bluuebunny/crossref_metadata_2025 huggingface dataset:
Awareness Level of Business Students regarding Drinking Water Safety and Associated Adulteration Accidents: A Multinomial Logistic Regression Approach
Authors: Zahid R. M. Ammar , Khurshid Muzammil , Khan Wajid , Hong Ziyue , Kasule Hawa
Published: August 2022

The industrialization of metropolis urban areas with dry and steppe climates raise substantial environmental contamination, particularly in the water domain. This research investigated the awareness levels of business students toward drinking water quality and safety. We further explored the knowledge of the business students regarding drinking water issues and remedies. Eighty‐four percent of respondents were happy with the quality of their drinking water, according to the findings. Approximately 66% of respondents paid special or rather high attention to drinking water quality and contamination incidents, particularly regarding possible harm to the human body and health, impact scope, and accident reasons. Few respondents reported to the health department or phoned the water safety department; 47.5% of respondents resolved drinking water issues independently. Age and education level did not play a significant role in the degree of public satisfaction with water quality or the public’s perception of water pollution incidents; however, business students in Samundri were more satisfied with their drinking water quality, and residents of Faisalabad Sadar were more aware of drinking water contamination incidents than residents in areas without such a network. Respondents with higher levels of education were more aware of water quality and pollution incidents than those with lower levels of education. The steppe climate, diverse human activities, and industrialization led to water pollution. The current research findings may provide fundamental data for efficient water management in the most populated and industrialized regions.
Blockchain‐Based Encryption Method for Internal and External Health Privacy Data of University Physical Education Class
Authors: Zhou Zheng , Liu Yang
Published: August 2022

In order to improve the security of the storage and scheduling of health privacy data inside and outside the university physical education class, a storage and scheduling method based on blockchain hybrid encryption is proposed. The distribution structure model of health privacy data blockchain inside and outside the university physical education class is established, arithmetic coding and quantitative feature analysis methods to schedule and adaptively control health privacy data blockchain inside and outside the university physical education class are adopted, public key coding configuration and vector quantization coding methods are combined to design encryption keys in the process of health privacy data transmission inside and outside the university physical education class, and blockchain hybrid encryption algorithm is adopted to design encryption keys for health privacy data inside and outside the university physical education class. The arithmetic coding is embedded in the encryption system, and the bit sequence output by the blockchain hybrid encryption is circularly shifted, so as to realize the encryption of health privacy data inside and outside the university physical education class and optimize the storage scheduling. The simulation results show that this method has good security encryption performance, strong antiattack ability, and balanced storage space allocation, which improves the security storage and transmission ability of health privacy data inside and outside the university physical education class.
Comparative Analysis of the Influence of Mobile Intelligent Terminal on Human Cardiopulmonary Function in Anaerobic and Aerobic Exercise Training
Authors: Yuan Yijuan , Wang Shaosong
Published: August 2022

In order to understand the impact of mobile smart terminals on human cardiopulmonary function in anaerobic and aerobic exercise training, we study the effects of moderate-intensity aerobic exercise and anaerobic exercise on improving human physical fitness, shape, etc. Measurement and analysis of body composition and cardiorespiratory fitness in humans during moderate-intensity aerobic and anaerobic exercise studies. The characteristics of diversified, emerging, and humanized mobile intelligent terminals have attracted the attention of college students. Mobile smart terminals have brought a lot of convenience to college students’ aerobic and anaerobic fitness. The results showed that people who participated in aerobic exercise and anaerobic exercise were more fit, and their BMI, WHR, and body fat rate were significantly better than those who did not participate in aerobic exercise and anaerobic exercise; at the same time, the lung capacity of people who participated in exercise was significantly higher. Stroke volume, maximum oxygen uptake, ejection fraction, etc., were significantly improved, and myocardial contractility was significantly improved, all better than those who did not participate in the exercise. Therefore, aerobic and anaerobic exercise can help improve a person’s body composition and improve cardiopulmonary function. Therefore, how to give full play to the value of mobile smart terminals in aerobic and anaerobic fitness has become a hot research topic.
A Product Modeling Design Decision Model Based on PGA Genetic Algorithm
Authors: Zong Licheng , Wang Nana
Published: August 2022

A Pareto-based genetic algorithm (PGA) product design decision model is proposed in this work to improve the efficiency of product design decisions and avoid the instability of individual decision differences. Based on the product modeling design decision constraint space, decision variables, and other factors, the model utilizes the PGA optimization algorithm to make an objective decision on a design scheme. Using the analytic hierarchy process, the design expectations, objectives, variables, and schemes are constructed into a hierarchical structure. The design decision problems are then mapped to a mathematical model, and a simulation of the design scheme decision process is performed. Finally, the feasibility of the proposed model is analyzed and verified by evaluating the design decisions of a brand electric scooter product to guide designers in making innovative design decisions.
Exploring the Feasibility of Virtually Delivered Auricular Point Acupressure in Self-Managing Chronic Pain: Qualitative Study
Authors: Kawi Jennifer , Yeh Chao Hsing , Lukkahatai Nada , Hardwicke Robin L. , Murphy Thomas , Christo Paul J.
Published: August 2022

