bluuebunny/crossref_metadata_2025 huggingface dataset:
Successful Implementation of a Rapid Screening Tool for Hantavirus Cardiopulmonary Syndrome: 5 Years of Experience From a Community Hospital in an Endemic Region
Authors: Oliver Tarrah T , Dyal Jonathan W , Talker Donna L , Safaeian Shahrokh , Yazzie Del , Kofman Aaron D , D’Andrea Shawn M , Saleki Mozafar , Ingall Glynnis B , Choi Mary J , Antone-Nez Ramona
Published: September 2021

Objectives

Hantavirus is endemic in the Four Corners region of Arizona, Colorado, New Mexico, and Utah, and hantavirus cardiopulmonary syndrome (HCPS) disproportionately affects the Navajo Nation. We describe the application of a rapid screening tool for identification of HCPS.

Methods

A rapid screening tool for HCPS was implemented at Tséhootsooí Medical Center (TMC) in collaboration with academic partners.

Results

Since its implementation in 2016, 20 TMC staff members have been trained to perform this test, and 189 screens for HCPS have been reported. Although hantavirus infection is rare even in high-risk areas, use of this tool resulted in the identification of 4 acute cases of hantavirus infection.

Conclusions

The results demonstrate the successful implementation of a 5-point screening tool for hantavirus infection in an endemic setting by a laboratory in a small community hospital.
MET Gene High Copy Number (Amplification/Polysomy) Identified in Melanoma for Potential Targeted Therapy
Authors: Ramani Nisha S , Morani Ajaykumar C , Zhang Shengle
Published: September 2021

Objectives

Aberrant expression of the mesenchymal epithelial transition factor (MET) gene has been observed in several malignancies, and drugs targeting the MET gene have been implicated in clinical trials with promising results. Hence, MET is a potentially targetable oncogenic driver. We explored the frequency of MET gene high copy number in melanomas and carcinomas.

Methods

The study group included 135 patients. Tissue microarrays were constructed with 19 melanomas and 116 carcinomas diagnosed from 2010 to 2012. We screened MET gene copy number by fluorescence in situ hybridization analysis using probes for MET gene and CEP7 as control.

Results

We found MET gene amplification in 2 (11%) of 19 melanoma cases, whereas 5 (26%) of 19 melanoma cases showed polysomy. For carcinomas, there was no MET gene amplification identified. However, 8 (7%) of 116 cases showed polysomy.

Conclusions

In our study, MET gene amplification was identified in 11% of melanomas and is relatively concordant with few reported studies. However, about 26% of the additional melanoma cases showed MET gene polysomy, which has not been reported as per our knowledge. If these results are validated with further orthogonal studies, more of the melanoma cases could potentially benefit from targeted therapy with MET tyrosine kinase inhibitors.
Performance of the LumiraDx Microfluidic Immunofluorescence Point-of-Care SARS-CoV-2 Antigen Test in Asymptomatic Adults and Children
Authors: Drain Paul , Sulaiman Raed , Hoppers Melanie , Lindner Nigel M , Lawson Vicki , Ellis Jayne E
Published: September 2021

Objectives

The LumiraDx SARS-CoV-2 Ag Test has previously been shown to accurately detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in individuals symptomatic for coronavirus disease 2019 (COVID-19). This evaluation investigated the LumiraDx SARS-CoV-2 Ag Test as an aid in the diagnosis of SARS-CoV-2 infection in asymptomatic adults and children.

Methods

Asymptomatic individuals at high risk of COVID-19 infection were recruited in 5 point-of-care (POC) settings. Two paired anterior nasal swabs were collected from each participant, tested by using the LumiraDx SARS-CoV-2 Ag Test at the POC, and compared with results from reverse transcription–polymerase chain reaction (RT-PCR) assays (cobas 6800 [Roche Diagnostics] or TaqPath [Thermo Fisher Scientific]). We calculated positive percent agreement (PPA) and negative percent agreement (NPA), then stratified results on the basis of RT-PCR reference platform and cycle threshold.

Results

Of the 222 included study participants confirmed to be symptom-free for at least 2 weeks before testing, the PPA was 82.1% (95% confidence interval [CI], 64.4%-92.1%). The LumiraDx SARS-CoV-2 Ag Test correctly identified 95.8% (95% CI, 79.8%-99.3%) of the samples confirmed positive in fewer than 33 RT-PCR cycles and 100% (95% CI, 85.1%-100%) in fewer than 30 RT-PCR cycles while maintaining 100% NPA.

Conclusions

This rapid, high-sensitivity test can be used to screen asymptomatic patients for acute SARS-CoV-2 infection in clinic- and community-based settings.
Determining Mitochondrial 3243A>G Heteroplasmy Using an ARMS-ddPCR Strategy
Authors: Xu Pu , Jia Manli , Yan Jimei , Yuan Xiangshu , Yu Weidong , Zhou Zhuohua , Fang Hezhi , Gao Feng , Shen Lijun
Published: September 2021

Objectives

Determining mitochondrial DNA (mtDNA) A-to-G substitution at nucleotide 3243 (m.3243A>G) heteroplasmy is essential for both precision diagnosis of m.3243A>G–associated mitochondrial disease and genetic counseling. Precise determination of m.3243A>G heteroplasmy is challenging, however, without appropriate strategies to accommodate heteroplasmic levels ranging from 1% to 100% in samples carrying thousands to millions of mtDNA copies.

