bluuebunny/crossref_metadata_2025 huggingface dataset:
Nomograms for Predicting Coexisting Cardiovascular Disease and Prognosis in Chronic Obstructive Pulmonary Disease: A Study Based on NHANES Data
Authors: Qiu Yuanjie , Wang Yan , Shen Nirui , Wang Qingting , Chai Limin , Wang Jian , Zhang Qianqian , Chen Yuqian , Liu Jin , Li Danyang , Chen Huan , Li Manxiang
Published: June 2022

Background. Chronic obstructive pulmonary disease (COPD) is a common chronic disease. Progression is further exacerbated by the coexistence of cardiovascular disease (CVD). We aim to construct a diagnostic nomogram for predicting the risk of coexisting CVD and a prognostic nomogram for predicting long-term survival in COPD. Methods. The 540 eligible participants selected from the NHANES 2005–2010 were included in this study. Logistic regression analysis was used to construct a diagnostic nomogram for the diagnosis of coexisting CVD in COPD. Cox regression analyses were used to construct a prognostic nomogram for COPD. A risk stratification system was developed based on the total score generated from the prognostic nomogram. We used C-index and ROC curves to evaluate the discriminant ability of the newly built nomograms. The models were also validated utilizing calibration curves. Survival curves were made using the Kaplan–Meier method and compared by the Log-rank test. Results. Logistic regression analysis showed that gender, age, neutrophil, RDW, LDH, and HbA1c were independent predictors of coexisting CVD and were included in the diagnostic model. Cox regression analysis indicated that CVD, gender, age, BMI, RDW, albumin, LDH, creatinine, and NLR were independent predictors of COPD prognosis and were incorporated into the prognostic model. The C-index and ROC curves revealed the good discrimination abilities of the models. And the calibration curves implied that the predicted values by the nomograms were in good agreement with the actual observed values. In addition, we found that coexisting with CVD had a worse prognosis compared to those without CVD, and the prognosis of the low-risk group was better than that of the high-risk group in COPD. Conclusions. The nomograms we developed can help clinicians and patients to identify COPD coexisting CVD early and predict the 5-year and 10-year survival rates of COPD patients, which has some clinical practical values.
Prediction for Distant Metastasis of Breast Cancer Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging Images under Deep Learning
Authors: Li Li , Tian Hongzhe , Zhang Baorong , Wang Weijun , Li Bo
Published: June 2022

This research aimed to explore the effect of using magnetic resonance imaging (MRI) radiomic features to establish a model for predicting distant metastasis under dynamic contrast-enhanced MRI imaging with deep learning algorithms. The deep learning algorithm was used to segment the images. A total of 96 cases with 100 lesions were included in the metastatic group, including 2 cases of bifocal breast cancer and 2 cases of multifocal breast cancer. There were 192 cases in the nonmetastatic group, with 197 lesions, including 5 cases of multifocal breast cancer. After dynamic contrast-enhancement, the morphological features and grayscale statistical features were extracted from the lesions to establish a prediction model through sum-sum check and feature dimension reduction. The accuracy, sensitivity, specificity, and area under receiver operator characteristic curve (AUC) of prediction models based only on imaging features were compared with those created by combining radiomic features with clinical and pathological features. The created predictive model based on radiomic features for distant metastases in breast cancer showed a sensitivity of 66.7%, a specificity of 84.2%, an accuracy of 78.3%, and an AUC of 0.744. The sensitivity of the prediction model for distant metastasis of breast cancer was 67.7%, the specificity was 86.8%, the accuracy was 80.5%, and the AUC was 0.763. Bone, lung, and liver were the most common distant metastatic sites of breast cancer. Under the dynamic contrast-enhanced MRI of deep learning, the prediction model combining radiomic features with clinical and pathological features showed better predictive performance.
Infrared Thermal Images of Solar PV Panels for Fault Identification Using Image Processing Technique
Authors: Kirubakaran V. , Preethi D. M. D. , Arunachalam U. , Rao Yarrapragada K. S. S. , Gatasheh Mansour K. , Hoda Nasrul , Anbese Endalkachew Mergia
Published: June 2022

Among the renewable forms of energy, solar energy is a convincing, clean energy and acceptable worldwide. Solar PV plants, both ground mounting and the rooftop, are mushrooming thought the world. One of the significant challenges is the fault identification of the solar PV module, since a vast power plant condition monitoring of individual panels is cumbersome. This paper attempts to identify the panel using a thermal imaging system and processes the thermal images using the image processing technique. An ordinary and thermal image has been processed in the image processing tool and proved that thermal images record the hot spots. Similarly, the new and aged solar photovoltaic panels were compared in the image processing technique since any fault in the panel has been recorded as hot spots. The image recorded in the aged panels records hot spots, and performance has been analyzed using conventional metrics. The experimental results have also been verified.
Subdivision of Artistic Objectives of Oil Painting Creation under the Evaluation of Deep Learning Model
Authors: Wu Meishuang
Published: June 2022