Background. Chronic pain remains highly prevalent. Current pharmacological and non-pharmacological strategies have not adequately managed chronic pain which has contributed to disability and high healthcare costs. With existing challenges in providing adequate pain care and access, we tested vAPA, a virtually delivered, self-management intervention using Auricular Point Acupressure (APA) by mobile app and virtual consultations (telehealth). Our key purpose was to evaluate the feasibility of the vAPA in self-managing chronic pain in preparation for a future randomized controlled trial. Methods. We conducted a descriptive, qualitative study evaluating our 4-week vAPA intervention among 18 participants. We used directed qualitative content analysis. Results and Conclusion. Participants perceived that vAPA was feasible (acceptable, useable, practical, and beneficial). In addition, the following themes were gathered: better control of pain, less use of pain medications, self-management and motivation in pain, and expectations for pain relief. Refinements were recommended for the app, content, and delivery to improve study interventions. Findings are relevant in moving forward to a future randomized controlled trial and for wider implementation in a pragmatic clinical trial.
How Internet Use Spurs Entrepreneurial Activities? Evidence from China
Authors: Wang Jiaqing , Zhou Deshui
Published: August 2022

Digital literacy has been increasingly important among workers in the labour market, and it also has been viewed as a micro reflection of the growing of China’s digital economy. Internet use is an integral part of workers’ digital literacy, which has a significant influence on entrepreneurial decision-making. This paper aims to explore the direct impact of Internet use on entrepreneurship, analyzing the mechanism and group differences of Internet use. It has a practical meaning to China’s policies of promoting employment. Based on the data of China Labour Dynamics Survey (CLDS), the paper uses Probit model and 2SLS regression analysis to examine the direct impact of Internet use on entrepreneurship, and to analyze its mechanism by adopting the mediation effect model. The study indicates that Internet use has significantly increased the probability of starting a business, the impact has been stronger on the new generation, rural residents and the groups with work experience. Further analysis shows that Internet use not only increases venture capital, social capital and income, but also helps to shape individual workers’ learning ability, which has an indirect effect on promoting entrepreneurship. The above results show the way of promoting workers’ willingness of entrepreneurship, which are expanding Internet access, promoting policies of improving workers’ Internet skills, focusing on cultivating comprehensive cognitive abilities including risk awareness and learning abilities.
The Use of Thinking Visualization Techniques in College Teaching Based on Improved Genetic Algorithms
Authors: Su Luyan
Published: August 2022

Current educational resources do not maximize energy efficiency, and scientific and proven teaching methods are necessary for today’s university education to help achieve the integration of teaching resources and improve teaching quality. This study discusses the application of artificial intelligence and thinking visualization technology in college education and teaching, firstly introduces the advantageous role of genetic algorithm in artificial intelligence and the energy efficiency of thinking visualization technology, then conducts a research analysis, introduces genetic algorithm as technical support in teaching and learning, uses thinking visualization technology as a tool, aims to study the application of thinking visualization technology in college teaching, and expects to use genetic algorithm and thinking visualization techniques to improve teaching effectiveness. The experimental results show that genetic algorithm and thinking visualization technology can effectively optimize the co-giving of educational services, reduce the workload of teachers, while reducing the cost of learning, enhance the learning effect and experience, and improve students' efficient thinking.
Construction and Performance Research of Reinforced Iron-Based Powder Metallurgy Materials Based on Phyllanthin as Drug Transport Carriers
Authors: Feng Xuehua , Tao Ali , Song Zurong
Published: August 2022

Iron-based powder metallurgy materials are the largest type of powder metallurgy materials, mainly used in structural parts, bearings, and friction materials. Iron-based powder metallurgy materials have a series of advantages such as low cost, good machinability, good weldability, and heat treatment. In recent years, the enhanced iron-based powder metallurgy materials based on lavender elements have become a hot spot in the development of material transportation carriers. In order to study the effects of different hot pressing and sintering temperatures on the density, microstructure, and hardness of the enhanced iron-based powders of caladium, we conducted related studies on the structure core properties of the enhanced iron-based powders of caladium to explore whether it can be used as a drug transport carrier. The research results show that hot pressing sintering can make the powder achieve high densification at lower temperature and shorter cycle, especially in the preparation of difficult-to-form and sintered powder metallurgy materials with unique advantages.
The Impact of Optical Coherence Tomography in the Early Identification of Children with Sickle Cell Retinopathy
Authors: Abdelkader Ashraf , Shaaban Mohamed , Zahran Mahmoud M. , Mohammed Mostafa F. , Ebrahim Anas M. , Galhoom Ahmed I.
Published: August 2022