Methods

We used a combined strategy of amplification-refractory mutation system–quantitative polymerase chain reaction (ARMS-qPCR) and droplet digital PCR (ddPCR) to determine m.3243A>G heteroplasmy. Primers were specifically designed and screened for both ARMS-qPCR and ddPCR to determine m.3243A>G heteroplasmy. An optimized ARMS-qPCR–ddPCR–based strategy was established using artificial standards, with different mixtures of m.3243A-containing and m.3243G-containing plasmids and further tested using clinical samples containing the m.3243A>G mutation.

Results

One of 20 primer pairs designed in the study was omitted for ARMS-qPCR–ddPCR strategy application according to criteria of 85% to 110%, R2> 0.98 amplification efficiency, melt curve with a single clear peak, and specificity for m.3243A and m.3243G artificial standards (|CtWt-CtMut|max). Using plasmid standards with various m.3243A>G heteroplasmy (1%-100%) at low, mid, and high copy numbers (3,000, 104, and 105-107, respectively) and DNA from the blood of 20 patients carrying m.3243A>G with mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes, we found that ARMS-qPCR was reliable for determining m.3243A>G at 3% to 100% for low copy number and 1% to 100% for mid to high copy number samples. Meanwhile, ddPCR was reliable for determining m.3243A>G at 1% to 100% at low to mid copy number samples.

Conclusions

An ARMS-qPCR–ddPCR–based strategy was successfully established for precise determination of m.3243A>G heteroplasmy in complex clinical samples.
Aerosol Analysis Using Handheld Raman Spectrometer: On-site Quantification of Trace Crystalline Silica in Workplace Atmospheres
Authors: Wei Shijun , Johnson Belinda , Breitenstein Michael , Zheng Lina , Snawder John , Kulkarni Pramod
Published: September 2021

A method for aerosol chemical analysis using handheld Raman spectrometer has been developed and its application to measurement of crystalline silica concentration in workplace atmosphere is described. The approach involves collecting aerosol as a spot sample using a wearable optical aerosol monitor, followed by direct-on-filter quantitative analysis of the spot sample for crystalline silica using handheld Raman spectrometer. The filter cassette of a commercially available optical aerosol monitor (designed to collect aerosol for post-shift analysis) was modified to collect 1.5-mm-diameter spot sample, which provided adequate detection limits for short-term measurements over a few tens of minutes or hours. The method was calibrated using aerosolized α-quartz standard reference material in the laboratory. Two Raman spectrometers were evaluated, one a handheld unit (weighing less than 410 g) and the other a larger probe-based field-portable unit (weighing about 5 kg). The lowest limit of quantification for α-quartz of 16.6 μg m−3 was obtained using the handheld Raman unit at a sample collection time of 1 h at 0.4 l min−1. Short-term measurement capability and sensitivity of the Raman method were demonstrated using a transient simulated workplace aerosol. Workplace air and personal breathing zone concentrations of crystalline silica of workers at a hydraulic fracturing worksite were measured using the Raman method. The measurements showed good agreement with the co-located samples analyzed using the standard X-ray powder diffraction (XRD) method, agreeing within 0.15–23.2% of each other. This magnitude of difference was comparable to the inter- and intra-laboratory analytical precision of established XRD and infrared methods. The pilot study shows that for silica-containing materials studied in this work it is possible to obtain quantitative measurements with good analytical figures of merit using handheld or portable Raman spectrometers. Further studies will be needed to assess matrix interferences and measurement uncertainty for several other types of particle matrices to assess the broader applicability of the method.
3D phytomer-based geometric modelling method for plants—the case of maize
Authors: Wen Weiliang , Wang Yongjian , Wu Sheng , Liu Kai , Gu Shenghao , Guo Xinyu
Published: September 2021

Geometric plant modelling is crucial in in silico plants. Existing geometric modelling methods have focused on the topological structure and basic organ profiles, simplifying the morphological features. However, the models cannot effectively differentiate cultivars, limiting FSPM application in crop breeding and management. This study proposes a 3D phytomer-based geometric modelling method with maize (Zea Mays) as the representative plant. Specifically, conversion methods between skeleton and mesh models of 3D phytomer are specified. This study describes the geometric modelling of maize shoots and populations by assembling 3D phytomers. Results show that the method can quickly and efficiently construct 3D models of maize plants and populations, with the ability to show morphological, structural and functional differences among four representative cultivars. The method takes into account both the geometric modelling efficiency and 3D detail features to achieve automatic operation of geometric modelling through the standardized description of 3D phytomers. Therefore, this study provides a theoretical and technical basis for the research and application of in silico plants.
Seed morphological traits as a tool to quantify variation maintained inex situcollections: a case study inPinus torreyana
Authors: Di Santo Lionel N , Polgar Monica , Nies Storm , Hodgkiss Paul , Canning Courtney A , Wright Jessica W , Hamilton Jill A
Published: September 2021

