bluuebunny/crossref_metadata_2025 huggingface dataset:
Characteristics and Risk Factors of Children Requiring Prolonged Mechanical Ventilation vs. Non-prolonged Mechanical Ventilation in the PICU: A Prospective Single-Center Study
Authors: Liu Yanling , Wang Qingyue , Hu Jun , Zhou Fang , Liu Chengjun , Li Jing , Fu Yueqiang , Dang Hongxing
Published: February 2022

Background

Prolonged mechanical ventilation (PMV) has become an enormous challenge in intensive care units (ICUs) around the world. Patients treated with PMV are generally in poor health. These patients represent a select cohort with significant morbidity, mortality, and resource utilization. The status of children who have undergone PMV in China is unknown. Our goal is to investigate the prevalence and characteristics of pediatric patients with PMV, as well as the risk factors of PMV in the pediatric intensive care unit (PICU).

Methods

The subjects were divided into two groups. The PMV group(MV ≥ 14 days) and the non-PMV group(2 days < MV <14 days). The baseline characteristics, treatments, mortality and other results between the two groups were compared. The risk factors associated with PMV were evaluated using univariate and multivariable analyses.

Results

Of the 382 children enrolled, 127 (33.2%) received prolonged mechanical ventilation. The most common cause of MV in the PMV group was acute lung disease (48.0%), followed by acute circulatory system disease (26.0%), acute neurological disease (15.0%), postoperative monitoring (10.2%), and others (0.8%). Comorbidities were more prevalent among the PMV group (P = 0.004). The patients with PMV had a higher rate of premature birth (24.4 vs. 14.1%, P = 0.013) and higher PIM3 score at admission [5.6(3.0–9.9) vs. 4.1(1.7–5.5), P < 0.001]. The use of inotropes/vasopressors (63.8 vs. 43.1%, P < 0.001) was more common in patients with PMV compared with those in the non-PMV group. In the PMV group, the rate of extubation failure (39.4 vs. 6.7%, P < 0.001) was higher than the non-PMV group. The median hospital stay [35(23.0–50.0)d vs. 20(14.0–31.0)d, P < 0.001], PICU stay [22(15.0–33.0)d vs. 9(6.0–12.0)d, P < 0.001], hospitalization costs [¥391,925(263,259–614,471) vs. ¥239,497(158,723–350,620), P < 0.001], and mortality after 1-month discharge (22.0 vs. 1.6%, P < 0.001) were higher in the PMV group. Multivariate analysis revealed that age <1 year old, a higher PIM3 score at admission, prematurity, the use of inotropes or vasopressors, extubation failure, and ventilator mode on the first day of MV were associated with PMV.

Conclusions

The incidence and mortality of PMV in pediatric patients is surprisingly high. Premature infants or patients with severe disease or extubation failure are at higher risk of PMV. Patients with PMV exhibit a greater burden with regard to medical costs than those on non-PMV. It is important to establish specialized weaning units for mechanically ventilated patients with stable conditions.
The Safety and Efficacy of the Modified Single Incision Non-thoracoscopic Nuss Procedure for Children With Pectus Excavatum
Authors: Song Jishuo , Wang Quan , Pan Zhengxia , Wu Chun , Li Yonggang , Wang Gang , Dai Jiangtao , Xi Linyun , Li Hongbo
Published: February 2022

Background

This study described and evaluated the safety and efficacy of a modified single incision non-thoracoscopic Nuss procedure in pectus excavatum (PE) children.

Methods

PE patients undergoing the non-thoracoscopic Nuss procedure at the Children's Hospital of Chongqing Medical University between January 2017 and December 2020 were retrospectively enrolled. The patients were divided into two groups according to operation procedures: the double incision Nuss (DN) group and the modified single incision Nuss (SN) group. Propensity score matching (PSM) was applied before evaluation of operative and postoperative characteristics to reduce selection bias.

Results

Of the 502 patients included, 261 were enrolled in the DN group, and 241 in the SN group. The operation time [35.0 (30.0–40.0) vs. 50.0 (40.0–55.0) minutes, P < 0.001] and postoperative inpatient stay [7.0 (6.0–8.0) vs. 7.0 (7.0–8.0) days, P < 0.001] of the patients in the SN group after PSM were significantly shorter than those of the patients in the DN group after PSM. Moreover, median blood loss was significantly less in the SN group after PSM than that in the DN group after PSM [2.0 (1.0–5.0) vs. 5.0 (2.0–5.0) ml, P < 0.001]. There were no significant differences in the incidence of complications between the two groups (P > 0.05). Bar removal was performed in 85 patients in the SN group within 24–42 months after surgery. Additionally, the SN group patients had a significantly lower Haller index (HI) after bar removal [2.36 (2.15–2.55) vs. 3.76 (3.18–4.26), P < 0.001] compared to the initial HI.