Introduction. Sickle cell disease is characterized by the production of abnormal hemoglobin, which affects hemoglobin molecule stability during hypoxia and leads to the formation of sickle cells, resulting in increased hematic viscosity, hemolysis, and microvascular blockage. Vasoocclusion is assumed to be the primary cause of vision-threatening retinopathy in sickle cell disease. The aim of this study was to improve the early detection of sickle cell retinopathy (SCR) in children with sickle cell disease (SCD) and investigate the link between systemic and ocular symptoms. Methods. This cross-sectional study comprised children with SCD. The patient files provided a detailed medical history. The laboratory tests included a blood count, reticulocyte count, and Hb electrophoresis. The slit lamp, fundus, optical coherence tomography (OCT), and optical coherence tomography angiography (OCTA) were all part of the ophthalmological examination. Results. The study comprised 15 children with sickle cell disease who met the inclusion and exclusion criteria, with a mean age of 11.15 ± 1.29 years. Nine of the children were males (60%) and six were females (40%). 8 (53.3%) of the children had Hb SS, three (20%) had Hb SC, three (20%) had Hb SB+, and one (6.7%) had Hb SB0. Four children (26.7%) had poor visual acuity. A fundus examination revealed significant abnormal findings in 12 of the 7 children’s eyes (40 percent). Macular thinning was detected by OCT in 10 eyes of 7 children (33.3%). Flow voids at the deep retinal capillary plexus were detected by OCTA in 10 eyes of 7 children (33.3%). Longer disease duration, higher reticulocytic percent, more painful crises, and noncompliance with hydroxyurea medication were all linked to the existence of eye abnormalities on fundus examination and OCT. Conclusion. OCTA can show early retinal damage in sickle cell patients with macular changes. Sickle cell retinopathy is usually associated with more severe disease.
Application of Convolutional Neural Network in Motor Bearing Fault Diagnosis
Authors: Zhou Shuiqin , Lin Lepeng , Chen Chu , Pan Wenbin , Lou Xiaochun
Published: August 2022

In the field of mechanical and electrical equipment, the motor rolling bearing is a workpiece that is extremely prone to damage and failure. However, the traditional fault diagnosis methods cannot keep up with the development pace of the times because they need complex manual pretreatment or the support of specific expert experience and knowledge. As a rising star, the data-driven fault diagnosis methods are increasingly favored by scholars and experts at home and abroad. The convolutional neural network has been widely used because of its powerful feature extraction ability for all kinds of complex information and its outstanding research results in image processing, target tracking, target diagnosis, time-frequency analysis, and other scenes. Therefore, this paper introduces a convolutional neural network and applies it to motor-bearing fault diagnosis. Aiming at the shortcomings of fault signal and convolutional neural network, a large-scale maximum pooling strategy is proposed and optimized by wavelet transform to improve the fault diagnosis efficiency of motor bearing under high-voltage operation. Compared with other machine learning algorithms, the convolution neural network fault diagnosis model constructed in this paper not only has high accuracy (up to 0.9871) and low error (only 0.032) but also is simple to use. It provides a new way for motor bearing fault diagnosis and has very important economic and social value.
Structural and Functional Characterization at the Molecular Level of the MATE Gene Family in Wheat in Silico
Authors: Debnath Sandip , Mohanta Deepika , Perveen Kahkashan , Husain Fohad Mabood , Kesari Kavindra Kumar , Ashraf Mohd. Shaikhul , Mukerjee Nobendu , Rahin Saima Ahmed
Published: August 2022

A series of multidrug extransporters known as the multidrug and potentially toxic extrusion (MATE) genes are found in all living things and are crucial for the removal of heavy metal ions, metalloids, exogenous xenobiotics, endogenous secondary metabolites, and other toxic substances from the cells. However, there has only been a small amount of them in silico analysis of the MATE family of genes in plant species. In the current study, the MATE gene family was characterized in silico where two families and seven subfamilies based on their evolutionary relationships were proposed. Plant breeders may use TraesCS1D02G030400, TraesCS4B02G244400, and TraesCS1A02G029900 genes for marker‐assisted or transgenic breeding to develop novel cultivars since these genes have been hypothesized from protein‐protein interaction study to play a critical role in the transport of toxic chemicals across cells. The exon number varies from 01 to 14. One exon has TraesCS1A02G188100, TraesCS5B02G562500, TraesCS6A02G256400, and TraesCS6D02G384300 genes, while 14 exons have only two genes that are TraesCS6A02G418800 and TraesCS6D02G407900. Biological stress (infestations of disease) affects the expression of most of the MATE genes, with the gene TraesCS5D02G355500 having the highest expression level in the wheat expression browser tool. Using the Grain interpretation search engine tool, it is found that the vast bulk of MATE genes are voiced throughout biotic environmental stresses caused by disease pests, with the genotype TraesCS5B02G326600.1 from family 1 exhibiting the greatest level of expression throughout Fusarium head blight infection by Fusarium graminearum after 4 days of infection. The researchers constructed 39 ternary plots, each with a distinct degree of expression under biotic and abiotic stress settings, and observed that 44% of the triplets have imbalanced outputs (extreme values) due to their higher tissue specificity and increased intensity.
Activating Mutation in the Receptor Tyrosine Kinase FLT3 with Clinicopathological Relevance in Canine Mast Cell Tumors
Authors: Manachai Nawin , Rattanapinyopituk Kasem , Fonghem Piyanoot , Phoomvuthisarn Panrawee , Nakahata Shingo , Morishita Kazuhiro , Rungsipipat Anudep
Published: August 2022

