bluuebunny/crossref_metadata_2025 huggingface dataset:
Overall Complications Following Robotic Heller Myotomy Are Lower Compared With Laparoscopy
Authors: Chacko Joel , Leeds Steven G. , Aladegbami Bola G. , Ogola Gerald O. , Ward Marc A.
Published: March 2022

Background:

The use of robotics in foregut surgery has become more prevalent in the United States over the last 10 years. We sought to find the differences in the clinical outcomes of robotic surgery compared with traditional laparoscopy in patients undergoing Heller myotomy.

Materials and Methods:

A retrospective population-based analysis was performed using the National Inpatient Sample (NIS) database for the span of 2010 to 2015. All patients who underwent laparoscopic or robotic Heller myotomy were included. Weighted multivariable random intercept linear and logistic regression models were used to assess the impact of robotic surgery on patient outcomes compared with laparoscopy.

Results:

There was a total of 11,562 patients with a median age of 54.2 years. Robotic Heller myotomy has a significantly decreased risk of overall complications for all centers (odds ratio=0.46; 95% confidence interval=0.29, 0.74). A subset analysis was performed looking specifically at high-volume centers (>20 operations per year), and overall complications remained lower in the robotic group. However, in high-volume centers, the robotic cohort did have a higher rate of esophageal perforation (2.7% vs. 0.8%, P<0.001). There was a higher length of stay in the laparoscopic Heller cohort (3.0 vs. 2.6 d, P=0.06) but higher overall charges in the robotic Heller cohort ($42,900 vs. $34,300, P=0.03).

Conclusions:

Robotic Heller myotomy is associated with lower overall complications and improved outcomes compared with laparoscopic Heller myotomy, even in high-volume centers. Robotic Heller myotomy is associated with a higher rate of esophageal perforations in high-volume centers despite the reduction in overall complications.
Zig Maneuver in Total Extraperitoneal Inguinal Hernia Repair
Authors: Kurtulus Idris , Culcu Osman D. , Degerli Mahmut S.
Published: March 2022

Background:

The difficulties in the hernia sac dissection in repairing large inguinal hernias with the endoscopic total extraperitoneal (TEP) technique prolong the operation and increase the risk of injury. This study investigates the effectiveness of the Zig maneuver (ligation of the hernia sac at the deep inguinal ring) in TEP in male patients with L3 inguinal hernia by European Hernia Society classification.

Materials and Methods:

A total of 224 male patients with L3 inguinal hernia who underwent laparoscopic TEP surgery in 2018 and 2019 were retrospectively screened and included in the study. The patients were divided into 2 groups as Zig group (n=99) and the non-Zig group (n=125), depending on whether the Zig maneuver was performed during TEP application.

Results:

The mean patient age was 45.49 for the non-Zig group and 47.12 for the Zig group. The median operative time was 50 minutes in the non-Zig group and 43 minutes in the Zig group (P<0.005). The median value of the postoperative first 24 hours pain score was 3 in the non-Zig group and 2 in the Zig group (P=0.033). Scrotal edema was 7.2% in the non-Zig group and 1% in the Zig group (P=0.023). According to logistic regression analysis, the Zig maneuver reduced the probability of scrotal edema by 87% in almost the entire population (odds ratio=0.130, 95% confidence interval: 0.016-1.047). There was no statistically significant difference between the groups in terms of early and late recurrence.

Conclusions:

Zig maneuver shortened the operative time and significantly reduced the feeling of pain in the first 24 hours postoperatively in male patients with indirect L3 hernia who underwent endoscopic TEP. It also significantly reduced the likelihood of scrotal edema in almost the entire population. As a result, the Zig maneuver is an effective method that could be applied during endoscopic TEP.
Unusual SARS-CoV-2 intrahost diversity reveals lineage superinfection
Authors: Dezordi Filipe Zimmer , Resende Paola Cristina , Naveca Felipe Gomes , do Nascimento Valdinete Alves , de Souza Victor Costa , Dias Paixão Anna Carolina , Appolinario Luciana , Lopes Renata Serrano , da Fonseca Mendonça Ana Carolina , Barreto da Rocha Alice Sampaio , Martins Venas Taina Moreira , Pereira Elisa Cavalcante , Paiva Marcelo Henrique Santos , Docena Cassia , Bezerra Matheus Filgueira , Machado Laís Ceschini , Salvato Richard Steiner , Gregianini Tatiana Schäffer , Martins Leticia Garay , Pereira Felicidade Mota , Rovaris Darcita Buerger , Fernandes Sandra Bianchini , Ribeiro-Rodrigues Rodrigo , Costa Thais Oliveira , Sousa Joaquim Cesar , Miyajima Fabio , Delatorre Edson , Gräf Tiago , Bello Gonzalo , Siqueira Marilda Mendonça , Wallau Gabriel Luz
Published: March 2022

