bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional characterization of rare NRXN1 variants identified in autism spectrum disorders and schizophrenia
Authors: Ishizuka Kanako , Yoshida Tomoyuki , Kawabata Takeshi , Imai Ayako , Mori Hisashi , Kimura Hiroki , Inada Toshiya , Okahisa Yuko , Egawa Jun , Usami Masahide , Kushima Itaru , Morikawa Mako , Okada Takashi , Ikeda Masashi , Branko Aleksic , Mori Daisuke , Someya Toshiyuki , Iwata Nakao , Ozaki Norio 
Published: September 2020

Abstract
Background
Rare genetic variants contribute to the etiology of both autism spectrum disorder (ASD) and schizophrenia (SCZ). Most genetic studies limit their focus to likely gene-disrupting mutations because they are relatively easier to interpret their effects on the gene product. Interpretation of missense variants is also informative to some pathophysiological mechanisms of these neurodevelopmental disorders; however, their contribution has not been elucidated because of relatively small effects. Therefore, we characterized missense variants detected in NRXN1, a well-known neurodevelopmental disease-causing gene, from individuals with ASD and SCZ.

Methods
To discover rare variants with large effect size and to evaluate their role in the shared etiopathophysiology of ASD and SCZ, we sequenced NRXN1 coding exons with a sample comprising 562 Japanese ASD and SCZ patients, followed by a genetic association analysis in 4273 unrelated individuals. Impact of each missense variant detected here on cell surface expression, interaction with NLGN1, and synaptogenic activity was analyzed using an in vitro functional assay and in silico three-dimensional (3D) structural modeling.

Results
Through mutation screening, we regarded three ultra-rare missense variants (T737M, D772G, and R856W), all of which affected the LNS4 domain of NRXN1α isoform, as disease-associated variants. Diagnosis of individuals with T737M, D772G, and R856W was 1ASD and 1SCZ, 1ASD, and 1SCZ, respectively. We observed the following phenotypic and functional burden caused by each variant. (i) D772G and R856W carriers had more serious social disabilities than T737M carriers. (ii) In vitro assay showed reduced cell surface expression of NRXN1α by D772G and R856W mutations. In vitro functional analysis showed decreased NRXN1α-NLGN1 interaction of T737M and D772G mutants. (iii) In silico 3D structural modeling indicated that T737M and D772G mutations could destabilize the rod-shaped structure of LNS2-LNS5 domains, and D772G and R856W could disturb N-glycan conformations for the transport signal.

Conclusions
The combined data suggest that missense variants in NRXN1 could be associated with phenotypes of neurodevelopmental disorders beyond the diagnosis of ASD and/or SCZ.
Twadn: an efficient alignment algorithm based on time warping for pairwise dynamic networks
Authors: Zhong Yuanke , Li Jing , He Junhao , Gao Yiqun , Liu Jie , Wang Jingru , Shang Xuequn , Hu Jialu 
Published: September 2020

AbstractBackgroundNetwork alignment is an efficient computational framework in the prediction of protein function and phylogenetic relationships in systems biology. However, most of existing alignment methods focus on aligning PPIs based on static network model, which are actually dynamic in real-world systems. The dynamic characteristic of PPI networks is essential for understanding the evolution and regulation mechanism at the molecular level and there is still much room to improve the alignment quality in dynamic networks.ResultsIn this paper, we proposed a novel alignment algorithm, Twadn, to align dynamic PPI networks based on a strategy of time warping. We compare Twadn with the existing dynamic network alignment algorithm DynaMAGNA++ and DynaWAVE and use area under the receiver operating characteristic curve and area under the precision-recall curve as evaluation indicators. The experimental results show that Twadn is superior to DynaMAGNA++ and DynaWAVE. In addition, we use protein interaction network of Drosophila to compare Twadn and the static network alignment algorithm NetCoffee2 and experimental results show that Twadn is able to capture timing information compared to NetCoffee2.ConclusionsTwadn is a versatile and efficient alignment tool that can be applied to dynamic network. Hopefully, its application can benefit the research community in the fields of molecular function and evolution.
A learning-based method for drug-target interaction prediction based on feature representation learning and deep neural network
Authors: Peng Jiajie , Li Jingyi , Shang Xuequn 
Published: September 2020

Abstract
Background
Drug-target interaction prediction is of great significance for narrowing down the scope of candidate medications, and thus is a vital step in drug discovery. Because of the particularity of biochemical experiments, the development of new drugs is not only costly, but also time-consuming. Therefore, the computational prediction of drug target interactions has become an essential way in the process of drug discovery, aiming to greatly reducing the experimental cost and time.