Recent research has focused on the receptor tyrosine kinase (RTK) KIT which is involved in the pathogenesis of canine mast cell tumors (MCT). However, the role of other RTKs in this neoplasm remains unclear. The present study aimed to determine the frequency of FLT3 mutations and to evaluate the mutational status and clinicopathological relevance of canine MCT patients. There were a total of 20 cases that were cytologically and histopathological diagnosed as canine MCTs; genomic polymerase chain reaction (PCR) and Sanger sequencing were used to identify mutations. For the juxtamembrane (JM) domain, the FLT3 14/15 primer pair was used to investigate exon 14/15 loci. Based on genomic PCR amplification of exon 14/15 and 20 of the FLT3 gene and Sanger sequencing of 20 cases of canine MCTs, the overall frequency of FLT3 mutation in canine MCTs was 75%. The majority of FLT3 mutations (70%) were internal tandem duplications (ITD) of the JM domain, while one case arose from deletion mutations of the tyrosine kinase domain (TKD). However, double mutations were not observed in this study. Furthermore, there is also clinicopathological relevance to MCT dogs carrying FLT3-ITD mutations, showing a tendency toward leukocytosis due to neutrophilia, and resembling human acute myeloid leukemia (AML) with FLT3-ITD mutations. A subset of MCTs with FLT3-ITD mutations, showing an enhanced signal of phosphorylated ERK1/2 identified by immunoblotting, suggests that an activating mutation may be driven by a distinct signal of the ERK pathway. Our results indicate that FLT3-ITD mutation is an oncogenic driver of canine MCTs, and that it shares some clinicopathologic features with human AML. These findings may offer new opportunities for further studies on canine mast cell tumorigenesis and a novel therapeutic target for canine MCT cases harboring FLT3-ITD mutations.
Facial Expression Recognition Based on LDA Feature Space Optimization
Authors: Zheng Fanchen
Published: August 2022

With the development of artificial intelligence, facial expression recognition has become an important part of the current research due to its wide application potential. However, the qualities of the face features will directly affect the accuracy of the model. Based on the KDEF face public dataset, the author conducts a comprehensive analysis of the effect of linear discriminant analysis (LDA) dimensionality reduction on facial expression recognition. First, the features of face images are extracted respectively by manual method and deep learning method, which constitute 35-dimensional artificial features, 128-dimensional deep features, and the hybrid features. Second, LDA is used to reduce the dimensionality of the three feature sets. Then, machine learning models, such as Naive Bayes and decision tree, are used to analyze the results of facial expression recognition before and after LDA feature dimensionality reduction. Finally, the effects of several classical feature reduction methods on the effectiveness of facial expression recognition are evaluated. The results show that after the LDA feature dimensionality reduction being used, the facial expression recognition based on these three feature sets is improved to a certain extent, which indicates the good effect of LDA in reducing feature redundancy.
Effect of Ultrasonic Osteotome on Therapeutic Efficacy and Safety of Spinal Surgery: A System Review and Meta-Analysis
Authors: Wu Leilei , Wang Sheng
Published: August 2022

Background. A meta-analysis was performed to evaluate the effectiveness and safety of ultrasonic osteotomes in spine surgery to standard spinal surgery procedures. Methods. Using the search keywords “bone curette”, “cutter”, “scalpel”, “bone shaver”, “aspirator”, “osteotome”, “ultrasonic”, “piezosurgery”, and “

dent
 
 

∗

” in the databases of PubMed (1966-2021.12), Cochrane Library, Embase (1986-2018.12), Web of Science (1978-2021.12), and China Academic Journals Full-Text Database (CNKI, 1979-2021.12). Two researchers reviewed the literature, extracted and extensively assessed the data, and included information on the study quality. RevMan v5.3.5.0 was used for the meta-analysis. Results. A total of 10 trials with a total of 911 patients were included. The meta-analysis findings revealed that, when compared to traditional methods, ultrasonic osteotomes could save operation time (

OR
=
−
18.83

, 95 percent CI (-22.76, -14.99),

P
=
0.03

) and reduce intraoperative bleeding (

OR
=
−
66.73

, 95 percent CI (-75.70, -57.76),

P
=
0.04

) and postoperative complications (

OR
=
0.38

, 95 percent CI (0.21, 0.69),

P
=
0.001

). There was, however, no significant difference in the hospital stay (

OR
=
−
1.34

, 95 percent CI (-1.90, -0.77),

P
=
0.23

) and symptom improvement rate (

OR
=
1.03

, 95 percent CI (0.73, 1.45),

P
=
0.86

). Conclusion. There is evidence that using an ultrasonic osteotome in spine surgery is safe and effective and may minimize intraoperative bleeding and save time. However, there is no significant difference in symptom improvement rate, hospital stay length, or postoperative complications compared to standard surgical equipment. Therefore, more high-quality investigations are needed to corroborate the initial results.
The Effect of Saffron (Crocus sativus L.) Supplementation on Renal Function: A Systematic Review and Meta-Analysis of Randomized Controlled Clinical Trials
Authors: Karimi Elham , Shahdadian Farnaz , Hadi Amir , Tarrahi Mohammad-Aref , Tarrahi Mohammad Javad
Published: August 2022

