Exploring the incidence of peripheral arterial occlusive disease following COVID-19 infection: A retrospective cohort study.

Peripheral arterial occlusive disease (PAOD) is a clinical manifestation of systemic atherosclerosis and is always associated with cerebrovascular disease and various complications. The aim of our study is to evaluate the relationship between the coronavirus disease 2019 (COVID-19) infection and the subsequent PAOD development. A retrospective cohort study was conducted and individuals with COVID-19 infection were identified from the TriNetX analytics platform. A total of 2 206 065 patients with COVID-19 infection and 2 206 065 patients without COVID-19 infection were recruited after exclusion and matching. The primary outcome was the development of PAOD after the COVID-19 infection. The Cox proportional hazard regression was adopted to yield the hazard ratio (HR) and 95% confidence interval (CI) of PAOD between groups. After the whole follow-up period, the incidence of PAOD was significantly higher in the COVID-19 group at both the 3-month follow-up (HR: 1.27, 95% CI: 1.24-1.30) and the 12-month follow-up (HR: 1.33, 95% CI: 1.31-1.35) The Kaplan-Meier analysis with the log-rank test demonstrated a higher cumulative probability of PAOD in the COVID-19 group compared to the non-COVID-19 group (p < 0.001). In stratified analysis using 65 years as the threshold, both age groups in the COVID-19 group exhibited a higher risk of PAOD. Similarly, in the sex and race stratified analysis, the COVID-19 group performed a higher risk of PAOD in both subgroups. In conclusion, the COVID-19 infections are strongly associated with an increment of PAOD incidence.

HO-3867, a curcumin analog, elicits cell apoptosis and p38-mediated caspase activation in hepatocellular carcinoma.

HO-3867, a synthetic curcumin analog, has displayed various tumor-suppressive characteristics and improved bioabsorption over its parent compound. However, its influences on the development of hepatocellular carcinoma (HCC) are poorly defined. To address this, we tested the anticarcinogenic impact of HO-3867 and investigated the underlying mechanisms in fighting liver cancer. Our result demonstrated that HO-3867 reduced the viability of HCC cells, accompanied by promotion of cell cycle arrest at the sub-G1 stage and apoptotic responses. Furthermore, a distinctive profile of apoptosis associated proteins, encompassing elevated heme oxygenase-1 (HO-1) level and caspase activation, was detected in HO-3867-stimulated HCC cells. In addition, such HO-3867-mediated elevation in caspase activation was dampened by pharmacological suppression of p38 activities. Taken together, our findings unveiled that HO-3867 triggered cell cycle arrest and apoptotic events in liver cancer, involving a p38-mediated activation of caspase cascades. These data highlighted a usefulness of curcumin or its analogs on the management of hepatocarcinogenesis.

Hyperbaric oxygen therapy suppresses hypoxia and reoxygenation injury to retinal pigment epithelial cells through activating peroxisome proliferator activator receptor-alpha signalling.

Retinal ischemia followed by reperfusion (IR) is a common cause of many ocular disorders, such as age-related macular degeneration (AMD), which leads to blindness in the elderly population, and proper therapies remain unavailable. Retinal pigment epithelial (RPE) cell death is a hallmark of AMD. Hyperbaric oxygen (HBO) therapy can improve IR tissue survival by inducing ischemic preconditioning responses. We conducted an in vitro study to examine the effects of HBO preconditioning on oxygen-glucose deprivation (OGD)-induced IR-injured RPE cells. RPE cells were treated with HBO (100% O2 at 3 atmospheres absolute for 90 min) once a day for three consecutive days before retinal IR onset. Compared with normal cells, the IR-injured RPE cells had lower cell viability, lower peroxisome proliferator activator receptor-alpha (PPAR-α) expression, more severe oxidation status, higher blood-retinal barrier disruption and more elevated apoptosis and autophagy rates. HBO preconditioning increased PPAR-α expression, improved cell viability, decreased oxidative stress, blood-retinal barrier disruption and cellular apoptosis and autophagy. A specific PPAR-α antagonist, GW6471, antagonized all the protective effects of HBO preconditioning in IR-injured RPE cells. Combining these observations, HBO therapy can reverse OGD-induced RPE cell injury by activating PPAR-α signalling.

Sparse-view synchrotron X-ray tomographic reconstruction with learning-based sinogram synthesis.