Understanding the within- and among-population distribution of trait variation within seed collections may provide a means to approximate standing genetic variation and inform plant conservation. This study aimed to estimate population- and family-level seed trait variability for existing seed collections of Torrey pine (Pinus torreyana), and to use these data to guide sampling of future collections. We quantified variation in 14 seed morphological traits and seedling emergence within and among Torrey pine populations. Using a simulation-based approach, we used estimates of within-population variance to assess the number of maternal families required to capture 95 % of trait variation within each existing seed collection. Substantial structure was observed both within and among Torrey pine populations, with island and mainland seeds varying in seed size and seed coat thickness. Despite morphological differences, seedling emergence was similar across populations. Simulations revealed that 83 % and 71 % of all maternal families within island and mainland seed collections respectively needed to be resampled to capture 95 % of seed trait variation within existing collections. From a conservation perspective, our results indicate that to optimize genetic diversity captured in Torrey pine seed collections, maximizing the number of maternal families sampled within each population will be necessary.
Co-constructing Social Justice: Language Educators Challenging Colonial Practices in Mexico
Authors: López-Gopar Mario E , Schissel Jamie L , Leung Constant , Morales Julio
Published: September 2021

This article involves the work of four language educators/researchers collaborating on an ongoing longitudinal multilingual participatory action research (PAR) project in a Bachelor of Arts (BA) language teaching program in Oaxaca, Mexico. Overall, this PAR project aims at the co-construction of social justice in ELT in Mexico. In particular, it explores an approach that would encourage learners to make full(er) use of their language resources to challenge the colonial othering discourses of inferiority, disability, and backwardness inherent in ELT in Mexico. The analyses reported in this article zooms in on the English learning experiences of three Indigenous background, low-socioeconomic status, female undergraduate students, and their alleged struggle with speaking English in teaching–learning and assessment activities. The purpose of this article is to illustrate how a local English teacher co-constructed social justice with these three students. To fulfill this purpose, we succinctly present the focal students life stories and address three emergent themes: (i) unveiling alienating practices in the classroom; (ii) carving out spaces for multilingualism in the English classroom; and (iii) authoring assessment as a way to enact social justice.
Brazilian Version of Addenbrooke’s Cognitive Examination—Revised in the Differential Diagnosis of Alzheimer’S Disease and Behavioral Variant Frontotemporal Dementia
Authors: Amaral-Carvalho Viviane , Lima-Silva Thais Bento , Mariano Luciano Inácio , de Souza Leonardo Cruz , Guimarães Henrique Cerqueira , Bahia Valéria Santoro , Nitrini Ricardo , Barbosa Maira Tonidandel , Yassuda Mônica Sanches , Caramelli Paulo
Published: September 2021

Introduction

Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are frequent causes of dementia and, therefore, instruments for differential diagnosis between these two conditions are of great relevance.

Objective

To investigate the diagnostic accuracy of Addenbrooke’s Cognitive Examination-Revised (ACE-R) for differentiating AD from bvFTD in a Brazilian sample.

Methods

The ACE-R was administered to 102 patients who had been diagnosed with mild dementia due to probable AD, 37 with mild bvFTD and 161 cognitively healthy controls, matched according to age and education. Additionally, all subjects were assessed using the Mattis Dementia Rating Scale and the Neuropsychiatric Inventory. The performance of patients and controls was compared by using univariate analysis, and ROC curves were calculated to investigate the accuracy of ACE-R for differentiating AD from bvFTD and for differentiating AD and bvFTD from controls. The verbal fluency plus language to orientation plus name and address delayed recall memory (VLOM) ratio was also calculated.

Results

The optimum cutoff scores for ACE-R were <80 for AD, <79 for bvFTD, and <80 for dementia (AD + bvFTD), with area under the receiver operating characteristic curves (ROC) (AUC) >0.85. For the differential diagnosis between AD and bvFTD, a VLOM ratio of 3.05 showed an AUC of 0.816 (Cohen’s d = 1.151; p < .001), with 86.5% sensitivity, 71.4% specificity, 72.7% positive predictive value, and 85.7% negative predictive value.

Conclusions

The Brazilian ACE-R achieved a good diagnostic accuracy for differentiating AD from bvFTD patients and for differentiating AD and bvFTD from the controls in the present sample.
Regression-Based Norms and Validation of the Cambridge Neuropsychological Test Automated Battery among Community-Living Older Adults in Singapore
Authors: Siew Savannah K H , Han Madeline F Y , Mahendran Rathi , Yu Junhong
Published: September 2021

Objective

The Cambridge Neuropsychological Test Automated Battery (CANTAB) is widely used in research and clinical settings. However, little is known about the use of the CANTAB in the local aging context. This study aimed to develop normative data for various CANTAB measures in community-living older adults in Singapore. Normative data were built using the regression-based approach. A secondary aim was to examine the concurrent validity of CANTAB measures with their traditional neurocognitive test counterparts.

Method

A total of 210 older adults (Mage = 67.27 years, SD = 5.45) from an existing cohort study completed standard neurocognitive tests and a CANTAB battery. A total of 160 were normal aging, 46 diagnosed with Mild Cognitive Impairment (MCI), and one diagnosed with Dementia. Older adults with MCI and Dementia were not included in the calculation of norms but were included in other analyses. For the CANTAB battery, regression-based norms were generated for each CANTAB measure, with age, sex, and education included as covariates. Concurrent validity was examined by correlating the CANTAB measures with their traditional neurocognitive counterparts.

Results

As expected, performance across most CANTAB measures declined significantly with increasing age and decreasing education levels. There were no significant effects of sex on most CANTAB measures. Our study also showed that some CANTAB measures demonstrated good concurrent validity as they significantly correlated with their traditional neurocognitive test counterparts.