Results
We propose a learning-based method based on feature representation learning and deep neural network named DTI-CNN to predict the drug-target interactions. We first extract the relevant features of drugs and proteins from heterogeneous networks by using the Jaccard similarity coefficient and restart random walk model. Then, we adopt a denoising autoencoder model to reduce the dimension and identify the essential features. Third, based on the features obtained from last step, we constructed a convolutional neural network model to predict the interaction between drugs and proteins. The evaluation results show that the average AUROC score and AUPR score of DTI-CNN were 0.9416 and 0.9499, which obtains better performance than the other three existing state-of-the-art methods.

Conclusions
All the experimental results show that the performance of DTI-CNN is better than that of the three existing methods and the proposed method is appropriately designed.
Spark-based parallel calculation of 3D fourier shell correlation for macromolecule structure local resolution estimation
Authors: Lü Yongchun , Zeng Xiangrui , Tian Xinhui , Shi Xiao , Wang Hui , Zheng Xiaohui , Liu Xiaodong , Zhao Xiaofang , Gao Xin , Xu Min 
Published: September 2020

AbstractBackgroundResolution estimation is the main evaluation criteria for the reconstruction of macromolecular 3D structure in the field of cryoelectron microscopy (cryo-EM). At present, there are many methods to evaluate the 3D resolution for reconstructed macromolecular structures from Single Particle Analysis (SPA) in cryo-EM and subtomogram averaging (SA) in electron cryotomography (cryo-ET). As global methods, they measure the resolution of the structure as a whole, but they are inaccurate in detecting subtle local changes of reconstruction. In order to detect the subtle changes of reconstruction of SPA and SA, a few local resolution methods are proposed. The mainstream local resolution evaluation methods are based on local Fourier shell correlation (FSC), which is computationally intensive. However, the existing resolution evaluation methods are based on multi-threading implementation on a single computer with very poor scalability.ResultsThis paper proposes a new fine-grained 3D array partition method by key-value format in Spark. Our method first converts 3D images to key-value data (K-V). Then the K-V data is used for 3D array partitioning and data exchange in parallel. So Spark-based distributed parallel computing framework can solve the above scalability problem. In this distributed computing framework, all 3D local FSC tasks are simultaneously calculated across multiple nodes in a computer cluster. Through the calculation of experimental data, 3D local resolution evaluation algorithm based on Spark fine-grained 3D array partition has a magnitude change in computing speed compared with the mainstream FSC algorithm under the condition that the accuracy remains unchanged, and has better fault tolerance and scalability.ConclusionsIn this paper, we proposed a K-V format based fine-grained 3D array partition method in Spark to parallel calculating 3D FSC for getting a 3D local resolution density map. 3D local resolution density map evaluates the three-dimensional density maps reconstructed from single particle analysis and subtomogram averaging. Our proposed method can significantly increase the speed of the 3D local resolution evaluation, which is important for the efficient detection of subtle variations among reconstructed macromolecular structures.
Control of Panama disease of banana by intercropping with Chinese chive (Allium tuberosum Rottler): cultivar differences
Authors: Li Zhenfang , Wang Tong , He Chenling , Cheng Kelin , Zeng Rensen , Song Yuanyuan 
Published: September 2020

AbstractPanama disease (Fusarium wilt disease) caused by Fusarium oxysporum f. sp. cubense race 4 (FOC) severely threatens banana (Musa spp.) production worldwide. Intercropping of banana with Allium plants has shown a potential to reduce Panama disease. In this study, six cultivars of Chinese chive (Allium tuberosum Rottler) were selected to compare their differences in antifungal activity and active compounds. Three cultivars Duokang Fujiu 11, Fujiuhuang 2, and Duokang Sijiqing with higher levels of antifungal compounds were further used for intercropping with banana in the pots and field to compare their effects on growth and disease incidence of banana.The six cultivars showed significant differences in antifungal activity against FOC mycelia growth in both leaf volatiles and aqueous leachates. The aqueous leachates displayed stronger antifungal activity than the volatiles. FJH cultivar showed the best inhibitory effect among all six cultivars. Contents of three main antifungal compounds dipropyl trisulfide (DPT), dimethyl trisulfide (DMT), and 2-methyl-2-pentenal (MP) in volatiles and aqueous leachates varied considerably among cultivars. Pot and field experiments showed that intercropping with three selected Chinese chive cultivars significantly improved banana vegetative growth, increased photosynthetic characteristics and yield but decreased disease incidence of Panama disease.Our results indicate that intercropping with Chinese chive shows potential to reduce banana Panama disease and selection of appropriate cultivars is vital for effective disease control.
Impact of temperature variability on childhood allergic rhinitis in a subtropical city of China
Authors: Wang Xu , Cheng Jian , Ling Li , Su Hong , Zhao Desheng , Ni Hong 
Published: September 2020

