.65]; P < 0.05), low sports (OR = 2.47, 95%CI [1.78-2.84]; P < 0.001), and low quality of life (OR = 3.34, 95%CI [2.88-3.94]; P < 0.001). ABSI was also a risk factor for deep vein thrombosis of the lower limb (OR = 2.14, 95%CI [1.88-2.36], P < 0.05] and ACL recurrent rupture (OR = 1.24, 95%CI [0.98-1.44], P < 0.05) after ACLR. CONCLUSION: ABSI is a risk factor for the poor prognosis of knee function in ACL athletes after ACLR, and the risk of poor knee function after ACLR, deep vein thrombosis of lower limb, and ACL recurrent rupture gradually increases with the rise of ABSI.

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.

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.

Microsomal prostaglandin E synthase-1 inhibition prevents adverse cardiac remodelling after myocardial infarction in mice.

BACKGROUND AND PURPOSE: Heart failure with reduced ejection fraction (HFrEF) is a major consequence of myocardial infarction (MI). The microsomal prostaglandin E synthase-1 (mPGES-1)/PGE2 pathway has been shown to constrain reperfusion injury after acute myocardial ischaemia. However, it is unknown whether pharmacological inhibition of mPGES-1, a target with lower risk of thrombosis compared with selective inhibition of cyclooxygenase-2, affects chronic cardiac remodelling after MI. EXPERIMENTAL APPROACH: Mice were subjected to left anterior descending coronary artery ligation, followed by intraperitoneal treatment with the mPGES-1 inhibitor compound III (CIII) or 118, celecoxib (cyclooxygenase-2 inhibitor) or vehicle, once daily for 28 days. Urinary prostanoid metabolites were measured by liquid chromatography-tandem mass spectrometry. KEY RESULTS: Chronic administration of CIII improved cardiac function in mice after MI compared with vehicle or celecoxib. CIII did not affect thrombogenesis or blood pressure. In addition, CIII reduced infarct area, augmented scar thickness, decreased collagen I/III ratio, decreased the expression of fibrosis-related genes and increased capillary density in the ischaemic area. Shunting to urinary metabolites of PGI2 , not thromboxane B2 or PGD2 , after inhibition of mPGES-1 was positively correlated with cardiac function after MI. CIII administration significantly increased urinary PGI2 /PGE2 metabolite ratio compared to vehicle or celecoxib. The PGI2 /PGE2 metabolite ratio correlated positively with ejection fraction, fractional shortening and scar thickness. Treatment with 118 also improved cardiac function. CONCLUSION AND IMPLICATIONS: Inhibition of mPGES-1 prevented chronic adverse cardiac remodelling via an augmented PGI2 /PGE2 metabolite ratio and therefore represents a potential therapeutic strategy for development of HFrEF after MI.

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.

A Novel Ionic Conductive Polyurethane Based on Deep Eutectic Solvent Continuing Traditional Merits.

Artificial intelligence (AI) has become increasingly popular along with the development of the bionic neural system. Ionic conductors play an important role in the AI system due to the ability of bionic sensing and signal transporting. Traditional low-polarity elastomers possess outstanding mechanical strength and stability, such as polyurethane, which is difficult to be directly endowed with ionic conductivity without impairing its properties. Herein, we have first put forward a new approach to synthesize a liquid-free ionic conductive polyurethane (CPU) through one-step copolymerization between a green deep eutectic solvent (DES) and a prepolymer of polyurethane. The as-prepared CPU can retain the native properties of the traditional polyurethane (PU) such as the homogeneous phase, ease of molding, high transparency (about 93.3%), and excellent mechanical properties. By introducing the DES as the covalent cross-linking agent and ionic conductor at the same time, the CPU also has fine ionic conductivity (3.78 × 10-5 S cm-1), environmental resistance like anti-freezing (-20 °C), and solvent resistance. Based on the excellent conductivity and mechanical strength, the flexible CPU can be applied as a sensing element in pressure sensors. The CPU-based sensor has presented long-term stability, high sensitivity, and wide-ranging response (0.17-3.28 MPa) to the applied pressure, which will be suitable for the industrial demands for practical applications.

Deconstruction of Knee Cartilage Injury in Athletes Using MR Images Based on Artificial Intelligence Segmentation Algorithm.

The knee joint is the second largest joint in the human body, with a wide range of functional activities and strong support for the human body. Moreover, the cartilage of the knee joint is hyaline cartilage, which is relatively brittle, so it is most vulnerable to trauma. In clinical work, the damage of articular cartilage is a disease with a high rate of orthopedic visits. In this paper, all the experimental group cases included in the observation were patients with acute articular cartilage injury or OA diagnosed by knee arthroscopy. All experimental groups and control groups did not have any strenuous exercise one day before MRI (magnetic resonance imaging), and they sat for 30 minutes before the examination. Conventional scanning sagittal FSE-T1WI, FSE-T2WI, FS-FSE-T1WI, FS-FSE-T2WI, FS-PDWI, and coronal FS-PDWI sequence. In the normal control group, after the T2 color map was generated in the workstation, the articular cartilage was divided on the midsagittal plane, and the patellar cartilage and tibial plateau were roughly divided into upper, middle, lower and anterior, middle, and posterior thirds. In order to ensure the maximum comparability of the results, an artificial intelligence segmentation algorithm is used to divide the region of interest equally, and the central part of each partition is selected as much as possible for measurement. The T2 values of the three partitions of each cartilage were measured one by one and averaged. For the comparison results of T2 value of cartilage in the same part: according to patellar cartilage, femoral cartilage, and tibial cartilage, the P values are 0.973, 0.150, and 0.525, respectively. Therefore, early detection and early treatment of articular cartilage injury are of great significance to the performance of athletes' competition level and the extension of sports life.

A portable clustering algorithm based on compact neighbors for face tagging.

We focus on the following problem: Given a collection of unlabeled facial images, group them into the individual identities where the number of subjects is not known. To this end, a Portable clustering algorithm based on Compact Neighbors called PCN is proposed. (1) Benefiting from the compact neighbor, the local density of each sample can be determined automatically and only one user-specified parameter, the number of nearest neighbors k, is involved in our model. (2) More importantly, the performance of PCN is not sensitive to the number of nearest neighbors. Therefore this parameter is relatively easy to determine in practical applications. (3) The computational overhead of PCN is O(nk(k2+log(nk))) that is nearly linear with respect to the number of samples, which means it is easily scalable to large-scale problems. In order to verify the effectiveness of PCN on the face clustering problem, extensive experiments based on a two-stage framework (extracting features using a deep model and performing clustering in the feature space) have been conducted on 16 middle- and 5 large-scale benchmark datasets. The experimental results have shown the efficiency and effectiveness of the proposed algorithm, compared with state-of-the-art methods. [code].

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.