bluuebunny/crossref_metadata_2025 huggingface dataset:
Complex functional brain network properties in anorexia nervosa
Authors: Gupta Arpana , Bhatt Ravi R. , Rivera-Cancel Alannah , Makkar Rishi , Kragel Philip A. , Rodriguez Thomas , Graner John L. , Alaverdyan Anita , Hamadani Kareem , Vora Priten , Naliboff Bruce , Labus Jennifer S. , LaBar Kevin S. , Mayer Emeran A. , Zucker Nancy
Published: February 2022

Background

Anorexia nervosa (AN) is a disorder characterized by an incapacitating fear of weight gain and by a disturbance in the way the body is experienced, facets that motivate dangerous weight loss behaviors. Multimodal neuroimaging studies highlight atypical neural activity in brain networks involved in interoceptive awareness and reward processing.

Methods

The current study used resting-state neuroimaging to model the architecture of large-scale functional brain networks and characterize network properties of individual brain regions to clinical measures. Resting-state neuroimaging was conducted in 62 adolescents, 22 (21 female) with a history of AN and 40 (39 female) healthy controls (HCs). Sensorimotor and basal ganglia regions, as part of a 165-region whole-brain network, were investigated. Subject-specific functional brain networks were computed to index centrality. A contrast analysis within the general linear model covarying for age was performed. Correlations between network properties and behavioral measures were conducted (significance q < .05).

Results

Compared to HCs, AN had lower connectivity from sensorimotor regions, and greater connectivity from the left caudate nucleus to the right postcentral gyrus. AN demonstrated lower sensorimotor centrality, but higher basal ganglia centrality. Sensorimotor connectivity dyads and centrality exhibited negative correlations with body dissatisfaction and drive for thinness, two essential features of AN.

Conclusions

These findings suggest that AN is associated with greater communication from the basal ganglia, and lower information propagation in sensorimotor cortices. This is consistent with the clinical presentation of AN, where individuals exhibit patterns of rigid habitual behavior that is not responsive to bodily needs, and seem “disconnected” from their bodies.
From efficacy to effectiveness: child and adolescent eating disorder treatments in the real world (Part 2): 7-year follow-up
Authors: Stewart Catherine S. , Baudinet Julian , Munuve Alfonce , Bell Antonia , Konstantellou Anna , Eisler Ivan , Simic Mima
Published: February 2022

Background

Eating disorders are often characterised as disabling, chronic or relapsing conditions with high mortality rates. This study reports follow-up outcomes for patients seen at the Maudsley Centre for Child and Adolescent Eating Disorders (MCCAED), whose end of treatment outcomes are reported in a separate paper.

Methods

Three-hundred-and-fifty-seven former patients, who received evidence-based treatment for an eating disorder as a child or adolescent in MCCAED between 2009 and 2014 were eligible to participate. Current contact information was available for 290, of whom 149 (51.4%) consented to follow-up. Participants were sent links to online questionnaires, with additional demographic information extracted from medical records. Descriptive analyses of key socioeconomic and health outcomes were performed on data collected.

Results

Mean length of follow-up was 6 years 11 months. Ten (6.7%) participants reported a current diagnosis of an eating disorder at follow-up. The great majority reported no (63.8%) or minimal (26.8%) interference from eating disorder difficulties. More than half (53.6%) reported other mental health diagnoses with most reporting no (33.8%) or minimal (50.7%) interference from those difficulties. One third (33.3%) had sought help for an eating disorder and around 20% received prolonged/intensive treatment during the follow-up period. Approximately 70% had sought treatment for other mental health difficulties (mostly anxiety or depression) and 35.4% had substantial treatment. At follow-up more than half (55.5%) reported doing generally well, and around two-thirds reported general satisfaction with their social well-being (65%). The majority (62.7%) had a good outcome on the Morgan Russell criteria, which was consistent with low self-reported ratings on EDE-Q, and low impact of eating disorder or mental health symptoms on work and social engagement. Most of the former patients who had day and/or inpatient treatment as a part of their comprehensive integrated care at MCCAED did well at follow-up.

Conclusions

Young people seen in specialist eating disorder services do relatively well after discharge at longer-term follow-up especially regarding eating disorders but less favourably regarding other mental health difficulties. Few reported a diagnosable eating disorder, and the great majority went on to perform similarly to their peers in educational and vocational achievements.
Is work-family conflict a pathway between job strain components and binge eating? A cross-sectional analysis from the ELSA-Brasil study
Authors: Juvanhol Leidjaira Lopes , Silva-Costa Aline , Rotenberg Lucia , Moreno Arlinda B. , Melo Enirtes Caetano Prates , Santos Itamar S. , Nunes Maria Angélica Antunes , Toivanen Susanna , Chor Dóra , Griep Rosane Härter
Published: February 2022

Background

Job strain has been reported as a trigger for binge eating, yet the underlying mechanisms have been unclear. The aim of this study was to evaluate whether work-family conflict is a pathway in the association between job strain and binge eating, considering the possible effect-modifying influence of body mass index (BMI).