Abstract
Background
Many studies have shown an association of childhood respiratory diseases with short-term temperature variability such as diurnal temperature range (DTR) and temperature change between two neighboring days (TCN). However, the impact of temperature variability on allergic rhinitis (AR) has not been investigated so far. This study sought to evaluate the short-term effect of temperature variability (i.e., TCN and DTR) on AR, as well as to identify vulnerable subpopulations.

Method
We collected daily data on emergency room visits and outpatients for AR and weather variables in Hefei, China during 2014–2016. A distributed lag non-linear model that controlled for long-term trend and seasonality, mean temperature, relative humidity, day of week was used to fit the associations of AR with DTR and TCN. Stratified analyses by age, sex and occupation were also performed.

Results
During the study period, there were a total of 53,538 cases and the average values of DTR and TCN were 8.4 °C (range: 1.0 °C to 21.2 °C) and 0 °C (range: − 12.2 °C to 5.9 °C), respectively. While we did not observe an adverse effect of DTR on AR, TCN was significantly associated with increased risk of AR. Specifically, a large temperature drop between two adjacent days (3.8 °C, 5th percentile of TCN) has a delayed and short-lasting effect on AR, with the estimated relative risk of 1.02 (95% confidence interval: 1.01 to 1.04) at lag 12. Moreover, boys and children older than 15 years seemed to be more vulnerable to the effect of TCN.

Conclusions
This study provided evidence of an adverse effect of large temperature drops between two adjacent days on childhood AR. Attention paid to boys and older children may help prevent AR attacks.
An improved strategy to analyse strigolactones in complex sample matrices using UHPLC–MS/MS
Authors: Floková Kristýna , Shimels Mahdere , Andreo Jimenez Beatriz , Bardaro Nicoletta , Strnad Miroslav , Novák Ondřej , Bouwmeester Harro J. 
Published: September 2020

Abstract
Background
Strigolactones represent the most recently described group of plant hormones involved in many aspects of plant growth regulation. Simultaneously, root exuded strigolactones mediate rhizosphere signaling towards beneficial arbuscular mycorrhizal fungi, but also attract parasitic plants. The seed germination of parasitic plants induced by host strigolactones leads to serious agricultural problems worldwide. More insight in these signaling molecules is hampered by their extremely low concentrations in complex soil and plant tissue matrices, as well as their instability. So far, the combination of tailored isolation—that would replace current unspecific, time-consuming and labour-intensive processing of large samples—and a highly sensitive method for the simultaneous profiling of a broad spectrum of strigolactones has not been reported.

Results
Depending on the sample matrix, two different strategies for the rapid extraction of the seven structurally similar strigolactones and highly efficient single-step pre-concentration on polymeric RP SPE sorbent were developed and validated. Compared to conventional methods, controlled temperature during the extraction and the addition of an organic modifier (acetonitrile, acetone) to the extraction solvent helped to tailor strigolactone isolation from low initial amounts of root tissue (150 mg fresh weight, FW) and root exudate (20 ml), which improved both strigolactone stability and sample purity. We have designed an efficient UHPLC separation with sensitive MS/MS detection for simultaneous analysis of seven natural strigolactones including their biosynthetic precursors—carlactone and carlactonoic acid. In combination with the optimized UHPLC–MS/MS method, attomolar detection limits were achieved. The new method allowed successful profiling of seven strigolactones in small exudate and root tissue samples of four different agriculturally important plant species—sorghum, rice, pea and tomato.

