bluuebunny/crossref_metadata_2025 huggingface dataset:
Angiotensin-converting enzyme 2 in peripheral lung club cells modulates the susceptibility to SARS-CoV-2 in chronic obstructive pulmonary disease
Authors: Peng Yang , Wang Zhao-Ni , Chen Shi-Ying , Xu Ai-Ru , Fang Zhang-Fu , Sun Jing , Zhou Zi-Qing , Hou Xiao-Tao , Cen Lai-Jian , Ma Jian-Juan , Zhao Jin-Cun , Guan Wei-Jie , Wang De-Yun , Zhong Nan-Shan
Published: March 2022

Accumulating evidence has confirmed that chronic obstructive pulmonary disease (COPD) is a risk factor for development of severe pathological changes in the peripheral lungs of patients with COVID-19. However, the underlying molecular mechanisms remain unclear. Because bronchiolar club cells are crucial for maintaining small airway homeostasis, we sought to explore whether the altered susceptibility to SARS-CoV-2 infection of the club cells might have contributed to the severe COVID-19 pneumonia in COPD patients. Our investigation on the quantity and distribution patterns of angiotensin-converting enzyme 2 (ACE2) in airway epithelium via immunofluorescence staining revealed that the mean fluorescence intensity of the ACE2-positive epithelial cells was significantly higher in club cells than those in other epithelial cells (including ciliated cells, basal cells, goblet cells, neuroendocrine cells, and alveolar type 2 cells). Compared with nonsmokers, the median percentage of club cells in bronchiolar epithelium and ACE2-positive club cells was significantly higher in COPD patients. In vitro, SARS-CoV-2 infection (at a multiplicity of infection of 1.0) of primary small airway epithelial cells, cultured on air-liquid interface, confirmed a higher percentage of infected ACE2-positive club cells in COPD patients than in nonsmokers. Our findings have indicated the role of club cells in modulating the pathogenesis of SARS-CoV-2-related severe pneumonia and the poor clinical outcomes, which may help physicians to formulate a novel therapeutic strategy for COVID-19 patients with coexisting COPD.
Mechanosensitive channel Piezo1 is required for pulmonary artery smooth muscle cell proliferation
Authors: Chen Jiyuan , Rodriguez Marisela , Miao Jinrui , Liao Jing , Jain Pritesh P. , Zhao Manjia , Zhao Tengteng , Babicheva Aleksandra , Wang Ziyi , Parmisano Sophia , Powers Ryan , Matti Moreen , Paquin Cole , Soroureddin Zahra , Shyy John Y.-J. , Thistlethwaite Patricia A. , Makino Ayako , Wang Jian , Yuan Jason X.-J.
Published: March 2022

Concentric pulmonary vascular wall thickening due partially to increased pulmonary artery (PA) smooth muscle cell (PASMC) proliferation contributes to elevating pulmonary vascular resistance (PVR) in patients with pulmonary hypertension (PH). Although pulmonary vasoconstriction may be an early contributor to increasing PVR, the transition of contractile PASMCs to proliferative PASMCs may play an important role in the development and progression of pulmonary vascular remodeling in PH. A rise in cytosolic Ca2+ concentration ([Ca2+]cyt) is a trigger for PASMC contraction and proliferation. Here, we report that upregulation of Piezo1, a mechanosensitive cation channel, is involved in the contractile-to-proliferative phenotypic transition of PASMCs and potential development of pulmonary vascular remodeling. By comparing freshly isolated PA (contractile PASMCs) and primary cultured PASMCs (from the same rat) in a growth medium (proliferative PASMCs), we found that Piezo1, Notch2/3, and CaSR protein levels were significantly higher in proliferative PASMCs than in contractile PASMCs. Upregulated Piezo1 was associated with an increase in expression of PCNA, a marker for cell proliferation, whereas downregulation (with siRNA) or inhibition (with GsMTx4) of Piezo1 attenuated PASMC proliferation. Furthermore, Piezo1 in the remodeled PA from rats with experimental PH was upregulated compared with PA from control rats. These data indicate that PASMC contractile-to-proliferative phenotypic transition is associated with the transition or adaptation of membrane channels and receptors. Upregulated Piezo1 may play a critical role in PASMC phenotypic transition and PASMC proliferation. Upregulation of Piezo1 in proliferative PASMCs may likely be required to provide sufficient Ca2+ to assure nuclear/cell division and PASMC proliferation, contributing to the development and progression of pulmonary vascular remodeling in PH.
Sacral neuromodulation of bladder underactivity induced by prolonged pudendal afferent firing in cats
Authors: Shen Bing , Wang Jicheng , Shen Zhijun , Jian Jianan , Goosby Khari , Beckel Jonathan , de Groat William C. , Tai Changfeng
Published: March 2022

