Local Implicit Normalizing Flow for Arbitrary-Scale Image Super-Resolution

Flow-based methods have demonstrated promising results in addressing the ill-posed nature of super-resolution (SR) by learning the distribution of high-resolution (HR) images with the normalizing flow. However, these methods can only perform a predefined fixed-scale SR, limiting their potential in real-world applications. Meanwhile, arbitrary-scale SR has gained more attention and achieved great progress. Nonetheless, previous arbitrary-scale SR methods ignore the ill-posed problem and train the model with per-pixel L1 loss, leading to blurry SR outputs. In this work, we propose "Local Implicit Normalizing Flow" (LINF) as a unified solution to the above problems. LINF models the distribution of texture details under different scaling factors with normalizing flow. Thus, LINF can generate photo-realistic HR images with rich texture details in arbitrary scale factors. We evaluate LINF with extensive experiments and show that LINF achieves the state-of-the-art perceptual quality compared with prior arbitrary-scale SR methods.Comment: CVPR 2023 camera-ready versio

A Novel Approach for Defect Detection of Wind Turbine Blade Using Virtual Reality and Deep Learning

Wind turbines are subjected to continuous rotational stresses and unusual external forces such as storms, lightning, strikes by flying objects, etc., which may cause defects in turbine blades. Hence, it requires a periodical inspection to ensure proper functionality and avoid catastrophic failure. The task of inspection is challenging due to the remote location and inconvenient reachability by human inspection. Researchers used images with cropped defects from the wind turbine in the literature. They neglected possible background biases, which may hinder real-time and autonomous defect detection using aerial vehicles such as drones or others. To overcome such challenges, in this paper, we experiment with defect detection accuracy by having the defects with the background using a two-step deep-learning methodology. In the first step, we develop virtual models of wind turbines to synthesize the near-reality images for four types of common defects - cracks, leading edge erosion, bending, and light striking damage. The Unity perception package is used to generate wind turbine blade defects images with variations in background, randomness, camera angle, and light effects. In the second step, a customized U-Net architecture is trained to classify and segment the defect in turbine blades. The outcomes of U-Net architecture have been thoroughly tested and compared with 5-fold validation datasets. The proposed methodology provides reasonable defect detection accuracy, making it suitable for autonomous and remote inspection through aerial vehicles

Protective Effects of Morus Root Extract (MRE) Against Lipopolysaccharide-Activated RAW264.7 Cells and CCl4-Induced Mouse Hepatic Damage

Background/Aims: Inflammation is one of the main contributors to chronic diseases such as cancer. It is of great value to identify the potential activity of various medicinal plants for regulating or blocking uncontrolled chronic inflammation. We investigated whether the root extract of Morus australis possesses antiinflammatory and antioxidative stress potential and hepatic protective activity. Methods: The microwave-assisted extractionwere was used to prepare the ethanol extract from the dried root of Morus australis (MRE), including polyphenolic and flavonoid contents. Lipopolysaccharide (LPS)-stimulated RAW264.7 cells was examined the anti-inflammatory and anti-oxidative potential of MRE. CCl4-induced mouse hepatic damage were performed to detect the hepatic protective potential in vivo. Immunohistochemistry (IHC) and western blot assays were used to detect target proteins. Results: MRE contained approximately 23% phenolic compounds and 3% flavonoids. The major flavonoid component of MRE was morusin. MRE and morusin inhibited lipopolysaccharide-induced production of nitrite and prostaglandin E2 in RAW264.7 cells. MRE and morusin also suppressed the formation of intracellular reactive oxygen species and the expression of iNOS and COX-2. In an in vivo study, a thiobarbituric acid reactive substances assay showed that MRE inhibited CCl4-induced oxidative stress and expression of nitrotyrosine. MRE also decreased CCl4-induced hepatic iNOS and COX-2 expression, as well as CCl4-induced hepatic inflammation and necrosis in mice. Conclusion: MRE exhibited antiinflammatory and hepatic protective activity