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has infected almost 200 million people worldwide by July 2021 and the pandemic has been characterized by infection waves of viral lineages showing distinct fitness profiles. The simultaneous infection of a single individual by two distinct SARS-CoV-2 lineages may impact COVID-19 disease progression and provides a window of opportunity for viral recombination and the emergence of new lineages with differential phenotype. Several hundred SARS-CoV-2 lineages are currently well phylogenetically defined, but two main factors have precluded major coinfection/codetection and recombination analysis thus far: (i) the low diversity of SARS-CoV-2 lineages during the first year of the pandemic, which limited the identification of lineage defining mutations necessary to distinguish coinfecting/recombining viral lineages; and the (ii) limited availability of raw sequencing data where abundance and distribution of intrasample/intrahost variability can be accessed. Here, we assembled a large sequencing dataset from Brazilian samples covering a period of 18 May 2020 to 30 April 2021 and probed it for unexpected patterns of high intrasample/intrahost variability. This approach enabled us to detect nine cases of SARS-CoV-2 coinfection with well characterized lineage-defining mutations, representing 0.61 % of all samples investigated. In addition, we matched these SARS-CoV-2 coinfections with spatio-temporal epidemiological data confirming its plausibility with the cocirculating lineages at the timeframe investigated. Our data suggests that coinfection with distinct SARS-CoV-2 lineages is a rare phenomenon, although it is certainly a lower bound estimate considering the difficulty to detect coinfections with very similar SARS-CoV-2 lineages and the low number of samples sequenced from the total number of infections.
Methods for the targeted sequencing and analysis of integrons and their gene cassettes from complex microbial communities
Authors: Ghaly Timothy M. , Penesyan Anahit , Pritchard Alexander , Qi Qin , Rajabal Vaheesan , Tetu Sasha G. , Gillings Michael R.
Published: March 2022

Integrons are microbial genetic elements that can integrate mobile gene cassettes. They are mostly known for spreading antibiotic resistance cassettes among human pathogens. However, beyond clinical settings, gene cassettes encode an extraordinarily diverse range of functions important for bacterial adaptation. The recovery and sequencing of cassettes has promising applications, including: surveillance of clinically important genes, particularly antibiotic resistance determinants; investigating the functional diversity of integron-carrying bacteria; and novel enzyme discovery. Although gene cassettes can be directly recovered using PCR, there are no standardised methods for their amplification and, importantly, for validating sequences as genuine integron gene cassettes. Here, we present reproducible methods for the amplification, sequence processing, and validation of gene cassette amplicons from complex communities. We describe two different PCR assays that either amplify cassettes together with integron integrases, or gene cassettes together within cassette arrays. We compare the performance of Nanopore and Illumina sequencing, and present bioinformatic pipelines that filter sequences to ensure that they represent amplicons from genuine integrons. Using a diverse set of environmental DNAs, we show that our approach can consistently recover thousands of unique cassettes per sample and up to hundreds of different integron integrases. Recovered cassettes confer a wide range of functions, including antibiotic resistance, with as many as 300 resistance cassettes found in a single sample. In particular, we show that class one integrons are collecting and concentrating resistance genes out of the broader diversity of cassette functions. The methods described here can be applied to any environmental or clinical microbiome sample.
A free classified advertising website is a high-risk unregulated source of domestic wild boar, pot-bellied pigs, and their hybrids with domestic swine in Canada: Implications for African Swine Fever Risk Preparedness
Authors: MacDonald Amanda M. , Brook Ryan K.
Published: March 2022

Invasive wild pigs are a global problem and are established in large areas across Canada. Domestic European wild boar were first introduced to Canadian farms in the 1980s, and their escape and intentional release have since led to free-ranging populations, which have expanded rapidly in numbers and range. Wild pigs are associated with widespread damage to crops and natural environments, as well as risks of disease transmission. African Swine Fever (ASF) is a highly contagious viral disease of global concern, that can spread between domestic and free-ranging swine and cause catastrophic economic impacts. As ASF preparedness requires a detailed understanding of the distribution and movements of all pig types, this paper aimed to characterize an unregulated ‘grey’ swine market in Canada to understand risks to domestic swine production and potential contributions to free-ranging wild pig populations. Kijiji.ca is a free Canadian internet classified advertising service, almost exclusively cash-based with no receipts and few, if any, records kept of transactions. We monitored Kijiji for sales of domestic wild boar, pot-bellied pigs, and their hybrids across Canada over two months from April 28 - June 30, 2021. Data was collected from all advertisements, including how the seller labelled pigs’ breed, age, sex, number for sale, sexual intactness, presence of tattoos and/or ear tags, as well as the date and location of the posting. Locations were mapped and compared to the spatial distribution of existing free-ranging wild pigs in Canada to identify areas they were likely to facilitate new populations or potentially supplement and genetically diversify existing populations. We identified 151 advertisements on Kijiji, the most coming from Ontario (34.4%; n = 52) and Alberta (29.1%; n = 44), followed by Saskatchewan (11.3%; n = 17), British Columbia (10.6%; n = 16), Nova Scotia (7.3%; n = 11), New Brunswick (4.0%; n = 6), Manitoba (2.0%; n = 3), Quebec (0.7%; n = 1), and Prince Edward Island (0.7%; n = 1). No listings were observed in Newfoundland and Labrador, or Yukon, Nunavut and Northwest Territories. Overall, 62 (41%) of advertisements were within watersheds with existing wild pigs that may contribute to supplementing additional swine, and 89 (59%) were within watersheds where wild pigs have not yet been identified. African swine fever preparedness should include policies and action to address this unmonitored and unregulated sale of swine in Canada, including ear tags, tattoos, genetic analysis, and mandatory reporting.
MSclassifR: an R Package for Supervised Classification of Mass Spectra with Machine Learning Methods
Authors: Godmer Alexandre , Benzerara Yahia , Varon Emmanuelle , Veziris Nicolas , Druart Karen , Mozet Renaud , Matondo Mariette , Aubry Alexandra , Giai Gianetto Quentin
Published: March 2022