Conclusions

The modified procedure is safe and effective for children with PE and is worthy of clinical application.
Advances in Mechanism Research on Polygonatum in Prevention and Treatment of Diabetes
Authors: Liu Shuang , Jia Qiao-Jun , Peng Yi-Qing , Feng Ting-Hui , Hu Shu-Ting , Dong Juan-e , Liang Zong-Suo
Published: February 2022

Diabetes mellitus is a fast-growing disease with a major influence on people’s quality of life. Oral hypoglycemic drugs and insulin are currently the main effective drugs in the treatment of diabetes, but chronic consumption of these drugs has certain side effects. Polysaccharides, saponins, flavonoids, and phenolics are the primary secondary metabolites isolated from the rhizomes of Polygonatum sibiricum Redouté [Asparagaceae], Polygonatum kingianum Collett & Hemsl [Asparagaceae], or Polygonatum cyrtonema Hua [Asparagaceae], which have attracted much more attention owing to their unique therapeutic role in the treatment and prevention of diabetes. However, the research on the mechanism of these three Polygonatum spp. in diabetes has not been reviewed. This review provides a summary of the research progress of three Polygonatum spp. on diabetes and its complications, reveals the potential antidiabetic mechanism of three Polygonatum spp., and discusses the effect of different processed products of three Polygonatum spp. in treating diabetes, for the sake of a thorough understanding of its effects on the prevention and treatment of diabetes and diabetes complications.
Montelukast Inhibits Platelet Activation Induced by Plasma From COVID-19 Patients
Authors: Camera Marina , Canzano Paola , Brambilla Marta , Rovati G. Enrico
Published: February 2022

Leukotrienes are important pro-inflammatory lipid mediators derived from the arachidonic acid metabolism. In particular, cysteinyl leukotrienes, namely LTC4, LTD4, and LTE4 are involved in many of the principal features of asthma, while more recently they have also been implicated in cardiovascular diseases. COVID-19 is characterized by an overwhelming state of inflammation, sometimes resulting in an acute respiratory distress syndrome. Furthermore, severe COVID-19 patients present an endothelial cell damage characterized by a hyperinflammatory/procoagulant state and a widespread thrombotic disease. Leukotriene receptor antagonists, such as montelukast, have long been proven to have an efficacy in asthma, while more recently they have been suggested to have a protective role also in cardiovascular diseases. As elevated levels of LTE4 have been detected in bronchoalveolar lavage of COVID-19 patients, and montelukast, in addition to its anti-inflammatory properties, has been suggested to have a protective role in cardiovascular diseases, we decided to investigate whether this drug could also affect the platelet activation characteristic of COVID-19 syndrome. In this contribution, we demonstrate that montelukast inhibits platelet activation induced by plasma from COVID-19 patients by preventing the surface expression of tissue factor (TF) and P-selectin, reducing the formation of circulating monocyte– and granulocyte–platelet aggregates, and, finally, in completely inhibiting the release of TFpos-circulating microvesicles. These data suggest the repurposing of montelukast as a possible auxiliary treatment for COVID-19 syndrome.
AI Models to Assist Vancomycin Dosage Titration
Authors: Wang Zhiyu , Ong Chiat Ling Jasmine , Fu Zhiyan
Published: February 2022

Background: Effective treatment using antibiotic vancomycin requires close monitoring of serum drug levels due to its narrow therapeutic index. In the current practice, physicians use various dosing algorithms for dosage titration, but these algorithms reported low success in achieving therapeutic targets. We explored using artificial intelligent to assist vancomycin dosage titration.

Methods: We used a novel method to generate the label for each record and only included records with appropriate label data to generate a clean cohort with 2,282 patients and 7,912 injection records. Among them, 64% of patients were used to train two machine learning models, one for initial dose recommendation and another for subsequent dose recommendation. The model performance was evaluated using two metrics: PAR, a pharmacology meaningful metric defined by us, and Mean Absolute Error (MAE), a commonly used regression metric.

Results: In our 3-year data, only a small portion (34.1%) of current injection doses could reach the desired vancomycin trough level (14–20 mcg/ml). Both PAR and MAE of our machine learning models were better than the classical pharmacokinetic models. Our model also showed better performance than the other previously developed machine learning models in our test data.

Conclusion: We developed machine learning models to recommend vancomycin dosage. Our results show that the new AI-assisted dosage titration approach has the potential to improve the traditional approaches. This is especially useful to guide decision making for inexperienced doctors in making consistent and safe dosing recommendations for high-risk medications like vancomycin.
Effect of 0.01% Atropine on Accommodation in Myopic Teenagers
Authors: Li Huixia , Zhang Liying , Tian Hong , Zhang Song , Zhang Xueyan , Zhang Han , Chen Yujing , Qi Wenping , Wu Xiaoying , Jiang Hongmei , Yang Hailong , Yang Yajun , Liu Lei , Zhang Guisen
Published: February 2022

Purpose: The purpose of the study is to evaluate the effects of 0.01% atropine eye drops on accommodative system parameters among teenagers with low myopia.

Methods: Ninety-five myopic teenagers [39 boys (8.69 ± 2.473) and 56 girls (8.54 ± 2.054) aged 5–17 years] with no history of eye disease were enrolled. Biometric and accommodative system parameters were evaluated before and at 1 week, 1 month, 3 months, and 6 months of 0.01% atropine eye drop instillation.