Conclusions

We have developed age, sex, and education-specific CANTAB norms for use in the local aging context. The advantages and challenges of using the CANTAB in the local aging context are discussed.
Kinesin family member 2C promotes hepatocellular carcinoma growth and metastasis via activating MEK/ERK pathway
Authors: Ding Qian , Jiang Caihua , Zhou Yajing , Duan Jianping , Lai Jianming , Jiang Min , Lin Dongdong
Published: September 2021

The current work was intended to explore the function and mechanism of Kinesin family member 2C (KIF2C) in hepatocellular carcinoma (HCC). In this study, KIF2C expression was at a high level in HCC and indicated poor prognosis. Silencing KIF2C significantly suppressed the proliferation, migration, and invasion in HCC cells. Furthermore, silencing KIF2C markedly decreased the expression of Snail, Vimentin, p-MEK, and p-ERK, but increased E-cadherin expression in HCC cells. Moreover, we also found that MEK/ERK inhibitor U0126 could enhance the impact on cell proliferation, migration, and invasion induced by silencing KIF2C in HCC. On the contrary, MEK/ERK activator PAF could weaken the impact induced by silencing KIF2C in HCC. Thus, our findings indicate that KIF2C can promote the proliferation, migration, and invasion by activating MEK/ERK pathway in HCC.
Social and physical environment independently affect oviposition decisions inDrosophila
Authors: Churchill Emily R , Dytham Calvin , Bridle Jon R , Thom Michael D F
Published: September 2021

In response to environmental stimuli, including variation in the presence of conspecifics, genotypes show highly plastic responses in behavioral and physiological traits influencing reproduction. Although extensively documented in males, such female responses are rather less studied. We expect females to be highly responsive to environmental variation and to differentially allocate resources to increase offspring fitness, given the major contribution of mothers to offspring number, size, and developmental conditions. Using Drosophila melanogaster, we (a) manipulate exposure to conspecific females, which mothers could use to anticipate the number of potential mates and larval density, and; (b) test how this interacts with the spatial distribution of potential oviposition sites, with females from higher densities expected to prefer clustered resources that can support a larger number of larvae. We found that high density females were slower to start copulating and reduced their copulation duration, the opposite effect to that observed in males. There was a parallel, perhaps related, effect on egg production: females previously housed in groups laid fewer eggs than those housed in solitude. Resource patchiness also influenced oviposition behavior: females preferred aggregated substrate, which attracted more females to lay eggs. However, we found no interaction between prior housing conditions and resource patchiness, indicating that females did not perceive the value of different resource distributions differently when exposed to environments that could signal expected levels of larval competition. We show that, although exposure to consexual competition changes copulatory behaviors of females, the distribution of oviposition resources has a greater effect on oviposition decisions.
Zebra finch song is a very short-range signal in the wild: evidence from an integrated approach
Authors: Loning Hugo , Griffith Simon C , Naguib Marc
Published: September 2021

Birdsong is typically seen as a long-range signal functioning in mate attraction and territory defense. Among birds, the zebra finch is the prime model organism in bioacoustics, yet almost exclusively studied in the lab. In the wild, however, zebra finch song differs strikingly from songbirds commonly studied in the wild as zebra finch males sing most after mating and in the absence of territoriality. Using data from the wild, we here provide an ecological context for a wealth of laboratory studies. By integrating calibrated sound recordings, sound transmission experiments and social ecology of zebra finches in the wild with insights from hearing physiology we show that wild zebra finch song is a very short-range signal with an audible range of about nine meters and that even the louder distance calls do not carry much farther (up to about fourteen meters). These integrated findings provide an ecological context for the interpretation of laboratory studies of this species and indicate that the vocal communication distance of the main laboratory species for avian acoustics contrasts strikingly with songbirds that use their song as a long-range advertisement signal.
Postcopulatory sexual selection is associated with sperm aggregate quality in Peromyscus mice
Authors: Hook Kristin A , Weber W David , Fisher Heidi S
Published: September 2021

In some species, sperm form coordinated groups that are hypothesized to improve their swimming performance in competitive contexts or to navigate through the viscous fluids of the female reproductive tract. Here we investigate sperm aggregation across closely related species of Peromyscus mice that naturally vary by mating system to test the predictions that sperm aggregates 1) are faster than solitary sperm in species that females mate multiply to aid cells in sperm competition, and 2) outperform solitary sperm cells in viscous environments. We find significant variation in the size of sperm aggregates, which negatively associates with relative testis mass, a proxy for sperm competition risk, suggesting that postcopulatory sexual selection has a stabilizing effect on sperm group size. Moreover, our results show that sperm aggregates are faster than solitary sperm in some, but not all, species, and this can vary by fluid viscosity. Of the two species that produce the largest and most frequent groups, we find that sperm aggregates from the promiscuous P. maniculatus are faster than solitary sperm in every experimentally viscous environment but aggregation provides no such kinematic advantage under these same conditions for the monogamous P. polionotus. The reduced performance of P. polionotus aggregates is associated with less efficient aggregate geometry and the inclusion of immotile or morphological abnormal sperm. Our cross-species comparison yields insight into the evolution of sperm social behaviors, provides evidence of extensive variation in the Peromyscus lineage, and reveals that differences in sperm aggregate quality associate with postcopulatory sexual selection.
A cross-study analysis of drug response prediction in cancer cell lines
Authors: Xia Fangfang , Allen Jonathan , Balaprakash Prasanna , Brettin Thomas , Garcia-Cardona Cristina , Clyde Austin , Cohn Judith , Doroshow James , Duan Xiaotian , Dubinkina Veronika , Evrard Yvonne , Fan Ya Ju , Gans Jason , He Stewart , Lu Pinyi , Maslov Sergei , Partin Alexander , Shukla Maulik , Stahlberg Eric , Wozniak Justin M , Yoo Hyunseung , Zaki George , Zhu Yitan , Stevens Rick
Published: September 2021