MSclassifR is an R package that has been specifically designed to improve the classification of mass spectra obtained from MALDI-TOF mass spectrometry. It offers a comprehensive range of functions that are focused on processing mass spectra, identifying discriminantm/zvalues, and making accurate predictions. The package introduces innovative algorithms for selecting discriminatingm/zvalues and making predictions. To assess the effectiveness of these methods, extensive tests were conducted using challenging real datasets, including bacterial subspecies of theMycobacterium abscessuscomplex, virulent and avirulent phenotypes ofEscherichia coli, different species of Streptococci and nasal swabs from individuals infected and uninfected with SARS-CoV-2. Additionally, multiple datasets of varying sizes were created from these real datasets to evaluate the robustness of the algorithms. The results demonstrated that the Machine Learning-based pipelines in MSclassifR achieved high levels of accuracy and Kappa values. On an in-house dataset, some pipelines even achieved more than 95% mean accuracy, whereas commercial system only achieved 62% mean accuracy. Certain methods showed greater resilience to changes in dataset sizes when constructing Machine Learning-based pipelines. These simulations also helped determine the minimum sizes of training sets required to obtain reliable results. The package is freely available online, and its open-source nature encourages collaborative development, customization, and fosters innovation within the community focused on improving diagnosis based on MALDI-TOF spectra.

Key points

MSclassifR is a comprehensive R package enabling the construction of data analysis pipelines for the precise classification of mass spectra.

Our R package contains an innovative method for variable selection from random forests, which delivered excellent results on real data.

In-depth analysis of various machine learning-based pipelines using our package allowed us to make conclusions about the optimal m/z selection and prediction methods depending on the size of the training dataset.

Using a publicly available dataset of mass spectra obtained from various MALDI-TOF instruments across different countries, MSclassifR is able to build robust pipelines capable of adapting to different instruments in an automatic way.

When tested on an in-house dataset, MSclassifR pipelines consistently outperformed a commercial software in terms of prediction accuracy.
Adenosine A1R/A3R Agonist AST-004 Reduces Brain Infarction in Mouse and Rat Models of Acute Ischemic Stroke
Authors: Fisher Elizabeth S. , Chen Yanan , Sifuentes Mikaela M. , Stubblefield Jeremy J. , Lozano Damian , Holstein Deborah M. , Ren JingMei , DeRosa Nicholas , Chen Tsung-pei , Nickel Gerard , Liston Theodore E. , Lechleiter James D.
Published: March 2022

Acute ischemic stroke (AIS) is the second leading cause of death globally. No Food and Drug Administration (FDA) approved therapies exist targeting cerebroprotection following stroke. Our group recently reported significant cerebroprotection with the adenosine A1/A3 receptor agonist, AST-004, in a transient stroke model in non-human primates (NHP) and in a preclinical mouse model of traumatic brain injury (TBI). However, the specific receptor pathway activated was only inferred based onin vitrobinding studies. The current study investigated the underlying mechanism of AST-004 cerebroprotection in two independent models of AIS: permanent photothrombotic stroke in mice and transient middle cerebral artery occlusion (MCAO) in rats. AST-004 treatments across a range of doses were cerebroprotective and efficacy could be blocked by A3R antagonism, indicating a mechanism of action that does not require A1R agonism. The high affinity A3R agonist MRS5698 was also cerebroprotective following stroke, but not the A3R agonist Cl-IB-MECA under our experimental conditions. AST-004 efficacy was blocked by the astrocyte specific mitochondrial toxin fluoroacetate, confirming an underlying mechanism of cerebroprotection dependent on astrocyte mitochondrial metabolism. An increase in A3R mRNA levels following stroke suggested an intrinsic cerebroprotective response that was mediated by A3R signaling. Together, these studies confirm certain A3R agonists, such as AST-004, are promising new therapeutics for the treatment of AIS.
Probabilistic Brain Extraction in MR Images via Conditional Generative Adversarial Networks
Authors: Moazami Saeed , Ray Deep , Pelletier Daniel , Oberai Assad A.
Published: March 2022