In order to fully segment and classify the artistic objectives of painting and realise the needs of automatic classification and retrieval of painting by computer, this paper proposes to establish convolution neural network with dual core compression activation module and deep separation convolution. The DKSE module is constructed based on the structural features of SKNet. SKNet extracts the overall image and detail features, SENet enhances the channel features. Using DKSE module and depth separable convolution, a convolution neural network is established to classify paintings. DKSE module can effectively improve the classification performance of the model, fully extract the overall and local detail features of oil painting images, and provide better classification accuracy than the traditional network model.
Application and Comparison of Machine Learning Algorithms for Predicting Rock Deformation in Hydraulic Tunnels
Authors: Liu Yixin , Ren Xuhua , Zhang Jixun , Zhang Yuxian
Published: June 2022

Prediction of tunnel surrounding rock deformation is important for tunnel construction safety evaluation. In this paper, machine learning algorithms are used to carry out a comparative study of the surrounding rock deformation prediction. The applications of Gaussian process regression (GPR), support vector machine (SVM), and long short-term memory network (LSTM) in the prediction of surrounding rock deformation sequences are compared and analyzed. The actual data of a diversion tunnel in a southwest region are used as an example to evaluate and compare the single-step prediction model and multistep prediction model established by the above algorithm. The results show that the machine learning algorithm has good operation effect on the prediction of surrounding rock deformation. Overall, the SVM model has the best prediction effect and outperforms the other two algorithms in terms of tracking the trend of data changes and the degree of data fit.
Amplitude-Based Smoothed Sparse Phase Retrieval Algorithm
Authors: Xiao Zhuolei , Liu Zhengyan
Published: June 2022

Sparse phase retrieval mainly solves nonconvex and nonsmooth problems. Aiming at the nonsmooth problem in sparse phase retrieval, we propose a smoothing algorithm which is called sparse smoothed amplitude flow (SPSAF). The proposed SPSAF algorithm is an amplitude-based nonconvex sparse smoothing phase retrieval algorithm. First, the original phase retrieval loss function is smoothed without modifying the gradient in the gradient refinement stage, thereby reducing the computational complexity of the overall algorithm. Secondly, the support of the original signal is estimated by differential analysis of the gaps, and the initialization can be obtained through a carefully designed method based on this support. Finally, we get sparse estimates by gradient descent based on hard thresholding. Numerical experiments show that the proposed SPSAF algorithm has significant improvements in recovery performance, convergence speed, and sampling complexity. Further, the SPSAF algorithm is stable in noisy environments.
Research and Application of Clustering Algorithm for Text Big Data
Authors: Chen Zi Li
Published: June 2022

In the era of big data, text as an information reserve database is very important, in all walks of life. From humanities research to government decision-making, from precision medicine to quantitative finance, from customer management to marketing, massive text, as one of the most important information carriers, plays an important role everywhere. The text data generated in these practical problems of humanities research, financial industry, marketing, and other fields often has obvious domain characteristics, often containing the professional vocabulary and unique language patterns in these fields and often accompanied by a variety of “noise.” Dealing with such texts is a great challenge for the current technical conditions, especially for Chinese texts. A clustering algorithm provides a better solution for text big data information processing. Clustering algorithm is the main body of cluster analysis, K-means algorithm with its implementation principle is simple, low time complexity is widely used in the field of cluster analysis, but its K value needs to be preset, initial clustering center random selection into local optimal solution, other clustering algorithm, such as mean drift clustering, K-means clustering in mining text big data. In view of the problems of the above algorithm, this paper first extracts and analyzes the text big data and then does experiments with the clustering algorithm. Experimental conclusion: by analyzing large-scale text data limited to large-scale and simple data set, the traditional K-means algorithm has low efficiency and reduced accuracy, and the K-means algorithm is susceptible to the influence of initial center and abnormal data. According to the above problems, the K-means cluster analysis algorithm for data sets with large data volumes is analyzed and improved to improve its execution efficiency and accuracy on data sets with large data volume set. Mean shift clustering can be regarded as making many random centers move towards the direction of maximum density gradually, that is, moving their mean centroid continuously according to the probability density of data and finally obtaining multiple maximum density centers. It can also be said that mean shift clustering is a kernel density estimation algorithm.
Bearing Fault Diagnosis of End‐to‐End Model Design Based on 1DCNN‐GRU Network
Authors: Zhiwei Liu
Published: June 2022

At present, the complex and varying operating conditions of bearings make the feature extraction become difficult and lack adaptability. An end‐to‐end fault diagnosis is proposed. A convolutional neural network (CNN) is good at mining spatial features of samples and has the advantage of “end‐to‐end.” Gates recurrent neural (GRU) network has good performance in processing time‐dependent characteristics of signals. We design an end‐to‐end adaptive 1DCNN‐GRU model (i.e., one‐dimensional neural network and gated recurrent unit) which combines the advantages of CNN’s spatial processing capability and GRU’s time‐sequence processing capability. CNN is applied instead of manual feature extraction to extract effective features adaptively. Moreover, GRU can learn further the features processed through the CNN and achieve the fault diagnosis. It was shown that the proposed model could adaptively extract spatial and time‐dependent features from the raw vibration signal to achieve an “end‐to‐end” fault diagnosis. The performance of the proposed method is validated using the bearing data collected by Case Western Reserve University (CWRU), and the results showed that the proposed model had recognition accuracy higher than 99%.
Dynamic Characteristics of Phase Change Material in a Square Cavity under Various Heating Modes
Authors: Chen Junqi
Published: June 2022