Synchrotron radiation can be used as a light source in X-ray microscopy to acquire a high-resolution image of a microscale object for tomography. However, numerous projections must be captured for a high-quality tomographic image to be reconstructed; thus, image acquisition is time consuming. Such dense imaging is not only expensive and time consuming but also results in the target receiving a large dose of radiation. To resolve these problems, sparse acquisition techniques have been proposed; however, the generated images often have many artefacts and are noisy. In this study, a deep-learning-based approach is proposed for the tomographic reconstruction of sparse-view projections that are acquired with a synchrotron light source; this approach proceeds as follows. A convolutional neural network (CNN) is used to first interpolate sparse X-ray projections and then synthesize a sufficiently large set of images to produce a sinogram. After the sinogram is constructed, a second CNN is used for error correction. In experiments, this method successfully produced high-quality tomography images from sparse-view projections for two data sets comprising Drosophila and mouse tomography images. However, the initial results for the smaller mouse data set were poor; therefore, transfer learning was used to apply the Drosophila model to the mouse data set, greatly improving the quality of the reconstructed sinogram. The method could be used to achieve high-quality tomography while reducing the radiation dose to imaging subjects and the imaging time and cost.

Deep Learning-Based Nuclear Morphometry Reveals an Independent Prognostic Factor in Mantle Cell Lymphoma.

Blastoid/pleomorphic morphology is associated with short survival in mantle cell lymphoma (MCL), but its prognostic value is overridden by Ki-67 in multivariate analysis. Herein, a nuclear segmentation model was developed using deep learning, and nuclei of tumor cells in 103 MCL cases were automatically delineated. Eight nuclear morphometric attributes were extracted from each nucleus. The mean, variance, skewness, and kurtosis of each attribute were calculated for each case, resulting in 32 morphometric parameters. Compared with those in classic MCL, 17 morphometric parameters were significantly different in blastoid/pleomorphic MCL. Using univariate analysis, 16 morphometric parameters (including 14 significantly different between classic and blastoid/pleomorphic MCL) emerged as significant prognostic factors. Using multivariate analysis, Biologic MCL International Prognostic Index (bMIPI) risk group (P = 0.025), low skewness of nuclear irregularity (P = 0.020), and high mean of nuclear irregularity (P = 0.047) emerged as independent adverse prognostic factors. Additionally, a morphometric score calculated from the skewness and mean of nuclear irregularity (P = 0.0038) was an independent prognostic factor in addition to bMIPI risk group (P = 0.025), and a summed morphometric bMIPI score was useful for risk stratification of patients with MCL (P = 0.000001). These results demonstrate, for the first time, that a nuclear morphometric score is an independent prognostic factor in MCL. It is more robust than blastoid/pleomorphic morphology and can be objectively measured.

Two-tiered deep-learning-based model for histologic diagnosis of Helicobacter gastritis.

AIMS: Helicobacter pylori (HP) infection is the most common cause of chronic gastritis worldwide. Due to the small size of HP and limited resolution, diagnosing HP infections is more difficult when using digital slides. METHODS AND RESULTS: We developed a two-tier deep-learning-based model for diagnosing HP gastritis. A whole-slide model was trained on 885 whole-slide images (WSIs) with only slide-level labels (positive or negative slides). An auxiliary model was trained on 824 areas with HP in nine positive WSIs and 446 negative WSIs for localizing HP. The whole-slide model performed well, with an area under the receiver operating characteristic curve (AUC) of 0.9739 (95% confidence interval [CI], 0.9545-0.9932). The calculated sensitivity and specificity were 93.3% and 90.1%, respectively, whereas those of pathologists were 93.3% and 84.2%, respectively. Using the auxiliary model, the highlighted areas of the localization maps had an average precision of 0.5796. CONCLUSIONS: HP gastritis can be diagnosed on haematoxylin-and-eosin-stained WSIs with human-level accuracy using a deep-learning-based model trained on slide-level labels and an auxiliary model for localizing HP and confirming the diagnosis. This two-tiered model can shorten the diagnostic process and reduce the need for special staining.

Deep Learning for Automatic Hyoid Tracking in Videofluoroscopic Swallow Studies.