Brain extraction, which refers to the task of segmenting brain tissue in an MR image of a subject, forms an essential first step for many quantitative neuroimaging applications. These include quantifying grey and white matter volumes, monitoring neurological diseases like multiple sclerosis (MS) and Alzheimer’s disease, and estimating brain atrophy. Over the years several algorithms that automate brain extraction have been proposed. More recently, novel image-to-image deep learning methods have been implemented for this task, and have demonstrated significant gains in accuracy and robustness. However, to our knowledge, none of these algorithms account for the uncertainty that is inherent in brain extraction. Motivated by this, we propose a novel, probabilistic deep learning algorithm for brain extraction that recasts this task as a Bayesian inference problem, and then utilizes a conditional generative adversarial network (cGAN) to solve it. The input to the generator network is an MR image of the head and the output is a collection of images of the brain that are drawn from a probability density conditioned on the input image. These images are used to generate a pixel-wise mean image, which serves as the best guess for an image of the brain, and a pixel-wise standard deviation image, which quantifies the uncertainty in the prediction. We test this algorithm on head MR images of fifty subjects and demonstrate that it is more accurate than a commonly used brain extraction tool, and that its performance compares well with the current state of the art in deep learning algorithms. We also demonstrate the utility of the estimates of uncertainty generated by the algorithm.
Detecting Patient Position Using Bed-Reaction Forces and Monitoring Skin-Bed Interface Forces for Pressure Injury Prevention and Management
Authors: Pupic Nikola , Gabison Sharon , Evans Gary , Fernie Geoff , Dolatabadi Elham , Dutta Tilak
Published: March 2022

Pressure injuries are largely preventable, yet they affect one in four Canadians across all healthcare settings. A key best practice to prevent and treat pressure injuries is to minimize prolonged tissue deformation by ensuring at-risk individuals are repositioned regularly (typically every 2 hours). However, adherence to repositioning is poor in clinical settings and expected to be even worse in homecare settings.

Our team has designed a position detection system for home use that uses machine learning approaches to predict a patient’s position in bed using data from load cells under the bed legs. The system predicts the patient’s position as one of three position categories: left-side lying, right-side lying, or supine. The objectives of this project were to: i) determine if measuring ground truth patient position with an inertial measurement unit can improve our system accuracy (predicting left-side lying, right-side lying, or supine) ii) to determine the range of transverse pelvis angles (TPA) that fully offloaded each of the great trochanters and sacrum and iii) evaluate the potential benefit of being able to predict the individual’s position with higher precision (classifying position into more than three categories) by taking into account a potential drop in prediction accuracy as well as the range of TPA for which the greater trochanters and sacrum were fully offloaded.

Data from 18 participants was combined with previous data sets to train and evaluate classifiers to predict the participants’ TPA using four different position bin sizes (∼70°, 45°, ∼30°, and 15°) and the effects of increasing precision on performance, where patients are left side-lying at -90°, right side-lying at 90° and supine at 0°). A leave-one-participant-out cross validation approach was used to select the best performing classifier, which was found to have an accuracy of 84.03% with an F1 score of 0.8399. Skin-bed interface forces were measured using force sensitive resistors placed on the greater trochanters and sacrum. Complete offloading for the sacrum was only achieved for the positions with TPA angles <-90° or >90°, indicating there was no benefit to predicting with greater precision than with three categories: left, right, and supine.
The Gut Microbiome and their Metabolites in Human Blood Pressure Variability
Authors: Dinakis Evany , Nakai Michael , Gill Paul , Ribeiro Rosilene , Yiallourou Stephanie , Sata Yusuke , Muir Jane , Carrington Melinda , Head Geoffrey A. , Kaye David M. , Marques Francine Z.
Published: March 2022

Blood pressure (BP) variability is an independent risk factor for cardiovascular events. Recent evidence supports a role for the gut microbiota in BP regulation. However, whether the gut microbiome is associated with BP variability is yet to be determined. Here, we aimed to investigate the interplay between the gut microbiome and their metabolites in relation to BP variability. Ambulatory BP monitoring was performed in 69 participants from Australia (55.1% women; mean±SD 59.8±7.26-years old, 25.2±2.83 kg/m2). This data was used to determine night-time dipping, morning BP surge (MBPS) and BP variability as standard deviation (SD). The gut microbiome was determined by 16S rRNA sequencing, and metabolite levels by gas chromatography. We identified specific taxa associated with systolic BP variability, night-time dipping and MBPS. Notably,AlistipesfinegoldiiandLactobacillus spp. were only present in participants within the normal ranges of BP variability, MBPS and dipping, whilePrevotella spp. and variousClostridiumspp. were found to be present in extreme dippers and the highest quartiles of BP SD and MBPS. There was a negative association between MBPS and microbial α-diversity (r=-0.244,P=0.046). MBPS was also negatively associated with total levels of microbial metabolites called short-chain fatty acids (SCFAs) in the plasma (r=-0.305,P=0.020), particularly acetate (r=-0.311,P=0.017). In conclusion, gut microbiome diversity, levels of microbial metabolites, and the bacteriaAlistipesfinegoldiiandLactobacilluswere associated with lower BP variability, andClostridiumandPrevotellawith higher BP variability. Thus, our findings suggest the gut microbiome and metabolites may be involved in the regulation of BP variability.
Low Vision Rehabilitation Training and Referral Patterns Among Ophthalmologists
Authors: Robinson Joshua L. , Kunnath Ansley , Law Janice C.
Published: March 2022

Objective

Vision impairment represents a growing burden to society and training protocols related to low vision rehabilitation (vision rehab) vary across ophthalmology residency programs. We surveyed practicing ophthalmologists regarding their vision rehab knowledge, confidence levels, and referral thresholds. We categorized subjects and compared response patterns between groups.