Methods

This cross-sectional analysis included 12,084 active civil servants from the multicenter Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Job strain was assessed using the Demand-Control-Support Questionnaire. Work-family conflict was considered as a latent variable comprising three items. Binge eating was defined as eating a large amount of food in less than 2 h at least twice a week in the last six months with a sense of lack of control over what and how much was eaten. Structural equation modelling was used to test the role of work-family conflict in the association between job strain and binge eating, stratifying for BMI.

Results

For individuals of normal weight, positive associations were found between skill discretion and binge eating (standardized coefficient [SC] = 0.209, 95%CI = 0.022–0.396), and between psychological job demands and work-family conflict (SC = 0.571, 95%CI = 0.520–0.622), but no statistically significant indirect effect was found. In overweight individuals, psychological job demands, skill discretion, and work-family conflict were positively associated with binge eating (SC = 0.099, 95%CI = 0.005–0.193; SC = 0.175, 95%CI = 0.062–0.288; and SC = 0.141, 95%CI = 0.077–0.206, respectively). Also, work-family conflict was observed to be a pathway on the associations of psychological job demands and decision authority with binge eating (SC = 0.084, 95%CI = 0.045–0.122; and SC =  − 0.008, 95%CI =  − 0.015– − 0.001, respectively).

Conclusions

Work-family conflict partly explains effects of high levels of psychological job demands and low levels of decision authority on binge eating among overweight individuals. Moreover, skill discretion is positively associated with binge eating, regardless of BMI category.
Psychometric comparison of the Persian Salzburg Emotional Eating Scale and Emotional Eater Questionnaire among Iranian adults
Authors: Ghafouri Sahar , Abdollahi Abbas , Suksatan Wanich , Chupradit Supat , Asmundson Aleiia J. N. , Thangavelu Lakshmi
Published: February 2022

Background

The Salzburg Emotional Eating Scale (SEES) and the Emotional Eater Questionnaire (EEQ) are self-reported measures developed to evaluate emotional eating in adults in Western countries. To date, the psychometric properties of the SEES and the EEQ have not been studied among Iranian adults. The aim of the current study is to translate the SEES and the EEQ from English to Persian and examine the psychometric properties of the SEES and EEQ.

Method

The sample of this study comprised of 489 Iranian adults who completed the SEES and the EEQ questionnaires online.

Results

Findings of face, content, and construct validity tests confirmed that the SEES and the EEQ had acceptable validity and appropriate reliability. The results from confirmatory factor analysis showed acceptable goodness-of-fit indices for two measures.

Conclusion

Results of Average Variance Extracted, Construct Reliability, and goodness-of-fit indices showed that the SEES was better for evaluating emotional eating among Iranian adults than the EEQ.
Bcl-xL DNAzymes promote radiosensitivity and chemosensitivity in colorectal cancer cells via enhancing apoptosis
Authors: Yu Zhen , Guo Jun , Meng Tao , Ge Lei , Liu Lin , Wang Haijiang , Yang Xinhui
Published: February 2022

Background

RNA-cleaving deoxyribozymes (DNAzymes) are catalytic deoxyribonucleic acid molecules that have become a promising new class of gene suppressors by binding and cleaving target mRNA. This study investigated whether DNAzymes targeting Bcl-xL enhanced the effectiveness of radiotherapy and chemotherapy in colorectal cancer (CRC) cells.

Methods

Two types of CRC cells, SW480 and SW837, were transfected with five DNAzymes. Cell viability, Bcl-xL expression and apoptosis were examined. SW480 xenograft model was used to examine the combined effects of Bcl-xL DNAzymes and 5-FU (or X-rays) on tumor growth.

Results

Three Bcl-xL DNAzymes, DT882, DT883, and DT884 were identified to be effective in suppressing Bcl-xL expression and causing cell apoptosis. Furthermore, DT882 combined with 5-FU or radiotherapy addictively promoted cell apoptosis and significantly inhibited the growth of SW480 xenografts in vivo.

Conclusions

These results suggest that Bcl-xL DNAzymes can enhance the radiosensitivity and chemosensitivity in CRC cells via inducing apoptosis.
Translation, cross-cultural adaptation and validation of the Mandarin version of the BDDQ-AS for rhinoplasty patients
Authors: Wijaya Wilson A. , Liu Yu , Zhou Min , Qing Yong , Li Zhengyong
Published: February 2022

Background

The BDDQ-AS (Body Dysmorphic Disorder Questionnaire—Aesthetic Surgery) is a simple and reliable patient-reported outcome measure. It can be used as a screening tool for body dysmorphic disorder (BDD) in patients undergoing aesthetic rhinoplasty. The aim of this study was to translate and culturally adapt the Mandarin version of the BDDQ-AS (M-BDDQ-AS) and evaluate its selected psychometric validation in patients after rhinoplasty.

Method

According to international guidelines, the BDDQ-AS questionnaire was translated from English to Mandarin. Twenty Mandarin-speaking rhinoplasty patients were interviewed in order to evaluate the understandability and acceptability of the translation and produce a final version. It was then administered to 137 patients with a mean age of 38.75 ± 6.24 years. Psychometric validation were evaluated using reliability (internal consistency, test–retest reliability) and item-reponse theory (IRT) test.