This study examined the effect of sacral neuromodulation on persistent bladder underactivity induced by prolonged pudendal nerve stimulation (PudNS). In 10 α‐chloralose-anesthetized cats, repetitive application of 30-min PudNS induced bladder underactivity evident as an increase in bladder capacity during a cystometrogram (CMG). S1 or S2 dorsal root stimulation (15 or 30 Hz) at 1 or 1.5 times threshold intensity (T) for inducing reflex hindlimb movement (S1) or anal sphincter twitch (S2) was applied during a CMG to determine if the stimulation can reverse the bladder underactivity. Persistent (>3 h) bladder underactivity consisting of a significant increase in bladder capacity to 163.1 ± 11.3% of control was induced after repetitive (1–10 times) application of 30-min PudNS. S2 but not S1 dorsal root stimulation at 15 Hz and 1 T intensity reversed the PudNS-induced bladder underactivity by significantly reducing the large bladder capacity to 124.3 ± 12.9% of control. Other stimulation parameters were not effective. After the induction of persistent underactivity, recordings of reflex bladder activity under isovolumetric conditions revealed that S2 dorsal root stimulation consistently induced the largest bladder contraction at 15 Hz and 1 T when compared with other frequencies (5–40 Hz) or intensities (0.25–1.5 T). This study provides basic science evidence consistent with the hypothesis that abnormal pudendal afferent activity contributes to the bladder underactivity in Fowler’s syndrome and that sacral neuromodulation treats this disorder by reversing the bladder inhibition induced by pudendal nerve afferent activity.
Aldehyde dehydrogenase 2 deficiency promotes skeletal muscle atrophy in aged mice
Authors: Kasai Akane , Jee Eunbin , Tamura Yuki , Kouzaki Karina , Kotani Takaya , Nakazato Koichi
Published: March 2022

Aldehyde dehydrogenase 2 (ALDH2) detoxifies acetaldehyde produced from ethanol. A missense single nucleotide polymorphism (SNP) rs671 in ALDH2 exhibits a dominant-negative form of the ALDH2 protein. Nearly 40% of people in East Asia carry an inactive ALDH2*2 mutation. Previous studies reported that ALDH2*2 is associated with increased risk of several diseases. In this study, we examined the effect of ALDH2 deficiency on age-related muscle atrophy and its underlying mechanisms. We found that ALDH2 deficiency promotes age-related loss of muscle fiber cross-sectional areas, especially in oxidative fibers. Furthermore, ALDH2 deficiency exacerbated age-related accumulation of 4-hydroxy-2-nonenal (4-HNE), a marker of oxidative stress in the gastrocnemius muscle. Similarly, mitochondrial reactive oxygen species (ROS) production increased in aged ALDH2-knockout mice, indicating that ALDH2 deficiency induced mitochondrial dysfunction. In summary, ALDH2 deficiency promotes age-related muscle loss, especially in oxidative fibers, which may be associated with an increased accumulation of oxidative stress via mitochondrial dysfunction.
Bursting emerges from the complementary roles of neurons in a four-cell network
Authors: Sakurai Akira , Katz Paul S.
Published: March 2022

Half-center oscillators composed of reciprocally inhibitory neurons have been posited for over a century to underlie the production of rhythmic movements. The Dendronotus swim central pattern generator may be the simplest such circuit with only two pairs of bilaterally represented neurons. This study completes the description of the mechanism by which this network oscillator functions, showing how stable rhythmic activity arises from the complementary membrane and synaptic properties of the two neurons in the competing modules.
Contribution of sensory feedback to soleus muscle activity during voluntary contraction in humans
Authors: Rasul Aqella , Lorentzen Jakob , Frisk Rasmus Feld , Sinkjær Thomas , Nielsen Jens Bo
Published: March 2022

Sensory feedback through spinal reflex pathways makes only a minor contribution to neural drive to muscles during voluntary ankle plantar flexion. This differs distinctly from observations during walking and suggests that the neural drive to ankle plantar flexors during voluntary contraction do not rely on sensory feedback through similar spinal interneuronal networks as during walking. In line with animal studies this suggests that the integration of sensory feedback in CNS is task specific.
Leveled Multi-Hop Multi-Identity Fully Homomorphic Encryption
Authors: Liu Wen , Wang Fuqun , Jin Xiaodan , Chen Kefei , Shen Zhonghua
Published: March 2022

Gentry, Sahai, and Waters (CRYPTO 2013) proposed the notion of multi-identity fully homomorphic encryption (MIFHE), which allows homomorphic evaluation of data encrypted under multiple identities. Subsequently, Clear and McGoldrick (CANS 2014, CRYPTO 2015) proposed leveled MIFHE candidates. However, the proposed MIFHE is either based on iO, which is a nonstandard assumption or single hop; that is, an arbitrary “evaluated” ciphertext under a set of identities is difficult to further evaluate when new ciphertexts are encrypted under additional identities. To overcome these drawbacks, we propose a leveled multi-hop MIFHE scheme. In a multi-hop MIFHE scheme, one can evaluate a group of ciphertexts under a set of identities to obtain an “evaluated” ciphertext, which can be further evaluated with other ciphertexts encrypted under additional identities. We also show that the proposed MIFHE scheme is secure against selective identity and chosen-plaintext attacks (IND-sID-CPA) under the learning with errors (LWE) assumption.
Construction of a Prognostic Nomogram Model for Patients with Mucinous Breast Cancer
Authors: Zhu Xulong , Li Ying , Liu Fende , Zhang Feifei , Li Jianhui , Cheng Chong , Shen Yanwei , Jiang Nan , Du Jia , Zhou Yajing , Huo Binliang
Published: March 2022

Objective. The objective of the study is to develop a nomogram for estimating three- and five-year survival rates in mucinous breast cancer patients. Methods. Between 2010 and 2016, the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) were searched as a data source for patients associated with mucinous breast cancer (MBC). A total of 3964 patients were recruited after screening. The multivariate Cox model and the univariate Kaplan-Meier (KM) approach were employed to evaluate the independent prognostic markers, followed by developing a nomogram for estimating three- and five-year survival rates in MBC patients. Consequently, the consistency index (C-index) was employed to assess the predictive accuracy of the generated nomogram. Results. Age, race, T stage, M stage, surgery, and radiotherapy were all independent predictive biomarkers for the MBC patients (