To enable personalized cancer treatment, machine learning models have been developed to predict drug response as a function of tumor and drug features. However, most algorithm development efforts have relied on cross-validation within a single study to assess model accuracy. While an essential first step, cross-validation within a biological data set typically provides an overly optimistic estimate of the prediction performance on independent test sets. To provide a more rigorous assessment of model generalizability between different studies, we use machine learning to analyze five publicly available cell line-based data sets: National Cancer Institute 60, ancer Therapeutics Response Portal (CTRP), Genomics of Drug Sensitivity in Cancer, Cancer Cell Line Encyclopedia and Genentech Cell Line Screening Initiative (gCSI). Based on observed experimental variability across studies, we explore estimates of prediction upper bounds. We report performance results of a variety of machine learning models, with a multitasking deep neural network achieving the best cross-study generalizability. By multiple measures, models trained on CTRP yield the most accurate predictions on the remaining testing data, and gCSI is the most predictable among the cell line data sets included in this study. With these experiments and further simulations on partial data, two lessons emerge: (1) differences in viability assays can limit model generalizability across studies and (2) drug diversity, more than tumor diversity, is crucial for raising model generalizability in preclinical screening.
Network-based analysis revealed significant interactions between risk genes of severe COVID-19 and host genes interacted with SARS-CoV-2 proteins
Authors: Qi Hao-xiang , Shen Qi-dong , Zhao Hong-yi , Qi Guo-zhen , Gao Lei
Published: September 2021

Whether risk genes of severe coronavirus disease 2019 (COVID-19) from genome-wide association study could play their regulatory roles by interacting with host genes that were interacted with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins was worthy of exploration. In this study, we implemented a network-based approach by developing a user-friendly software Network Calculator (https://github.com/Haoxiang-Qi/Network-Calculator.git). By using Network Calculator, we identified a network composed of 13 risk genes and 28 SARS-CoV-2 interacted host genes that had the highest network proximity with each other, with a hub gene HNRNPK identified. Among these genes, 14 of them were identified to be differentially expressed in RNA-seq data from severe COVID-19 cases. Besides, by expression enrichment analysis in single-cell RNA-seq data, compared with mild COVID-19, these genes were significantly enriched in macrophage, T cell and epithelial cell for severe COVID-19. Meanwhile, 74 pathways were significantly enriched. Our analysis provided insights for the underlying genetic etiology of severe COVID-19 from the perspective of network biology.
Identification of potential therapeutic targets and mechanisms of COVID-19 through network analysis and screening of chemicals and herbal ingredients
Authors: Wang Hong , Zhang Jingqing , Lu Zhigang , Dai Weina , Ma Chuanjiang , Xiang Yun , Zhang Yonghong
Published: September 2021

After experiencing the COVID-19 pandemic, it is widely acknowledged that a rapid drug repurposing method is highly needed. A series of useful drug repurposing tools have been developed based on data-driven modeling and network pharmacology. Based on the disease module, we identified several hub proteins that play important roles in the onset and development of the COVID-19, which are potential targets for repositioning approved drugs. Moreover, different network distance metrics were applied to quantify the relationship between drug targets and COVID-19 disease targets in the protein–protein-interaction (PPI) network and predict COVID-19 therapeutic effects of bioactive herbal ingredients and chemicals. Furthermore, the tentative mechanisms of candidates were illustrated through molecular docking and gene enrichment analysis. We obtained 15 chemical and 15 herbal ingredient candidates and found that different drugs may play different roles in the process of virus invasion and the onset and development of the COVID-19 disease. Given pandemic outbreaks, our method has an undeniable immense advantage in the feasibility analysis of drug repurposing or drug screening, especially in the analysis of herbal ingredients.
STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction
Authors: Basith Shaherin , Lee Gwang , Manavalan Balachandran
Published: September 2021

Protein post-translational modification (PTM) is an important regulatory mechanism that plays a key role in both normal and disease states. Acetylation on lysine residues is one of the most potent PTMs owing to its critical role in cellular metabolism and regulatory processes. Identifying protein lysine acetylation (Kace) sites is a challenging task in bioinformatics. To date, several machine learning-based methods for the in silico identification of Kace sites have been developed. Of those, a few are prokaryotic species-specific. Despite their attractive advantages and performances, these methods have certain limitations. Therefore, this study proposes a novel predictor STALLION (STacking-based Predictor for ProkAryotic Lysine AcetyLatION), containing six prokaryotic species-specific models to identify Kace sites accurately. To extract crucial patterns around Kace sites, we employed 11 different encodings representing three different characteristics. Subsequently, a systematic and rigorous feature selection approach was employed to identify the optimal feature set independently for five tree-based ensemble algorithms and built their respective baseline model for each species. Finally, the predicted values from baseline models were utilized and trained with an appropriate classifier using the stacking strategy to develop STALLION. Comparative benchmarking experiments showed that STALLION significantly outperformed existing predictor on independent tests. To expedite direct accessibility to the STALLION models, a user-friendly online predictor was implemented, which is available at: http://thegleelab.org/STALLION.
DeepHost: phage host prediction with convolutional neural network
Authors: Ruohan Wang , Xianglilan Zhang , Jianping Wang , Shuai Cheng L I
Published: September 2021