Result

High internal consistency of 0.823 was found using Cronbach's α coefficient. Reliability of the M-BDDQ-AS resulted in Intraclass Correlation Coefficient (ICC) = 0.863. Besides, based on IRT analysis, the discrimination abilities of all the items were good (over 2.0), and their difficulty estimates were reasonable.

Conclusion

The M-BDDQ-AS is a reliable and valid self-reported questionnaire that can be used in rhinoplasty patients. The very good psychometric validation of the M-BDDQ-AS indicates that it can be used in clinical practice and scientific research.

Graphical Abstract
The role of structured inquiry, open inquiry, and epistemological beliefs in developing secondary students’ scientific and mathematical literacies
Authors: Wang Hsin-Hui , Hong Zuway-R , She Hsiao-Ching , Smith Thomas J. , Fielding Jill , Lin Huann-shyang
Published: February 2022

Background

The recommendation from national documents and reports to promote inquiry-related science activities has not been supported by recent studies, which have found the overall frequency of inquiry activities to be negatively associated with student learning outcomes. This study was inspired by such conflicting reports and aimed to clarify the associations of science-specific, inquiry-related activities and epistemological beliefs with students’ mathematical and scientific literacies.

Results

A secondary analysis of the database from the Programme for International Student Assessment 2015 of Australia (N1 = 14,530) and Taiwan (N2 = 7708) utilizing structural equation modelling revealed that these two countries exhibited similar data patterns. Results suggested that open-inquiry activities (such as debating and planning experiments) had a negative relationship with secondary students’ mathematical and scientific literacies. Structured inquiry learning (such as students explaining their ideas and teacher explaining how an idea can be applied to different phenomena) and epistemological beliefs about science were significant and positive predictors of student mathematical and scientific literacy performance.

Conclusions

The current study further highlights and provides empirical evidence that the teacher’s role in structured inquiry (especially pertaining to the relevance and applicability of these ideas) appears to be essential to the development of student literacy. Educational implications and recommendations are discussed.
What validation tests can be done by the clinical medical physicist while waiting for the standardization of quantitative SPECT/CT imaging?
Authors: Piwowarska-Bilska Hanna , Supińska Aleksandra , Birkenfeld Bożena
Published: February 2022

Objective

The aim of the study was to assess the accuracy of quantitative SPECT/CT imaging in a clinical setting and to compare test results from two nuclear medicine departments.

Methods

Phantom studies were carried out with two gamma cameras manufactured by GE Healthcare: Discovery NM/CT 670 and NM/CT 850, used in two nuclear medicine departments. The data were collected using a cylindrical uniform phantom and a NEMA/IEC NU2 Body Phantom, filled with 99mTc-pertechnetate.

Results

The convergence of activity concentration recovery was validated for the two gamma cameras operating in two medical centers using the cylindrical uniform phantom. The comparison of results revealed a 5% difference in the background calibration factor Bg. cal; 6% difference in COV, and a 0.6% difference in total activity deviation ∆Atot. Recovery coefficients (RCmax) for activity concentration in spheres of the NEMA/IEC NU2 Body Phantom were measured for different image reconstruction techniques. RCmax was in the range of 0.2–0.4 for the smallest sphere (ϕ 10 mm), and 1.3–1.4 for the largest sphere (ϕ 37 mm). Conversion factors for SUVmax and SUVmean for the gamma camera systems used were 0.99 and 1.13, respectively.

Conclusions

(1) Measurements taken in our study confirmed the clinical suitability of 5 parameters of image quality (Bg. cal—background calibration factor, ∆Atot—total activity deviation, COV—coefficient of variation used for image noise assessment, QH—hot contrast, AM—accuracy of measurements, or RC—recovery coefficient) for the validation of SPECT/CT system performance in terms of correct quantitative acquisitions of images. (2) This work shows that absolute SPECT/CT quantification is achievable in clinical nuclear medicine centers. Results variation of quantitative analyses between centers is mainly related to the use of different reconstruction methods. (3) It is necessary to standardize the technique of measuring the SUV conversion factor obtained with different SPECT/CT scanners.
A novel semiautomated method for background activity and biological tumour volume definition to improve standardisation of 18F-FET PET imaging in glioblastoma
Authors: Brighi Caterina , Puttick Simon , Li Shenpeng , Keall Paul , Neville Katherine , Waddington David , Bourgeat Pierrick , Gillman Ashley , Fay Michael
Published: February 2022

Background

Multicentre clinical trials evaluating the role of 18F-Fluoroethyl-l-tyrosine (18F-FET) PET as a diagnostic biomarker in glioma management have highlighted a need for standardised methods of data analysis. 18F-FET uptake normalised against background in the contralateral brain is a standard imaging technique to delineate the biological tumour volume (BTV). Quantitative analysis of 18F-FET PET images requires a consistent and robust background activity. Currently, defining background activity involves the manual selection of an arbitrary region of interest, a process that is subject to large variability. This study aims to eliminate methodological errors in background activity definition through the introduction of a semiautomated method for region of interest selection. A new method for background activity definition, involving the semiautomated generation of mirror-image (MI) reference regions, was compared with the current state-of-the-art method, involving manually drawing crescent-shape (gCS) reference regions. The MI and gCS methods were tested by measuring values of background activity and resulting BTV of 18F-FET PET scans of ten patients with recurrent glioblastoma multiforme generated from inputs provided by seven readers. To assess intra-reader variability, each scan was evaluated six times by each reader. Intra- and inter-reader variability in background activity and BTV definition was assessed by means of coefficient of variation.