Phase change material (PCM) is particularly advantageous in developing low-carbon buildings. However, its melting efficiency is severely determined by the dynamics of the molten phase, which is greatly associated with the applied heating orientation. This work aims to describe the dynamic character in the melting process of paraffin under different heating modes. A total of four heating modes are considered for the paraffin enclosed in a square cavity, including side heating, top heating, bottom heating, and around heating. The around heating can be regarded as the combination of the first three heating modes along a single wall. A comparative study of numerical and experimental results of temperature is firstly performed for the side heating case to verify the computational model, which is then extended to study the dynamic state during the melting process of paraffin. The evolutions of the solid/liquid interface and the internal flow field show that the bottom heating can maximally activate the involvement of natural convection of the liquid paraffin and thus has the highest efficiency than the side and top heating. The contribution rate of the bottom heating is about 1.55 times over that of the top heating. This observation is useful to identify the contribution of each heating mode to the heat transfer in the paraffin and guide its practical application.
Early Fault Diagnosis Model Design of Reciprocating Compressor Valve Based on Multiclass Support Vector Machine and Decision Tree
Authors: Yu Zhihong , Zhang Bosi , Hu Guangxia , Chen Zhigang
Published: June 2022

According to the character of frequent fault occurrence, difficult diagnosis of large reciprocating compressor valves, an early fault diagnosis model of reciprocating compressor valve based on multiclass support vector machine and decision tree is designed. A series of simulation experiments of the suction valve and exhaust valve on a large-scale reciprocating compressor experimental bench are made and the valve fault principle is analyzed. Using the advantages of fast and efficient decision tree classification and the prominent characteristics of support vector machine in small sample binary classification, a multivariate classification and recognition model is constructed. The typical characteristic parameters of gearbox vibration signal are extracted as the fault feature vector training model under different fault conditions, and the samples are tested. The experimental results show that the recognition effect of this method is significantly better than that of the neural network method in the case of small samples, and the recognition efficiency is improved more than that of the conventional multivariate support vector machine method which can be effectively applied to reciprocating compressor valve fault diagnosis.
Stachys pilifera Benth: A Review of Its Botany, Phytochemistry, Therapeutic Potential, and Toxicology
Authors: Sadeghi Heibatollah , Rostamzadeh Davoud , Panahi Kokhdan Esmaeel , Asfaram Arash , Doustimotlagh Amir Hossein , Hamidi Neda , Hossein Sadeghi
Published: June 2022

Background. Stachys L. (Lamiaceae) includes more than 300 annual or perennial species growing in temperate regions of Southern Africa, the Mediterranean, America, and Asia. Stachys pilifera Benth (S. pilifera), also known as Marzeh Kuhi, is an endemic species from Iran. It is found in the mountainous habitats of the Zagros area. It has various traditional uses, and the phytochemical ingredients and some biological activities of this species have been examined in previous studies. Methods. PubMed, Science Direct, Google Scholar, Scopus, and Science Web databases were used to gather the data. The purpose of this review is to consolidate the scattered knowledge reported in the literature about botany, traditional uses, phytochemistry, pharmacological properties, and safety of S. pilifera and suggest its potential medicinal properties. Key Findings. In traditional Iranian medicine, S. pilifera manages various illnesses, such as rheumatoid arthritis, common cold, infections, asthma, and tussive. More than 30 compounds have been identified in S. pilifera essential oil. The compounds found in S. pilifera are phenolic compounds, monoterpenes, sesquiterpenes, flavonoids, alkaloids, and terpenoids, which have various properties such as antioxidant, nephroprotective, anti-inflammatory, antimicrobial, hepatoprotective, and anticancer properties. Conclusions. The literature reveals that S. pilifera is an essential source of bioactive phytochemicals and illustrates the unknown area of this plant for new investigations. Moreover, we recommend that future research focus on toxicology and quality control studies for S. pilifera to fill the knowledge gap and provide theoretical support for the plant’s possible functional and clinical uses.
A Stability Result for a Swelling Porous System with Nonlinear Boundary Dampings
Authors: Al-Mahdi Adel M. , Messaoudi Salim A. , Al-Gharabli Mohammad M.
Published: June 2022

In this work, we consider a swelling porous system where the damping terms are on the boundary. We establish an explicit and general decay result, without imposing restrictive growth assumption near the origin on the damping terms. Our result allows a larger class of damping terms, and the usual exponential and polynomial decay estimates are only special cases. We also give some illustrative examples.
Film and Video Quality Optimization Using Attention Mechanism-Embedded Lightweight Neural Network Model
Authors: Ma Youwen
Published: June 2022

In filming, the collected video may be blurred due to camera shake and object movement, causing the target edge to be unclear or deforming the targets. In order to solve these problems and deeply optimize the quality of movie videos, this work proposes a video deblurring (VD) algorithm based on neural network (NN) model and attention mechanism (AM). Based on the scale recurrent network, Haar planar wavelet transform (WT) is introduced to preprocess the video image and to deblur the video image in the wavelet domain. Additionally, the spatial and channel AMs are fused into the overall network framework to improve the feature expression ability. Further, the residual inception spatial-channel attention (RISCA) mechanism is introduced to extract the multiscale feature information from video images. Meanwhile, skip spatial-channel attention (SSCA) accelerates the network training time to achieve a better VD effect. Finally, relevant experiments are designed, factoring in peak signal-to-noise ratio (PSNR) and structural similarity (SSI). The experimental findings corroborate that the proposed Haar and attention video deblurring (HAVD) outperforms multisize network Haar (MSNH) in PSNR and structural similarity (SSIM), improved by 0.10 dB and 0.005, respectively. Therefore, embedding the dual AMs can improve the model performance and optimize the video quality. This work provides technical support for solving the video distortion problems.
Analysis on the Independent Innovation Path and Development Trend of Emerging Marine Industry Based on DEA Model
Authors: Liu Yufeng
Published: June 2022