P
<
0.05

). The nomogram was finally developed based on the underlined factors. Furthermore, the C-index of 0.803 and reliable calibration curves were obtained in the nomogram’s assessment. Conclusions. In patients with mucinous breast cancer, the proposed nomogram provides a viable tool for accurate prognostic prediction. In clinical practice, it could serve as a personalized diagnosis tool, estimate prognosis, and help in suggesting treatment plans for patients with MBC.
Seungmagalgeun-Tang, a Traditional Herbal Formula, Alleviates Skin Inflammation and Depression-Like Behavior in Atopic Dermatitis Mice under Sleep Deprivation Conditions
Authors: Thi Huong Nguyen Ly , Choi Min-Jin , Shin Heung-Mook , Yang In-Jun
Published: March 2022

Atopic dermatitis (AD) is a common inflammatory skin disease, which can be worsened under sleep deprivation (SD) conditions. This study investigated the efficacy and the mechanism of action of the traditional herbal formula Seungmagalgeun-tang (SMGGT) on the inflammation and behavioral changes in a mouse model of AD exposed to SD. SMGGT decreased levels of IgE, TNF-α, IL-4, IL-13, and mast cell infiltration and reduced the expression of CD3 in the mouse skin. SMGGT also reversed the SD-induced increase in corticosterone and decrease in melatonin level. Furthermore, SMGGT reduced the immobility time in the tail suspension test significantly. HaCaT cells and HMC-1 cells were used to investigate the effects of SMGGT on cell signaling pathways. In TNF-α/IFN-γ (TI) treated HaCaT cells, SMGGT reduced production of TARC/CCL17 and MDC/CCL22 and suppressed the p38 MAPK, STAT1, and NF-κB pathways. In substance P (SP)/CRH-stimulated HMC-1 cells, SMGGT decreased VEGF production and inhibited ERK phosphorylation. Network pharmacology and molecular docking analysis revealed that puerarin and paeoniflorin might contribute to the effects of SMGGT by targeting several AD-related molecules and pathways. Puerarin and paeoniflorin exerted anti-inflammatory effects by decreasing production of MDC/CCL22 and IL-6 in TI-treated HaCaT cells and VEGF production in SP/CRH-stimulated HMC-1 cells. This study suggests that SMGGT with puerarin and paeoniflorin as main bioactive components alleviates skin inflammation and depression-like behavior in a sleep-deprived mouse model of AD.
Validation of the Japanese Version of the Questionnaire for Impulsive-Compulsive Disorders in Parkinson’s Disease-Rating Scale (QUIP-RS)
Authors: Takahashi Maiko , Koh Jinsoo , Yorozu Shoko , Kajimoto Yoshinori , Nakayama Yoshiaki , Sakata Mayumi , Yasui Masaaki , Hiwatani Yasuhiro , Weintraub Daniel , Ito Hidefumi
Published: March 2022

Introduction. The Questionnaire for Impulsive-Compulsive Disorders in Parkinson’s Disease (PD)-Rating Scale (QUIP-RS) was developed to assess the severity of impulsive and compulsive behaviors (ICBs) in PD. We aimed to validate the Japanese version of QUIP-RS and determine the characteristics of ICBs in Japan. Methods. We translated the QUIP-RS into Japanese, back-translated it to English, and obtained confirmation from the original author that the questionnaire remained appropriate. The participants for the validation study were 161 PD patients, identified by continuous sampling at two institutions, who were diagnosed with ICBs through a semistructured interview and completed the QUIP-RS-J. Sensitivity, specificity, and cutoff values were calculated using receiver operating characteristic (ROC) curves. Interinstitutional reliability and test-retest reliability were also assessed for a subset of participants. Results. Twenty-six (16.1%) participants were diagnosed with ICB. The optimal cutoff value of the QUIP-RS-J total score was 6, with area under the curve (AUC) = 0.889 and sensitivity/specificity of 0.92/0.71. Each subscale also showed high AUC (0.89–1.00), sensitivity (0.92–1.00), and specificity (0.71–1.00). Compared with the English version, the optimal cutoff point for binge eating was higher and hypersexuality lower. The total score tended to be higher when described by an informant. Conclusion. The present study validated the Japanese version of QUIP-RS. Use of QUIP-RS-J enables standardized assessment of ICBs and can be used in clinical research, including international multicenter studies.
Diabetes Mellitus Diagnosis and Screening in Australian General Practice: A National Study
Authors: Zheng Mingyue , Bernardo Carla De Oliveira , Stocks Nigel , Gonzalez-Chica David
Published: March 2022

Aims. To investigate the epidemiology of diabetes diagnosis and screening in Australian general practice. Methods. Cross-sectional study using electronic health records of 1,522,622 patients aged 18+ years attending 544 Australian general practices (MedicineInsight database). The prevalence of diagnosed diabetes and diabetes screening was explored using all recorded diagnoses, laboratory results, and prescriptions between 2016 and 2018. Their relationship with patient sociodemographic and clinical characteristics was also investigated. Results. Overall, 7.5% (95% CI 7.3, 7.8) of adults had diabetes diagnosis, 0.7% (95% CI 0.6, 0.7) prediabetes, and 0.3% (95% CI 0.3, 0.3) unrecorded diabetes/prediabetes (elevated glucose levels without a recorded diagnosis). Patients with unrecorded diabetes/prediabetes had clinical characteristics similar to those with recorded diabetes, except for a lower prevalence of overweight/obesity (55.5% and 69.9%, respectively). Dyslipidaemia was 1.8 times higher (36.2% vs. 19.7%), and hypertension was 15% more likely (38.6% vs. 33.8%) among patients with prediabetes than with diabetes. Diabetes screening (last three years) among people at high risk of diabetes was 55.2% (95% CI 52.7, 57.7), with lower rates among young or elderly males. Conclusions. Unrecorded diabetes/prediabetes is infrequent in Australian general practice, but prediabetes diagnosis was also lower than expected. Diabetes screening among high-risk individuals can be improved, especially in men, to enhance earlier diabetes diagnosis and management.
A Bridge Structure 3D Representation for Deep Neural Network and Its Application in Frequency Estimation
Authors: Hu Kejian , Wu Xiaoguang
Published: March 2022