Results

Compared to the gCS method, the MI method showed significantly lower intra- and inter-reader variability both in background activity and in BTV definition.

Conclusions

The proposed semiautomated MI method minimises intra- and inter-reader variability, providing a valuable approach for standardisation of 18F-FET PET quantitative parameters.

Trial registration ANZCTR, ACTRN12618001346268. Registered 9 August 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374253
Development of tricot warp knitted fabrics with moisture management for casual shirt
Authors: Chen Qing , Feng Jie , Ma Bomou , Fu Bailu , Zheng Rong , Fan Jintu
Published: February 2022

Warp knitted mesh fabric was usually applied to sportswear due to good air transmission, but without multilayer structure and one-way transport property. In order to solve this problem, the miss-lapping structure was applied to examine the possibility to fabricate multilayer and improve water transport in warp knitting structure. Besides, the effect of thread type and warp density on comfort properties were also exploited to enhance the moisture management. The moisture management test, water vapor permeability and air permeability were examined. Long float at the back side in structure I formed by miss-lapping could improve liquid transport and air permeability, but slightly reduce water vapor permeability. With proper density, there existed the optimal one-way transport capacity and overall moisture management. Warp density in 20 cpc was an optimal parameter of knitting process. Taking advantage of miss-lapping, sample 5 where polypropylene was partly threaded on GB1 provided best moisture management, water vapor permeability and air permeability.
Solitary pulmonary metastasis after meningioma surgery of the head: a case report
Authors: Utsumi Takahiro , Saito Tomohito , Ishida Mitsuaki , Maru Natsumi , Matsui Hiroshi , Taniguchi Yohei , Hino Haruaki , Murakawa Tomohiro
Published: February 2022

Background

Meningioma is the most common type of benign primary brain tumor that is rarely associated with distant metastasis. No established treatment strategy for metastatic meningiomas exists to date. Herein, we report a case of solitary pulmonary metastasis of meningioma detected 2 years after neurosurgical resection of the primary tumor.

Case presentation

A 75-year-old male patient underwent neurosurgical resection of a convexity meningioma (World Health Organization grade II atypical meningioma), followed by postoperative radiotherapy for the residual tumor. Two postoperative years later, a solitary 10-mm pulmonary nodule in the left lower lung lobe was detected on chest computed tomography. The patient underwent video-assisted thoracoscopic left lower lobectomy for suspected pulmonary metastasis of meningioma. The pathological diagnosis was solitary pulmonary metastasis of meningioma. No sign of further recurrence was noted at 8 months postoperatively.

Conclusions

We present a rare and unique surgical case of solitary pulmonary metastasis of meningioma. Further investigation is necessary to establish the standardized treatment strategy for metastatic meningiomas.
Co-production: a kind revolution
Authors: Staniszewska Sophie , Hickey Gary , Coutts Pippa , Thurman Ben , Coldham Tina
Published: February 2022

Carnegie UK (CUK) and National Institute for Health Research (NIHR) INVOLVE held a meeting on the co-production of research, how we work together on equal terms. We brought together public contributors and individuals from organisations focused on research. We wanted to discuss how co-production could work in research, how it could be seen as business as usual, and to think through the barriers that stop us from working together, as well as the things that can help us move forward. While we agreed that the idea of working together is important, we recognised there are still many challenges to co-production being seen as a normal activity in research and the development of a ‘business case’ to persuade others is still needed. We also considered the wider civic roles that Universities are adopting as important in helping co-production become normal practice. Discussion focused on issues such as power and how it works in research. We recognised that we also need to create the right conditions for co-production, changing research culture so it becomes kinder, with a focus on the development of relationships. We also recognised the need for enough time for honest, high quality conversations between patients, public contributors and researchers that take account of how power works in research. Co-production was seen as a societal ‘good,’ helping us live well by undertaking research together that benefits the health of the public. We also identified a range of ways we could move co-production forward, recognising we are on a journey and that current societal changes brought about by Covid-19 may result in us being more radical in how we rethink the ways we want to work in research.
Studies on biological control potential of Steinernema abbasi CS-39 against Helicoverpa armigera (Hub.) (Lepidoptera: Noctuidae) by adopting the regression probit model
Authors: Srivastava Shreyansh , Heena  , Chaubey Ashok Kumar
Published: February 2022

Background

In India, application of entomopathogenic nematodes (EPNs) as a bio-agent against insect pests was known since 5–6 decades with the application of the exotic species Steinernema carpocapsae (DD-136 Strain). EPNs have a strong potential to control the soil-borne insect pests. In the present study isolated strain was identified as Steinernema abbasi and docketed as CS-39. The efficacy of the isolated strain was tested against the American bollworm, Helicoverpa armigera (Hub.) (Lepidoptera: Noctuidae).