The hyoid bone excursion is one of the most important gauges of larynx elevation in swallowing, contributing to airway protection and bolus passage into the esophagus. However, the implications of various parameters of hyoid bone excursion, such as the horizontal or vertical displacement and velocity, remain elusive and raise the need for a tool providing automatic kinematics analysis. Several conventional and deep learning-based models have been applied automatically to track the hyoid bone, but previous methods either require partial manual localization or do not transform the trajectory by anatomic axis. This work describes a convolutional neural network-based algorithm featuring fully automatic hyoid bone localization and tracking and spine axis determination. The algorithm automatically estimates the hyoid bone trajectory and calculates several physical quantities, including the average velocity and displacement in horizontal or vertical anatomic axis. The model was trained in a dataset of 365 videos of videofluoroscopic swallowing from 189 patients in a tertiary medical center and tested using 44 videos from 44 patients with different dysphagia etiologies. The algorithm showed high detection rates for the hyoid bone. The results showed excellent inter-rater reliability for hyoid bone detection, good-to-excellent inter-rater reliability for calculating the maximal displacement and the average velocity of the hyoid bone in horizontal or vertical directions, and moderate-to-good reliability in calculating the average velocity in horizontal direction. The proposed algorithm allows for complete automatic kinematic analysis of hyoid bone excursion, providing a versatile tool with high potential for clinical applications.

Biological Correlates of the Effects of Auricular Point Acupressure on Pain.

BACKGROUND: To identify candidate inflammatory biomarkers for the underlying mechanism of auricular point acupressure (APA) on pain relief and examine the correlations among pain intensity, interference, and inflammatory biomarkers. DESIGN: This is a secondary data analysis. METHODS: Data on inflammatory biomarkers collected via blood samples and patient self-reported pain intensity and interference from three pilot studies (chronic low back pain, n = 61; arthralgia related to aromatase inhibitors, n = 20; and chemotherapy-induced neuropathy, n = 15) were integrated and analyzed. This paper reports the results based on within-subject treatment effects (change in scores from pre- to post-APA intervention) for each study group (chronic low back pain, cancer pain), between-group differences (changes in scores from pre- to post-intervention between targeted-point APA [T-APA] and non-targeted-point APA [NT-APA]), and correlations among pain intensity, interference, and biomarkers. RESULTS: Within-group analysis (the change score from pre- to post-APA) revealed statistically significant changes in three biomarkers: TNF-α (cancer pain in the APA group, p = .03), ß-endorphin (back pain in the APA group, p = .04), and IL-2 (back pain in the NT-APA group, p = .002). Based on between-group analysis in patients with chronic low back pain (T-APA vs NT-APA), IL-4 had the largest effect size (0.35), followed by TNF-α (0.29). A strong positive monotonic relationship between IL-1ß and IL-2 was detected. CONCLUSIONS: The current findings further support the potential role of inflammatory biomarkers in the analgesic effects of APA. More work is needed to gain a comprehensive understanding of the underlying mechanisms of APA on chronic pain. Because it is simple, inexpensive, and has no negative side effects, APA can be widely disseminated as an alternative to opioids.

Assessing Continuous Epidural Infusion and Programmed Intermittent Epidural Bolus for Their Effectiveness in Providing Labor Analgesia: A Mono-Centric Retrospective Comparative Study.

Background and Objectives: Local anesthetics administered via epidural catheters have evolved from intermittent top-ups to simultaneous administration of continuous epidural infusion (CEI) and patient-controlled epidural analgesia (PCEA) using the same device. The latest programmed intermittent epidural bolus (PIEB) model is believed to create a wider and more even distribution of analgesia inside the epidural space. The switch from CEI + PCEA to PIEB + PCEA in our department began in 2018; however, we received conflicting feedback regarding workload from the quality assurance team. This study aimed to investigate the benefits and drawbacks of this conversion, including the differences in acute pain service (APS) staff workload, maternal satisfaction, side effects, and complications before and after the changeover. Materials and Methods: Items from the APS records included total delivery time, average local anesthetic dosage, and the formerly mentioned items. The incidence of side effects, the association between the duration of delivery and total dosage, and hourly medication usage in the time subgroups of the CEI and PIEB groups were compared. The staff workload incurred from rescue bolus injection, catheter adjustment, and dosage adjustment was also analyzed. Results: The final analysis included 214 and 272 cases of CEI + PCEA and PIEB + PCEA for labor analgesia, respectively. The total amount of medication and average hourly dosage were significantly lower in the PIEB + PCEA group. The incidences of dosage change, manual bolus, extra visits per patient, and lidocaine use for rescue bolus were greater in the PIEB + PCEA group, indicating an increased staff workload. However, the two groups did not differ in CS rates, labor time, maternal satisfaction, and side effects. Conclusions: This study revealed that while PIEB + PCEA maintained the advantage of decreasing total drug doses, it inadvertently increased the staff burden. Increased workload might be a consideration in clinical settings when choosing between different methods of PCEA.