Background. The present systematic review and meta‐analysis of randomized controlled trials (RCTs) aimed at determining the effect of saffron supplementation on renal function. Methods. Electronic databases were searched up to February 2021. The risk of bias in individual studies was assessed using the Cochrane Collaboration tool. The overall weighted mean difference (WMD) and their 95% confidence intervals (CIs) were calculated using random-effect models.P<0.05was considered statistically significant. Results. A total of 11 trials were included in this study. Saffron had beneficial effect on BUN (WMD = −0.69 mg/dl; 95% CI, −1.36 to −0.01;P=0.046) compared to placebo, with significant heterogeneity (I2 = 49.6%,P=0.037). However, it had no significant effect on serum Cr (WMD = 0.04 mg/dl; 95% CI: −0.01 to 0.09;P=0.127). Conclusion. It seems that saffron supplementation had no significant effect on Cr as a renal function factor. However, BUN reduction was significant in the saffron group compared to placebo.
Study on the Distance Learners’ Academic Emotions Using Online Learning Behavior Data
Authors: Sun Yang , Wang Shaoze
Published: August 2022

In recent years, computer vision, artificial intelligence, machine learning, and other high-tech technologies have advanced rapidly. These strategies lay a new technical foundation for online learning and intelligent education by making it easier to promote the scientific, intelligent, and data-driven growth of learners’ academic emotions. However, at present, online learning can better make up for the shortcomings of traditional learning and enable people to realize distance learning. However, as an important indicator, learners’ learning emotion has a direct impact on learners’ learning quality and effect. Therefore, this paper analyzes distance learners’ academic emotions based on online learning behavior data. It extracts online learning behavior data by using a deep learning algorithm and multimodal weighted feature fusion based on DS (Dempster-Shafer) evidence theory, establishing distance learners’ academic cognition motivation model, and constructs an online learning emotion measurement framework. Finally, it is determined through a correlation study of distance learners’ academic emotions and learning impacts those learners’ academic emotions in class. It will have a beneficial influence on learning since learners’ academic emotion is favorably connected with instructors’ emotion, and learners’ addition, deletion, and modification behavior is positively correlated with learners’ academic emotion.
Multifunctional mRNA-Based CAR T Cells Display Promising Antitumor Activity Against Glioblastoma
Authors: Meister Hanna , Look Thomas , Roth Patrick , Pascolo Steve , Sahin Ugur , Lee Sohyon , Hale Benjamin D. , Snijder Berend , Regli Luca , Ravi Vidhya M. , Heiland Dieter Henrik , Sentman Charles L. , Weller Michael , Weiss Tobias
Published: August 2022

Purpose:

Most chimeric antigen receptor (CAR) T-cell strategies against glioblastoma have demonstrated only modest therapeutic activity and are based on persistent gene modification strategies that have limited transgene capacity, long manufacturing processes, and the risk for uncontrollable off-tumor toxicities. mRNA-based T-cell modifications are an emerging safe, rapid, and cost-effective alternative to overcome these challenges, but are underexplored against glioblastoma.

Experimental Design:

We generated mouse and human mRNA-based multifunctional T cells coexpressing a multitargeting CAR based on the natural killer group 2D (NKG2D) receptor and the proinflammatory cytokines IL12 and IFNα2 and assessed their antiglioma activity in vitro and in vivo.

Results:

Compared with T cells that either expressed the CAR or cytokines alone, multifunctional CAR T cells demonstrated increased antiglioma activity in vitro and in vivo in three orthotopic immunocompetent mouse glioma models without signs of toxicity. Mechanistically, the coexpression of IL12 and IFNα2 in addition to the CAR promoted a proinflammatory tumor microenvironment and reduced T-cell exhaustion as demonstrated by ex vivo immune phenotyping, cytokine profiling, and RNA sequencing. The translational potential was demonstrated by image-based single-cell analyses of mRNA-modified T cells in patient glioblastoma samples with a complex cellular microenvironment. This revealed strong antiglioma activity of human mRNA-based multifunctional NKG2D CAR T cells coexpressing IL12 and IFNα2 whereas T cells that expressed either the CAR or cytokines alone did not demonstrate comparable antiglioma activity.

Conclusions:

These data provide a robust rationale for future clinical studies with mRNA-based multifunctional CAR T cells to treat malignant brain tumors.
A Phase II Randomized Trial of Chemoradiation with or without Metformin in Locally Advanced Cervical Cancer
Authors: Han Kathy , Fyles Anthony , Shek Tina , Croke Jennifer , Dhani Neesha , D'Souza David , Lee Ting-Yim , Chaudary Naz , Bruce Jeffrey , Pintilie Melania , Cairns Rob , Vines Douglass , Pakbaz Sara , Jaffray David , Metser Ur , Rouzbahman Marjan , Milosevic Michael , Koritzinsky Marianne
Published: August 2022

Purpose:

Tumor hypoxia is associated with poor response to radiation (RT). We previously discovered a novel mechanism of metformin: enhancing tumor RT response by decreasing tumor hypoxia. We hypothesized that metformin would decrease tumor hypoxia and improve cervical cancer response to RT.