Design

Prospective observational

Subjects

185 practicing ophthalmologists

Methods

We created an Ophthalmology Low Vision Questionnaire and administered it to all enrolled subjects via email. We categorized subjects based on duration of practice, subspecialty area, and exposure to vision rehab during residency training. We drew conclusions by comparing responses between various subject categories.

Main Outcome Measures

The primary outcome measure was comparison of confidence levels and thresholds for vision rehab referral across groups. We used statistical tests to look for associations between practice duration, subspecialty area, vision rehab exposure during residency, and referral patterns.

Results

Ophthalmologists practicing for 6 or less years were more likely to have had a formal vision rehab rotation during their residency training compared to ophthalmologists practicing for 7 or more years (P = 0.03). Ophthalmologists who completed a formal vision rehab rotation during residency reported greater confidence in their ability to appropriately identify patients who could benefit from vision rehab referral (P = 0.04) and referred patients at earlier visual acuity thresholds (P = 0.04). Clinical subspecialty did not have a significant effect on vision rehab referral confidence or thresholds.

Conclusions

Vision rehab rotations during residency lead to improved referral confidence and earlier referral for these vital services. Standardization of vision rehab exposure across ophthalmology residency programs can help to improve outcomes for visually impaired patients.
Comprehensive interactome analysis for the sole adenylyl cyclase Cyr1 of Candida albicans
Authors: Zeng Guisheng , Neo Suat Peng , Pang Li Mei , Gao Jiaxin , Gunaratne Jayantha , Wang Yue
Published: March 2022

Cyr1, the sole adenylyl cyclase of the fungal pathogen Candida albicans, is a central component of the cAMP/PKA signaling pathway that controls the yeast-to-hyphal morphogenesis. Cyr1 functions as a multivalent senor and integrator of various external and internal signals. To better understand how these signals are relayed to Cyr1 and how Cyr1 activity is regulated, we sought to identify global interacting partners of Cyr1 using stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative proteomics. From the proteins co-immunoprecipitated with Myc-tagged Cyr1, 38 were assigned as authentic Cyr1-interacting partners, including two previously characterized Cyr1-binding proteins, Cap1 and Act1. Many of the identified proteins remain uncharacterized, but some can be classified into several functional groups, such as actin regulatory proteins, cell wall components, and mitochondrial proteins. We used biochemical and genetic methods to further characterize the interaction of Cyr1 with Mp65, a cell surface mannoprotein previously reported to have a role in cell wall integrity and possess several virulence-related traits. Taken together, our comprehensive analysis of the Cyr1-interacting proteins provides important information for establishing the Cyr1 interactome and uncovers a potential role for cell wall proteins in Cyr1-mediated cAMP signaling.
Hypothalamic-pituitary-adrenal axis dysfunction worsens epilepsy outcomes and increases SUDEP risk
Authors: Basu Trina , Antonoudiou Pantelis , Weiss Grant L. , Friedman Daniel , Laze Juliana , Devinsky Orrin , Maguire Jamie
Published: March 2022

Epilepsy is often comorbid with psychiatric illnesses, including anxiety and depression. Despite the high incidence of psychiatric comorbidities in people with epilepsy, few studies address the underlying mechanisms. Stress can trigger both epilepsy and depression and significant accumulating evidence, from both human and animal studies, support that hypothalamic-pituitary-adrenal (HPA) axis dysfunction may contribute to the comorbidity of these two disorders1. Here we directly investigate the contribution of HPA axis dysfunction to epilepsy outcomes and psychiatric comorbidities. We generated a novel mouse model (KCC2/Crh mice) that lacks the K+/Cl- co-transporter, KCC2, in corticotropin-releasing hormone (CRH) neurons, which exhibit stress- and seizure-induced hyperactivation of the HPA axis.2,3 Here we demonstrate that HPA axis dysfunction in KCC2/Crh mice is associated with increased vulnerability to behavioral deficits in chronically epileptic mice and more severe neuropathological features associated with chronic epilepsy (e.g. increased mossy fiber sprouting). Despite equivalent seizure burden, HPA axis dysfunction in these chronically epileptic mice increased the incidence of sudden unexpected death in epilepsy (SUDEP). Suppressing HPA axis hyperexcitability in this model using a pharmacological or chemogenetic approach decreased SUDEP incidence, supporting HPA axis dysfunction in SUDEP vulnerability. We also observed changes in neuroendocrine markers in individuals that died of SUDEP compared to people with epilepsy or individuals without a history of epilepsy. Together, these findings describe a novel, nongenetic mouse model of SUDEP which will benefit preclinical SUDEP research to gain a better understanding of the underlying pathological mechanisms contributing to SUDEP. HPA axis dysfunction increases vulnerability to psychiatric comorbidities in epilepsy and may be a risk factor for SUDEP.
Targeting an evolutionarily conserved “E-L-L” motif in the spike protein to develop a small molecule fusion inhibitor against SARS-CoV-2
Authors: Das Jana Indrani , Bhattacharya Prabuddha , Mayilsamy Karthick , Banerjee Saptarshi , Bhattacharje Gourab , Das Sayan , Aditya Seemanti , Ghosh Anandita , McGill Andrew R. , Srikrishnan Syamanthak , Das Amit Kumar , Basak Amit , Mohapatra Shyam S. , Chandran Bala , Bhimsaria Devesh , Mohapatra Subhra , Roy Arunava , Mondal Arindam
Published: March 2022