Conclusion
The established method provides efficient strigolactone extraction with aqueous mixtures of less nucleophilic organic solvents from small root tissue and root exudate samples, in combination with rapid single-step pre-concentration. This method improves strigolactone stability and eliminates the co-extraction and signal of matrix-associated contaminants during the final UHPLC–MS/MS analysis with an electrospray interface, which dramatically increases the overall sensitivity of the analysis. We show that the method can be applied to a variety of plant species.
Antimicrobial prophylaxis is considered sufficient to preserve an acceptable surgical site infection rate in clean orthopaedic and neurosurgeries in dogs
Authors: Välkki Kirsi Johanna , Thomson Katariina Hanne , Grönthal Thomas Sven Christer , Junnila Jouni Juho Tapio , Rantala Merja Hilma Johanna , Laitinen-Vapaavuori Outi Maria , Mölsä Sari Helena 
Published: September 2020

AbstractBackgroundSurgical site infections (SSI) are associated with increased morbidity and mortality. To lower the incidence of SSI, antimicrobial prophylaxis is given 30–60 min before certain types of surgeries in both human and veterinary patients. However, due to the increasing concern of antimicrobial resistance, the benefit of antimicrobial prophylaxis in clean orthopaedic and neurosurgeries warrants investigation. The aims of this retrospective cross-sectional study were to review the rate of SSI and evaluate the compliance with antimicrobial guidelines in dogs at a veterinary teaching hospital in 2012–2016. In addition, possible risk factors for SSI were assessed.ResultsNearly all dogs (377/406; 92.9%) received antimicrobial prophylaxis. Twenty-nine dogs (7.1%) did not receive any antimicrobials and only four (1.1%) received postoperative antimicrobials. The compliance with in-house and national protocols was excellent regarding the choice of prophylactic antimicrobial (cefazolin), but there was room for improvement in the timing of prophylaxis administration. Follow-up data was available for 89.4% (363/406) of the dogs. Mean follow-up time was 464 days (range: 3–2600 days). The overall SSI rate was 6.3%: in orthopaedic surgeries it was 6.7%, and in neurosurgeries it was 4.2%. The lowest SSI rates (0%) were seen in extracapsular repair of cranial cruciate ligament rupture, ulnar ostectomy, femoral head and neck excision, arthrotomy and coxofemoral luxation repair. The highest SSI rate (25.0%) was seen in arthrodesis. Omission of antimicrobials did not increase the risk for SSI (P = 0.56; OR 1.7; CI95%0.4–5.0). Several risk factors for SSI were identified, including methicillin-resistantStaphylococcus pseudintermediuscarriage (P = 0.02; OR 9.0; CI95%1.4–57.9) and higher body temperature (P = 0.03; OR 1.69; CI95%1.0–2.7; mean difference + 0.4 °C compared to dogs without SSI).ConclusionsAntimicrobial prophylaxis without postoperative antimicrobials is sufficient to maintain the overall rate of SSI at a level similar to published data in canine clean orthopedic and neurosurgeries.
Whether the risk of gestational diabetes mellitus is affected by TNF-α, IL-6, IL-10 or ADIPOQ polymorphisms: a meta-analysis
Authors: Huang Qiqi , Wang Yi , Gu Binbin , Xu Yanwen 
Published: September 2020

Abstract
Background
Whether polymorphisms in tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-10 (IL-10) or adiponectin (ADIPOQ) influence the risk of gestational diabetes mellitus (GDM) or not remain inconclusive. Therefore, the authors conducted a meta-analysis to robustly assess relationships between polymorphisms in TNF-α, IL-6, IL-10 or ADIPOQ and the risk of GDM by merging the results of eligible publications.

Methods
A through literature searching in Medline, Embase, Wanfang, VIP and CNKI was conducted by the authors to identify eligible publications, and twenty-two publications were finally found to be eligible for merged quantitative analyses.

Results
The merged quantitative analyses revealed that ADIPOQ + 45T/G (rs2241766) polymorphism was significantly associated with the risk of GDM in overall population (dominant comparison: OR = 0.70, p < 0.001; recessive comparison: OR = 1.95, p < 0.001; over-dominant comparison: OR = 1.18, p = 0.03; allele comparison: OR = 0.71, p < 0.001) and Asians (dominant comparison: OR = 0.70, p < 0.001; recessive comparison: OR = 1.94, p < 0.001; allele comparison: OR = 0.72, p < 0.001). Nevertheless, we did not observe any positive results for TNF-α − 238G/A (rs361525), TNF-α − 308G/A (rs1800629), IL6 − 174G/C (rs1800795), IL-10 − 819C/T (rs1800871), IL-10 − 592C/A (rs1800872), IL-10 − 1082A/G (rs1800896) and ADIPOQ + 276G/T (rs1501299) polymorphisms.