The development trend of the emerging marine industry affects the development of the marine economy, to study the independent innovation path of the emerging marine industry and the empirical analysis of its development trend. Based on the independent innovation path of the emerging marine industry, explore the development trend of the emerging marine industry. Select the added value of the emerging marine industry as the dependent variable; R&D personnel and R&D funds as the intermediary variables; innovation efficiency as the explanatory variable; and technical capabilities, technical management capabilities, technical strategies, and network capabilities as control variables, using data packets. The network analysis method establishes a development trend measurement model and analyzes the independent innovation path and development trend of the emerging marine industry through the established model. The four independent innovation paths of technological capability, technological management capability, technological strategy, and network capability have a positive incentive effect on the development of emerging marine industries, and technological capability has a higher incentive for the development of emerging marine industries. Based on the results of empirical analysis, it proposes strategies to promote the development of emerging marine industries, such as enhancing public awareness of emerging marine industries, improving long‐term mechanisms for the development of emerging marine industries, and enhancing the independent innovation capabilities of emerging marine industries.
Edible Bird’s Nest Regulates Hepatic Cholesterol Metabolism through Transcriptional Regulation of Cholesterol Related Genes
Authors: Yida Zhang , Al-Shuwayah Hussah , Ismail Maznah , Imam Mustapha Umar
Published: June 2022

Objective. Hypercholesterolemia is a strong risk factor for cardiovascular diseases. Side effects associated with the use of pharmaceutical agents can cancel out their benefits. Dietary management of hypercholesterolemia is, therefore, receiving much attention due to fewer side effects. In this study, we explored the effectiveness of edible bird’s nest (EBN) in the prevention of hypercholesterolemia in rats. Methods. High-cholesterol diet (HCD) (4.5% cholesterol and 0.5% cholic acid) with or without EBN (low (2.5%) or high dose (20%)) was given to rats for 12 weeks, and their weights were observed. Simvastatin (10 mg/kg/day) was administered for the same period as a control drug. Serum and tissue samples were collected at the end of the study, from which biochemical parameters (lipid profiles, oxLDL, liver enzymes, urea, creatinine, uric acid, and lipase activity) and hepatic mRNA levels were measured. Results. The HCD group had higher levels of serum lipids, liver enzymes, uric acid, urea, and lipase activity compared with those of the other groups. The hepatic mRNA levels of cholesterol metabolism genes (APOB, PCSK9, HMGCR, LDLR, and CYP7A1) in the HCD group also tended toward increased cholesterol production and reduced cholesterol clearance. EBN, especially the highest dose, attenuated the HCD-induced changes, partly through improving the transcriptional regulation of hepatic cholesterol metabolism genes with fold changes of 0.7, 0.6, 0.5, 1.7, and 2.7, respectively, in comparison to the HCD group. In fact, EBN produced better results than simvastatin. Conclusion. Thus, the results suggest that EBN can regulate cholesterol metabolism and, therefore, be a source of functional ingredients for the management of hypercholesterolemia.
Upregulation of PGC-1α Attenuates Oxygen-Glucose Deprivation-Induced Hippocampal Neuronal Injury
Authors: Han Bin , Zhao Hui , Gong Xingji , Sun Jinping , Chi Song , Liu Tao , Xie Anmu
Published: June 2022

Hippocampal neuronal damage likely underlies cognitive impairment in vascular dementia (VaD). PPARγ coactivator-1α (PGC-1α) is a master regulator of mitochondrial biogenesis. However, the role and the precise mechanism of how PGC-1α alleviates hippocampal neuronal injury remain unknown. To address this question, HT-22 cells, an immortalized hippocampal neuron cell line, with or without PGC-1α overexpression were subjected to oxygen-glucose deprivation (OGD), which mimics the circumstance of chronic cerebral hypoperfusion in VaD. After OGD, cell viability was assessed using the MTS assay. The mitochondrial function and reactive oxygen species (ROS) were both detected. ChIP-Seq analysis was employed to discover the underlying molecular mechanism of PGC-1α-mediated neuroprotective effects. Our results showed that mitochondrial membrane potentials were increased and ROS production was decreased in PGC-1α overexpressing cells, which increased cell viability. The further bioinformatics analysis from ChIP-Seq data indicated that PGC-1α may participate in the regulation of apoptosis, autophagy, and mitophagy pathways in HT-22 cells. We found that PGC-1α promoted the LC3-II formation and reduced the neuronal apoptosis determined by TUNEL staining. In addition, PGC-1α upregulated the expressions of mitochondrial antioxidants, including SOD2, Trx2, and Prx3. In summary, our findings indicate that PGC-1α may attenuate OGD-induced hippocampal neuronal damage by regulating multiple mechanisms, like autophagy and mitochondrial function. Thus, PGC-1α may be a potential therapeutic target for hippocampal damage associated with cognitive impairment.
English Writing Feedback Based on Online Automatic Evaluation in the Era of Big Data
Authors: Li Jing
Published: June 2022