Currently, most predictions related to bridge geometry use shallow neural networks, which limit the network’s ability to fit since the input form limits the depth of the neural network. Therefore, this study proposed a new 3D representation of bridge structures. Based on the geometric parameters of the bridge structure, three 4D tensors were formed. This form of representation not only retained all geometric information but also expressed the spatial relationship of the structure. Then, this study constructed the corresponding 3D convolutional neural network and used it to estimate the frequency of the bridge. In addition, this study also developed a traditional shallow neural network for comparison. The application of 3D representation and 3D convolution could effectively reduce the prediction error. The 3D representation presented in this study could be used not only for frequency prediction but also for any prediction problems related to bridge geometry.
Evaluation Methods of Interactive Effects of Collaborative English Learning in Colleges in Online Environment
Authors: Zhang Yang , Zhang Hai , Wang Yining
Published: March 2022

The rapid development of modern teaching information technology, especially the application of modern information technology, represented by multimedia technology and Internet information technology in education, makes collaborative learning (CL) in an online environment more critical, and its evaluation issues are more prominent. This article aims to study the interactive effect of the evaluation method of college English CL in the online environment. This paper mainly analyzes the composition of cooperative learning, the effect evaluation function of online cooperative learning, the elements of interactive design, and other teaching activities on learning. Combining the experimental method and the questionnaire survey method, a class of non-English majors in a university is selected as the research object. All students perform English CL in an online environment, and we finally analyze the interactive effects of students’ CL based on the data obtained from pretests and questionnaires. The experimental results show that the interaction of teachers and students through the CL of online platforms has become closer.
Estimation of Entropy for Log‐Logistic Distribution under Progressive Type II Censoring
Authors: Shrahili M. , El-Saeed Ahmed R. , Hassan Amal S. , Elbatal Ibrahim , Elgarhy Mohammed
Published: March 2022

Entropy is a useful indicator of information content that has been used in a number of applications. The Log‐Logistic (LL) distribution is a probability distribution that is often employed in survival analysis. This paper addresses the problem of estimating multiple entropy metrics for an LL distribution using progressive type II censoring. We derive formulas for six different types of entropy measurements. To obtain the estimators of the proposed entropy measures, the maximum likelihood approach is applied. Approximate confidence intervals are calculated for the entropy metrics under discussion. A numerical evaluation is performed using various censoring methods and sample sizes to characterize the behavior of estimator’s measures using relative biases, related mean squared errors, average interval lengths, and coverage probabilities. Numerical analysis revealed that the accuracy measures improve with sample size, and the suggested entropy estimates approach the genuine values as censoring levels decrease. Finally, an actual dataset was evaluated for demonstration purposes.
Intestinal Flora: A Potential Mechanism by Which Yinlai Decoction Treats Lipopolysaccharide-Induced Pneumonia
Authors: Xu Jingnan , Ma Xueyan , Bai Chen , Jiang Xin , Huang Ling , Gao Fei , Li Yini , Yu He , Liu Tiegang , Gu Xiaohong
Published: March 2022

Background. We intended to explore the mechanism of Yinlai decoction in the treatment of lipopolysaccharide (LPS)-induced pneumonia from the perspective of intestinal flora. Methods. Thirty Sprague–Dawley rats were randomly assigned to the blank control group (N), the pneumonia group (P), and the Yinlai decoction group (PT). The rat pneumonia model was established using LPS inhalation (0.5 mg/mL, 5 mL, 30 min/day, 3 days). Yinlai decoction was administered intragastrically (2 mL/100 g, 3 days). Lung tissue pathology, organ indexes, serum inflammatory factors, tumor necrosis factor-alpha (TNF-α), and intestinal flora changes were measured. Results. Lung tissue inflammation was prevented by Yinlai decoction. IL-6 levels showed a higher tendency to be higher, and IL-12 and TNF-α were significantly higher in the PT group than in the P group. The structure of the intestinal flora in the P differed from that in the N. The relative abundance of 10 out of 12 microflora was significantly higher in the P group than in the N and PT groups. In the PT group, the structure and the distribution of microbial groups were like those of the N group. Conclusions. Yinlai decoction inhibited LPS-induced lung and systemic inflammation in rats and may help the intestinal flora restore equilibrium by inhibiting the colonization of pathogenic bacteria and adjusting the ratio between probiotics and pathogenic bacteria. Intestinal flora may serve as a mediator of Yinlai decoction’s effect on LPS-induced pneumonia.
Some More Results on Reciprocal Degree Distance Index and ℱ‐Sum Graphs
Authors: Razzaque Asima , Noor Saima , Kanwal Salma , Manzoor Ayesha
Published: March 2022