Next-generation sequencing expands the known phage genomes rapidly. Unlike culture-based methods, the hosts of phages discovered from next-generation sequencing data remain uncharacterized. The high diversity of the phage genomes makes the host assignment task challenging. To solve the issue, we proposed a phage host prediction tool—DeepHost. To encode the phage genomes into matrices, we design a genome encoding method that applied various spaced $k$-mer pairs to tolerate sequence variations, including insertion, deletions, and mutations. DeepHost applies a convolutional neural network to predict host taxonomies. DeepHost achieves the prediction accuracy of 96.05% at the genus level (72 taxonomies) and 90.78% at the species level (118 taxonomies), which outperforms the existing phage host prediction tools by 10.16–30.48% and achieves comparable results to BLAST. For the genomes without hits in BLAST, DeepHost obtains the accuracy of 38.00% at the genus level and 26.47% at the species level, making it suitable for genomes of less homologous sequences with the existing datasets. DeepHost is alignment-free, and it is faster than BLAST, especially for large datasets. DeepHost is available at https://github.com/deepomicslab/DeepHost.
Characterization of gastric cancer stem-like molecular features, immune and pharmacogenomic landscapes
Authors: Wei Chen , Chen Mingkai , Deng Wenying , Bie Liangyu , Ma Yijie , Zhang Chi , Liu Kangdong , Shen Wei , Wang Shuyi , Yang Chaogang , Luo Suxia , Li Ning
Published: September 2021

Cancer stem cells (CSCs) actively reprogram their tumor microenvironment (TME) to sustain a supportive niche, which may have a dramatic impact on prognosis and immunotherapy. However, our knowledge of the landscape of the gastric cancer stem-like cell (GCSC) microenvironment needs to be further improved. A multi-step process of machine learning approaches was performed to develop and validate the prognostic and predictive potential of the GCSC-related score (GCScore). The high GCScore subgroup was not only associated with stem cell characteristics, but also with a potential immune escape mechanism. Furthermore, we experimentally demonstrated the upregulated infiltration of CD206+ tumor-associated macrophages (TAMs) in the invasive margin region, which in turn maintained the stem cell properties of tumor cells. Finally, we proposed that the GCScore showed a robust capacity for prediction for immunotherapy, and investigated potential therapeutic targets and compounds for patients with a high GCScore. The results indicate that the proposed GCScore can be a promising predictor of prognosis and responses to immunotherapy, which provides new strategies for the precision treatment of GCSCs.
Deep learning in retrosynthesis planning: datasets, models and tools
Authors: Dong Jingxin , Zhao Mingyi , Liu Yuansheng , Su Yansen , Zeng Xiangxiang
Published: September 2021

In recent years, synthesizing drugs powered by artificial intelligence has brought great convenience to society. Since retrosynthetic analysis occupies an essential position in synthetic chemistry, it has received broad attention from researchers. In this review, we comprehensively summarize the development process of retrosynthesis in the context of deep learning. This review covers all aspects of retrosynthesis, including datasets, models and tools. Specifically, we report representative models from academia, in addition to a detailed description of the available and stable platforms in the industry. We also discuss the disadvantages of the existing models and provide potential future trends, so that more abecedarians will quickly understand and participate in the family of retrosynthesis planning.
RNA–RNA interactions between SARS-CoV-2 and host benefit viral development and evolution during COVID-19 infection
Authors: Zhang Song , Amahong Kuerbannisha , Zhang Chenyang , Li Fengcheng , Gao Jianqing , Qiu Yunqing , Zhu Feng
Published: September 2021

Some studies reported that genomic RNA of SARS-CoV-2 can absorb a few host miRNAs that regulate immune-related genes and then deprive their function. In this perspective, we conjecture that the absorption of the SARS-CoV-2 genome to host miRNAs is not a coincidence, which may be an indispensable approach leading to viral survival and development in host. In our study, we collected five datasets of miRNAs that were predicted to interact with the genome of SARS-CoV-2. The targets of these miRNAs in the five groups were consistently enriched immune-related pathways and virus-infectious diseases. Interestingly, the five datasets shared no one miRNA but their targets shared 168 genes. The signaling pathway enrichment of 168 shared targets implied an unbalanced immune response that the most of interleukin signaling pathways and none of the interferon signaling pathways were significantly different. Protein–protein interaction (PPI) network using the shared targets showed that PPI pairs, including IL6-IL6R, were related to the process of SARS-CoV-2 infection and pathogenesis. In addition, we found that SARS-CoV-2 absorption to host miRNA could benefit two popular mutant strains for more infectivity and pathogenicity. Conclusively, our results suggest that genomic RNA absorption to host miRNAs may be a vital approach by which SARS-CoV-2 disturbs the host immune system and infects host cells.
Advances, challenges and opportunities of phylogenetic and social network analysis using COVID-19 data
Authors: Wang Yue , Zhao Yunpeng , Pan Qing
Published: September 2021