Under the influence of the continuous development of modern information technology, the online automatic evaluation system for English writing teaching was born in response to demand. The rise of the online automatic assessment and correction system has broken through the limitations of the campus, making English writing teaching no longer restricted by time and space. Adapting to the needs of English writing development in the era of big data, making full use of modern information technology to improve writing effect, further promoting the development of educational informatization and the transformation of writing teaching, and realizing the mutual blending and innovative development of education and information technology have become the inevitable trend of future development. This paper applies the combination of teacher feedback and automatic feedback to the teaching of English writing in senior high school and discusses whether the combination of the two can change the disadvantages of the automatic writing evaluation system and solve the problem of traditional single teacher evaluation. In this paper, the text feedback system is introduced into the context information, and the context information is used to filter the difference between the active context and the active context, so as to further reduce the number of participants in collaborative filtering and improve the real-time computing efficiency of the algorithm. By distinguishing dynamic text quality indicators from stable text quality indicators, this paper proposes a similar context-aware neighborhood model. Based on experimental analysis, the accuracy of feedback results is 45.2% higher than that of the original online automatic evaluation system.
Intravesical VAX014 Synergizes with PD-L1 Blockade to Enhance Local and Systemic Control of Bladder Cancer
Authors: Tsuji Shingo , Reil Katherine , Nelson Kinsey , Proclivo Veronica H. , McGuire Kathleen L. , Giacalone Matthew J.
Published: June 2022

Emerging clinical evidence indicates that the combination of local administration of immunotherapy with systemic immune-checkpoint blockade targeting the PD-1/PD-L1 pathway improves response rates in select solid tumor indications; however, limited clinical experience with this approach exists in advanced bladder cancer patients. VAX014 is a novel bacterial minicell-based, integrin-targeted oncolytic agent undergoing clinical investigation for intravesical (IVE) treatment of nonmuscle-invasive bladder cancer. Here, we demonstrated that the antitumor activity of VAX014 following IVE administration was dependent upon CD4+ and CD8+ T cells in two syngeneic orthotopic bladder tumor models (MB49 and MBT-2). PD-L1 upregulation was found to be an acquired immune-resistance mechanism in the MB49 model, and the combination of VAX014 with systemic PD-L1 blockade resulted in a significant improvement in bladder tumor clearance rates and development of protective antitumor immunologic memory. Combination treatment also led to enhanced systemic antitumor immune responses capable of clearing distal intradermal tumors and controlling pulmonary metastasis. Distal tumors actively responding to combination therapy demonstrated a phenotypic shift from regulatory T cell to Th1 in intratumoral CD4+ T cells, which was accompanied by a higher percentage of activated CD8+ T cells and higher IFNγ. Finally, VAX014’s target integrins α3β1 and α5β1 were overexpressed in tumor biopsies from advanced-stage bladder cancer patients, as well as in both the MB49 and MBT-2 orthotopic mouse models of bladder cancer. These collective findings provide a rationale for the clinical investigation of VAX014 and systemic PD-1/PD-L1 blockade in advanced-stage bladder cancer.
TAK-676: A Novel Stimulator of Interferon Genes (STING) Agonist Promoting Durable IFN-dependent Antitumor Immunity in Preclinical Studies
Authors: Carideo Cunniff Elizabeth , Sato Yosuke , Mai Doanh , Appleman Vicky A. , Iwasaki Shinji , Kolev Vihren , Matsuda Atsushi , Shi Judy , Mochizuki Michiyo , Yoshikawa Masato , Huang Jian , Shen Luhua , Haridas Satyajeet , Shinde Vaishali , Gemski Chris , Roberts Emily R. , Ghasemi Omid , Bazzazi Hojjat , Menon Saurabh , Traore Tary , Shi Pu , Thelen Tennille D. , Conlon Joseph , Abu-Yousif Adnan O. , Arendt Christopher , Shaw Michael H. , Okaniwa Masanori
Published: June 2022

Oncology therapies targeting the immune system have improved patient outcomes across a wide range of tumor types, but resistance due to an inadequate T-cell response in a suppressive tumor microenvironment (TME) remains a significant problem. New therapies that activate an innate immune response and relieve this suppression may be beneficial to overcome this hurdle. TAK-676 is a synthetic novel stimulator of interferon genes (STING) agonist designed for intravenous administration. Here we demonstrate that TAK-676 dose-dependently triggers activation of the STING signaling pathway and activation of type I interferons. Furthermore, we show that TAK-676 is a highly potent modulator of both the innate and adaptive immune system and that it promotes the activation of dendritic cells, natural killer cells, and T cells in preclinical models. In syngeneic murine tumor models in vivo, TAK-676 induces dose-dependent cytokine responses and increases the activation and proliferation of immune cells within the TME and tumor-associated lymphoid tissue. We also demonstrate that TAK-676 dosing results in significant STING-dependent antitumor activity, including complete regressions and durable memory T-cell immunity. We show that TAK-676 is well tolerated, exhibits dose-proportional pharmacokinetics in plasma, and exhibits higher exposure in tumor. The intravenous administration of TAK-676 provides potential treatment benefit in a broad range of tumor types. Further study of TAK-676 in first-in-human phase I trials is ongoing.