Conclusions
The present meta-analysis shows that among investigated TNF-α, IL-6, IL-10 or ADIPOQ polymorphisms, only ADIPOQ + 45T/G (rs2241766) polymorphism may affect the risk of GDM.
Dynamic changes of the fecal bacterial community in dairy cows during early lactation
Authors: Huang Shuai , Ji Shoukun , Wang Feiran , Huang Jie , Alugongo Gibson Maswayi , Li Shengli 
Published: September 2020

AbstractThe dynamics of the community structure and composition of the dairy cow fecal bacterial communities during early lactation is unclear, therefore this study was conducted to characterize the fecal bacterial communities in dairy cows during early lactation using 16S rRNA gene sequencing. Feces were sampled from 20 healthy fresh Holstein dairy cows on day 1 (Fresh1d group) and day 14 (Fresh14d group) after calving. After calving, cows were fed the same fresh diet. The dominant phyla Firmicutes and Proteobacteria were decreased (P ≤ 0.01) with lactating progress and phyla Bacteroidetes were increased (P = 0.008) with lactating progress and dietary transition. At family level, the predominant families were Ruminococcaceae (35.23%), Lachnospiraceae (11.46%), Rikenellaceae (10.44%) and Prevotellaceae (6.89%). A total of 14 genera were different between fecal samples from Fresh1d and Fresh14d, included the predominant genera, such as Ruminococcaceae_UCG-005 (P = 0.008), Rikenellaceae_RC9_gut_group (P = 0.043) and Christensenellaceae_R-7_group (P = 0.008). All fecal bacterial communities shared members of the genera Ruminococcaceae_UCG-005, Bacteroides and Rikenellaceae_RC9_gut_group. These findings help to improve our understanding of the composition and structure of the fecal microbial community in fresh cows and may provide insight into bacterial adaptation time and dietary in lactating cows.
What is the prevalence of current alcohol dependence and how is it measured for Indigenous people in Australia, New Zealand, Canada and the United States of America? A systematic review
Authors: Weatherall Teagan J. , Conigrave Katherine M. , Conigrave James H. , Lee K. S. Kylie 
Published: September 2020

AbstractBackgroundAlcohol affects Indigenous communities globally that have been colonised. These effects are physical, psychological, financial and cultural. This systematic review aims to describe the prevalence of current (12-month) alcohol dependence in Indigenous Peoples in Australia, New Zealand, Canada and the United States of America, to identify how it is measured, and if tools have been validated in Indigenous communities. Such information can help inform estimates of likely treatment need.MethodsA systematic search of the literature was completed in six electronic databases for reports on current alcohol dependence (moderate to severe alcohol use disorder) published between 1 January 1989–9 July 2020. The following data were extracted: (1) the Indigenous population studied; country, (2) prevalence of dependence, (3) tools used to screen, assess or diagnose current dependence, (4) tools that have been validated in Indigenous populations to screen, assess or diagnose dependence, and (5) quality of the study, assessed using the Appraisal Tool for Cross-Sectional Studies.ResultsA total of 11 studies met eligibility criteria. Eight were cross-sectional surveys, one cohort study, and two were validation studies. Nine studies reported on the prevalence of current (12-month) alcohol dependence, and the range varied widely (3.8–33.3% [all participants], 3–32.8% [males only], 1.3–7.6% [females only]). Eight different tools were used and none were Indigenous-specific. Two tools have been validated in Indigenous (Native American) populations.ConclusionFew studies report on prevalence of current alcohol dependence in community or household samples of Indigenous populations in these four countries. Prevalence varies according to sampling method and site (for example, specific community versus national). Prior work has generally not used tools validated in Indigenous contexts. Collaborations with local Indigenous people may help in the development of culturally appropriate ways of measuring alcohol dependence, incorporating local customs and values. Tools used need to be validated in Indigenous communities, or Indigenous-specific tools developed, validated and used. Prevalence findings can inform health promotion and treatment needs, including funding for primary health care and specialist treatment services.