bluuebunny/crossref_metadata_2025 huggingface dataset:
Indicator metrics and temporal aggregations introduce ambiguities in water scarcity estimates
Authors: Wolkeba Fitsume T. , Mekonnen Mesfin M. , Brauman Kate A. , Kumar Mukesh
Published: July 2024

Water scarcity is a global challenge affecting billions of people worldwide. This study systematically assesses differences in the estimation of the global population exposed to water scarcity based on 7 water scarcity indicators and 11 Environmental Flow Requirements (EFR) evaluated at various spatial and temporal resolutions. All indicators show an increase in water scarcity since 1901. However, considering monthly average water scarcity estimates spatially aggregated at the basin scale found 35% less population exposed than estimates based on a distributed grid over the landscape. Estimates temporally disaggregated to consider water scarcity for at least one month a year found 50% (tenfold) larger population exposed compared to average monthly (annual) estimates. The study illustrates that estimates of the impacts of water scarcity are an artifact of how water scarcity is defined and calculated. This suggests caution is needed when relying on a single method and emphasizes the importance of considering the diversity of factors that can influence estimates of impact when assessing water scarcity.
Impact of MTHFR gene polymorphism on the outcome of methotrexate treatment in a sample of Iraqi rheumatoid arthritis patients
Authors: Mutlak Qassim Mahdi , Kasim Ali Abdulhussain
Published: July 2024

Analyze the relationship between genetic variations in the MTHFR gene at SNPs (rs1801131 and rs1801133) and the therapy outcomes for Iraqi patients with rheumatoid arthritis (RA). The study was conducted on a cohort of 95 RA Iraqi patients. Based on their treatment response, the cohort was divided into two groups: the responder (47 patients) and the nonresponder (48 patients), identified after at least three months of methotrexate (MTX) treatment. A polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP) technique was employed to analyze the MTHFR variations, specifically at rs1801133 and rs1801131. Overall, rs1801131 followed both codominant and dominate models, in which in the codominant model, GG [OR (95% CI) 0.11 (0.022–0.553)] and TG [OR (95% CI) 0.106 (0.021–0.528)] predict responders compared to the TT genotype; meanwhile, for the dominate model, the presence of both GG and TG genotypes [OR (95% CI) 0.108 (0.023–0.507)] together predict responders compared to the TT genotype. The Ars1801133Grs1801131 haplotype was significantly associated with responders [OR (95% CI): 0.388 (0.208–0.723)], while the Grs1801133Trs1801131 haplotype was associated marginally with nonresponders [OR (95% CI) 1.980 (0.965–4.064)]. In the final multivariate analysis, GG/TGrs1801131 genotypes were independently related to responders after adjustment for patients, disease, and treatment characteristics, while TTrs1801131 genotypes were associated with nonresponders. The Iraqi RA patients showed genetic polymorphism in MTHFR gene rs1801131 with T carrier allele associated with nonresponders to MTX therapy. The rs1801131 followed both codominant and dominant models. The G-carried allele for rs1801131 showed an independent association with responder to MTX therapy after adjustment for patients, disease, and treatment characteristics.
Benefits and limits of biological nitrification inhibitors for plant nitrogen uptake and the environment
Authors: Kuppe Christian W. , Postma Johannes A.
Published: July 2024

Plant growth and high yields are secured by intensive use of nitrogen (N) fertilizer, which, however, pollutes the environment, especially when N is in the form of nitrate. Ammonium is oxidized to nitrate by nitrifiers, but roots can release biological nitrification inhibitors (BNIs). Under what conditions does root-exudation of BNIs facilitate nitrogen N uptake and reduce pollution by N loss to the environment? We modeled the spatial–temporal dynamics of nitrifiers, ammonium, nitrate, and BNIs around a root and simulated root N uptake and net rhizosphere N loss over the plant’s life cycle. We determined the sensitivity of N uptake and loss to variations in the parameter values, testing a broad range of soil–plant-microbial conditions, including concentrations, diffusion, sorption, nitrification, population growth, and uptake kinetics. An increase in BNI exudation reduces net N loss and, under most conditions, increases plant N uptake. BNIs decrease uptake in the case of (1) low ammonium concentrations, (2) high ammonium adsorption to the soil, (3) rapid nitrate- or slow ammonium uptake by the plant, and (4) a slowly growing or (5) fast-declining nitrifier population. Bactericidal inhibitors facilitate uptake more than bacteriostatic ones. Some nitrification, however, is necessary to maximize uptake by both ammonium and nitrate transporter systems. An increase in BNI exudation should be co-selected with improved ammonium uptake. BNIs can reduce N uptake, which may explain why not all species exude BNIs but have a generally positive effect on the environment by increasing rhizosphere N retention.
Prolonged ventricular repolarization associated with mild cognitive impairment and white matter hyperintensities: a cross-sectional study
Authors: Mao Ming , Wei Yiran , Wang Chaoqun , Han Xiaolei , Liu Rui , Dong Yi , Song Lin , Cong Lin , Wang Yongxiang , Du Yifeng , Qiu Chengxuan
Published: July 2024