Significance:

TAK-676 is a novel systemic STING agonist demonstrating robust activation of innate and adaptive immune activity resulting in durable antitumor responses within multiple syngeneic tumor models. Clinical investigation of TAK-676 is ongoing.
Replication Stress Defines Distinct Molecular Subtypes Across Cancers
Authors: Takahashi Nobuyuki , Kim Sehyun , Schultz Christopher W. , Rajapakse Vinodh N. , Zhang Yang , Redon Christophe E. , Fu Haiqing , Pongor Lorinc , Kumar Suresh , Pommier Yves , Aladjem Mirit I. , Thomas Anish
Published: June 2022

Endogenous replication stress is a major driver of genomic instability. Current assessments of replication stress are low throughput precluding its comprehensive assessment across tumors. Here we develop and validate a transcriptional profile of replication stress by leveraging established cellular characteristics that portend replication stress. The repstress gene signature defines a subset of tumors across lineages characterized by activated oncogenes, aneuploidy, extrachromosomal DNA amplification, immune evasion, high genomic instability, and poor survival, and importantly predicts response to agents targeting replication stress more robustly than previously reported transcriptomic measures of replication stress. Repstress score profiles the dual roles of replication stress during tumorigenesis and in established cancers and defines distinct molecular subtypes within cancers that may be more vulnerable to drugs targeting this dependency. Altogether, our study provides a molecular profile of replication stress, providing novel biological insights of the replication stress phenotype, with clinical implications.

Significance:

We develop a transcriptional profile of replication stress which characterizes replication stress and its cellular response, revealing phenotypes of replication stress across cancer types. We envision the repstress score to serve as an effective discovery platform to predict efficacy of agents targeting replication stress and clinical outcomes.
An Unusual Case of Unilateral Maculopathy
Authors: Shipton Chloe Jennifer , Gilmour David Francis
Published: June 2022

A 44-year-old male presented with unilateral sudden onset reduced visual acuity. The optical coherence tomography (OCT) scan demonstrated submacular fluid with thickening and hyper-reflectivity of the outer retinal layers, together with subfoveal retinal pigment epithelial hyper-reflectivity corresponding to a small area of foveal interdigitation zone/ellipsoid zone (IZ/EZ) loss in the detached retina. An OCT 4 months later showed resolution of the submacular fluid, but the IZ/EZ loss persisted with thinning of the outer nuclear layer, resulting in a poor visual outcome. The clinical findings most likely represent a case of unilateral acute idiopathic maculopathy; however, the OCT features and poor visual outcome are not typical. Differential diagnoses include acute solar maculopathy, central serous chorioretinopathy, poppers maculopathy, whiplash maculopathy, and acute retinal pigment epitheliitis.
Essential Roles of TDO2 in Gastric Cancer: TDO2 Is Associated with Cancer Progression, Patient Survival, PD-L1 Expression, and Cancer Stem Cells
Authors: Pham Quoc Thang , Taniyama Daiki , Akabane Shintaro , Takashima Tsuyoshi , Maruyama Ryota , Sekino Yohei , Sentani Kazuhiro , Yasui Wataru , Oue Naohide
Published: June 2022

Introduction: Tryptophan metabolism has been shown to be involved in tumor development. Two main tryptophan-degrading enzymes, tryptophan 2,3-dioxygenase (TDO2) and indoleamine 2,3-dioxygenase 1 (IDO1), may potently promote cancer cell survival and distant metastasis in diverse types of cancer, such as lung and breast cancer. IDO1 overexpression is an independent prognosticator in gastric cancer (GC). This work aimed to uncover the expression of TDO2 and its clinicopathologic significance in GC. Methods: TDO2 expression was evaluated in public data of The Cancer Genome Atlas cohort STAD and in two different GC cohorts. Correlation between TDO2 and immune cell infiltrates as well as PD-L1 tumor staining was investigated. The biofunction of TDO2 was examined with MTT, colony formation, and spheroid formation assays by RNA interference. Results: TDO2 expression was correlated with both progressive disease and clinical outcome, and its expression was an independent predictor of prognosis in GC. TDO2 expression was correlated with infiltration of immune cells and tumor expression of PD-L1. Inhibition of TDO2 expression suppressed cell proliferation, colony formation, and cell invasion of GC cells. Additionally, suppression of TDO2 expression inhibited spheroid body-formation and viability of GC organoids. Conclusion: Our data show that TDO2 might be a crucial marker for predicting prognosis and targeted therapy in GC.
LAight® Therapy Is an Effective Treatment Option to Maintain Long-Term Remission of Hurley I and II Hidradenitis Suppurativa: Results from Period B of RELIEVE, a Multicenter Randomized, Controlled Trial
Authors: Schultheis Michael , Staubach Petra , Grabbe Stephan , Ruckes Christian , von Stebut Esther , Kirschner Uwe , Matusiak Łukasz , Szepietowski Jacek C. , Nikolakis Georgios
Published: June 2022

