Oxygen-Generating Hydrogels as Oxygenation Therapy for Accelerated Chronic Wound Healing.

Hypoxia in chronic wounds impairs the activities of reparative cells, resulting in tissue necrosis, bacterial infections, decreased angiogenesis, and delayed wound healing. To achieve effective oxygenation therapy and restore oxygen homeostasis, oxygen-generating hydrogels based on different oxygen sources have been developed to release dissolved oxygen in the wound bed, which not only alleviate hypoxia, but also accelerate chronic wound healing. This review first discusses the vital role of oxygen and hypoxia in the wound healing process. The advancements in oxygen-generating hydrogels, which produce oxygen through the decomposition of hydrogen peroxide, metal peroxides, glucose-activated cascade reactions, and photosynthesis of algae microorganisms for chronic wound healing, are discussed and summarized. The therapeutic effects and challenges of using oxygen-generating hydrogels for the clinical treatment of chronic wounds are concluded and prospected.

Nomogram for predicting the likelihood of liver metastases at initial diagnosis in patients with Siewert type II gastroesophageal junction adenocarcinoma.

The liver is one of the most ordinary metastatic sites of gastroesophageal junction adenocarcinoma and significantly affects its prognosis. Therefore, this study tried to construct a nomogram that can be applied to predict the likelihood of liver metastases from gastroesophageal junction adenocarcinoma. 3001 eligible patients diagnosed with gastroesophageal junction adenocarcinoma between 2010 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were involved in the analysis. Patients were randomly divided into a training cohort and an internal validation cohort using R software, with an allocation ratio of 7:3. According to the consequences of univariate and multivariate logistic regression, we constructed a nomogram for predicting the risk of liver metastases. The discrimination and calibration ability of the nomogram was appraised by the C-index, ROC curve, calibration plots, and decision curve analysis (DCA). We also used Kaplan-Meier survival curves to compare differences in overall survival in patients with gastroesophageal junction adenocarcinoma with and without liver metastases. Liver metastases developed in 281 of 3001 eligible patients. The overall survival of patients with gastroesophageal junction adenocarcinoma with liver metastases before and after propensity score matching (PSM) was obviously lower than that of patients without liver metastases. Six risk factors were finally recognized by multivariate logistic regression, and a nomogram was constructed. The C-index was 0.816 in the training cohort and 0.771 in the validation cohort, demonstrating the good predictive capacity of the nomogram. The ROC curve, calibration curve, and decision curve analysis further demonstrated the good performance of the predictive model. The nomogram can accurately predict the likelihood of liver metastases in gastroesophageal junction adenocarcinoma patients.

Improved deep convolutional neural networks using chimp optimization algorithm for Covid19 diagnosis from the X-ray images.

Applying Deep Learning (DL) in radiological images (i.e., chest X-rays) is emerging because of the necessity of having accurate and fast COVID-19 detectors. Deep Convolutional Neural Networks (DCNN) have been typically used as robust COVID-19 positive case detectors in these approaches. Such DCCNs tend to utilize Gradient Descent-Based (GDB) algorithms as the last fully-connected layers' trainers. Although GDB training algorithms have simple structures and fast convergence rates for cases with large training samples, they suffer from the manual tuning of numerous parameters, getting stuck in local minima, large training samples set requirements, and inherently sequential procedures. It is exceedingly challenging to parallelize them with Graphics Processing Units (GPU). Consequently, the Chimp Optimization Algorithm (ChOA) is presented for training the DCNN's fully connected layers in light of the scarcity of a big COVID-19 training dataset and for the purpose of developing a fast COVID-19 detector with the capability of parallel implementation. In addition, two publicly accessible datasets termed COVID-Xray-5 k and COVIDetectioNet are used to benchmark the proposed detector known as DCCN-Chimp. In order to make a fair comparison, two structures are proposed: i-6c-2 s-12c-2 s and i-8c-2 s-16c-2 s, all of which have had their hyperparameters fine-tuned. The outcomes are evaluated in comparison to standard DCNN, Hybrid DCNN plus Genetic Algorithm (DCNN-GA), and Matched Subspace classifier with Adaptive Dictionaries (MSAD). Due to the large variation in results, we employ a weighted average of the ensemble of ten trained DCNN-ChOA, with the validation accuracy of the weights being used to determine the final weights. The validation accuracy for the mixed ensemble DCNN-ChOA is 99.11%. LeNet-5 DCNN's ensemble detection accuracy on COVID-19 is 84.58%. Comparatively, the suggested DCNN-ChOA yields over 99.11% accurate detection with a false alarm rate of less than 0.89%. The outcomes show that the DCCN-Chimp can deliver noticeably superior results than the comparable detectors. The Class Activation Map (CAM) is another tool used in this study to identify probable COVID-19-infected areas. Results show that highlighted regions are completely connected with clinical outcomes, which has been verified by experts.