As newer variants of SARS-CoV-2 continue to pose major threats to global human health and economy, identifying novel druggable antiviral targets is the key towards sustenance. Here, we identify an evolutionary conserved “E-L-L” motif present within the HR2 domain of all human and non-human coronavirus spike (S) proteins that play a crucial role in stabilizing the post-fusion six-helix bundle (6-HB) structure and thus, fusion-mediated viral entry. Mutations within this motif reduce the fusogenicity of the S protein without affecting its stability or membrane localization. We found that posaconazole, an FDA-approved drug, binds to this “E-L-L” motif resulting in effective inhibition of SARS-CoV-2 infection in cells. While posaconazole exhibits high efficacy towards blocking S protein-mediated viral entry, mutations within the “E-L-L” motif rendered the protein completely resistant to the drug, establishing its specificity towards this motif. Our data demonstrate that posaconazole restricts early stages of infection through specific inhibition of membrane fusion and viral genome release into the host cell and is equally effective towards all major variants of concerns of SARS-CoV-2 including beta, kappa, delta, and omicron. Together, we show that this conserved essential “E-L-L” motif is an ideal target for the development of prophylactic and therapeutic interventions against SARS-CoV-2.
Effect of synchrotron X-ray radiation damage on phase transitions in coordination polymers at high pressure
Authors: Collings Ines E. , Hanfland Michael
Published: March 2022

The high-pressure phase-transition behaviour of metal–organic frameworks and coordination polymers upon varying degrees of X-ray irradiation are highlighted with four example studies. These show that, in certain cases, the radiation damage, while not extreme in changing unit-cell values, can impact the existence of a phase transition. In particular, pressure-induced phase transitions are suppressed after a certain absorbed dose threshold is reached for the sample. This is thought to be due to partial amorphization and/or defect formation in the sample, hindering the co-operative structural distortions needed for a phase transition. The high-pressure experiments were conducted with several crystals within the sample chamber in order to measure crystals with minimal X-ray irradiation at the highest pressures, which are compared with the crystals measured continuously upon pressure increase. Ways to minimize radiation damage are also discussed within the frame of high-pressure experiments.
Structure determination from unindexed powder data from scratch by a global optimization approach using pattern comparison based on cross-correlation functions
Authors: Habermehl Stefan , Schlesinger Carina , Schmidt Martin U.
Published: March 2022

A method of ab initio crystal structure determination from powder diffraction data for organic and metal–organic compounds, which does not require prior indexing of the powder pattern, has been developed. Only a reasonable molecular geometry is required, needing knowledge of neither unit-cell parameters nor space group. The structures are solved from scratch by a global fit to the powder data using the new program FIDEL-GO (`FIt with DEviating Lattice parameters - Global Optimization'). FIDEL-GO uses a similarity measure based on cross-correlation functions, which allows the comparison of simulated and experimental powder data even if the unit-cell parameters deviate strongly. The optimization starts from large sets of random structures in various space groups. The unit-cell parameters, molecular position and orientation, and selected internal degrees of freedom are fitted simultaneously to the powder pattern. The optimization proceeds in an elaborate multi-step procedure with built-in clustering of duplicate structures and iterative adaptation of parameter ranges. The best structures are selected for an automatic Rietveld refinement. Finally, a user-controlled Rietveld refinement is performed. The procedure aims for the analysis of a wide range of `problematic' powder patterns, in particular powders of low crystallinity. The method can also be used for the clustering and screening of a large number of possible structure candidates and other application scenarios. Examples are presented for structure determination from unindexed powder data of the previously unknown structures of the nanocrystalline phases of 4,11-difluoro-, 2,9-dichloro- and 2,9-dichloro-6,13-dihydro-quinacridone, which were solved from powder patterns with 14–20 peaks only, and of the coordination polymer dichloro-bis(pyridine-N)copper(II).
Neural networks for anatomical therapeutic chemical (ATC) classification
Authors: Nanni Loris , Lumini Alessandra , Brahnam Sheryl
Published: March 2022

Purpose

Automatic anatomical therapeutic chemical (ATC) classification is progressing at a rapid pace because of its potential in drug development. Predicting an unknown compound's therapeutic and chemical characteristics in terms of how it affects multiple organs and physiological systems makes automatic ATC classification a vital yet challenging multilabel problem. The aim of this paper is to experimentally derive an ensemble of different feature descriptors and classifiers for ATC classification that outperforms the state-of-the-art.