Results: Participants without accommodative demand at 6 months demonstrated insignificant changes after the atropine instillation (all p > 0.05). Nevertheless, there were significant differences in accommodative sensitivity, accommodative amplitude, accommodative responsiveness, and negative relative accommodation (NRA) at 3 months compared with baseline after atropine instillation (all p < 0.05). Except spherical equivalent refraction, cornea thickness, intraocular pressure, and axial length were stable after the 0.01% atropine instillation (all p > 0.05).

Conclusion: Morphologically, current measurements suggested that 0.01% atropine had favorable reduction of accommodation for childhood low myopia over a half-year period.
Hermitian and Non-Hermitian Dirac-Like Cones in Photonic and Phononic Structures
Authors: Luo Jie , Lai Yun
Published: February 2022

Accidental degeneracy plays an important role in the generation of novel band dispersions. Photonic structures that exhibit an accidental Dirac-like conical dispersion at the center of the Brillouin zone can behave like a zero-index material at the Dirac-point frequency, leading to a number of unique features, such as invariant phase in space, wave tunneling, photonic doping and anti-doping, etc. Such a phenomenon has been explored in on-chip structures or three dimensions recently. The introduction of non-Hermiticity into the system via loss or gain could transform the accidental Dirac-like cone into a spawning ring of exceptional points, a complex Dirac-like cone or other unique dispersions. Similar Dirac-like cones and related physics are also observed in phononic structures. This review presents an overview of the accidental-degeneracy-induced Dirac-like cones at the center of the Brillouin zone in both photonic and phononic structures, including the fundamental physics, effective-medium description and experimental demonstration, as well as current challenges and future directions.
Potential Role of Domains Rearranged Methyltransferase7 in Starch and Chlorophyll Metabolism to Regulate Leaf Senescence in Tomato
Authors: Wen Yu Xin , Wang Jia Yi , Zhu Hui Hui , Han Guang Hao , Huang Ru Nan , Huang Li , Hong Yi Guo , Zheng Shao Jian , Yang Jian Li , Chen Wei Wei
Published: February 2022

Deoxyribonucleic acid (DNA) methylation is an important epigenetic mark involved in diverse biological processes. Here, we report the critical function of tomato (Solanum lycopersicum) Domains Rearranged Methyltransferase7 (SlDRM7) in plant growth and development, especially in leaf interveinal chlorosis and senescence. Using a hairpin RNA-mediated RNA interference (RNAi), we generated SlDRM7-RNAi lines and observed pleiotropic developmental defects including small and interveinal chlorosis leaves. Combined analyses of whole genome bisulfite sequence (WGBS) and RNA-seq revealed that silencing of SlDRM7 caused alterations in both methylation levels and transcript levels of 289 genes, which are involved in chlorophyll synthesis, photosynthesis, and starch degradation. Furthermore, the photosynthetic capacity decreased in SlDRM7-RNAi lines, consistent with the reduced chlorophyll content and repression of genes involved in chlorophyll biosynthesis, photosystem, and photosynthesis. In contrast, starch granules were highly accumulated in chloroplasts of SlDRM7-RNAi lines and associated with lowered expression of genes in the starch degradation pathway. In addition, SlDRM7 was activated by aging- and dark-induced senescence. Collectively, these results demonstrate that SlDRM7 acts as an epi-regulator to modulate the expression of genes related to starch and chlorophyll metabolism, thereby affecting leaf chlorosis and senescence in tomatoes.
The Advent of Coronavirus Disease 2019 and the Impact of Mobile Learning on Student Learning Performance: The Mediating Role of Student Learning Behavior
Authors: Wang Zhiwei , Qadir Alia , Asmat Alia , Aslam Mian Muhammad Sheeraz , Luo Xiaoli
Published: February 2022

The recent coronavirus disease 2019 (COVID-19) pandemic pushed almost all institutions to adopt online and virtual education. The uncertainty of this situation produced various questions that perplexed educationists regarding what implications the pandemic would have on educational institutions, especially regarding how the switch to online education would impact the behavior and performance of students. The vast importance of this matter attracted the attention of researchers and served as the motivation for this research, which aims to resolve this confusion by studying the use of mobile learning (ML) among students for educational purposes during the COVID-19 period. This study also examines how this situation has affected student learning behavior (LB) and performance (SP) in the higher education setting. This research is based on collaborative learning theory, sociocultural learning theory, and ML theory. This quantitative research employed the convenient sampling technique to collect data through structured questionnaires distributed to 396 students of higher education institutions who carry a mobile device. This study used descriptive and inferential statistics to make the data more meaningful. Structural equation modeling (SEM) with AMOS software was used for hypothesis testing. The results showed that ML was a significant and positive predictor of SP and LB. Moreover, student LB partially mediated the relationship between ML and SP. The findings suggest that the academic performance of students can be enhanced by building a ML environment that aligns with the LB of students. Nevertheless, content suitable for ML must be developed, and future research should be conducted on this topic.
Exploring the Impact of Music Education on the Psychological and Academic Outcomes of Students: Mediating Role of Self-Efficacy and Self-Esteem
Authors: Sun Jian
Published: February 2022