Results

Laboratory bioassay revealed that the median lethal concentration (LC50 = 83.21 IJs) of the S. abbasi isolate CS-39 was quite sufficient to achieve 100% mortality after 24 h of exposure. Mean mortality percentage was estimated > 75% at all concentrations, i.e., 25, 50, 100 and 200 IJs/larva, and 100% mortality was achieved at 200 IJs/larva after 24 h of concentration exposure. Positive relationship was found at every concentration of exposure and % mortality of the insect pest (H. armigera) after 36 (p < 0.01) and 48 h of exposure (p < 0.02).

Conclusions

Steinernema abbasi isolate CS-39 found to be highly virulent to H. armigera. As the result urged, 200 IJs / larva showed 100% mortality at 36 h, whereas 100 IJs / larva showed 100% mortality at 60 h. Difference in time duration might be because of action of bacterial symbionts which were the main precursor of pathogenicity. Extensive study of secondary metabolites of the bacterial symbionts may extend the present study to the new dimension.
Risk factors of school bullying and its relationship with psychiatric comorbidities: a literature review
Authors: Ahmed Gellan K. , Metwaly Nabil A. , Elbeh Khaled , Galal Marwa Salah , Shaaban Islam
Published: February 2022

Background

School bullying is described as violence to other people. It is perpetrated at schools or other activities when the power of a student or a group of students is used to injure others or other groups.

Main body

The prevalence of school bullying is varied from one country to another. There are many types of bullying, such as physical, verbal, social relations, psychological, sexual, and cyber-bullying. Many risk factors could affect school bullying, especially individual, peer and parent factors. Researches found that adults who had school bullying are more vulnerable to develop future psychiatric disorders.

Conclusions

School bullying is one of the crucial problems among pupils. The wide range of the prevalence of school bullying may be due to different methodologies and the presence of many risk factors. It is recommended to have long-term researches about the student with bullying behavior. Also, prevention programs are required to increase knowledge and early detection of affected students to prevent future psychiatric disorders.
Reversed ophthalmic artery flow in patients with acute ischemic stroke and ipsilateral significant extracranial carotid artery stenosis, and its effect in functional outcome
Authors: Fahmy Yosra , Abo El Naga Yousry , Hazzou Ahmed , Helmy Shahinaz
Published: February 2022

Background

Cerebral hemodynamics and collateral circulation have an important role in determining stroke outcome, while the role of primary collateral is well known, the role of secondary collaterals including ophthalmic artery flow is still controversial. Our aim was to evaluate the flow of ophthalmic artery in patients with acute ischemic stroke and significant extracranial carotid stenosis and assess its role on the functional outcome. Thirty patients with acute ischemic stroke and extracranial carotid stenosis were included from Ain Shams University hospitals, color coded duplex was used to assess extracranial carotid arteries, ophthalmic artery was assessed by transcranial color-coded duplex. According to ophthalmic artery flow patients were divided into two groups, one with forward and other with reversed flow. Modified Rankin Scale (MRS) after 3 months was compared between the two groups

Results

Reversed ophthalmic artery flow (ROAF) was seen among 10 (33.33%) patients. After 3 month MRS was better in ROAF group (1.5 ± 1.958) than forward ophthalmic artery flow (FOAF) group (2.1 ± 1.954) but with no statistical difference (p value 0.398); furthermore, the difference between MRS after 3 months and discharge was significant in ROAF group (p value 0.042).

Conclusions

Transcranial duplex is a noninvasive, safe method in determining ophthalmic artery flow; furthermore, ROAF could help in better stroke outcome.
Management of asthma patients during the COVID-19 pandemic: pathophysiological considerations to address the challenges
Authors: Tabassum Tahani , Rahman Ahsab , Araf Yusha , Ullah Md. Asad , Hosen Mohammad Jakir
Published: February 2022

Background

The coronavirus disease 2019 (COVID-19) has become a serious global health issue, especially for people with pre-existing health conditions. Patients dealing with asthma are presumed to be at higher risk as COVID-19 may cause severe respiratory distress.

Main body

From the initial stage of the pandemic, several clinical trials and studies have assessed the association between COVID-19 and asthma; however, no significant association was reported. This may be due to the fact that most of the asthma cases remained undiagnosed and overlapping respiratory features make it difficult to differentiate between these two diseases. The pathomechanism of the conditions and the immune response generated in response to the conditions suggest that the presence of any of the conditions is very likely to influence the presence or severity of the other condition. So far, no specific treatments are known for COVID-19; however, the use of plasma therapy and broad-spectrum antiviral drugs during the initial phase of the pandemic and widespread vaccination during the latter phase has given positive outcomes in reducing COVID-19 cases as well as disease severity.