Coronavirus disease 2019 (COVID-19) has attracted research interests from all fields. Phylogenetic and social network analyses based on connectivity between either COVID-19 patients or geographic regions and similarity between syndrome coronavirus 2 (SARS-CoV-2) sequences provide unique angles to answer public health and pharmaco-biological questions such as relationships between various SARS-CoV-2 mutants, the transmission pathways in a community and the effectiveness of prevention policies. This paper serves as a systematic review of current phylogenetic and social network analyses with applications in COVID-19 research. Challenges in current phylogenetic network analysis on SARS-CoV-2 such as unreliable inferences, sampling bias and batch effects are discussed as well as potential solutions. Social network analysis combined with epidemiology models helps to identify key transmission characteristics and measure the effectiveness of prevention and control strategies. Finally, future new directions of network analysis motivated by COVID-19 data are summarized.
Dissecting and predicting different types of binding sites in nucleic acids based on structural information
Authors: Jiang Zheng , Xiao Si-Rui , Liu Rong
Published: September 2021

The biological functions of DNA and RNA generally depend on their interactions with other molecules, such as small ligands, proteins and nucleic acids. However, our knowledge of the nucleic acid binding sites for different interaction partners is very limited, and identification of these critical binding regions is not a trivial work. Herein, we performed a comprehensive comparison between binding and nonbinding sites and among different categories of binding sites in these two nucleic acid classes. From the structural perspective, RNA may interact with ligands through forming binding pockets and contact proteins and nucleic acids using protruding surfaces, while DNA may adopt regions closer to the middle of the chain to make contacts with other molecules. Based on structural information, we established a feature-based ensemble learning classifier to identify the binding sites by fully using the interplay among different machine learning algorithms, feature spaces and sample spaces. Meanwhile, we designed a template-based classifier by exploiting structural conservation. The complementarity between the two classifiers motivated us to build an integrative framework for improving prediction performance. Moreover, we utilized a post-processing procedure based on the random walk algorithm to further correct the integrative predictions. Our unified prediction framework yielded promising results for different binding sites and outperformed existing methods.
An evo-devo perspective of the female reproductive tract
Authors: Major Andrew T , Estermann Martin A , Roly Zahida Y , Smith Craig A
Published: September 2021

The vertebrate female reproductive tract has undergone considerable diversification over evolution, having become physiologically adapted to different reproductive strategies. This review considers the female reproductive tract from the perspective of evolutionary developmental biology (evo-devo). Very little is known about how the evolution of this organ system has been driven at the molecular level. In most vertebrates, the female reproductive tract develops from paired embryonic tubes, the Müllerian ducts. We propose that formation of the Müllerian duct is a conserved process that has involved co-option of genes and molecular pathways involved in tubulogenesis in the adjacent mesonephric kidney and Wolffian duct. Downstream of this conservation, genetic regulatory divergence has occurred, generating diversity in duct structure. Plasticity of the Hox gene code and wnt signaling, in particular, may underlie morphological variation of the uterus in mammals, and evolution of the vagina. This developmental plasticity in Hox and Wnt activity may also apply to other vertebrates, generating the morphological diversity of female reproductive tracts evident today.
Longitudinal trends in physician preferences for referrals to same-sex surgeons: a population-based study
Authors: Dossa F , Urbach D R , Sutradhar R , Baxter N N
Published: September 2021

This population-based study of over 27 million referrals to surgeons demonstrated that patient sharing among physicians and surgeons is influenced by the sex of the patient, referring physician, and surgeon. Importantly, the study demonstrated that male patients are unlikely to be referred to female surgeons, particularly if seen by a male physician. These disparities are not improving over time .
Next-generation three-dimensional modelling software for personalized surgery decision-making in perihilar cholangiocarcinoma: multicentre study
Authors: Lopez-Lopez V , Gomez-Perez B , de Vicente E , Jiménez-Galanes S , Mora-Oliver I , Sabater L , Huber T , Lang H , Brusadin R , López Conesa A , Melendez R , Castro Santiago M J , Ferreras D , Crespo M J , Cayuela V , Robles-Campos R
Published: September 2021

Next-generation three-dimensional modelling software for personalized surgery allows spatially accurate depiction of the hepatic and vasculature anatomy based on the complexity and individual variation in each patient, and could facilitate decision-making about preoperative strategy in perihilar cholangiocarcinoma.
Intervention versus surveillance in patients with common bile duct stones detected by intraoperative cholangiography: a population-based registry study
Authors: Johansson E , Österberg J , Sverdén E , Enochsson L , Sandblom G
Published: September 2021

Background

Each year 13 000 patients undergo cholecystectomy in Sweden, and routine intraoperative cholangiography (IOC) is recommended to minimize bile duct injuries. The risk of requiring endoscopic retrograde cholangiopancreatography (ERCP) following cholecystectomy for common bile duct (CBD) stones where IOC is omitted and in patients with CBD stones left in situ is not well known.

Methods

Data were retrieved from the population-based Swedish Registry of Gallstone Surgery and ERCP between 1 January 2009 and 10 December 2019. Primary outcome was risk for postoperative ERCP for retained CBD stones.