Design/methodology/approach

The proposed method is an ensemble generated by the fusion of neural networks (i.e. a tabular model and long short-term memory networks (LSTM)) and multilabel classifiers based on multiple linear regression (hMuLab). All classifiers are trained on three sets of descriptors. Features extracted from the trained LSTMs are also fed into hMuLab. Evaluations of ensembles are compared on a benchmark data set of 3883 ATC-coded pharmaceuticals taken from KEGG, a publicly available drug databank.

Findings

Experiments demonstrate the power of the authors’ best ensemble, EnsATC, which is shown to outperform the best methods reported in the literature, including the state-of-the-art developed by the fast.ai research group. The MATLAB source code of the authors’ system is freely available to the public at https://github.com/LorisNanni/Neural-networks-for-anatomical-therapeutic-chemical-ATC-classification.

Originality/value

This study demonstrates the power of extracting LSTM features and combining them with ATC descriptors in ensembles for ATC classification.
Color intensity, luminosity, contrast and art prices: the case of Jean-Michel Basquiat
Authors: Garay Urbi , Pérez Eduardo , Casanova Jose , Kratohvil Michelle
Published: March 2022

Purpose

The price of a painting is determined by multiple variables, including color-related variables. Colors are important in an economic analysis. This study aims to analyze the paintings executed by Jean-Michel Basquiat (the famous street artist from the 1980s' New York City) and sold at auction to study the potential effect of color intensity, luminosity and color contrast on the prices of his paintings. The authors also study the case of the op art master, Carlos Cruz-Diez, as a robustness analysis to the main results. The analysis that the authors present may be of interest to academicians and to participants in the art market.

Design/methodology/approach

The authors run a hedonic regression model considering 306 paintings (executed by Basquiat alone), and 41 works painted collaboratively between Basquiat and Warhol and sold at auction (2003–2017). The data and the images corresponding to each painting were hand-collected from the websites of several auction houses and complemented with information obtained from the Artprice and Blouin websites.

Findings

Increases in color intensity, luminosity and color contrast have a positive effect on art prices. The authors also find that color intensity is even more recognized (as reflected by higher prices) for paintings belonging to Basquiat's most appreciated (understood as most expensive) artistic period (1980–1983) and during the second part of the sample period (2011–2017). The authors find similar results for Cruz-Diez. The authors also estimate that Basquiat's artworks made collaboratively with Andy Warhol are worth 55% less than those made only by Basquiat. An investment in Basquiat's paintings generated an average annual compounded return of 16.81% (2003–2017), clearly overperforming the S&P 500.

Research limitations/implications

The main limitation of the hedonic regression method lies in the need to have a significant and varied sample to identify the true effect of each variable on the price of the good. Another limitation is that we are only able to use art prices from auctions, as this is the only comprehensive source of data that is publicly available. These two limitations are common to all studies that use the hedonic pricing model. This paper has implications not only for the art pricing (and more generally, asset pricing) literature, but also for the fields of psychology and marketing.

Originality/value

This is the first paper that highlights the importance of analyzing the price impact of color intensity throughout the artistic periods of a painter, finding that color intensity is even more appreciated (as reflected by higher prices) for paintings belonging to an artist's most recognized period. In the case of color contrast, the authors present a novel way to estimate this variable.
A comprehensive review on tourism destination competitiveness (TDC) literature
Authors: Mior Shariffuddin Nur Shahirah , Azinuddin Muaz , Hanafiah Mohd Hafiz , Wan Mohd Zain Wan Mohd Adzim
Published: March 2022

Purpose

This study aims to provide current and organised insights into past published studies on tourism destination competitiveness (TDC) in the past decade through systematic literature analysis.

Design/methodology/approach

A comprehensive review was performed by systematically gathering the literature published from 1983 to 2021 and coded according to categories such as author, year, article title, name of journal and TDC determinants.

Findings

The key findings of this review reveal that no universal set of items, attributes or indicators to measure the competitiveness of tourism destinations exists; the complexity and variability of many definitions and measuring elements from various perspectives portray the multi-faceted concept of competitiveness; and synergistic connection between the source of comparative and competitive advantages of TDC focusing on destination image, tourism experience and loyalty.

Research limitations/implications

Research works considered in the study are only from indexed and peer-reviewed journal publications.

Originality/value

The study findings reveal a lack of studies that address the relationship between destination image, tourism experience and loyalty within the TDC realm. Future studies should consider complementing the tourism supply and demand side to avoid a “strategic drift” of TDC concepts, perceptions and practices.
Design for safety in construction: a study of design professionals in Kuwait
Authors: Sharar Mohammed , Agyekum Kofi , Manu Patrick , Che Ibrahim Che Khairil Izam , Mahamadu Abdul-Majeed , Antwi-Afari Maxwell Fordjour , Danso Frederick Owusu
Published: March 2022

Purpose

Design for safety (DfS), also known as prevention through design (PtD), is a concept that mitigates accidents and hazards through considerations during the design stage of building projects. The literature provides much information on this concept, but such information is only limited to a few developed countries such as the UK, the USA and Australia. There is limited insight into DfS implementation in the construction industry of several countries, including countries in the Gulf Cooperation Council (GCC) such as Kuwait. Therefore, this study investigates DfS implementation among design professionals in the Kuwait construction industry.