Evaluation of the Risk Factors for Cellulitis among Patients with Peripheral Artery Disease.

Background and objectives: The objective of this study is to elucidate peripheral occlusion artery disease (PAOD) as a risk factor for cellulitis. Materials and Methods: This is a retrospective population-based cohort study. The database is the Longitudinal Health Insurance Database, which covers two million beneficiaries from the entire population of the 2010 registry for beneficiaries in Taiwan. The PAOD group is composed of patients who were newly diagnosed with PAOD from 2001 to 2014. The non-PAOD group is composed of patients who were never diagnosed with PAOD from 2001 to 2015. All patients were followed until the onset of cellulitis, death, or until the end of 2015. Results: Finally, 29,830 patients who were newly diagnosed with PAOD were included in the PAOD group, and 29,830 patients who were never diagnosed with PAOD were included in the non-PAOD group. The incidence densities (ID) of cellulitis were 26.05 (95% CI = 25.31-26.80) patients per 1000 person-years in the PAOD group and 49.10 (95% CI = 48.04-50.19) in the non-PAOD group. The PAOD group had an increased risk of cellulitis (adjusted HR = 1.94, 95% CI = 1.87-2.01) compared to the non-PAOD group. Conclusions: Patients with PAOD were associated with a higher risk of subsequent cellulitis compared to patients without PAOD.

The diurnal emission of floral scent in Oncidium hybrid orchid is controlled by CIRCADIAN CLOCK ASSOCIATED 1 (CCA1) through the direct regulation on terpene synthase.

BACKGROUND: To adapt the periodic fluctuation of environmental factors, plants are subtle to monitor the natural variation for the growth and development. The daily activities and physiological functions in coordination with the natural variation are regulated by circadian clock genes. The circadian emission of floral scents is one of the rhythmic physiological activities controlled by circadian clock genes. Here, we study the molecular mechanism of circadian emission pattern of ocimene and linalool compounds in Oncidium Sharry Baby (Onc. SB) orchid. RESULTS: GC-Mass analysis revealed that Onc. SB periodically emitted ocimene and linalool during 6 to 14 o'clock daily. Terpene synthase, one of the key gene in the terpenoid biosynthetic pathway is expressed in coordination with scent emission. The promoter structure of terpene synthase revealed a circadian binding sequence (CBS), 5'-AGATTTTT-3' for CIRCADIAN CLOCK ASSOCIATED1 (CCA1) transcription factor. EMSA data confirms the binding affinity of CCA1. Transactivation assay further verified that TPS expression is regulated by CCA1. It suggests that the emission of floral scents is controlled by CCA1. CONCLUSIONS: The work validates that the mechanism of circadian emission of floral scents in Onc. Sharry Baby is controlled by the oscillator gene, CCA1(CIRCADIAN CLOCK ASSOCIATED 1) under light condition. CCA1 transcription factor up-regulates terpene synthase (TPS) by binding on CBS motif, 5'-AGATTTTT-3' of promoter region to affect the circadian emission of floral scents in Onc. SB.

Anti-inflammatory mouthwashes for the prevention of oral mucositis in cancer therapy: an integrative review and meta-analysis.

PURPOSE: Mucositis is severely painful and often reported as one of the most distressing adverse effects of cancer therapy; it is a significant threat to quality of life as well as life itself. Anti-inflammatory agents may modulate physiologic mechanisms that perpetuate mucositis and be useful in prevention efforts. Because systemic anti-inflammatory agents are not appropriate for many patients, locally acting agents (mouthwashes) may be more feasible for use. This review and meta-analysis evaluates the role that anti-inflammatory mouthwashes have in preventing or reducing oral mucositis associated with chemotherapy and radiation therapy. METHODS: A systematic literature review was conducted to identify studies evaluating the efficacy of anti-inflammatory mouthwashes to prevent therapy-associated mucositis. Meta-analysis was conducted to determine efficacy in preventing any mucositis and dose-limiting mucositis. RESULTS: Eight peer-reviewed publications were identified; corticosteroid and nonsteroidal anti-inflammatory mouthwashes are effective in reducing overall incidence of mucositis and are associated with lower severity of mucositis. Meta-analysis reveals significant reduction in symptomatic mucositis incidence (OR 6.00, 95% CI 4.39-8.20, p < 0.0001) and reduction of dose-limiting mucositis (OR 2.12, 95% CI 1.07-4.28, p = 0.032). CONCLUSION: Mouthwashes containing anti-inflammatory agents are a potential effective means to prevent or reduce mucositis associated with cancer therapy. There are limited adverse effects from these agents, and adherence is high, indicating safety and feasibility of use. Anti-inflammatory mouthwashes should be considered for supportive care in persons at risk for mucositis and must be further evaluated to investigate efficacy across multiple chemotherapy agents, adverse effects, and impacts on symptoms, pain, and quality of life.