Background: Hidradenitis suppurativa is a chronic, inflammatory, burdensome skin disease where current first-line treatments are limited to topical and/or systemic antibiotics which cannot be applied for long-term disease management. Period B of the RELIEVE study analyzes whether LAight® therapy can sustain or even increase remission after a first topical antibiotic treatment cycle. Methods: The RELIEVE study was performed as a two-period multicenter randomized controlled trial with blinded assessment. For period A from week 0 to week 16, the 88 participating Hurley I and II patients were randomized to either a group receiving topical clindamycin 1% solution combined with 8 additional bi-weekly treatments with LAight® therapy (group TC + L) or a group which was treated with topical clindamycin 1% solution only (group TC). After 16 weeks, patients entered open-label period B and both groups were treated exclusively with LAight® therapy for an additional 16 weeks (8 sessions, group TC + L/L and group TC/L). Results: In total, 88 patients were enrolled in RELIEVE. Seventy-eight patients entered period B; 39 belonged to group TC + L/L and 39 to group TC/L. The IHS4-response at the start of period B was 62% (group TC + L/L) and 33% (group TC + L). During the 16 weeks of additional monotherapy with LAight, in both groups >90% of patients who responded to therapy in period A maintained their IHS4-response at week 32. IHS4 response rates continued to rise up to 79% of the TC + L/L group and up to 71% of the TC/L group during period B at week 32. Achievement of HiSCR and certain patient reported outcomes confirmed primary endpoint results. Conclusion: LAight® therapy is an effective approved therapy option for Hurley I and II HS that can be used continuously to maintain treatment success. During 16 weeks of follow-up in period B, over 90% of patients with response after period A maintained their treatment outcome, while more than 60% of prior nonresponders gained response. The fact that LAight® therapy can be applied continuously, is very effective and is well tolerated makes it a valuable treatment tool in the design of HS long-term treatment modalities.
EPIDEMIOLOGY AND SEASONAL VARIATION OF APPENDICITIS – A SINGLE CENTER RETROSPECTIVE STUDY FROM NORTH-EAST INDIA
Authors: Kumar R. , Singh T. B. , Pandey R. , Bhalla S. , Singh O.
Published: June 2022

Background. Acute appendicitis is the most common surgical emergency presenting in emergency department, and appendectomy is one of the most common surgeries. There is a wide variation in the incidence of acute appendicitis reported for different countries, different regions, race, sex, age and also seasons.
Objective. The aim of this study was to understand the epidemiological trend and the seasonal variation of appendicitis in the northeast region of India.
Methods. It was a retrospective hospital-based study conducted in Jan 2016 – Dec 2020 at a Tertiary Care Teaching Hospital in the northeast region of India. The patient data were obtained from the Medical Record Department of the hospital and the data regarding the weather was obtained from the Indian Meteorological Department (IMD) and the website www.worldweather.com. The statistical analysis was done using SPSS software version 24.0, and the seasonal variation was studied using Kruskal Wallis test.
Results. Acute appendicitis affected both the sexes equally with a marginal higher incidence in males. It also had higher peak during the second and third decade of life in both the sexes. The incidence of acute appendicitis was high in the pre-monsoon and monsoon season with peak in the monsoon season.
Conclusions. Acute appendicitis is more common during the pre-monsoon and monsoon season, a period known for humidity, high incidence of bacterial and viral infections.
VITAMIN D3 IN TREATMENT OF OSTEOPENIC SYNDROME IN CHILDREN WITH GROWTH DISORDERS
Authors: Shcherbatiuk N. Yu.
Published: June 2022

Background. The efficacy of vitamin D3 agents for impaired growth of children of different cause was studied in the research. A positive effect on bone mineralization and calcium-phosphorus metabolism was evidenced. The treatment and prophylaxis charts using this drug for osteopenic syndrome are developed for children with hypothalamic-pituitary dwarfism, subdwarfism and dwarfism of constitutional genesis.
Objective. The aim of the research is to study the effect of calcimine and vitamin D3 in cases of impaired bone mineral density in children aged 6-18 years old with growth retardation of the hypothalamic-pituitary genesis, subdwarfism and dwarfism of constitutional origin.
Methods. The study involved 25 children, aged 6-18 years old with growth retardation: hypothalamic-pituitary (10 children), subdwarfism (5 children) and dwarfism of constitutional origin (10 children). The control group consisted of 20 children. The structural and functional state of bone tissue was studied using a two-photon X-ray densitometer “Lunar”. In the study of calcium-phosphorus homeostasis, the level of calcium and the level of phosphorus in the blood serum were determined. Serum alkaline phosphatase levels were also studied as a marker for bone formation.
Results. In the examined children, there was a significant calcium deficiency at the level of the vertebrae L1–L4. The calcium content in L1 was 72.8%, L2 – 75.7%, L3 – 81.2%, L4 – 80.1%, which significantly differed from bone density in healthy children of a similar age and body weight. It was also revealed that in children diagnosed with growth retardation of the pituitary genesis, bone rarefaction was diagnosed in 100% of cases, while with subdwarfism and dwarfism of constitutional genesis these indicators were 43% and 24%, respectively.
Conclusions. A differentiated choice of vitamin D3 treatment, depending on the degree of osteopenia in children, allows adjusting the calcium metabolism and preventing osteoporosis in children with stunted growth. Vitamin D3 in the complex treatment of osteoporosis in children with growth impairment of different genesis normalizes calcium-phosphorus homeostasis, which increases bone mineral density and, therefore, reduces osteoporotic changes by stopping leaching of calcium from bones.
CURRENT DIAGNOSIS, PREVENTION AND TREATMENT OF DRY SOCKET
Authors: Hutor N. S.
Published: June 2022