Short conclusion

Taking asthma as an increased risk factor for COVID-19 morbidity, this article aims to provide comprehensive insights into the risk and proper management of asthma patients during this COVID-19 pandemic. The common medications of asthma patients suppress their respiratory immune response that might facilitate cytokine storm in COVID-19 patients. Similarly, there are risks of viral-induced asthma exacerbations. Besides, different social issues such as shortage of medicines, SDOH, and delayed clinical trials put asthma patients through inconvenience. The primary focus at this point should be to reduce probable asthma attacks and severity to prevent hospitalization of asthma patients. Moreover, for better management of asthma patients maintaining an asthma action plan and healthy lifestyle, ensuring a nutritious diet, and developing self-management interventions can play a crucial role.
Opioid-free anesthesia in oncologic surgery: the rules of the game
Authors: De Cassai Alessandro , Geraldini Federico , Tulgar Serkan , Ahiskalioglu Ali , Mariano Edward R. , Dost Burhan , Fusco Pierfrancesco , Petroni Gian Marco , Costa Fabio , Navalesi Paolo
Published: February 2022

Background

Opioids are frequently used in the postoperative period due to their analgesic properties. While these drugs reduce nociceptive somatic, visceral, and neuropathic pain, they may also lead to undesirable effects such as respiratory depression, urinary retention, nausea and vomiting, constipation, itching, opioid-induced hyperalgesia, tolerance, addiction, and immune system disorders. Anesthesiologists are in the critical position of finding balance between using opioids when they are necessary and implementing opioid-sparing strategies to avoid the known harmful effects. This article aims to give an overview of opioid-free anesthesia.

Main body

This paper presents an overview of opioid-free anesthesia and opioid-sparing anesthetic techniques. Pharmacological and non-pharmacological strategies are discussed, highlighting the possible advantages and drawbacks of each approach.

Conclusions

Choosing the best anesthetic protocol for a patient undergoing cancer surgery is not an easy task and the available literature provides no definitive answers. In our opinion, opioid-sparing strategies should always be implemented in routine practice and opioid-free anesthesia should be considered whenever possible. Non-pharmacological strategies such as patient education, while generally underrepresented in scientific literature, may warrant consideration in clinical practice.
Extracorporeal Membrane Oxygenation for Pregnant and Postpartum Patients
Authors: Wong Michael J. , Bharadwaj Shobana , Galey Jessica L. , Lankford Allison S. , Galvagno Samuel , Kodali Bhavani Shankar
Published: February 2022

Extracorporeal membrane oxygenation (ECMO) has seen increasing use for critically ill pregnant and postpartum patients over the past decade. Growing experience continues to demonstrate the feasibility of ECMO in obstetric patients and attest to its favorable outcomes. However, the interaction of pregnancy physiology with ECMO life support requires careful planning and adaptation for success. Additionally, the maintenance of fetal oxygenation and perfusion is essential for safely continuing pregnancy during ECMO support. This review summarizes the considerations for use of ECMO in obstetric patients and how to address these concerns.
Thyroid Disease Prediction Using XGBoost Algorithms
Authors: Sankar S. , Potti Anupama , Chandrika G. Naga , Ramasubbareddy Somula
Published: February 2022

Nowadays, thyroid disease is increasing rapidly all over the world. Significantly, one out of ten people is affected by the thyroid in India. In recent years, many researchers have done various research works on thyroid disease detection. Therefore, the early stage of thyroid disease prediction is difficult to protect and avoid the worst health condition. In this regard, the machine learning plays a crucial role to detect the disease accurately. We consider the UC Irvin knowledge discovery dataset. So, this paper proposes the XGBoost algorithm to predict thyroid disease accurately. The best features are selected using XGBoost function. The proposed XGBoost algorithm’s efficacy is compared to decision tree, logistic regression, k-Nearest Neighbor (kNN) methods. The performance of all four algorithms is compared and analyzed. It is observed that the accuracy of the XGBoost algorithm increases by 2% than the KNN algorithm.
Futuristic IoT based Smart Precision Agriculture: Brief Analysis
Authors: Swamidason Iwin Thanakumar Joseph , Pandiyarajan Shanthini , Velswamy Karunakaran , Jancy P. Leela
Published: February 2022

Agriculture is considered as the backbone of any nation across the globe. With the advent of modern technologies, smart tools and techniques are used in the agriculture/farming to build on the quantity as well as quality of the agriculture production to feed the basic necessity of the humans. Smart technology such as Internet of Things play a vital role in monitoring and analyzing various environmental parameters such as water level, humidity, soil moisture, air quality, UV level, rain etc. which are highly essential to ensure the fruitful yield of any nutritious crops. In this research article, precision agriculture concepts are investigated widely with the focus of improving the productivity level and also the effective utilization of resources with the minimal cost while compared with the conventional methodologies.
The first study on seroprevalence and risk factors for zoonotic transmission of ovine and caprine brucellosis in the Province of Bam, Burkina Faso
Authors: Tialla Dieudonné
Published: February 2022

Background and Aim: Brucellosis is a bacterial disease notorious for its ability to infect a wide range of domestic and wildlife animals, as well as humans. This study aimed to determine the seroprevalence of ovine and caprine brucellosis and the associated risk factors in the Province of Bam in Burkina Faso.

Materials and Methods: The individual serological status of 300 unvaccinated sheep and 300 unvaccinated goats was determined by Rose Bengal and indirect enzyme-linked immunosorbent assay (iELISA) serological tests used in parallel. The frequency of behaviors conferring risk of developing this zoonotic disease was determined through two epidemiological questionnaires, which identified known risk factors for the transmission of brucellosis between animals and humans.