A chemical invariant of graphical structure is a unique value characteristic that remains unchanged under graph automorphisms. In the study of QSAR/QSPR, like many other chemical invariants, reciprocal degree distance has played a significant role to estimate the bioactivity of several compounds in chemistry. Reciprocal degree distance is a chemical invariant, which is the degree weighted version of Harary index, i.e., . Eliasi and Taeri proposed four new graphic unary operations: , and , frequently implemented in sum of graphs, symbolized as , i.e., sum of two graphs , is one of the unary graphic operations . This work provides constraints for the above‐mentioned invariant for this binary graphic operation F‐sum of graphs.
Post-Laparoendoscopic Single-Site Donor Nephrectomy Ipsilateral Testicular Pain, Does Operative Technique Matter? A Single Center Experience and Review of Literature
Authors: El Hennawy Hany M. , Al Faifi Abdullah S. , Al Atta Eisa , Safar Omar , Thamer Saad , El Nazer Weam , Kamal Ahmed I. , Abdelaziz Abdelaziz A. , Kawasmeh Shaher A. , Mirza Naveed , Zaitoun Mohammad F. , Al-Alsheikh Khalid , Shalkamy Osama , Mahedy Ahmed
Published: March 2022

Aim. To assess incidence and characteristics of post-laparoendoscopic single-site donor nephrectomy (LESS DN) testicular pain. Materials and Methods. A prospective comparative study of all male donors post-left LESS DN (group A) vs. postopen nephrectomies (group B) was performed at our center. Patients’ demographics, perioperative data, and postoperative consultation reports were reviewed. Testicular pain, swelling, numbness, urinary symptoms, and sexual dysfunction were evaluated. Patients with a history of scrotal pathology or surgical procedure were excluded. Pain and tenderness were scored on a standard 10-point scale. Results. From September 2017 to December 2020, 85 and 35 male patients of groups A and B met the evaluation criteria. Ipsilateral testicular pain developed in 11 patients (15.3%) and 2 patients (9.5%) in groups A and B, respectively. In most instances, the pain was mild to moderate in severity, started after 6 ± 2.1 and 4 ± 1.1 days postoperatively in groups A and B, respectively. Six patients in group A were evaluated with transscrotal ultrasonography that showed no abnormalities. All patients in both groups responded well to medical treatment. Conclusions. Post-LESS DN ipsilateral testicular pain is usually mild and self-limited. Preoperative patient education and discussion of the possibility of development of testicular pain and its management should be an integral component of laparoscopic donor nephrectomy informed consent.
Increased Expression of SETDB1 Predicts Poor Prognosis in Multiple Myeloma
Authors: Xiang Jing , Chen Xiaotong , Chen Mengping , Hou Jian
Published: March 2022

Several genes on chromosome 1q21 region predict a high risk of multiple myeloma (MM); however, the underlying molecular pathology remains elusive. Overexpression, amplification, or activation of SET Domain Bifurcated 1 (SETDB1), which is located on 1q21, is closely associated with poor prognosis of many human solid malignancies. In our study, upregulation of SETDB1 might indicate an unfavorable prognosis of MM using bioinformatics analysis from GEO databases and MMRF‐CoMMpass. Here, increased SETDB1 expression was observed in the plasma cells from newly diagnosed multiple myeloma patients compared to those from the normal controls. Meanwhile, SETDB1 overexpression was the result of increased copy numbers of SETDB1 gene. In MM patients, the Kaplan‐Meier analysis was employed to demonstrate that increased SETDB1 expression was associated with shorter overall survival (OS) and event‐free survival (EFS). Besides, we conducted multifactorial cox regression analysis to state that SETDB1 expression was an independent biomarker for OS and EFS. MM patients with higher SETDB1 expression showed higher levels of beta‐2 microglobulin (β2M), lactate dehydrogenase (LDH), and bone marrow biopsy plasma cells (BMPC) and lower levels of haemoglobin (HGB). Functional enrichment analysis suggested that SETDB1 could promote cell cycle progression in myeloma. Finally, we observed that SETDB1 was distinctly correlated with tumor immunity in MM. SETDB1 expression in myeloma cells was positively correlated with CD56dim natural killer cells but negatively correlated with infiltrating levels of type17 T helper cells, effector memory CD8 T cells, activated dendritic cells, and natural killer T cells from whole bone marrow (WBM) biopsies. Taken together, these results indicated that SETDB1 could be used as a novel biomarker for predicting the prognosis of MM patients.
Phenonizer: A Fine‐Grained Phenotypic Named Entity Recognizer for Chinese Clinical Texts
Authors: Zou Qunsheng , Yang Kuo , Shu Zixin , Chang Kai , Zheng Qiguang , Zheng Yi , Lu Kezhi , Xu Ning , Tian Haoyu , Li Xiaomeng , Yang Yuxia , Zhou Yana , Yu Haibin , Zhang Xiaoping , Xia Jianan , Zhu Qiang , Poon Josiah , Poon Simon , Zhang Runshun , Li Xiaodong , Zhou Xuezhong
Published: March 2022