Improving Voice Outcomes After Thyroid Surgery – Review of Safety Parameters for Using Energy-Based Devices Near the Recurrent Laryngeal Nerve

Technological advances in thyroid surgery have rapidly increased in recent decades. Specifically, recently developed energy-based devices (EBDs) enable simultaneous dissection and sealing tissue. EBDs have many advantages in thyroid surgery, such as reduced blood loss, lower rate of post-operative hypocalcemia, and shorter operation time. However, the rate of recurrent laryngeal nerve (RLN) injury during EBD use has shown statistically inconsistent. EBDs generate high temperature that can cause iatrogenic thermal injury to the RLN by direct or indirect thermal spread. This article reviews relevant medical literatures of conventional electrocauteries and different mechanisms of current EBDs, and compares two safety parameters: safe distance and cooling time. In general, conventional electrocautery generates higher temperature and wider thermal spread range, but when applying EBDs near the RLN adequate activation distance and cooling time are still required to avoid inadvertent thermal injury. To improve voice outcomes in the quality-of-life era, surgeons should observe safety parameters and follow the standard procedures when using EBDs near the RLN in thyroid surgery

Case report: Presentations and cytokine profiles of inflammatory non-pulmonary COVID-19 and related diseases in children

The coronavirus disease 2019 (COVID-19) pandemic has evolved to dynamic waves of different SARS-CoV-2 variants. Initially, children diagnosed with COVID-19 presented pulmonary involvement characterized by mild diseases. In the later waves of the COVID-19 pandemic, life-threatening non-pulmonary inflammatory diseases such as (1) aseptic meningoencephalitis (ME), (2) acute necrotizing encephalopathies (ANE), and (3) multisystem inflammatory syndrome in children (MIS-C) have been reported, affecting the pediatric population. To alert timely identification and prevention of the life-threatening non-pulmonary COVID-19, we present the cases of ME, ANE, and MIS-C in terms of clinical manifestation, cytokine profile, and follow-up consequences. Based on the immunopathogenesis and risk factors associated with non-pulmonary COVID-19, we delineate strategies for an early diagnosis and treatment to reduce morbidity and mortality in children

Pretreatment carcinoembryonic antigen level is a risk factor for para-aortic lymph node recurrence in addition to squamous cell carcinoma antigen following definitive concurrent chemoradiotherapy for squamous cell carcinoma of the uterine cervix

<p>Abstract</p> <p>Background</p> <p>To identify pretreatment carcinoembryonic antigen (CEA) levels as a risk factor for para-aortic lymph node (PALN) recurrence following concurrent chemoradiotherapy (CCRT) for cervical cancer.</p> <p>Methods</p> <p>From March 1995 to January 2008, 188 patients with squamous cell carcinoma (SCC) of the uterine cervix were analyzed retrospectively. No patient received PALN irradiation as the initial treatment. CEA and squamous cell carcinoma antigen (SCC-Ag) were measured before and after radiotherapy. PALN recurrence was detected by computer tomography (CT) scans. We analyzed the actuarial rates of PALN recurrence by using Kaplan-Meier curves. Multivariate analyses were carried out with Cox regression models. We stratified the risk groups based on the hazard ratios (HR).</p> <p>Results</p> <p>Both pretreatment CEA levels ≥ 10 ng/mL and SCC-Ag levels < 10 ng/mL (<it>p </it>< 0.001, HR = 8.838), SCC-Ag levels ≥ 40 ng/mL (<it>p </it>< 0.001, HR = 12.551), and SCC-Ag levels of 10-40 ng/mL (<it>p </it>< 0.001, HR = 4.2464) were significant factors for PALN recurrence. The corresponding 5-year PALN recurrence rates were 51.5%, 84.8%, and 27.5%, respectively. The 5-year PALN recurrence rate for patients with both low (< 10 ng/mL) SCC and CEA was only 9.6%. CEA levels ≥ 10 ng/mL or SCC-Ag levels ≥ 10 ng/mL at PALN recurrence were associated with overall survival after an isolated PALN recurrence. Pretreatment CEA levels ≥ 10 ng/mL were also associated with survival after an isolated PALN recurrence.</p> <p>Conclusions</p> <p>Pretreatment CEA ≥ 10 ng/mL is an additional risk factor of PALN relapse following definitive CCRT for SCC of the uterine cervix in patients with pretreatment SCC-Ag levels < 10 ng/mL. More comprehensive examinations before CCRT and intensive follow-up schedules are suggested for early detection and salvage in patients with SCC-Ag or CEA levels ≥ 10 ng/mL.</p