Patients and Methods:

A window-of-opportunity, phase II randomized trial was performed in stage IB–IVA cervical cancer. Patients underwent screening positron emission tomography (PET) imaging with hypoxia tracer fluoroazomycin arabinoside (FAZA). Only patients with FAZA uptake (hypoxic tumor) were included and randomized 2:1 to receive metformin in combination with chemoRT or chemoRT alone. A second FAZA-PET/CT scan was performed after 1 week of metformin or no intervention (control). The primary endpoint was a change in fractional hypoxic volume (FHV) between FAZA-PET scans, compared using the Wilcoxon signed-rank test. The study was closed early due to FAZA availability and the COVID-19 pandemic.

Results:

Of the 20 consented patients, 6 were excluded due to no FAZA uptake and 1 withdrew. FHV of 10 patients in the metformin arm decreased by an average of 10.2% (44.4%–34.2%) ± SD 16.9% after 1 week of metformin, compared with an average increase of 4.7% (29.1%–33.8%) ± 11.5% for the 3 controls (P = 0.027). Those with FHV reduction after metformin had significantly lower MATE2 expression. With a median follow-up of 2.8 years, the 2-year disease-free survival was 67% for the metformin arm versus 33% for controls (P = 0.09).

Conclusions:

Metformin decreased cervical tumor hypoxia in this trial that selected for patients with hypoxic tumor.

See related commentary by Lyng et al., p. 5233
Systemic Checkpoint Blockade by PD-L1 Single-Chain Antibody Confers Potent Antitumor Immunity and Long-term Survival
Authors: Wang Hong , Khattar Vinayak , Hensel Jonathan A. , Ashton Reading , Lu Yun , Sorace Anna G. , Wang Yong , Deshane Jessy S. , Mieher Joshua L. , Deivanayagam Champion , Ponnazhagan Selvarangan
Published: August 2022

Immune checkpoint inhibitors (ICI) are promising in adjuvant settings for solid tumors and hematologic malignancies. They are currently used in the treatment as mAbs in high concentrations, raising concerns of toxicity and adverse side effects. Among various checkpoint molecules, targeting the programmed cell death protein-1 (PD-1)–programmed death-ligand 1 (PD-L1) axis has garnered more clinical utility than others have. To develop a physiologically relevant and systemically stable level of ICIs from a one-time application by genetic antibody engineering, we endeavored using a nonpathogenic, replication-deficient recombinant adeno-associated vector (rAAV) expressing single-chain variable fragments (scFv) of PD-L1 antibody and tested in syngeneic mouse therapy models of MC38 colorectal and EMT6 breast tumors. Results of this study indicated a significant protection against PD-L1–mediated inhibition of CD8+ T-cell function, against the growth of primary and secondary tumors, and durable antitumor CTLs activity by adoptive CD8+ T-cell transfer. Stable maintenance of PD-L1 scFv in vivo resulted in an increase in PD-1− CD8+ T cells and a concomitant decrease in regulatory T cells, M2 macrophages, and myeloid-derived suppressor cells in the tumor microenvironment. Overall, these data demonstrate the potential of rAAV-PD-L1-scFv as an alternative to mAb targeting of PD-L1 for tumor therapy.
Expression of Osteopontin and Integrin αvβ3 Receptor in Retina of Diabetic Guinea Pigs with High Myopia
Authors: Dong Jinghong , Hu Lingfei , Li Chenhao , Zhang Rongrong , Zheng Minmin , Wu Xueji , Wu Changfan
Published: August 2022

Introduction: The study aimed to investigate the effect of high myopia on the expression of retinal osteopontin (OPN) and integrin αvβ3 receptor in guinea pigs and determine the relationship between high myopia and diabetic retinopathy (DR). Methods: Ninety-three-week-old male guinea pigs were randomly divided into four groups that included normal control group (NOR, n = 18), high myopia group (HM, n = 24), diabetes group (DR, n = 24), and diabetes with high myopia group (DR+HM, n = 24). HM was induced by form deprivation (FDHM) in the right eye. The DR group was injected with 5% streptozotocin 280 mg/kg intraperitoneally in the lower left abdomen of guinea pigs. The DRHM group was subjected to the same treatment as the HM and DR groups. Eighteen guinea pigs in each group were randomly selected to complete the experimental measurement. After enucleation of eyeballs, HE and immunohistochemical staining were performed to observe the retina morphology and count the positive rate of OPN and integrin αvβ3 receptor. Results: Diabetic retinal changes were found in group DR and HM+DR. The degree of retinal change in group HM+DR was less than that in group DR. In the DR group, the morphology of retinal tissue was loose, the number of cells decreased, retinal microaneurysms were increased, and a small amount of small artery embolism and venous thrombosis were observed. Although the retinal structure in the HM+DR group also became thinner, looser, and disordered, only a small number of microaneurysms were observed compared with the diabetic group. Immunohistochemical staining showed that the expression of OPN and integrin αvβ3 receptors in the diabetic groups (DR, HM+DR) was significantly higher than in the HM and NOR groups. The positive expression rates of OPN and integrin αvβ3 receptors in group HM+DR were significantly lower than those in group DR (p < 0.05). Conclusion: The expression of OPN and integrin αvβ3 receptor in the retina of diabetic guinea pigs with high myopia was lower than that of diabetic models, which may be due to the influence of high myopia on neovascularization in DR.
Remoto ou remotos: a saúde e o uso do território nos municípios rurais brasileiros
Authors: Bousquat Aylene , Fausto Márcia Cristina Rodrigues , Almeida Patty Fidelis de , Lima Juliana Gagno , Seidl Helena , Sousa Amandia Braga Lima , Giovanella Ligia
Published: August 2022