In recent years, there has been a growing interest in scholars and practitioners to explore the factors that lead to an improvement in Students’ psychological wellbeing. Due to the tough challenges faced by students during their academic life, severe issues of stress, anxiety, and other mental health issues emerge, which affect their academic performance and have a long-lasting impact on their future careers. The pandemic accelerates the stress levels, anxiety, and mental issues of students. The main purpose of this study was to explore how music education impacts on Students’ psychological wellbeing and academic performance. This study also investigates the mediating effect of self-esteem and self-efficacy. To the best of our knowledge, there has been little to no study exploring the relationship of music education on the psychological wellbeing and performance of students, especially from the perspective of Asian countries. This study was conducted in undergraduate and graduate institutions of China. This study was quantitative in nature and data were collected from 319 respondents. The structural equation modeling (SEM) technique was employed for data analysis. Results reveal that music education has a significant positive impact on psychological wellbeing, which improves Students’ academic performance. Moreover, psychological wellbeing also has a significant and positive impact on Students’ academic performance. Self-efficacy and self-esteem significantly mediate the relationship between music education and psychological wellbeing. The findings of this study open new avenues for future research in music education and psychological wellbeing. This study suggests that the policymakers and practitioners should make such policies that encourage educational institutes to adopt music education to improve the psychological wellbeing of students.
The Function and Structure of Precuneus Is Associated With Subjective Sleep Quality in Major Depression
Authors: Ma Lu , Zhang Cun
Published: February 2022

Background

Poor sleep quality is related to depression. However, the investigation of the neural basis for poor sleep quality in individuals with major depression (MD) is limited.

Methods

Resting state functional and structural MRI data were derived from 114 MD individuals and 74 normal controls (NCs). Fractional amplitude of low-frequency fluctuation (fALFF) and gray matter volume (GMV) were used to measure function and structure of the brain. Pittsburgh Sleep Quality Index (PSQI) was performed to evaluate subjective sleep quality. Correlations were carried out to investigate links of PSQI score with brain imaging indices in MD and NCs, separately. We also examined the differences in fALFF and GMV of brain regions related to PSQI score between MD and NCs.

Results

In contrast to NCs, MD individuals had higher PSQI score. The higher PSQI score was associated with lower fALFF and lower GMV in bilateral precuneus in MD individuals. Moreover, the MD individuals exhibited increased fALFF in bilateral precuneus compared with NCs. However, the correlation between subjective sleep quality and neuroimaging parameters was not significant in NCs.

Conclusion

The implication of these findings is that the function and structure of precuneus provides a neural basis for subjective poor sleep quality in MD. Understanding this may lead to better intervention of depression and associated sleep complaints.
Characterizing Potentially Preventable Hospitalizations of High-Cost Patients in Rural China
Authors: Lu Shan , Zhang Yan , Zhang Liang , Klazinga Niek S. , Kringos Dionne S.
Published: February 2022

Introduction

High-cost patients are characterized by repeated hospitalizations, and inpatient cost accounts for a large proportion of their total health care spending. This study aimed to assess the occurrence and costs of potentially preventable hospitalizations and explore contributing factors among high-cost patients in rural China.

Methods

We examined a population-based sample of patients using the 2016 New Rural Cooperative Medical Scheme in Dangyang city, China. Eighteen thousand forty-three high-cost patients were identified. A validated tool and logistic regression analysis were used to determine preventable hospitalizations and their patient-level and supply-side factors.

Results

High-cost patients were older (average age of 54 years) than non-high-cost patients (50 years) and more likely to come from poverty-stricken families. The occurrence of preventable hospitalization was 21.65% among high-cost patients. The proportion of preventable inpatient cost in total inpatient and outpatient expenditure among high-cost patients (5.81%) was lower than that of non-high-cost patients (7.88%) but accounted for 75.87% of the overall preventable inpatient cost. High-cost patients with more hospitalizations were more likely to experience preventable hospitalization, and those with heart failure, COPD, diabetes and mixed conditions were at a higher risk of preventable hospitalization, while those with more outpatient visits were less likely to show preventable hospitalization.

Conclusions

The occurrence of preventable hospitalization among high-cost patients in rural China was sizeable. The preventable inpatient cost of the overall population was concentrated among high-cost patients. Interventions such as improving preventive care and disease management targeting high-cost patients within counties may improve patients' health outcomes and quality of life and reduce overall preventable inpatient cost.
Prevalence of COVID-19 Pandemic, Self-Esteem and Its Effect on Depression Among University Students in Saudi Arabia
Authors: Azmi Fatima M. , Khan Habib Nawaz , Azmi Aqil M. , Yaswi Arooj , Jakovljevic Mihajlo
Published: February 2022

Background and Aims

University students are commonly identified as susceptible, suffering from higher anxiety, stress, and depression than the overall population. During the Corona Virus Disease pandemic (COVID), education was shifted to the virtual learning environment. Students' ambiguity regarding academic accomplishment, imminent careers, changes in social life, and other concerns all these factors played a role in amplifying their stress levels, anxiety, and depression worldwide. This study investigates university students' self-esteem and depressions after they have been online learning for over 1 year due to the COVID-19 pandemic in Saudi Arabia.

Methods

For this research, an adapted questionnaire of Rosenberg (Self-Esteem Scale) and Zung (Self-Rating Depression Scale) was used to get the responses of the participants of public and private universities in Saudi Arabia during March-April 2021. We received a total of 151 valid responses from respondents. For data analysis, we used descriptive statistics, ANOVA, multiple regression and binary logistic regression.