Automatic recognition of whole-spine sagittal alignment and curvature analysis through a deep learning technique.

PURPOSE: Artificial intelligence based on deep learning (DL) approaches enables the automatic recognition of anatomic landmarks and subsequent estimation of various spinopelvic parameters. The locations of inflection points (IPs) and apices (APs) in whole-spine lateral radiographs could be mathematically determined by a fully automatic spinal sagittal curvature analysis system. METHODS: We developed a DL model for automatic spinal curvature analysis of whole-spine lateral plain radiographs by using 1800 annotated images of various spinal disease etiologies. The DL model comprised a landmark localizer to detect 25 vertebral landmarks and a numerical algorithm for the generation of an individualized spinal sagittal curvature. The characteristics of the spinal curvature, including the IPs, APs, and curvature angle, could thus be analyzed using mathematical definitions. The localization error of each landmark was calculated from the predictions of 300 test images to evaluate the performance of the landmark localizer. The interrater reliability among a senior orthopedic surgeon, a radiologist, and the DL model was assessed using the intraclass correlation coefficient (ICC). RESULTS: The accuracy of the landmark localizer was within an acceptable range (median error: 1.7-4.1 mm), and the interrater reliabilities between the proposed DL model and each expert were good to excellent (all ICCs > 0.85) for the measurement of spinal curvature characteristics. CONCLUSION: The interrater reliability between the proposed DL model and human experts was good to excellent in predicting the locations of IPs, APs, and curvature angles. Future applications should be explored to validate this system and improve its clinical efficiency.

Self-assembly of biological networks via adaptive patterning revealed by avian intradermal muscle network formation.

Networked structures integrate numerous elements into one functional unit, while providing a balance between efficiency, robustness, and flexibility. Understanding how biological networks self-assemble will provide insights into how these features arise. Here, we demonstrate how nature forms exquisite muscle networks that can repair, regenerate, and adapt to external perturbations using the feather muscle network in chicken embryos as a paradigm. The self-assembled muscle networks arise through the implementation of a few simple rules. Muscle fibers extend outward from feather buds in every direction, but only those muscle fibers able to connect to neighboring buds are eventually stabilized. After forming such a nearest-neighbor configuration, the network can be reconfigured, adapting to perturbed bud arrangement or mechanical cues. Our computational model provides a bioinspired algorithm for network self-assembly, with intrinsic or extrinsic cues necessary and sufficient to guide the formation of these regenerative networks. These robust principles may serve as a useful guide for assembling adaptive networks in other contexts.

Evaluating Auricular Point Acupressure for Chronic Low Back Pain Self-Management Using Technology: A Feasibility Study.