Bundle of Care Promotes Arteriovenous Fistula Maturity in Patients with End-Stage Kidney Disease.

BACKGROUND: Arteriovenous fistula (AVF), as the hemodialysis access, has the advantages of safety, sufficient blood flow, and long use time. To establish an ideal AVF, patients require good vascular condition. However, many teams often neglect preoperative preparation and exercises and have no concept of specialized nursing or bundle of care, directly leading to stenosis of the outflow tract and seriously affected surgical efficacy. This study aimed to evaluate the influence of bundle of care on AVF. METHODS: A total of 260 patients with end-stage kidney disease were included from January 2019 to December 2020 at Qilu Hospital, Shandong University. Patients were divided into 2 groups, and were treated with ordinary nursing care (the control group) or bundle of care (the observation group). Maturity of AVF fistula and postoperative complications were compared between 2 groups. RESULTS: The observation group was associated with larger internal diameter of the cephalic vein (6.524 ± 0.347 vs. 6.346 ± 0.32 4 mm) and faster blood flow at the anastomosis of AVF (568.2 ± 26.8 vs. 565.7 ± 27.5 mL/min) than the control group at 2 weeks after surgery (both P < 0.05). The observation group had a higher maturity rate than the control group (93.1% vs. 81.5%, P < 0.05) at 8 weeks after surgery. There were lower incidences of fistula stenosis (4.6% vs. 10.8%) and fistula thrombosis (2.3% vs. 7.7%) in the observation group than in the control group (both P < 0.05). The secondary patency was higher in the observation group than in the control group (97.7% vs. 92.3%, P < 0.05). CONCLUSIONS: The use of bundle of care promotes AVF maturity and reduces postoperative complications in patients with end-stage kidney disease.

Automatic detection of abnormal hand gestures in patients with radial, ulnar, or median nerve injury using hand pose estimation.

Background: Radial, ulnar, or median nerve injuries are common peripheral nerve injuries. They usually present specific abnormal signs on the hands as evidence for hand surgeons to diagnose. However, without specialized knowledge, it is difficult for primary healthcare providers to recognize the clinical meaning and the potential nerve injuries through the abnormalities, often leading to misdiagnosis. Developing technologies for automatically detecting abnormal hand gestures would assist general medical service practitioners with an early diagnosis and treatment. Methods: Based on expert experience, we selected three hand gestures with predetermined features and rules as three independent binary classification tasks for abnormal gesture detection. Images from patients with unilateral radial, ulnar, or median nerve injuries and healthy volunteers were obtained using a smartphone. The landmark coordinates were extracted using Google MediaPipe Hands to calculate the features. The receiver operating characteristic curve was employed for feature selection. We compared the performance of rule-based models with logistic regression, support vector machine and of random forest machine learning models by evaluating the accuracy, sensitivity, and specificity. Results: The study included 1,344 images, twenty-two patients, and thirty-four volunteers. In rule-based models, eight features were finally selected. The accuracy, sensitivity, and specificity were (1) 98.2, 91.7, and 99.0% for radial nerve injury detection; (2) 97.3, 83.3, and 99.0% for ulnar nerve injury detection; and (3) 96.4, 87.5, and 97.1% for median nerve injury detection, respectively. All machine learning models had accuracy above 95% and sensitivity ranging from 37.5 to 100%. Conclusion: Our study provides a helpful tool for detecting abnormal gestures in radial, ulnar, or median nerve injuries with satisfying accuracy, sensitivity, and specificity. It confirms that hand pose estimation could automatically analyze and detect the abnormalities from images of these patients. It has the potential to be a simple and convenient screening method for primary healthcare and telemedicine application.

Application Analysis of UPOINT System in Chinese Type III Prostatitis Patients: A Single Center Experience.