Results: Individual seroprevalence was estimated at 6.0% (18/300) in sheep and 4.3% (13/300) in goats. The "herd" prevalence of brucellosis was estimated at 60% in sheep while 40% in goats. Positivity in the iELISA serological test was significantly associated with age, sex, and husbandry system in sheep and goats.

Conclusion: These results indicate that Brucella melitensis circulates in sheep and goat farms in the Province of Bam in Burkina Faso. As B. melitensis is highly pathogenic to humans, adequate measures must be taken to protect the population against this zoonotic disease.
Trabajo sexual y pandemia de la COVID-19: salud sexual y mental de una muestra de trabajadoras sexuales de Colombia
Authors:   Fundación Universitaria Konrad Lorenz, Bogotá, Colombia, Rebellón-Pinillos Paola Andrea , Gómez-Lugo Mayra ,   Fundación Universitaria Konrad Lorenz, Bogotá, Colombia
Published: February 2022

Introducción: En diversos países las mujeres trabajadoras sexuales han sido estigmatizadas y discriminadas, lo que causa en ellas problemas de salud mental y sexual. No obstante, se desconoce cómo la pandemia por COVID-19 y el distanciamiento social han impactado en su salud. El objetivo de la presente investigación, de tipo descriptivo, fue evaluar factores psicosociales, la salud mental, las estrategias para prácticas sexuales con protección, las actitudes hacia el VIH y la sexualidad durante el periodo de confinamiento. Método: Participaron 98 mujeres trabajadoras sexuales de tres sectores de la Bogotá, quienes respondieron a escalas psicométricas en salud mental y sexual. Resultados: Más del 60 % de las participantes indican sentir abandono estatal, baja clientela y poco o ningún ingreso económico; afectación emocional, una tendencia a presentar actitudes negativas frente a la sexualidad, actitudes favorables hacia el uso del condón, las pruebas de detección del VIH y una alta tendencia a emplear estrategias de persuasión cuando el cliente se niega a usar protección. Conclusiones: Las problemáticas en salud mental y sexual se mantienen e intensifican en pandemia para las trabajadoras sexuales en Colombia, lo cual sigue siendo un reto a escala nacional que requiere una intervención eficaz y efectiva desde lo económico y psicosocial.
Evaluating query languages and systems for high-energy physics data
Authors: Graur Dan , Müller Ingo , Proffitt Mason , Fourny Ghislain , Watts Gordon T. , Alonso Gustavo
Published: February 2022

In the domain of high-energy physics (HEP), query languages in general and SQL in particular have found limited acceptance. This is surprising since HEP data analysis matches the SQL model well: the data is fully structured and queried using mostly standard operators. To gain insights on why this is the case, we perform a comprehensive analysis of six diverse, general-purpose data processing platforms using an HEP benchmark. The result of the evaluation is an interesting and rather complex picture of existing solutions: Their query languages vary greatly in how natural and concise HEP query patterns can be expressed. Furthermore, most of them are also between one and two orders of magnitude slower than the domain-specific system used by particle physicists today. These observations suggest that, while database systems and their query languages are
in principle
viable tools for HEP, significant work remains to make them relevant to HEP researchers.
Distributed hop-constrained s-t simple path enumeration at billion scale
Authors: Hao Kongzhang , Yuan Long , Zhang Wenjie
Published: February 2022

Hop-constrained
s-t
simple path (HC-s-t path) enumeration is a fundamental problem in graph analysis and has received considerable attention recently. Straightforward distributed solutions are inefficient and suffer from poor scalabiltiy when addressing this problem in billion-scale graphs due to the disability of pruning fruitless exploration or huge memory consumption. Motivated by this, in this paper, we aim to devise an efficient and scalable distributed algorithm to enumerate the HC-s-t paths in billion-scale graphs. We first propose a new hybrid search paradigm tailored for HC-s-t path enumeration. Based on the new search paradigm, we devise a distributed enumeration algorithm following the divide-and-conquer strategy. The algorithm can not only prune fruitless exploration, but also well bound the memory consumption with high parallelism. We also devise an effective workload balance mechanism that is automatically triggered by the idle machines to handle skewed workloads. Moreover, we explore the bidirectional search strategy to further improve enumeration efficiency. The experiment results demonstrate the efficiency of our proposed algorithm.
METRO
Authors: Cui Yue , Zheng Kai , Cui Dingshan , Xie Jiandong , Deng Liwei , Huang Feiteng , Zhou Xiaofang
Published: February 2022

Multivariate time series forecasting has been drawing increasing attention due to its prevalent applications. It has been commonly assumed that leveraging latent dependencies between pairs of variables can enhance prediction accuracy. However, most existing methods suffer from static variable relevance modeling and ignorance of correlation between temporal scales, thereby failing to fully retain the dynamic and periodic interdependencies among variables, which are vital for long- and short-term forecasting. In this paper, we propose METRO, a generic framework with multi-scale temporal graphs neural networks, which models the dynamic and cross-scale variable correlations simultaneously. By representing the multivariate time series as a series of temporal graphs, both intra- and inter-step correlations can be well preserved via message-passing and node embedding update. To enable information propagation across temporal scales, we design a novel sampling strategy to align specific steps between higher and lower scales and fuse the cross-scale information efficiently. Moreover, we provide a modular interpretation of existing GNN-based time series forecasting works as specific instances under our framework. Extensive experiments conducted on four benchmark datasets demonstrate the effectiveness and efficiency of our approach. METRO has been successfully deployed onto the time series analytics platform of Huawei Cloud, where a one-month online test demonstrated that up to 20% relative improvement over state-of-the-art models w.r.t. RSE can be achieved.
LargeEA
Authors: Ge Congcong , Liu Xiaoze , Chen Lu , Gao Yunjun , Zheng Baihua
Published: February 2022