Biomedical named entity recognition (BioNER) from clinical texts is a fundamental task for clinical data analysis due to the availability of large volume of electronic medical record data, which are mostly in free text format, in real‐world clinical settings. Clinical text data incorporates significant phenotypic medical entities (e.g., symptoms, diseases, and laboratory indexes), which could be used for profiling the clinical characteristics of patients in specific disease conditions (e.g., Coronavirus Disease 2019 (COVID‐19)). However, general BioNER approaches mostly rely on coarse‐grained annotations of phenotypic entities in benchmark text dataset. Owing to the numerous negation expressions of phenotypic entities (e.g., “no fever,” “no cough,” and “no hypertension”) in clinical texts, this could not feed the subsequent data analysis process with well‐prepared structured clinical data. In this paper, we developed Human‐machine Cooperative Phenotypic Spectrum Annotation System (http://www.tcmai.org/login, HCPSAS) and constructed a fine‐grained Chinese clinical corpus. Thereafter, we proposed a phenotypic named entity recognizer: Phenonizer, which utilized BERT to capture character‐level global contextual representation, extracted local contextual features combined with bidirectional long short‐term memory, and finally obtained the optimal label sequences through conditional random field. The results on COVID‐19 dataset show that Phenonizer outperforms those methods based on Word2Vec with an F1‐score of 0.896. By comparing character embeddings from different data, it is found that character embeddings trained by clinical corpora can improve F‐score by 0.0103. In addition, we evaluated Phenonizer on two kinds of granular datasets and proved that fine‐grained dataset can boost methods’ F1‐score slightly by about 0.005. Furthermore, the fine‐grained dataset enables methods to distinguish between negated symptoms and presented symptoms. Finally, we tested the generalization performance of Phenonizer, achieving a superior F1‐score of 0.8389. In summary, together with fine‐grained annotated benchmark dataset, Phenonizer proposes a feasible approach to effectively extract symptom information from Chinese clinical texts with acceptable performance.
Column Study for Adsorption of Copper and Cadmium Using Activated Carbon Derived from Sewage Sludge
Authors: Al-mahbashi Najib , Kutty S.R.M , Jagaba A.H. , Al-Nini Ahmed , Ali Mujahid , Saeed A.A.H. , Ghaleb A.A.S , Rathnayake Upaka
Published: March 2022

Among the water‐polluting substances, heavy metals stand out due to their carcinogenic and toxic effects on the creatures and environment. This study aimed to scrutinize the effectiveness of sewage sludge‐based activated carbon in the removal of copper and cadmium from aqueous solutions in column study. Detection of breakthrough curves and related parameters was conducted by varying bed depths (3, 6, and 9 cm). The solution with an initial metal concentration (IMC) of 100 ppm was pumped to the column at a flow rate of 2 mL/min. In the process of copper removal, the breakthrough points for depths 3 cm, 6 cm, and 9 cm were achieved at 10 min, 15 min, and 60 min, respectively, whereas breakthrough points of similar depths in cadmium removal process were achieved at 5 min, 10 min, and 30 min, respectively. Adsorption kinetics were analyzed using the Adams–Bohart, Yoon–Nelson, and Thomas kinetics models. The Adams–Bohart model described only the initial part of breakthrough curves. The Thomas model represented the adsorption process with coefficients of determination (R2) ranging between 0.90–0.95 for cadmium removal and 0.89–0.96 for copper removal, while the coefficients of determination of Yoon–Nelson ranged between 0.89–0.94 for cadmium and 0.95–0.97 for copper. Yoon–Nelson was fitted well with copper removal data, while removal of cadmium data was best described by the Thomas model. This study demonstrated that using sewage sludge‐based activated carbon to remove heavy metals is an alternative, more cost‐effective option to reach the objectives of sustainable development.
Application of Multilevel Local Feature Coding in Music Genre Recognition
Authors: Xiao Yangxin , Zhang Qiang , Wu Meng , Kailing Dong
Published: March 2022

When the current method is used to recognize music genre style, the extracted features are not fused, which leads to poor recognition effectiveness. Therefore, the application research based on multilevel local feature coding in music genre recognition is proposed. Features of music are extracted from timbre, rhythm, and pitch, and the extracted features are fused based on D-S evidence theory. The fused music features are input into the improved deep learning network, and the storage system structure is determined from the advantages of cloud storage availability, manageability, and expansibility. It is divided into four modules: storage layer, management layer, structure layer, and access layer. The model of music genre style recognition is constructed to realize the application research based on multilevel local feature coding in music genre recognition. The experimental results show that the recognition accuracy of the proposed method is always at a high level, and the mean square error positively correlated with the number of beats. After segmentation, the waveform is denser, which has a good application effect.
A High-Precision and Wide Range Method for Inner Diameter Measurement
Authors: Zhang Zhenchao , Yan Yufeng , Yu Xin , Li Chenxiao , Gong Lekai
Published: March 2022

Inner diameter measurement technology with high precision and wide measuring ranges is a difficult area to master. It is challenging to achieve high precision and a wide measuring range for inner diameter measurement. The dispersive confocal technique is used to describe a high accuracy, large range approach for measuring inner diameter. The inner diameter is measured utilizing a rotating scanning approach that combines the dispersive confocal technique with least squares. Meanwhile, a plane mirror deflects the optical path of a dispersive confocal sensor, focusing monochromatic light of a certain wavelength on the object’s surface in the radial direction. The measuring range of the device may be modified to fit different objects by modifying the distance between the dispersive confocal sensor and the plane mirror, as well as the eccentricity of the dispersive confocal sensor. Furthermore, this study examines the method’s accuracy and suggests a calibration technique. As a consequence, the procedure may ensure measurement precision as well as a measurement range. Finally, experiments are utilized to test the validity of the strategy. To accomplish a 3 μm inner diameter measurement precision and a measuring range of 76 mm to 150 mm, a dispersive confocal sensor with a range of just 20 mm was utilized.
Exploration of the Immuno-Inflammatory Potential Targets of Xinfeng Capsule in Patients with Ankylosing Spondylitis Based on Data Mining, Network Pharmacology, and Molecular Docking
Authors: Fang Yanyan , Liu Jian , Xin Ling , Wen Jianting , Guo Jinchen , Huang Dan , Li Xu
Published: March 2022