Prolonged ventricular repolarization has been associated with cardiovascular disease. We sought to investigate the association of prolonged ventricular repolarization with mild cognitive impairment (MCI) and the potential underlying neuropathological mechanisms in older adults. This cross-sectional study included 4328 dementia-free participants (age ≥ 65 years; 56.8% female) in the baseline examination of the Multidomain INterventions to delay dementia and Disability in rural China; of these, 989 undertook structural brain magnetic resonance imaging (MRI) scans. QT, QTc, JT, JTc, and QRS intervals were derived from 12-lead electrocardiograph. MCI, amnestic MCI (aMCI), and non-amnestic MCI (naMCI) were defined following the Petersen’s criteria. Volumes of gray matter (GM), white matter, cerebrospinal fluid, total white matter hyperintensities (WMH), periventricular WMH (PWMH), and deep WMH (DWMH) were automatically estimated. Data were analyzed using logistic and general linear regression models. Prolonged QT, QTc, JT, and JTc intervals were significantly associated with an increased likelihood of MCI and aMCI, but not naMCI (p < 0.05). In the MRI subsample, QT, QTc, JT, and JTc intervals were significantly associated with larger total WMH and PWMH volumes (p < 0.05), but not with DWMH volume. Statistical interactions were detected, such that prolonged QT and JT intervals were significantly associated with reduced GM volume only among participants with coronary heart disease or without APOE ε4 allele (p < 0.05). Prolonged ventricular repolarization is associated with MCI and cerebral microvascular lesions in a general population of older adults. This underlies the importance of cognitive assessments and brain MRI examination among older adults with prolonged QT interval.
Exploration and verification a 13-gene diagnostic framework for ulcerative colitis across multiple platforms via machine learning algorithms
Authors: Wang Jing , Li Lin , Chen Pingbo , He Chiyi , Niu Xiaoping
Published: July 2024

Ulcerative colitis (UC) is a chronic inflammatory bowel disease with intricate pathogenesis and varied presentation. Accurate diagnostic tools are imperative to detect and manage UC. This study sought to construct a robust diagnostic model using gene expression profiles and to identify key genes that differentiate UC patients from healthy controls. Gene expression profiles from eight cohorts, encompassing a total of 335 UC patients and 129 healthy controls, were analyzed. A total of 7530 gene sets were computed using the GSEA method. Subsequent batch correction, PCA plots, and intersection analysis identified crucial pathways and genes. Machine learning, incorporating 101 algorithm combinations, was employed to develop diagnostic models. Verification was done using four external cohorts, adding depth to the sample repertoire. Evaluation of immune cell infiltration was undertaken through single-sample GSEA. All statistical analyses were conducted using R (Version: 4.2.2), with significance set at a P value below 0.05. Employing the GSEA method, 7530 gene sets were computed. From this, 19 intersecting pathways were discerned to be consistently upregulated across all cohorts, which pertained to cell adhesion, development, metabolism, immune response, and protein regulation. This corresponded to 83 unique genes. Machine learning insights culminated in the LASSO regression model, which outperformed others with an average AUC of 0.942. This model's efficacy was further ratified across four external cohorts, with AUC values ranging from 0.694 to 0.873 and significant Kappa statistics indicating its predictive accuracy. The LASSO logistic regression model highlighted 13 genes, with LCN2, ASS1, and IRAK3 emerging as pivotal. Notably, LCN2 showcased significantly heightened expression in active UC patients compared to both non-active patients and healthy controls (P < 0.05). Investigations into the correlation between these genes and immune cell infiltration in UC highlighted activated dendritic cells, with statistically significant positive correlations noted for LCN2 and IRAK3 across multiple datasets. Through comprehensive gene expression analysis and machine learning, a potent LASSO-based diagnostic model for UC was developed. Genes such as LCN2, ASS1, and IRAK3 hold potential as both diagnostic markers and therapeutic targets, offering a promising direction for future UC research and clinical application.
Loss of dysbindin-1 in excitatory neurons in mice impacts NMDAR-dependent behaviors, neuronal morphology and synaptic transmission in the ventral hippocampus
Authors: Bhardwaj Sanjeev K. , Nath Moushumi , Wong Tak Pan , Srivastava Lalit K.
Published: July 2024

Dysbindin-1, a protein encoded by the schizophrenia susceptibility gene DTNBP1, is reduced in the hippocampus of schizophrenia patients. It is expressed in various cellular populations of the brain and implicated in dopaminergic and glutamatergic transmission. To investigate the impact of reduced dysbindin-1 in excitatory cells on hippocampal-associated behaviors and synaptic transmission, we developed a conditional knockout mouse model with deletion of dysbindin-1 gene in CaMKIIα expressing cells. We found that dysbindin-1 reduction in CaMKII expressing cells resulted in impaired spatial and social memories, and attenuation of the effects of glutamate N-methyl-d-asparate receptor (NMDAR) antagonist MK801 on locomotor activity and prepulse inhibition of startle (PPI). Dysbindin-1 deficiency in CaMKII expressing cells also resulted in reduced protein levels of NMDAR subunit GluN1 and GluN2B. These changes were associated with increased expression of immature dendritic spines in basiliar dendrites and abnormalities in excitatory synaptic transmission in the ventral hippocampus. These results highlight the functional relevance of dysbindin-1 in excitatory cells and its implication in schizophrenia-related pathologies.
A new nomogram based on ultrasound and clinical features for distinguishing epididymal tuberculosis and nontuberculous epididymitis
Authors: Liu Pengju , Gu Hai , Cai Guofeng , Qin Yong
Published: July 2024