Molecular Cloning of a New Immunomodulatory Protein from Anoectochilus formosanus which Induces B Cell IgM Secretion through a T-Independent Mechanism

An immunomodulatory protein (IPAF) was purified and cloned from Anoectochilus formosanus, an Orchidaceae herbal plant in Asia. The major targeting immune cells of IPAF and its modulating effects toward B lymphocytes were investigated. Rapid amplification of cDNA ends (RACE) was conducted to clone the IPAF gene, and the obtained sequence was BLAST compared on the NCBI database. MACS-purified mouse T and B lymphocytes were stimulated with IPAF and the cell proliferation, activation, and Igs production were examined. IPAF comprised a 25 amino acids signal peptide and a 138 amino acids protein which was homologous to the lectins from Orchidaceae plant. IPAF selectively induced the cell proliferation in mouse splenic B lymphocytes but not T lymphocytes. The IPAF-induced B cells exhibited increased CD69 and MHC class II expression, and a dose- and time-dependent enhancement in IgM production. These results suggested potential benefits of IPAF to strengthen the humoral immunity

Clinical association of body symptoms and primary dysmenorrhea among young and middle-aged women: an observational study

BackgroundThe mechanism of primary dysmenorrhea remains unraveled. Body symptoms not related to menstrual cycle may indicate the potential mechanism of primary dysmenorrhea, albeit the association has not been proven. Furthermore, we hypothesize that the cumulative burden of these symptoms may influence the incidence of primary dysmenorrhea. Therefore, we aim to design a study to identify bodily symptoms potentially related to primary dysmenorrhea and test the hypothesis in understanding and managing primary dysmenorrhea.MethodsA total of 3,140 female participants aged 30–50 years were enrolled from the Taiwan Biobank. Stepwise logistic regression was used to select potential body symptoms associated with primary dysmenorrhea from a training dataset. Selected body symptoms were validated in a test dataset. Female participants without dysmenorrhea in the baseline survey were divided into two groups (with and without body symptoms) in a baseline survey. Cox regression and Kaplan-Meier survival analyses were used to evaluate the risk of incident dysmenorrhea.ResultsWomen with body symptoms such as cold extremities (adjusted odds ratio [AdjOR], 1.53, 95% confidence interval [CI], 1.12–2.21), dull abdominal pain (AdjOR, 1.45, 95% CI, 1.03–2.04), and edema (AdjOR, 1.43, 95% CI, 1.02–1.99) were significantly associated with dysmenorrhea. Women with the three body symptoms had a significantly higher risk of dysmenorrhea (adjusted hazard ratio, 2.74, 95%CI, 1.18–6.31; log-rank test, p = 0.0017) than those without body symptoms. Trend analysis showed that the risk of dysmenorrhea increased with the number of body symptoms (p-trend = 0.025).ConclusionThis study identified cold extremities, dull abdominal pain, and edema as predictors of primary dysmenorrhea, with their accumulation associated with a higher risk of developing dysmenorrhea. We propose that further research explore pharmacological and non-pharmacological interventions targeting these symptoms, as they may provide long-term benefits in the management of primary dysmenorrhea

International Validation of the SORG Machine-learning Algorithm for Predicting the Survival of Patients with Extremity Metastases Undergoing Surgical Treatment