Objective. This study aimed to ascertain the immuno-inflammatory molecular targets of Xinfeng capsules (XFC) in the treatment of ankylosing spondylitis (AS) based on data mining, network pharmacology, and molecular docking. Methods. The efficacy of XFC in the treatment of AS was assessed by clinical data mining. Network pharmacology was utilized to establish a network of the targets for XFC active ingredients in the treatment of AS. The binding mode and affinity of XFC active ingredients to the key targets for AS were predicted using molecular docking. Results. XFC significantly diminished immuno-inflammatory indicators of AS. In total, 208 targets of XFC were obtained from the TCMSP database and 629 disease targets of AS were screened from the GeneCards database, which were intersected to yield 57 targets of XFC in the treatment of AS. Protein-protein interaction, gene ontology, and Kyoto genome encyclopedia analyses showed that XFC might activate TNF and NF-κB signaling pathways. Quercetin, kaempferol, triptolide, and formononetin had free binding energies < -9 kcal/mol to inflammatory targets (TNF and PTGS2) in the molecular docking analysis of XFC-active ingredients, indicating that TNF and PTGS2 might be the targets of the action of XFC. Conclusions. Collectively, XFC had a significant therapeutic effect on AS. Specifically, the active ingredients of XFC, including quercetin, kaempferol, triptolide, and formononetin, inhibited the inflammatory response in AS by downregulating TNF and PTGS2 in the TNF and NF-κB signaling pathways.
Treatment of Degenerative Lumbar Spondylolisthesis by Tongdu Bushen Acupuncture, Intradermal Acupuncture, and Moxibustion Integrated Therapy Combined with Core Muscle Training Program: Study Protocol for a Randomized Controlled Clinical Trial
Authors: Song Xiaolei , Qi Shikui , Gao Jing , Ruan Xiaodi , Yin Shuai , Wu Mingli , Fu Wenbin
Published: March 2022

Background. Degenerative lumbar spondylolisthesis (DLS), one of the most common causes of low back pain, is defined as the displacement of a vertebral body over the lower vertebral body with degenerative changes and the absence of fracture or defect in the vertebral ring. This disease is a common and frequently occurring disease. Currently, there are many clinical treatment methods, but there is no specific method, and most of them have the characteristics of slow effect and easy recurrence. Objective. The objective of this study is to summarize and analyze the effects of treatment of degenerative lumbar spondylolisthesis by Tongdu Bushen acupuncture, intradermal acupuncture, and moxibustion integrated therapy combined with core muscle training program (CMT) on the improvement of pain degree and dysfunction index, as well as the gait characteristics. Methods. 120 patients with DLS will be recruited and randomly divided into two groups using electroacupuncture combined with the CMT group as the control group. Visual Analogue Scale (VAS), Oswestry Disability Index (ODI), and Japanese Orthopedic Association score (JOA) will be used for evaluation. The spatiotemporal and kinematics parameters in gait analysis, as well as the ability of lumbar muscle contraction, fatigue resistance, relaxation, and coordination of lumbar muscle in surface electromyography (sEMG), will be used as objective observation indexes to observe the effectiveness of Tongdu Bushen acupuncture, intradermal acupuncture, and moxibustion integrated therapy combined with CMT. Discussion. Tongdu Bushen acupuncture, intradermal acupuncture, and moxibustion integrated therapy is a traditional Chinese medicine treatment for DLS. Our results will provide evidence to determine whether the integrated therapy can effectively treat DLS, as well as its advantages and safety, and lay a foundation for further research. This trial is registered with ChiCTR2100050409.
An Empirical Study on the Measurement of Forestry Total Factor Productivity Based on DEA Malmquist Model
Authors: Yin Hui , Cao Yukun
Published: March 2022

Based on the forestry total factor productivity of 31 provinces in China from 1997 to 2020, this study uses the DEA Malmquist model to measure its forestry total factor productivity. The results show that the overall development trend of forestry total factor productivity in China is fluctuating and rising, and the main driving force of growth comes from technological change; from other influencing factors, the reduction in human investment, the rationalization of industrial structure and the improvement of the level of scientific, and technological and economic development can also effectively improve the total factor productivity of forestry.
Cutaneous Mucormycosis in an Immunocompetent Child following a Minor Skin Trauma
Authors: Shingde Rashmi , Cui Rebecca , Perera Ruwan
Published: March 2022

Cutaneous mucormycosis is a rare infection by the Zygomycetes class of fungi, which carries significant morbidity and mortality. While typically associated in patients with underlying immunocompromise (especially in the current era of COVID-19), it may also be seen in immunocompetent patients. We report a case of a healthy 4-year-old girl with acute right leg cellulitis and abscess formation, who required surgical debridement following poor response to antibiotic therapy and initial incision and drainage. Tissue histopathology returned cutaneous zygomycosis despite negative tissue cultures. At four-week follow-up, her wound was healed well. Clinicians should maintain a high degree of clinical suspicion for cutaneous mucormycosis given its potential for rapidly progressive and disseminated disease. Currently, the mainstay of diagnostic investigations is tissue histopathology, with a growing role for tissue fungal PCR. Treatment involves multidisciplinary management between surgeons and Infectious Diseases team to guide the role for surgical debridement and antifungal therapy.
Rating of Modern Color Image Cryptography: A Next-Generation Computing Perspective
Authors: Samiullah Muhammad , Aslam Waqar , Khan Muhammad Asghar , Alshahrani Haya Mesfer , Mahgoub Hany , Abdullah Ako Muhammad , Ullah M. Ikram , Chen Chien-Ming
Published: March 2022