Findings

The results showed that 75% of the students experienced different levels of depressions, with half (37.5%) having moderate to extreme levels of depression. A total of 41% of students experienced low self-esteem (38% females and 45% males). The regression results indicated depressive symptoms for low self-esteem. Furthermore, results of logistic regression showed that high self-esteem reduces the chances of getting depressive symptoms by 17%. The depressive symptoms were higher in female students than their male counterparts; furthermore, males experienced depressive symptoms less than females by 38%.

Conclusions

Based on the current research results, it is concluded that the presence of the COVID-19 pandemic has dramatically increased the depressive symptoms in students, especially in female students. The findings suggested instant consideration and support for students. It is also suggested to the quest for potential managing policies that have been known and effective during the pandemic. Moreover, training should be provided for students to shift their educational experience mindset to an adaptive mindset, which can help them adapt to the new ways of learning and education.
Pyroptosis-Related Signatures for Predicting Prognosis in Breast Cancer
Authors: Ren Tong , Guo Xuhui , Zhang Jingyang , Liu Zhenzhen
Published: February 2022

Background

Female breast cancer (BC) has become the most common cancer in the world, and its mortality was considerably higher in transitioning vs. transitioned countries. Pyroptosis, an inflammation-dependent programmed cell death mediated by inflammasomes, has been observed in human colorectal tumors and gliomas. However, the characteristics of pyrolysis-related genes and their influence and mechanism on the tumorigenesis and progress of BC were unknown.

Methods

Based on the global public database, we used comprehensive bioinformatics analysis to systematically analyze the expression of pyroptosis-related genes in BC and their relationship in tumor progression. In addition, BC patients were divided into two groups, and the clinical features and outcomes could be better predicted by the consistent clustering of pyroptosis-related genes. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to establish a risk score. Then, we further explored the prognostic value and clinical features of pyroptosis genes. Finally, we used the Human Protein Atlas (HPA) platform to identify the expression at protein levels of the key genes.

Results

We confirmed that the expression of pyroptosis-related genes was different in BC and normal breast tissues. A high frequency of somatic mutations occurred in BC. In addition, 33 pyroptosis-related proteins interacted frequently. Based on univariate analysis and the LASSO Cox model, five pyroptosis-related genes [including GADMA, interleukin-6 (IL-6), NLR pyrin domain-containing protein 6 (NLRP6), caspase-1 (CASP1), and caspase-9 (CASP9)], were obtained to calculate a risk score. The risk score was identified as an independent risk factor for the prognosis of BC and might play an auxiliary role in clinical classification. The HPA platform confirmed that the expression trends of the key genes were consistent with our previous studies.

Conclusion

Pyroptosis had an important effect on the progression of BC. And the pyroptosis-related genes could be used as new prognostic biomarkers and therapeutic targets for BC.
Wound Irrigation Using Wet Gauze May Reduce Surgical Site Infection Following Laparoscopic Appendectomy
Authors: Al-Sawat Abdullah , Mun Ji Yeon , Yoon Sung Hoon , Lee Chul Seung
Published: February 2022

Purpose

This study aimed to compare the perioperative outcomes of wet gauze and conventional irrigation after laparoscopic appendectomy to determine whether wet gauze irrigation can help reduce surgical site infection (SSI).

Methods

A total of 308 patients undergoing laparoscopic appendectomy were included in this study between December 2018 and May 2020. Of these, 132 (42.9%) received gauze irrigation (group 1), and 176 patients (57.1%) received conventional irrigation (group 2). Pre-operative outcomes and complications, including SSI, were compared after propensity score matching (PSM) to adjust for baseline differences and selection bias.

Results

After 1:1 PSM, 92 well-matched patients in each group were evaluated. Regarding perioperative outcomes between groups 1 and 2, the rate of severe complications (Clavien-Dindo Classification grades III, IV, and V), operative time, and readmission rate did not differ between the groups. Superficial/deep SSIs were observed more frequently in group 2 (8/92 cases) than in group 1 (1/92 cases; p = 0.017). The organ/space SSIs rate was not significantly different between the two groups (1/92 group 1 and 0/92 group 2, p = 0.316). However, post-operative hospital stay was significantly longer in group 2 (2.8 ± 1.3 days) than in group 1 (1.6 ± 1.2 days; p < 0.001). In the univariate analyses, wound irrigation using wet gauze was an independent protective factor for superficial or deep SSI (p = 0.044).

Conclusions

Wound irrigation using wet gauze after fascia closure has a significant beneficial effect on reducing post-operative superficial/deep SSI following laparoscopic appendectomy.
Efficacy and Safety of Sphincter-Preserving Surgery in the Treatment of Complex Anal Fistula: A Network Meta-Analysis
Authors: Huang Hua , Ji Lijiang , Gu Yunfei , Li Youran , Xu Shanshan
Published: February 2022

Background

There are many surgical methods of sphincter preservation in treating complex anal fistula, but the therapeutic effects of each operation are different. Therefore, this study aimed to compare the impact of other treatment methods through a network meta-analysis to evaluate the best sphincter preservation method for treating complex anal fistula.