Background The Skeletal Oncology Research Group machine-learning algorithms (SORG-MLAs) estimate 90- day and 1-year survival in patients with long-bone metastases undergoing surgical treatment and have demonstrated good discriminatory ability on internal validation. However, the performance of a prediction model could potentially vary by race or region, and the SORG-MLA must be externally validated in an Asian cohort. Furthermore, the authors of the original developmental study did not consider the Eastern Cooperative Oncology Group (ECOG) performance status, a survival prognosticator repeatedly validated in other studies, in their algorithms because of missing data. Questions/purposes (1) Is the SORG-MLA generalizable to Taiwanese patients for predicting 90-day and 1-year mortality? (2) Is the ECOG score an independent factor associated with 90-day and 1-year mortality while controlling for SORG-MLA predictions? Methods All 356 patients who underwent surgery for long-bone metastases between 2014 and 2019 at one tertiary care center in Taiwan were included. Ninety-eight percent (349 of 356) of patients were of Han Chinese descent. The median (range) patient age was 61 years (25 to 95), 52% (184 of 356) were women, and the median BMI was 23 kg/m2 (13 to 39 kg/m2). The most common primary tumors were lung cancer (33% [116 of 356]) and breast cancer (16% [58 of 356]). Fifty-five percent (195 of 356) of patients presented with a complete pathologic fracture. Intramedullary nailing was the most commonly performed type of surgery (59% [210 of 356]), followed by plate screw fixation (23% [81 of 356]) and endoprosthetic reconstruction (18% [65 of 356]). Six patients were lost to follow-up within 90 days; 30 were lost to follow-up within 1 year. Eighty-five percent (301 of 356) of patients were followed until death or for at least 2 years. Survival was 82% (287 of 350) at 90 days and 49% (159 of 326) at 1 year. The model's performance metrics included discrimination (concordance index [c-index]), calibration (intercept and slope), and Brier score. In general, a c-index of 0.5 indicates random guess and a c-index of 0.8 denotes excellent discrimination. Calibration refers to the agreement between the predicted outcomes and the actual outcomes, with a perfect calibration having an intercept of 0 and a slope of 1. The Brier score of a prediction model must be compared with and ideally should be smaller than the score of the null model. A decision curve analysis was then performed for the 90-day and 1-year prediction models to evaluate their net benefit across a range of different threshold probabilities. A multivariate logistic regression analysis was used to evaluate whether the ECOG score was an independent prognosticator while controlling for the SORG-MLA's predictions. We did not perform retraining/recalibration because we were not trying to update the SORG-MLA algorithm in this study. Results The SORG-MLA had good discriminatory ability at both timepoints, with a c-index of 0.80 (95% confidence interval 0.74 to 0.86) for 90-day survival prediction and a c-index of 0.84 (95% CI 0.80 to 0.89) for 1-year survival prediction. However, the calibration analysis showed that the SORG-MLAs tended to underestimate Taiwanese patients' survival (90-day survival prediction: Calibration intercept 0.78 [95% CI 0.46 to 1.10], calibration slope 0.74 [95% CI 0.53 to 0.96]; 1-year survival prediction: Calibration intercept 0.75 [95% CI 0.49 to 1.00], calibration slope 1.22 [95% CI 0.95 to 1.49]). The Brier score of the 90-day and 1-year SORG-MLA prediction models was lower than their respective null model (0.12 versus 0.16 for 90-day prediction; 0.16 versus 0.25 for 1-year prediction), indicating good overall performance of SORG-MLAs at these two timepoints. Decision curve analysis showed SORG-MLAs provided net benefits when threshold probabilities ranged from 0.40 to 0.95 for 90-day survival prediction and from 0.15 to 1.0 for 1-year prediction. The ECOG score was an independent factor associated with 90-day mortality (odds ratio 1.94 [95% CI 1.01 to 3.73]) but not 1-year mortality (OR 1.07 [95% CI 0.53 to 2.17]) after controlling for SORG-MLA predictions for 90-day and 1- year survival, respectively. Conclusion SORG-MLAs retained good discriminatory ability in Taiwanese patients with long-bone metastases, although their actual survival time was slightly underestimated. More international validation and incremental value studies that address factors such as the ECOG score are warranted to refine the algorithms, which can be freely accessed online at https://sorg-apps.shinyapps. io/extremitymetssurvival/

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field