Issues such as inefficient encryption architectures, nonstandard formats of image datasets, weak randomness of chaos-based Pseudorandom Number Generators (PRNGs), omitted S-boxes, and unconvincing security metrics leading to increased computational time and inadequate security level of chaos and Deoxyribonucleic Acid- (DNA-) based image encryption schemes need careful examination towards the development of more stable encryption schemes in terms of efficiency and reasonable security. A new taxonomy of image encryption based on chaotic systems, hyperchaotic systems, and DNA is propounded to assess the impact of these issues on the performance and security metrics. The primary emphasis of this research is to study various recent encryption architectures centered on a variety of confusion and diffusion methods. It is aimed at assessing the performance and security of various ciphers using a cipher rating criterion that categorizes ciphers into different classes. The parameters that are included in the rating criteria are information entropy, chi-squared goodness of fit test for histogram uniformity analysis, encryption efficiency, key space, differential attacks (Number of Pixels Change Rate and Universal Average Changing Intensity), key sensitivity analysis, encryption time, randomness tests such as NIST-R (a statistical suite for validating the randomness designed by the National Institute of Standards and Technology), correlation coefficient analysis, contrast analysis, energy analysis, homogeneity analysis, Mean Absolute Error, peak signal-to-noise ratio, and robustness to noise and occlusion attacks.
Research on Data Mining Combination Model Analysis and Performance Prediction Based on Students’ Behavior Characteristics
Authors: Chen Liyan , Wang Lihua , Zhou Yuxin
Published: March 2022

Using data mining technology to analyze students’ behavior can effectively predict students’ performance and other evaluation indicators, which is of great significance to improving the level of school information management. Aiming at the problems of imperfect information management platforms and low data analysis ability in colleges and universities, a data mining algorithm based on students’ behavior characteristics is proposed. Firstly, the characteristics of the GBDT algorithm, the ANN algorithm, and the K-means algorithm are analyzed, and the three algorithms are combined to establish a combined prediction model. At the same time, five standard data sets are combined for simulation training. Then, an analysis and prediction platform based on the characteristics of students’ behavior is built. Combined with the management systems such as “Campus All-in-one Card,” educational administration, and library, the data collection, modeling, analysis, and mining are realized, and the evaluation index system of students’ behavior is established. Finally, the data of students’ consumption laws, living habits, learning, and Internet access are used to verify the combined model. The results show that compared with a single algorithm, the combined model has fast run speed and high accuracy, and the prediction results are consistent with the actual situation. The prediction platform can analyze the characteristics and laws of student behavior data, effectively predict the learning effects, grasp the dynamics of students’ lives and learning in real time, and provide decision-making for school teaching management and teachers’ teaching reform.
A Dynamic Evaluation Model of University Brand Value Based on Analytic Hierarchy Process
Authors: Li Mingchao , Gong Bin
Published: March 2022

In recent years, great changes have taken place in the economic environment, policies, competitive environment, and market of colleges and universities. Furthermore, factors including the reduction of number of students every year has led to the continuous decline in the number of students enrolled in colleges and universities. Facing this problem, it is essential that colleges and universities should build their own brand value and attract more high school graduates with the brand value of colleges and universities. Nowadays, higher education has been popularized and internationalized, and the competition among colleges and universities has gradually increased. In fact, colleges and universities can obtain high-quality school running resources by relying on their own loyalty, reputation and social status, and can also achieve greater development space in the field of education. Therefore, university managers began to pay attention to their own brand value. The brand value of colleges and universities cannot be directly reflected, but needs to be reflected from different aspects. For this problem, this paper uses analytic hierarchy process (AHP) to study the brand value of colleges and universities. By selecting many aspects as the indicators of the dynamic evaluation system of brand value of colleges and universities, this paper constructs a dynamic evaluation model of brand value of colleges and universities based on analytic hierarchy process. After analysis, the total score of the brand value of a university is 84.12 and the grade is “B.” Based on the analysis of the results, it can be concluded that the overall score of the university is high and has a certain brand value. However, it is weak in talent training and academic reputation.
A Machine Learning Based Intelligent Decision Support System for Flotation Dynamics in Simulation of Clay Minerals
Authors: Chen Wanying , Li Zhihong , Hao Bo , Gao Jianchuan , Fan Minqiang
Published: March 2022

In coal mines, process management is related with planning and flow of coal minerals from their mining points to journey’s end. The process is dependent on the operational decisions, which should be completed during coal production. In these systems, simulation modelling is assumed a powerful tool for decision making. The simulation modelling can further be enhanced through applying artificial intelligence (AI) and machine learning (ML) methods. The communication of water with clay minerals upholds the water adsorption on the clay surface, which makes them complex systems. Therefore, evading the water absorption from the clay turns out to be a hard job. The computational trainings of clay minerals are needed to comprehend the dynamics of water distribution. Tradition of coal slurry treatment is completed by adding medicament of its mineral flocculation sedimentation. As a result of coal, slime water contains a lot of clay minerals that are rich in kaolinite versatility and it is difficult to settle. The flotation will be one of the kaolinite recycling. In this paper, clay minerals containing a variety of minerals were taken as samples, and sodium dodecyl sulfate and sodium oleate were used as collectors to explore the flotation effect through test and molecular dynamics simulation. A machine learning based intelligent decision support system is designed to improve the outputs of the simulation model. The results show that when the pH value is 8 and the amount of collector and sec-octanol are 150 g/t and 250 g/t, respectively, the flotation rate of fine mineral can reach 63.25%. According to the molecular dynamics simulation results, the addition of the collector can reduce the hydrophilicity of the kaolinite surface, and the physical adsorption of SDS only occurs on the (001) surface.