OBJETIVO Caracterizar os municípios rurais remotos brasileiros segundo suas lógicas de inserção na dinâmica socioespacial, discutindo as implicações dessas características para as políticas de saúde. MÉTODOS Partindo da categoria de análise – o uso do território – elaborou-se uma tipologia, com delimitação de seis clusters . Os clusters foram comparados a partir de dados socioeconômicos e da distância em minutos para a metrópole, capital regional e centro sub-regional. Foram calculados a média, o erro padrão e o desvio padrão das variáveis quantitativas e realizados testes de diferenças de média. RESULTADOS Os seis clusters identificados aglutinam 97,2% dos municípios rurais remotos e foram denominados de: Matopiba; Norte de Minas; vetor Centro-Oeste; Semiárido; Norte Águas; e Norte Estradas. Observam-se diferenças entre os clusters nas variáveis analisadas, indicando a existência de distintas realidades. Os municípios rurais remotos dos clusters Norte Água e Norte Estrada são os mais populosos, mais extensos e distam milhares de quilômetros de centros urbanos, enquanto os do Norte de Minas e do Semiárido tem áreas menores com distância de cerca de 200 km. Por outro lado, os municípios rurais remotos do vetor Centro-Oeste se diferem por uma economia dinâmica, inserida no circuito econômico mundial devido à presença do agronegócio. A Estratégia de Saúde da Família é o modelo predominante na organização da atenção primária à saúde. CONCLUSÃO Os municípios rurais remotos distinguem-se em suas características socioespaciais e de inserção na lógica econômica, demandando políticas de saúde customizadas. A estratégia de construção das regiões de saúde, com oferta de serviços regionais especializados, tende a ser mais efetiva nos municípios rurais remotos mais próximos de centros urbanos, desde que articulada à política de transporte sanitário. O uso de tecnologia de informação e ampliação do escopo das atividades de telessaúde é mandatório para enfrentamento das distâncias em cenários como esse. A atenção primária à saúde integral com forte componente cultural é peça-chave para garantir o direito à saúde para os cidadãos que aí residem.
ECG T‐Wave Morphologic Variations Predict Ventricular Arrhythmic Risk in Low‐ and Moderate‐Risk Populations
Authors: Ramírez Julia , Kiviniemi Antti , van Duijvenboden Stefan , Tinker Andrew , Lambiase Pier D. , Junttila Juhani , Perkiömäki Juha S. , Huikuri Heikki V. , Orini Michele , Munroe Patricia B.
Published: August 2022

Background

Early identification of individuals at risk of sudden cardiac death (SCD) remains a major challenge. The ECG is a simple, common test, with potential for large‐scale application. We developed and tested the predictive value of a novel index quantifying T‐wave morphologic variations with respect to a normal reference (TMV), which only requires one beat and a single‐lead ECG.

Methods and Results

We obtained reference T‐wave morphologies from 23 962 participants in the UK Biobank study. With Cox models, we determined the association between TMV and life‐threatening ventricular arrhythmia in an independent data set from UK Biobank study without a history of cardiovascular events (N=51 794; median follow‐up of 122 months) and SCD in patients with coronary artery disease from ARTEMIS (N=1872; median follow‐up of 60 months). In UK Biobank study, 220 (0.4%) individuals developed life‐threatening ventricular arrhythmias. TMV was significantly associated with life‐threatening ventricular arrhythmias (hazard ratio [HR] of 1.13 per SD increase [95% CI, 1.03–1.24];
P
=0.009). In ARTEMIS, 34 (1.8%) individuals reached the primary end point. Patients with TMV ≥5 had an HR for SCD of 2.86 (95% CI, 1.40–5.84;
P
=0.004) with respect to those with TMV <5, independently from QRS duration, corrected QT interval, and left ventricular ejection fraction. TMV was not significantly associated with death from a cause other than SCD.

Conclusions

TMV identifies individuals at life‐threatening ventricular arrhythmia and SCD risk using a single‐beat single‐lead ECG, enabling inexpensive, quick, and safe risk assessment in large populations.
What is Dendrobium concolor hort.? A reply to Idrees and Shaw, Phytotaxa 522 (2): 161–163 (2021)
Authors: SCHUITEMAN ANDRÉ
Published: August 2022

N/A
Rediscovery of presumed extinct Hypoestes lanata (Acanthaceae), a little known endemic species from the Western Ghats of Maharashtra, India
Authors: RASKAR SHIVAJI V. , PATALE MADHUKAR W. , SALUNKHE CHANDRAKANT B. , BRAMHADANDE SNEHA P. , NANDIKAR MAYUR D.
Published: August 2022