Methods

We searched PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, Chinese Biomedical Literature Database, VIP Journal Database, and the Wanfang Database to collate randomized controlled trials on sphincter-preserving surgery for complex anal fistula.

Results

A total of 29 articles were included in this meta-analysis. The cure rates showed no statistically significant differences between any two interventions (P > 0.05). The recurrence rate results showed that the rate of patients after Fistulectomy was higher than others (P < 0.05). The incidence rate of complications showed that the incidence rate after fistulectomy treatment was higher than that of others (P < 0.05). The surface under the cumulative ranking (SUCRA) was used to arrange their advantages and disadvantages, and a larger SUCRA value indicates that the intervention may be more effective. The results showed that TROPIS may have the highest cure rate (SUCRA = 78.6%), stem cell transplantation (SCT) may have the lowest recurrence rate (SUCRA = 85.5%), and imLIFT may have the least complications (SUCRA = 88.2%).

Conclusion

According to the existing literature data, for patients with complex anal fistula, TROPIS may be the surgical method with the highest cure rate, SCT may be the treatment method with the lowest recurrence rate, and imLIFT may be the surgical method with the lowest incidence of postoperative complications.

Systematic Review Registration

PROSPERO, identifier: CRD42020221907.
Increasing Medical Student Exposure to Neurosurgery: The Educational Value of Special Study Modules, Student Selected Components, and Other Undergraduate Student Projects
Authors: Tiefenbach Jakov , Kaliaperumal Chandrasekaran , Demetriades Andreas K.
Published: February 2022

Objectives

Neurosurgery is a tertiary specialty, and exposure to medical students limited. One way to increase engagement and offer experience in neurosurgery is through Student Selected Components (SSC), Special Study Modules (SSM), or independent projects. Our aim was to assess the educational value of such projects and evaluate their effectiveness in exposing students to the field.

Methods

A survey was designed and distributed to Edinburgh University medical students and alumni who completed a neurosurgical project within the last 5 years. The survey was anonymous and collected responses over a fortnight. The results were analyzed in Microsoft Excel 2020 Software.

Results

Twenty-four respondents completed the survey −42% were students and 58% junior doctors. Respondents overwhelmingly enjoyed their project (96%) and reported increased interest in neurosurgery (62%). The project helped improve their knowledge of neurosurgical procedures, pathologies, and/or clinical presentations and allowed connections with the local department. On a Likert scale, 37% felt they gained a good insight into the field. Only 33% felt the project was a good “taster” for the specialty. This is reasonable given that 92% of projects focused on data analysis, and none were designed as clinical attachments. A large number of students had their work published (50%) and presented at conferences (55%).

Conclusion

Lack of exposure to neurosurgery at medical school is a known limitation within a busy curriculum. Selected Components/Special Study Modules/independent projects help students learn about certain aspects of neurosurgery and raise their level of interest. A majority of participants either achieved presentation at conferences or published their work. However, our results suggest neurosurgical projects complement but do not replace traditional clinical attachments in providing insight into the craft of this specialty.
Placental Macrophages Following Maternal SARS-CoV-2 Infection in Relation to Placental Pathology
Authors: Sharps Megan C. , Garrod Ainslie , Aneni Emmanuel , Jones Carolyn J. P. , Batra Gauri , Heazell Alexander E. P.
Published: February 2022

Introduction

In December 2019, a novel coronavirus, SARS-CoV-2, was identified. Whilst pregnant women appear to be at risk of severe infection, pre-term birth, and stillbirth, it is unclear whether placental dysfunction is a consistent feature of maternal SARS-CoV-2 infection during pregnancy. We aim to describe the immune response in placentas of women who had COVID-19 infection during pregnancy and investigate whether there are any associated morphological changes.

Methods

The placentas of women testing positive for COVID-19 during their pregnancy were compared to contemporaneous controls who were not known to have had COVID-19 during pregnancy. Samples of each placenta were sent for histopathological analysis or underwent immunohistochemical staining for CD163, CD20, CD3, CD31, and SARS-CoV-2 spike protein. A subset of samples were sent for transmission electron microscopy.

Results

There was a significant increase in the number of CD163+ macrophages in the Post COVID group (p = 0.0020). There was no difference in the percentage of CD3+, CD20+ cells, but there was an increase in placental vascularity in the Post COVID group compared to controls (p = 0.026).

There were no structural differences observed between the samples sent for EM analysis. However, one of the placentas from the Post COVID group was seen to have several large sub-apical vacuoles in the syncytiotrophoblast. We did not observe any virions within the vacuoles and SARS-CoV-2 spike protein staining was negative for the sample. Histopathological investigations indicated that there was no specific placental pathology caused by maternal COVID-19 infection in this cohort of samples.