Objective: UPOINT clinical phenotype system was used to estimate the type III prostatitis patients. Put in the erectile dysfunction (ED) domain and analysis the ED domain's effect towards the UPOINT system. Methods: A total of 126 patients with type III prostatitis were prospectively collected and classified in each domain of the UPOINT system, including urinary, psychosocial, organ-specific, infection, neurological/systemic, and tenderness. Symptom severity was measured using the national institutes of health chronic prostatitis symptom index (NIH-CPSI) and the international prostate symptom score (IPSS). The erectile function was evaluated using the international index of erectile function (IIEF-5). Mental state was evaluated using the Symptom Checklist 90 (SCL-90). The quality of life of patients was assessed by the Quality of Life scale (QoL). Results: The percentage of patients positive for each domain was 60.32%, 43.65%, 53.17%, 11.11%, 42.06%, and 33.33% for the urinary, psychosocial, organ-specific, infection, neurological/systemic, and tenderness, respectively. There were significant correlations between the number of positive UPOINT domains and total NIH-CPSI (r = 0.630, P < 0.001) and IPSS (r = 0.429, P < 0.001). Symptom duration was associated with a number of positive domains (r = 0.194, P < 0.05). After adding an ED domain to establish a modified UPOINT system, the correlation between the number of positive domains and symptom severity was not improved (0.630 to 0.590, P < 0.001). The percentage of the patients who suffered psychosocial problems was 43.65%. Conclusions: In our cohort, the number of positive domains was correlated with symptom severity. Inclusion of the ED phenotype in the UPOINT phenotype classification system did not significantly enhance the association of positive presentation with symptom severity. Our findings presented do not support the utility of using ED as a stand-alone item in the UPOINT domain. Psychological problems should be considered when treating type III prostatitis patients.

Hexaconazole Application Saves the Loss of Grey Mold Disease but Hinders Tomato Fruit Ripening in Healthy Plants.

Hexaconazole (HEZ) is a triazole fungicide registered to prevent and control grey mold disease on tomatoes. Many triazole fungicides exhibit plant regulator functions. Therefore, it is necessary to understand the effects of HEZ fungicides on the growth and development of tomatoes. In the present study, the effect of HEZ on healthy and Botrytis cinerea (B. cinerea)-infected tomato plants was investigated. We found that HEZ delayed fruit ripening when applied to healthy tomato plants and further changed the taste and flavor of these fruit. HEZ increased the size and prevented the rotting of the tomato fruit, thus saving grey mold infection-related losses. Moreover, compared with applying HEZ on healthy plants, the application of HEZ on B. cinerea-infected plants increased the metabolism of sugars, acids, and aromatic compounds in these fruit. Therefore, HEZ can effectively control fungal pathogens but reduce the quality of tomato fruit.

Higgs Boson Emerging from the Dark.

We propose a new nonthermal mechanism of dark matter production based on vacuum misalignment. A global X-charge asymmetry is generated at high temperatures, under which both the will-be Higgs boson and the dark matter are charged. At lower energies, the vacuum changes alignment and breaks the U(1)_{X}, leading to the emergence of the Higgs bosonand of a fraction of charge asymmetry stored in the stable dark matter relic. This mechanism can be present in a wide variety of models based on vacuum misalignment, and we demonstrate it in a composite Higgs template model, where all the necessary ingredients are naturally present. A light pseudo-scalar η is always predicted, with interesting implications for cosmology, future supernova observations and exotic Z→γη decays.

Vanadium dioxide based broadband THz metamaterial absorbers with high tunability: simulation study.

With their unprecedented flexibility in manipulating electromagnetic waves, metamaterials provide a pathway to structural materials that can fill the so-called "THz gap". It has been reported that vanadium dioxide (VO2) experiences a three orders of magnitude increase in THz electrical conductivity when it undergoes an insulator-to-metal transition. Here, we propose a VO2 based THz metamaterial absorber exhibiting broadband absorptivity that arises from the multiple resonances supported by a delicately balanced doubly periodic array of VO2 structures and numerically demonstrate that the corresponding absorption behavior is highly dependent on the VO2's THz electrical properties. Considering the phase transition induced dramatic change in VO2's material property, the proposed metamaterial absorbers have the potential for strong modulation and switching of broadband THz radiation.

Clnk plays a role in TNF-alpha-induced cell death in murine fibrosarcoma cell line L929.

Clnk, as a third member of the Blnk/SLP-76 adapter family, is involved in the positive regulation of immunoreceptor signaling. Here we provide findings that Clnk may be is required for TNF induced cell death, it functions downstream of RIP3 and promotes TNF- induced ROS generation and MLKL tetramer formation and subsequent necrosis of L929 cells. Therefore, Clnk, as an adaptor protein, may take part in the other cellular processes.