Entity alignment (EA) aims to find equivalent entities in different knowledge graphs (KGs). Current EA approaches suffer from scalability issues, limiting their usage in real-world EA scenarios. To tackle this challenge, we propose LargeEA to align entities between large-scale KGs. LargeEA consists of two channels, i.e., structure channel and name channel. For the structure channel, we present METIS-CPS, a memory-saving mini-batch generation strategy, to partition large KGs into smaller mini-batches. LargeEA, designed as a general tool, can adopt any existing EA approach to learn entities' structural features within each mini-batch independently. For the name channel, we first introduce NFF, a name feature fusion method, to capture rich name features of entities without involving any complex training process; we then exploit a name-based data augmentation to generate seed alignment without any human intervention. Such design fits common real-world scenarios much better, as seed alignment is not always available. Finally, LargeEA derives the EA results by fusing the structural features and name features of entities. Since no widely-acknowledged benchmark is available for large-scale EA evaluation, we also develop a large-scale EA benchmark called DBP1M extracted from real-world KGs. Extensive experiments confirm the superiority of LargeEA against state-of-the-art competitors.
Answering regular path queries through exemplars
Authors: Chauhan Komal , Jain Kartik , Ranu Sayan , Bedathur Srikanta , Bagchi Amitabha
Published: February 2022

Regular simple path query (RPQ) is one of the fundamental operators in graph analytics. In an RPQ, the input is a graph, a source node and a regular expression. The goal is to identify all nodes that are connected to the source through a simple path whose label sequence satisfies the given regular expression. The regular expression acts as a formal specification of the search space that is of interest to the user. Although regular expressions have high expressive power, they act as barrier to non-technical users. Furthermore, to fully realize the power of regular expressions, the user must be familiar with the domain of the graph dataset. In this study, we address this bottleneck by bridging RPQs with the
query-by-example
paradigm. More specifically, we ask the user for an exemplar pair that characterizes the paths of interest, and the regular expression is automatically inferred from this exemplar. This novel problem introduces several new challenges. How do we infer the regex? Given that answering RPQs is NP-hard, how do we scale to large graphs? We address these challenges through a unique combination of
Biermann and Feldman's algorithm
with
NFA-guided random walks with restarts.
Extensive experiments on multiple real, million-scale datasets establish that RQuBE is at least 3 orders of magnitude faster than baseline strategies with an average accuracy in excess of 90%.
HET
Authors: Miao Xupeng , Zhang Hailin , Shi Yining , Nie Xiaonan , Yang Zhi , Tao Yangyu , Cui Bin
Published: February 2022

Embedding models have been an effective learning paradigm for high-dimensional data. However, one open issue of embedding models is that their representations (latent factors) often result in large parameter space. We observe that existing distributed training frameworks face a scalability issue of embedding models since updating and retrieving the shared embedding parameters from servers usually dominates the training cycle. In this paper, we propose HET, a new system framework that significantly improves the scalability of huge embedding model training. We embrace skewed popularity distributions of embeddings as a performance opportunity and leverage it to address the communication bottleneck with anembedding cache.To ensure consistency across the caches, we incorporate a new consistency model into HET design, which provides fine-grained consistency guarantees on a per-embedding basis. Compared to previous work that only allows staleness for read operations, HET also utilizes staleness for write operations. Evaluations on six representative tasks show that HET achieves up to 88% embedding communication reductions and up to 20.68×performance speedup over the state-of-the-art baselines.
FINEdex
Authors: Li Pengfei , Hua Yu , Jia Jingnan , Zuo Pengfei
Published: February 2022

Index structures in memory systems become important to improve the entire system performance. The promising learned indexes leverage deep-learning models to complement existing index structures and obtain significant performance improvements. Existing schemes rely on a delta-buffer to support the scalability, which however incurs high overheads when a large number of data are inserted, due to the needs of checking both learned indexes and extra delta-buffer. The practical system performance also decreases since the shared delta-buffer quickly becomes large and requires frequent retraining due to high data dependency. To address the problems of limited scalability and frequent retraining, we propose a FINE-grained learned index scheme with high scalability, called FINEdex, which constructs independent models with a flattened data structure (i.e., the data arrays with low data dependency) under the trained data array to concurrently process the requests with low overheads. By further efficiently exploring and exploiting the characteristics of the workloads, FINEdex processes the new requests in-place with the support of non-blocking retraining, hence adapting to the new distributions without blocking the systems. We evaluate FINEdex via YCSB and real-world datasets, and extensive experimental results demonstrate that FINEdex improves the performance respectively by up to 1.8× and 2.5× than state-of-the-art XIndex and Masstree. We have released the open-source codes of FINEdex for public use in GitHub.