Conclusions

This study did not confirm previous studies which describe a possible increase in cases of both maternal and fetal vascular malperfusion, and placentitis in women who had COVID-19, which were seen in association with adverse pregnancy outcomes. It remains unclear whether observed abnormalities are caused by maternal infection, or whether maternal infection exacerbates existing placental pathology; understanding why some placentas generate these abnormalities is a key goal.
Goal Programming and Mathematical Modelling for Developing a Capacity Planning Decision Support System-Based Framework in Higher Education Institutions
Authors: Makki Anas A. , Sindi Hatem F. , Brdesee Hani , Alsaggaf Wafaa , Al-Hayani Abdulmonem , Al-Youbi Abdulrahman O.
Published: February 2022

Achieving the Saudi Kingdom’s vision 2030 in the higher education sector requires higher education institutions to make a significant simultaneous change in their current practices. This encompasses the transitioning of government-funded educational institutions to be financially independent. Therefore, a prompt, agile transition is required while maintaining a positive socioeconomic impact, entrepreneurship and innovation, and high-quality education. This necessitates the transition to lean processes and the review of current practices. One of the most vital processes in educational institutions is student admission/enrollment capacity planning. This study puts forward a capacity planning decision support system (DSS)-based framework for university student enrollment. The framework was applied to the case of KAU, where current practice and challenges are presented, and from which data were collected. A top-down/bottom-up approach was followed and applied using the goal programming technique and a developed mathematical model, respectively. Results show that the proposed framework effectively affects student admission/enrollment capacity planning on strategic and operational levels. Moreover, it can be used in other planning aspects of higher education in universities, such as human resources planning, teaching load planning, faculty-to-student ratios, accreditation, quality requirements, lab capacity planning, equipment/teaching aids procurement, and financial planning, to mention a few. The implications of this study include assisting decision-makers in higher education institutions in matching their admission/enrollment capacity of student numbers between the macro-strategic and the micro-operational level.
Hardware-In-the-Loop Simulation of Time-Delayed Anti-Swing Controller for Quadrotor with Suspended Load
Authors: Omar Hanafy M.
Published: February 2022

Quadrotor flying vehicles with suspended loads have a lot of applications, such as mine detection and transferring loads for delivery, or through places where ground vehicles cannot reach. In these applications, the payload will be suspended underneath the vehicle and it is subjected to large oscillations due to external disturbances or the acceleration of the vehicle itself. These oscillations add additional forces and moments to the quadrotor, and this deteriorates its performance and stability. In this paper, we developed a hardware-in-the-loop (HIL) simulation platform for a quadrotor with a suspended load system using Gazebo. The developed platform can be used to understand the dynamics of the system and design control systems to suppress the oscillation of the suspended load. An anti-swing controller that is based on time-delayed feedback of the load swing angles is implemented in the designed HIL environment to show the usefulness of the newly developed system and the effectiveness of the anti-swing controller.
Efficacy Study of Fault Trending Algorithm to Prevent Fault Occurrence on Automatic Trampoline Webbing Machine
Authors: Feng Shi , Mo John P. T.
Published: February 2022

Nowadays, fault diagnostics is widely applied under Industry 4.0 to reduce machine maintenance costs, improve productivity, and increase machine availability. However, fault diagnostics are mostly post-mortem. When the fault is identified, it is already too late because damages have been done to the product and machine. This paper compares the efficacy of several signal data processing techniques for detecting faults that are about to occur. Our aim is to find an efficient way to predict the fault before it occurs. A continuous wavelet transform synchrosqueezed scalogram was found to be most suitable for this purpose, but it is difficult to apply. A novel procedure is proposed to count the number of pulses in the synchrosqueezed scalogram. A new method for detecting the trend from the pulse counts is then developed to predict the fault before it happens. The procedure and method are illustrated with experimental data collected while running an automated double-thread trampoline webbing machine.
Design and Application of Secret Codes for Learning Medical Data
Authors: Jo Dongsik , Chung Jin-Ho
Published: February 2022

In distributed learning for data requiring privacy preservation, such as medical data, the distribution of secret information is an important problem. In this paper, we propose a framework for secret codes in application to distributed systems. Then, we provide new methods to construct such codes using the synthesis or decomposition of previously known minimal codes. The numerical results show that new constructions can generate codes with more flexible parameters than original constructions in the sense of the number of possible weights and the range of weights. Thus, the secret codes from new constructions may be applied to more general situations or environments in distributed systems.
Bent and Branched Microstrip-Line Antennas for Circular Polarization
Authors: Hirose Kazuhide , Nakamura Kohei , Nakano Hisamatsu
Published: February 2022

We analyze three transmission-line antennas using the moment method. Each line antenna comprises a coplanar feed line, loops, and straight segments connecting the loops and feedline. First, we investigate bent and branched line antennas with loops on one side of the feedline. It is found that the segment length affects both the beam direction and axial ratio for the bent line antenna; in contrast, it only affects the branched line antenna’s axial ratio, resulting in a more straightforward design. Subsequently, the branched line antenna is modified with loops on both sides of the feedline to enhance the gain. It is observed that the antenna shows a gain enhancement of 2.0 dB, maintaining the same axial-ratio bandwidth as that of the original branched line antenna. The simulated results are validated by experimental work.
Feature Transformation Framework for Enhancing Compactness and Separability of Data Points in Feature Space for Small Datasets
Authors: ElMorshedy Mahmoud Maher , Fathalla Radwa , El-Sonbaty Yasser
Published: February 2022