Results

A total of 134 419 patients that underwent cholecystectomy were included and 2691 (2.0 per cent) subsequently underwent ERCP for retained CBD stones. When adjusting for emergency or planned cholecystectomy, preoperative symptoms suggestive of CBD stones, sex and age, there was an increased risk for ERCP when IOC was not performed (hazard ratio (HR) 1.4, 95 per cent c.i. 1.3 to 1.6). The adjusted risk for ERCP was also increased if CBD stones identified by IOC were managed with surveillance (HR 5.5, 95 per cent c.i. 4.8 to 6.4). Even for asymptomatic small stones (less than 4 mm), the adjusted risk for ERCP was increased in the surveillance group compared with the intervention group (HR 3.5, 95 per cent c.i. 2.4 to 5.1).

Conclusion

IOC plus an intervention to remove CBD stones identified during cholecystectomy was associated with reduced risk for retained stones and unplanned ERCP, even for the smallest asymptomatic CBD stones.
Transoral endoscopic thyroidectomy by a vestibular approach: cadaver simulation experience and ethicolegal issues
Authors: Oliva A , Grassi S , Minelli N , Zedda M , Arena V , Romaniello N , Dionigi G , Makay Ö , De Crea C , Celik S , Spagnolo A Gioacchino , Bellantone R , Raffaelli M
Published: September 2021

This article describes the use of transoral endoscopic thyroidectomy by a vestibular approach on cadavers to improve the technical and non-technical skills of surgeons.
Nationwide paediatric cohort study of a protective association between allergy and complicated appendicitis
Authors: Omling E , Salö M , Stenström P , Merlo J , Gudjonsdottir J , Rudolfson N , Hagander L
Published: September 2021

Background

In a nationwide cohort the potentially protective association between allergy and complicated appendicitis was analysed, and the influence of seasonal antigens, antihistamine treatment, and timing of allergy onset assessed.

Methods

Some 1 112 571 children born between 2000 and 2010 were followed from birth until the end of 2014. A cross-sectional analysis of appendicitis cases, with comparison of allergic versus non-allergic children for absolute risk and odds of complicated appendicitis was first undertaken. This was followed by a longitudinal analysis of children with allergy and matched controls who had never had an allergy, for incidence rate and hazard of subsequent complicated or simple appendicitis.

Results

Of all children, 20.4 per cent developed allergy and 0.6 per cent had appendicitis during follow-up. Among children with appendicitis, complicated appendicitis was more common among non-allergic children (18.9 per cent, 948 of 5016) than allergic children (12.8 per cent, 173 of 1351) (P < 0.001), and allergic children had a lower adjusted odds of complicated appendicitis (adjusted odds ratio (OR) 0.80, 95 per cent c.i. 0.67 to 0.96; P = 0.021 ). The risk of complicated appendicitis among children with manifest allergy was reduced by one-third in the longitudinal analysis (incidence rate 0.13 versus 0.20 per 1000 person-years; hazard ratio (HR) 0.68, 95 per cent c.i. 0.58 to 0.81; P < 0.001), whereas the risk of simple appendicitis remained unchanged (incidence rate 0.91 versus 0.91; HR 1.00, 0.94 to 1.07; P = 0.932 ). Seasonal antigen exposure was a protective factor (adjusted OR 0.82, 0.71 to 0.94; P = 0.004) and ongoing antihistamine medication a risk factor (adjusted OR 2.28, 1.21 to 4.28; P = 0.012).

Conclusion

Children with allergy have a lower risk of complicated appendicitis, but the same overall risk of simple appendicitis. Seasonal antigen exposure reduced, and antihistamine treatment increased, the risk of complicated disease.
Maternal risk factors for paediatric inguinal hernia
Authors: Auger Nathalie , del Giorgio Francesca , Le-Nguyen Annie , Bilodeau-Bertrand Marianne , Piché Nelson
Published: September 2021

Background

Risk factors for paediatric inguinal hernia are poorly understood. This longitudinal cohort study assessed whether children with a maternal history of inguinal hernia or connective tissue disorders have a higher risk of developing inguinal hernias before 13 years of age.

Methods

The study included children followed up between birth and 13 years of age in Quebec, Canada, 2006–2019. Newborns whose mothers had inguinal hernias or connective tissue disorders were followed over time to identify future hospital admissions for inguinal hernia. Cox proportional hazards regression adjusted for patient characteristics was used to estimate hazard ratios (HRs) and 95 per cent confidence intervals for the association between maternal hernia or connective tissue disorders and future childhood hernias. Associations in girls and boys were examined separately.

Results

The study included 786 322 children with 6 186 448 person-years of follow-up. There were 6861 children with inguinal hernias, corresponding to an incidence of 11.1 per 10 000 person-years. Children with a maternal history of inguinal hernia had 2.92 (95 per cent c.i. 2.39 to 3.58) times the risk of having inguinal hernias relative to children whose mothers had no such history. Children with a maternal history of connective tissue disorders had 1.30 (1.00 to 1.68) times the risk. Maternal hernias were strongly associated with risk of inguinal hernias in girls (HR 5.34, 3.82 to 7.47), whereas maternal connective tissue disorders were associated with inguinal hernias in boys (HR 1.35, 1.02 to 1.79).

Conclusion

Paediatric inguinal hernias may be associated with maternal inguinal hernias and connective tissue disorders, but the underlying reason for this relationship requires further investigation.