Background. Tooth extraction is the most common surgical intervention in the outpatient practice of a dental surgeon. In most cases, bone wound healing is uncomplicated. However, in some patients the course of healing is complicated by acute inflammatory process of dry socket (alveolar osteitis), the frequency of which increases with increasing trauma of surgery. In dentally healthy patients with typical tooth extraction, dry socket occurs in 2.55%, with difficult – in 9.84%, with atypical extraction of the lower wisdom tooth – in 31.03% of cases. In the presence of diabetes, the incidence of dry socket with typical removal is much higher and according to various authors it is 9.7-13.5%.
Objective. The aim of the research was to study the publications and their analysis on the current diagnosis, prevention and treatment of patients with dry socket.
Methods. Scientific sources were the articles in world periodicals on dental surgery and therapy, microbiology as well as some electronic resources and patents.
Results. At present, many techniques, methods, schemes, compositions for treatment of various forms of dry socket are established. Most often, antibacterial drugs or their combinations with other drugs are used. However, antibacterial drugs do not always have a pronounced anti-inflammatory effect due to the high resistance of the oral microflora. In these cases, contemporary drugs in the form of a composition with long-term antiseptic, anti-inflammatory and analgesic action are rational.
Conclusions. The action of a Flupetsal composition, which contains antimicrobial and immunomodulatory drug flurenizide, was clinically proven for treatment of patients with dry socket; the properties of the available ingredients provide a high disinfectant effect, prevent development of inflammation in the tissues and its transition to purulence. A contemporary effective method of treating patients with dry socket is carried out according to the developed method.
CURRENT TRENDS IN PRESCRIBING PATTERN OF ANTI-MIGRAINE DRUGS IN PATIENTS OF MIGRAINE AT A TERTIARY CARE TEACHING HOSPITAL
Authors: Soni G. , Jain S. , Rathi P. , Goswami P.
Published: June 2022

Background. An inappropriate prescribing pattern of antimigraine drugs by doctors may often encourage inappropriate self-medication by patients because of the asymmetry of medical information.
Objective. The study is aimed to assess the current trends in prescribing patterns of anti-migraine drugs, rationality of prescription, and pattern of migraine severity in patients of migraine.
Methods. A cross sectional study was conducted at a tertiary care teaching hospital. All the prescribing details including patient’s demographic details, diagnosis, details of drug therapy (drug name, dose, duration, and frequency) were recorded. Rationality of prescription was assessed using the WHO core drug prescribing indicators and the pattern of severity of migraine was assessed using MIDAS scoring system.
Results. Out of 85 patients, 71 were female (83.5%), mostly around 21-30 years of age, and 27 (31.7%) patients had other comorbidities. Naproxen was the most commonly used NSAID for termination of acute migraine attack (15.3 %). The most common drugs prescribed for prophylaxis included beta adrenergic blockers (Propranolol, 14.66%), antidepressants (Amitriptyline, 9.33% and Fluoxetine 3.33%), and antipsychotics (Prochlorperazine, 4.66%). Domperidone (17.30%) was the most commonly prescribed antiemetic. Prescription of triptans was low (2.66%) with Rizatriptan as the most commonly prescribed triptan.
Conclusions. The current study revealed that further improvements are required in prescribing practices especially in average number of drugs per prescription, prescription of drugs with generic names, and prescription of drugs of the essential drugs list.
RETROSPECTIVE ANALYSIS OF GENDER-AGE STRUCTURE AND COMORBID PATHOLOGY OF PATIENTS WITH VIRAL AND BACTERIAL PNEUMONIA ASSOCIATED WITH COVID-19
Authors: Romanyuk L. B. , Volch I. R. , Kravets N. Y. , Pyatkovskyy T. I. , Zahrychuk O. M.
Published: June 2022

Background. In December 2019 first case of COVID-19 was first registered in Wuhan, Hubei province, China. This infectious disease primarily causes respiratory tract infection, but can also affect the other organs and systems.
Objective. In this study, the features of the gender-age structure and comorbid pathology of the patients with viral and bacterial pneumonia who were treated in inpatient department in the period from September to December 2020 are summarized.
Methods. The research was conducted in Ternopil Municipal Hospital No. 3, Ternopil, Ukraine. Clinical cases of 262 patients with viral and bacterial pneumonia associated with COVID-19 were studied retrospectively.
Results. Both men and women has been affected by this pathology in Ternopil region with the same frequency in contrast with the established fact that men are less resistant to infections that women. Most of the patients ranged in age from 51 to 70 years, however, a fair number of patients were over the age of 70 years. Concomitant pathology was diagnosed in 65.5% of the patients with coronavirus infection. Coronary heart disease (34.5%) is leading in the structure of comorbid conditions.
Conclusions. During the COVID-19 pandemic, timely diagnosis and medical care of the patients over 50 years of age is of great importance. The analysis of concomitant pathology proves that the people with cardiovascular pathology are in the increased risk group.