Compactness and separability of data points are two important properties that contribute to the accuracy of machine learning tasks such as classification and clustering. We propose a framework that enhances the goodness criteria of the two properties by transforming the data points to a subspace in the same feature space, where data points of the same class are most similar to each other. Most related research about feature engineering in the input data points space relies on manually specified transformation functions. In contrast, our work utilizes a fully automated pipeline, in which the transformation function is learnt via an autoencoder for extraction of latent representation and multi-layer perceptron (MLP) regressors for the feature mapping. We tested our framework on both standard small datasets and benchmark-simulated small datasets by taking small fractions of their samples for training. Our framework consistently produced the best results in all semi-supervised clustering experiments based on K-means and different seeding techniques, with regards to clustering metrics and execution time. In addition, it enhances the performance of linear support vector machine (LSVM) and artificial neural network (ANN) classifier, when embedded as a preprocessing step before applying the classifiers.
Self-Supervised Noise Reduction in Low-Dose Cone Beam Computed Tomography (CBCT) Using the Randomly Dropped Projection Strategy
Authors: Han Young-Joo , Yu Ha-Jin
Published: February 2022

Deep learning-based denoising methods have proved efficient for medical imaging. Obtaining a three-dimensional representation of a scanned object is essential, such as in the computed tomography (CT) system. A sufficient radiation dose needs to be irradiated to a scanned object to obtain a high-quality image. However, the radiation dose is insufficient in many cases due to hardware limitations or health care issues. A deep learning-based denoising method can be a solution to obtaining good images, even when the radiation dose is insufficient. However, most existing deep learning-based denoising methods require numerous paired low-dose CT (LDCT) images and normal-dose CT (NDCT) images. It is almost impossible to obtain numerous well-paired LDCT and NDCT images. Self-supervised denoising methods were proposed to train a denoising neural network on only noisy images. These methods can be applied to the projection domain in LDCT. However, applying denoising in the projection image domain is a challenging task, because the projection images for LDCT have extremely weak signals. To solve this problem, we propose a noise reduction method based on the dropped projection strategy. The proposed method works by first reconstructing the 3D image with the degraded versions of the projection images generated by Bernoulli sampling. Subsequently, the denoising neural network is trained to restore the signal dropped out by Bernoulli sampling in the projection image domain. As such, the method we propose solves the over-smoothing problem in previous methods and is able to be trained with a small amount of data. We verified the performance of our proposed method on the SPARE challenge dataset and the in-house lithium polymer dataset. The experiments on two datasets show that the proposed method outperforms the conventional denoising methods by at least 4.47 dB of PSNR value.
In-the-Loop Simulation Experiment of Aero-Engine Fault-Tolerant Control Technology
Authors: Zhang Mengtian , Huang Xianghua , Wang Shengchao , Luo Liantan
Published: February 2022

Aeroengines are prone to failure due to their large range of working envelopes and bad working environments. Fault diagnosis and a fault-tolerant control strategy for aeroengines and control systems are important means to improve the reliability of aeroengine. In this article, the turbofan engine is taken as the research object, and the fault diagnosis and fault-tolerant control of an aeroengine control system are studied. First, based on the principle of component-level modeling and the algorithm of the extended Kalman filter, an adaptive turbofan model is established, and the adaptive effect of the model in the range of the full envelopment is verified by digital simulation. Next, based on the analytical redundancy provided by the adaptive model, sensor fault diagnosis and fault-tolerant control are studied. The low-voltage speed closed-loop control and EPR closed-loop control are designed, and the sensor fault-tolerant control based on analytic redundancy and the switching control rate is studied. The simulation results show that the filter based on the adaptive model can accurately locate and diagnose the sensor faults, and the sensor fault-tolerance based on the analytic redundancy and switching control rate can be effective fault tolerance for the sensor faults. Finally, as a hardware platform, this article selects MC203 VxWorks as an embedded system, the adaptive model for a turbofan engine as the research object, and has carried on the fault diagnosis and fault-tolerant control in the loop simulation experiment research; the experimental results show that the adaptive model can provide accurate analytical redundancy, and the real-time and fault tolerance of sensor fault effect is better.
Biosensors Based on Bivalent and Multivalent Recognition by Nucleic Acid Scaffolds
Authors: Kim Hokyung , Choi Hayeon , Heo Yoonji , Kim Cheoljae , Kim Min , Kim Ki Tae
Published: February 2022

Several biological macromolecules adopt bivalent or multivalent interactions to perform various cellular processes. In this regard, the development of molecular constructs presenting multiple ligands in a specific manner is becoming crucial for the understanding of multivalent interactions and for the detection of target macromolecules. Nucleic acids are attractive molecules to achieve this goal because they are capable of forming various, structurally well-defined 2D or 3D nanostructures and can bear multiple ligands on their structures with precisely controlled ligand–ligand distances. Thanks to the features of nucleic acids, researchers have proposed a wide range of bivalent and multivalent binding agents that strongly bind to target biomolecules; consequently, these findings have uncovered new biosensing strategies for biomolecule detection. To date, various bivalent and multivalent interactions of nucleic acid architectures have been applied to the design of biosensors with enhanced sensitivity and target accuracy. In this review, we describe not only basic biosensor designs but also recently designed biosensors operating through the bivalent and multivalent recognition of nucleic acid scaffolds. Based on these designs, strategies to transduce bi- or multivalent interaction signals into readable signals are discussed in detail, and the future prospects and challenges of the field of multivalence-based biosensors are explored.