Hypoestes lanata Dalzell (Acanthaceae), a narrow endemic species is rediscovered after a lapse of 80 years from the type locality, i.e. north Konkan, Maharashtra, India. A distribution note on the genus Hypoestes, detailed description of the species, illustration, distribution map, threat status and photographs are provided to facilitate identification. As multiple specimens are associated with H. lanata, a note on the original material is provided and lectotype designated.
Probing the Explainability of Neural Network Cloud-Top Pressure Models for LEO and GEO Imagers
Authors: White Charles H. , Heidinger Andrew K. , Ackerman Steven A.
Published: August 2022

Satellite low-Earth-orbiting (LEO) and geostationary (GEO) imager estimates of cloud-top pressure (CTP) have many applications in both operations and in studying long-term variations in cloud properties. Recently, machine learning (ML) approaches have shown improvement upon physically based algorithms. However, ML approaches, and especially neural networks, can suffer from a lack of interpretability, making it difficult to understand what information is most useful for accurate predictions of cloud properties. We trained several neural networks to estimate CTP from the infrared channels of the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Advanced Baseline Imager (ABI). The main focus of this work is assessing the relative importance of each instrument’s infrared channels in neural networks trained to estimate CTP. We use several ML explainability methods to offer different perspectives on feature importance. These methods show many differences in the relative feature importance depending on the exact method used, but most agree on a few points. Overall, the 8.4- and 8.6-μm channels appear to be the most useful for CTP estimation on ABI and VIIRS, respectively, with other native infrared window channels and the 13.3-μm channel playing a moderate role. Furthermore, we find that the neural networks learn relationships that may account for properties of clouds such as opacity and cloud-top phase that otherwise complicate the estimation of CTP.

Significance Statement

Model interpretability is an important consideration for transitioning machine learning models to operations. This work applies several explainability methods in an attempt to understand what information is most important for estimating the pressure level at the top of a cloud from satellite imagers in a neural network model. We observe much disagreement between approaches, which motivates further work in this area but find agreement on the importance of channels in the infrared window region around 8.6 and 10–12 μm, informing future cloud property algorithm development. We also find some evidence suggesting that these neural networks are able to learn physically relevant variability in radiation measurements related to key cloud properties.
Machine Learning Crop Yield Models Based on Meteorological Features and Comparison with a Process-Based Model
Authors: Liu Qinqing , Yang Meijian , Mohammadi Koushan , Song Dongjin , Bi Jinbo , Wang Guiling
Published: August 2022

A major challenge for food security worldwide is the large interannual variability of crop yield, and climate change is expected to further exacerbate this volatility. Accurate prediction of the crop response to climate variability and change is critical for short-term management and long-term planning in multiple sectors. In this study, using maize in the U.S. Corn Belt as an example, we train and validate multiple machine learning (ML) models predicting crop yield based on meteorological variables and soil properties using the leaving-one-year-out approach, and compare their performance with that of a widely used process-based crop model (PBM). Our proposed long short-term memory model with attention (LSTMatt) outperforms other ML models (including other variations of LSTM developed in this study) and explains 73% of the spatiotemporal variance of the observed maize yield, in contrast to 16% explained by the regionally calibrated PBM; the magnitude of yield prediction errors in LSTMatt is about one-third of that in the PBM. When applied to the extreme drought year 2012 that has no counterpart in the training data, the LSTMatt performance drops but still shows advantage over the PBM. Findings from this study suggest a great potential for out-of-sample application of the LSTMatt model to predict crop yield under a changing climate.

Significance Statement

Changing climate is expected to exacerbate extreme weather events, thus affecting global food security. Accurate estimation and prediction of crop productivity under extremes are crucial for long-term agricultural decision-making and climate adaptation planning. Here we seek to improve crop yield prediction from meteorological features and soil properties using machine learning approaches. Our long short-term memory (LSTM) model with attention and shortcut connection explains 73% of the spatiotemporal variance of the observed maize yield in the U.S. Corn Belt and outperforms a widely used process-based crop model even in an extreme drought year when meteorological conditions are significantly different from the training data. Our findings suggest great potential for out-of-sample application of the LSTM model to predict crop yield under a changing climate.
The Pairwise Similarity Partitioning Algorithm: A Method for Unsupervised Partitioning of Geoscientific and Other Datasets Using Arbitrary Similarity Metrics
Authors: Petty Grant W.
Published: August 2022

A simple yet flexible and robust algorithm is described for fully partitioning an arbitrary dataset into compact, nonoverlapping groups or classes, sorted by size, based entirely on a pairwise similarity matrix and a user-specified similarity threshold. Unlike many clustering algorithms, there is no assumption that natural clusters exist in the dataset, although clusters, when present, may be preferentially assigned to one or more classes. The method also does not require data objects to be compared within any coordinate system but rather permits the user to define pairwise similarity using almost any conceivable criterion. The method therefore lends itself to certain geoscientific applications for which conventional clustering methods are unsuited, including two nontrivial and distinctly different datasets presented as examples. In addition to identifying large classes containing numerous similar dataset members, it is also well suited for isolating rare or anomalous members of a dataset. The method is inductive in that prototypes identified in representative subset of a larger dataset can be used to classify the remainder.