Design/methodology/approach

The study used a questionnaire survey to obtain data from design professionals. The data were analysed using descriptive and inferential statistics (i.e. analysis of variance and t-test).

Findings

The results revealed that DfS awareness among design professionals is very high; there is a very high willingness among design professionals to apply the concept, and design professionals generally view DfS implementation as important. Despite these, the frequency of implementation of DfS practices is generally moderate. In addition, the results revealed that though there is a high interest in DfS training among the design professionals, their actual engagement in training is low. The results also suggest some association between the frequency of engagement in the DfS practices and designers' DfS awareness, training and education. DfS related regulations, industry guidance, formal education and training are considered by design professionals to have the greatest influence on DfS implementation in Kuwait.

Originality/Value

These emerging findings both mirror and contradict aspects of the outcomes of previous DfS studies in other countries. Furthermore, the findings from this study provide insights into a less investigated area regarding work-related health and safety in the GCC region. It offers new and additional information and insights into the current state-of-the-art DfS implementation in the construction industry in Kuwait. In view of the findings, joined-up efforts by government, industry and academia are needed to enhance DfS implementation by design professionals in Kuwait.
COVID-19 impact on hospitality retail employees’ turnover intentions
Authors: McCartney Glenn , Chi In Charlene Lai , Pinto José Soares de Albergaria Ferreira
Published: March 2022

Purpose

This study aims to examine effects of the COVID-19-induced lockdown on turnover intentions (TI) for the hospitality retail sector.

Design/methodology/approach

This study reviews employee TI literature before and during the COVID-19 pandemic. The data for the present study were derived from a sample of 301 hospitality retail workers employed within the integrated resorts on The Cotai Strip, Macao. Data were analysed using structural equation modelling.

Findings

This study showed a significant positive relationship between job satisfaction (JS) and the two variables of workload and pay (WP) and company support (CS). Co-worker relationship did not influence JS. Furthermore, JS had a significant negative effect on employee TI. WP had the greatest influence on whether to leave the sector or not.

Practical implications

The suggested framework can assist hospitality retail management in developing an employee-retention strategy as the sector recovers from pandemic restrictions.

Originality/value

To the best of the authors’ knowledge, this is one of the first studies to develop a TI framework for the hospitality retail sector during the pandemic.
Professional event associations in crisis: exploring the relationship between recovery strategy fit and organizational commitments from the perspective of members
Authors: Jung Shinyong , Kang Jiyun , Shin Hhye Won
Published: March 2022

Purpose

This study aims to explore how professional event associations’ recovery strategies are perceived by members and to measure the consequent influence of the perceived fit of recovery strategies on organizational identification (OI), consistent behavioral intentions and long-term commitment intentions.

Design/methodology/approach

Data were collected from current members of professional event management associations who work not only as event planners but also as service providers in the hospitality and tourism industry. The authors used partial least squares structural equation modeling to test the proposed model.

Findings

The perceived fit between recovery strategy and internal domains, the self in particular, was found to be the most important in exerting effects directly on OI, and its indirect effects are significant on all the behavioral intentions toward the association, while the perceived fit of recovery strategy with external domains, especially the industry, was not significant with any of the other factors.

Practical implications

The findings from the present study provide professional event association leaderships with significant managerial implications in establishing a sustainable business model to retain current members and increase their intentions toward consistent engagement and long-term commitment.

Originality/value

Stepping forward from the strategic management and organizational behavior literature in the private sector, the authors shed light on a crisis recovery mechanism of professional associations in the event industry, to the best of the authors’ knowledge, the first such attempt in the event management literature.
For love or money? The effect of deadline proximity on completion contributions in online crowdfunding
Authors: Cox Joe , Tosatto Jann , Nguyen Thang
Published: March 2022

Purpose

The authors investigate whether the individual “completion contributions” that enable online crowdfunding campaigns to meet or exceed their targets tend to be larger in relative terms when made nearer to the funding deadline. As these contributions are likely to have a disproportionate impact upon campaign outcomes, the authors assess whether the investment patterns they observe are consistent with the theory of impact philanthropy.

Design/methodology/approach

The authors use campaign-level data incorporating observations on campaigns from reward (both all-or-nothing, AoN and keep-it-all, KiA), donation and equity-based platforms. To the knowledge of the authors, the coverage of the data is unparalleled elsewhere in the crowdfunding literature. Using these data, the authors analyze whether completion contributions tend to vary contingent upon both the proximity of the deadline and form of crowdfunding.

Findings

The authors find that completion contributions tend to vary significantly and positively with proximity to funding deadlines. The authors also find that this relationship tends to be more pronounced among AoN than for KiA campaigns, as well as for donation-based platforms compared with equity-based platforms. Altogether, the patterns of behavior observed are consistent with the theory of impact philanthropy.

Originality/value

The authors help develop a better understanding of the behaviors of contributors to online crowdfunding campaigns and whether those behaviors are consistent with altruistic motivations. The findings also have considerable value in understanding the non-financial factors associated with the informal financing of business startups.