BACKGROUND: Chronic low back pain, one of the most common reasons for seeking healthcare services, causes significant negative impacts on individuals and society. Nonpharmacologic therapies and self-management are included in practice guidelines, but their implementation is challenging. AIM: To assess the feasibility of using an auricular point acupressure (APA) mobile app as a self-guided tool to learn and self-administer APA to manage chronic low back pain (cLBP) and to compare cLBP outcomes between 2 groups (app vs app + telehealth). DESIGN: A 2-phase study design was used. In phase 1, participants (app group, n = 18) had in-person study visits and installed the app to learn and self-administer APA to manage cLBP. In phase 2, all research activities occurred remotely due to the COVID-19 pandemic, so a second group was recruited (app + telehealth, n = 19). The app + telehealth group underwent a virtual session, installed the app, and were provided the opportunity for questions and verification on the accuracy of the self-administered APA. SETTING: The participants were recruited by distributing study flyers at outpatient clinics and referrals. PARTICIPANTS: Participants with chronic low back pain were eliglbe for the study. METHODS: Using a quasi-experimental design with a mixed methods approach, all participants were instructed to download the APA app, provided an APA kit (includes seeds embedded within pre-cut squares of adhesive tape), and advised to self-administer APA with guidance from the app for 4 weeks to manage their cLBP. Study outcomes were collected at the preintervention time point as well as postintervention and 1-month follow-up. Interviews were also conducted at the postintervention time point. RESULTS: Of the 37 participants enrolled, six dropped out, and the attrition rate was 16%. Adherence to APA practice was high (85%-94%). After 4 weeks of APA treatment, participants in the app + telehealth group experienced a 29% decrease in pain intensity during the postintervention time point and a 35% reduction during the 1-month follow-up. Similar improvements were noted in pain interference (28%) and physical function (39%) for participants in the app + telehealth group at the 1-month follow-up. These changes are slightly higher compared with those in the app group (21% pain intensity reduction, 23% improved pain interferences, and 26% improved physical function) during the 1-month follow-up. Overall, APA was found to be feasible using the app and the qualitative findings showed acceptability of the intervention in both groups. CONCLUSIONS: It is feasible to learn and self-administer APA with an app, supplemented with either in-person or telehealth sessions, presenting a promising intervention toward cLBP self-management. Telehealth was found to boost this intervention effectively.

Niclosamide Suppresses Migration and Invasion of Human Osteosarcoma Cells by Repressing TGFBI Expression via the ERK Signaling Pathway.

Osteosarcoma is a highly common malignant bone tumor. Its highly metastatic properties are the leading cause of mortality for cancer. Niclosamide, a salicylanilide derivative, is an oral antihelminthic drug of known anticancer potential. However, the effect of niclosamide on osteosarcoma cell migration, invasion and the mechanisms underlying have not been fully clarified. Therefore, this study investigated niclosamide's underlying pathways and antimetastatic effects on osteosarcoma. In this study, U2OS and HOS osteosarcoma cell lines were treated with niclosamide and then subjected to assays for determining cell migration ability. The results indicated that niclosamide, at concentrations of up to 200 nM, inhibited the migration and invasion of human osteosarcoma U2OS and HOS cells and repressed the transforming growth factor beta-induced protein (TGFBI) expression of U2OS cells, without cytotoxicity. After TGFBI knockdown occurred, cellular migration and invasion behaviors of U2OS cells were significantly reduced. Moreover, niclosamide significantly decreased the phosphorylation of ERK1/2 in U2OS cells and the combination treatment of the MEK inhibitor (U0126) and niclosamide resulted in the intensive inhibition of the TGFBI expression and the migratory ability in U2OS cells. Therefore, TGFBI derived from osteosarcoma cells via the ERK pathway contributed to cellular migration and invasion and niclosamide inhibited these processes. These findings indicate that niclosamide may be a powerful preventive agent against the development and metastasis of osteosarcoma.

Identification of nodal micrometastasis in colorectal cancer using deep learning on annotation-free whole-slide images.

Detection of nodal micrometastasis (tumor size: 0.2-2.0 mm) is challenging for pathologists due to the small size of metastatic foci. Since lymph nodes with micrometastasis are counted as positive nodes, detecting micrometastasis is crucial for accurate pathologic staging of colorectal cancer. Previously, deep learning algorithms developed with manually annotated images performed well in identifying micrometastasis of breast cancer in sentinel lymph nodes. However, the process of manual annotation is labor intensive and time consuming. Multiple instance learning was later used to identify metastatic breast cancer without manual annotation, but its performance appears worse in detecting micrometastasis. Here, we developed a deep learning model using whole-slide images of regional lymph nodes of colorectal cancer with only a slide-level label (either a positive or negative slide). The training, validation, and testing sets included 1963, 219, and 1000 slides, respectively. A supercomputer TAIWANIA 2 was used to train a deep learning model to identify metastasis. At slide level, our algorithm performed well in identifying both macrometastasis (tumor size > 2.0 mm) and micrometastasis with an area under the receiver operating characteristics curve (AUC) of 0.9993 and 0.9956, respectively. Since most of our slides had more than one lymph node, we then tested the performance of our algorithm on 538 single-lymph node images randomly cropped from the testing set. At single-lymph node level, our algorithm maintained good performance in identifying macrometastasis and micrometastasis with an AUC of 0.9944 and 0.9476, respectively. Visualization using class activation mapping confirmed that our model identified nodal metastasis based on areas of tumor cells. Our results demonstrate for the first time that micrometastasis could be detected by deep learning on whole-slide images without manual annotation.

Self-efficacy in symptom management for adolescents and young adults with cancer: a systematic review.

BACKGROUND: Adolescents and young adults (AYAs) have more frequent and intense adverse effects from cancer therapy than other age groups. Self-efficacy, the ability for persons to maintain health-related behavior change, may assist with symptom management but the role it plays in AYAs with cancer has not been thoroughly investigated. This review explores the role that self-efficacy has in symptom management for AYAs with cancer and provides guidance for clinicians to utilize self-efficacy as a means to reduce side effects of therapy. METHODS: A systematic review of peer-reviewed literature was conducted to identify works discussing self-efficacy and symptom management for AYAs with cancer. Five databases were searched with key terms and articles that discussed relationships between self-efficacy and cancer therapy symptoms were retained for analysis. FINDINGS: Twelve manuscripts representing 1180 individuals age 12 to 43 years were identified. Self-efficacy was found to be related to (1) health management behaviors, (2) psychosocial health, (3) sexual and reproductive health, and (4) physical symptoms. Self-efficacy had direct correlations with physical activity, nutritional intake, symptom regulation, mental health, sexual health, and fertility preservation. The included studies did not find significant relationships with medication adherence or pain management. DISCUSSION: Self-efficacy is an attribute that impacts behavior change, health maintenance, and overall wellness and can be changed over time and through interventions to improve symptoms of cancer therapy. Self-efficacy should be evaluated as a construct in relevant studies aimed at improving side effects of cancer therapy to better understand outcomes from interventions. Symptoms, toxicities, and adverse effects of cancer therapy may be improved by increasing self-efficacy of patients.

Timing of do-not-resuscitate orders and health care utilization near the end of life in cancer patients: a retrospective cohort study.

PURPOSE: The objectives are to explore the prevalence of DNR orders, the factors influencing them, and the association between DNR signing and health care utilization among advanced cancer patients. METHODS: This was a retrospective cohort study. Data from cancer decedents in three hospitals in China from January 2016 to December 2017 during their last hospitalization before death were obtained from the electronic medical records system. RESULTS: In total, 427 cancer patients were included; 59.0% had a DNR order. Patients who had solid tumors, lived in urban areas, had more than one comorbidity, and had more than five symptoms were more likely to have DNR orders. The cut-off of the timing of obtaining a DNR order was 3 days, as determined by the median number of days from the signing of a DNR order to patient death. Patients with early DNR orders (more than 3 days before death) were less likely to be transferred to the intensive care unit and undergo cardiopulmonary resuscitation, tracheal intubation, and ventilation, while they were more likely to be given morphine and psychological support compared with those with late (within 3 days before death) and no orders. CONCLUSIONS: Advanced cancer patients with solid tumors living in urban areas with more symptoms and comorbidities are relatively more likely to have DNR orders. Early DNR orders are associated with less aggressive procedures and more comfort measures. However, these orders are always signed late. Future studies are needed to better understand the timing of DNR orders.

Kaempferol inhibits the cell migration of human hepatocellular carcinoma cells by suppressing MMP-9 and Akt signaling.

Metastasis is the most prevalent cause of cancer-related deaths and treatment failure in patients with hepatocellular carcinoma (HCC). Kaempferol is a natural flavonol belonging to the subgroup of flavonoids and exhibits potent anticancer activities. This study provides molecular evidence on the anti-invasive and anti-migratory effects of kaempferol on human HCC cells. The anti-invasive effect was investigated by applying kaempferol on two human HCC cell lines (Huh-7 and SK-Hep-1). Kaempferol reduced the invasion and migration of Huh-7 and SK-Hep-1 cells by Boyden chamber invasion assay and wound healing assay, respectively. A protease array analysis showed that Matrix Metalloproteinase-9 (MMP-9) was dramatically downregulated in HCC cells after kaempferol treatment. Gelatin zymography and Western blot assay showed that kaempferol reduced the activities and protein expression of MMP-9, respectively. Kaempferol also sufficiently suppressed the phosphorylation of the Akt expression. Overall, kaempferol inhibited the invasive properties of human HCC cells by targeting MMP-9 and Akt pathways. Hence, kaempferol could be used as an adjuvant therapeutic agent for the treatment of human HCC cells.