Using ultrasound findings and clinical characteristics, we constructed and validated a new nomogram for distinguishing epididymal tuberculosis from nontuberculous epididymitis, both of which share similar symptoms. We retrospectively examined data of patients with epididymal tuberculosis and nontuberculous epididymitis hospitalized between January 1, 2013, and March 31, 2023. Eligible patients were randomly assigned to derivation and validation cohorts (ratio, 7:3). We drew a nomogram to construct a diagnostic model through multivariate logistic regression and visualize the model. We used concordance index, calibration plots, and decision curve analysis to assess the discrimination, calibration, and clinical usefulness of the nomogram, respectively. In this study, 136 participants had epididymal tuberculosis and 79 had nontuberculous epididymitis. Five variables—C-reactive protein level, elevated scrotal skin temperature, nodular lesion, chronic infection, and scrotal skin ulceration—were significant and used to construct the nomogram. Concordance indices of the derivation and validation cohorts were 0.95 and 0.96, respectively (95% confidence intervals, 0.91–0.98 and 0.92–1.00, respectively). Decision curve analysis of this nomogram revealed that it helped differentiate epididymal tuberculosis from nontuberculous epididymitis. This nomogram may help clinicians distinguish between epididymal tuberculosis and nontuberculous epididymitis, thereby increasing diagnosis accuracy.
Classification of brain tumor types through MRIs using parallel CNNs and firefly optimization
Authors: Li Chen , Zhang Faxue , Du Yongjian , Li Huachao
Published: July 2024

Image segmentation is a critical and challenging endeavor in the field of medicine. A magnetic resonance imaging (MRI) scan is a helpful method for locating any abnormal brain tissue these days. It is a difficult undertaking for radiologists to diagnose and classify the tumor from several pictures. This work develops an intelligent method for accurately identifying brain tumors. This research investigates the identification of brain tumor types from MRI data using convolutional neural networks and optimization strategies. Two novel approaches are presented: the first is a novel segmentation technique based on firefly optimization (FFO) that assesses segmentation quality based on many parameters, and the other is a combination of two types of convolutional neural networks to categorize tumor traits and identify the kind of tumor. These upgrades are intended to raise the general efficacy of the MRI scan technique and increase identification accuracy. Using MRI scans from BBRATS2018, the testing is carried out, and the suggested approach has shown improved performance with an average accuracy of 98.6%.
The association between 2D:4D digit ratio and sex-typed play in children with and without siblings
Authors: Ernsten Luisa , Körner Lisa M. , Heil Martin , Schaal Nora K.
Published: July 2024

The 2D:4D digit ratio is commonly used as a surrogate possibly reflecting prenatal testosterone levels. Indirect evidence comes from studies investigating the association between 2D:4D and human characteristics that likely relate to prenatal testosterone. In children, sex-typed play reveals large sex differences early in development and an influence of prenatal testosterone is likely. Findings on the association between 2D:4D and children’s sex-typed play are heterogeneous and other influences on the development of sex-typed play have been suggested, most of all social influences like siblings, their sex and birth order. The current study examined the association between right and left 2D:4D, a proposed surrogate for prenatal testosterone exposure, which was assessed in right and left hands of N = 505 6-month-old children, and sex-typed play behavior, which was evaluated 3.5 years later using the Pre-School Activities Inventory (PSAI), and the influence of siblings. To capture differential effects of siblings’ sex and birth order, dummy-coded variables were used reflecting having no siblings as well as older or younger sisters or brothers. Multiple regression models were used to investigate the association between PSAI scores and sex, right and left 2D:4D, being a singleton as well as having an older or younger sister or brother. It was shown that sex and having an older brother were significant predictors for sex-typed play. Effects were further disentangled by conducting separate regression analyses in boys and girls. In boys, a significant association between PSAI scores and having an older brother was revealed, in girls, no significant associations were found. Results are discussed highlighting the non-significant association between 2D:4D and children’s sex-typed play, which weakens the applicability of 2D:4D as a surrogate reflecting influences of prenatal T. Further, the importance of social factors like siblings on children’s sex-typed play is discussed.
An adjustable acoustic metamaterial cell using a magnetic membrane for tunable resonance
Authors: Gardiner Alicia , Domingo-Roca Roger , Windmill James F. C. , Feeney Andrew
Published: July 2024

Acoustic metamaterials are growing in popularity for sound applications including noise control. Despite this, there remain significant challenges associated with the fabrication of these materials for the sub-100 Hz regime, because acoustic metamaterials for such frequencies typically require sub-mm scale features to control sound waves. Advances in additive manufacturing technologies have provided practical methods for rapid fabrication of acoustic metamaterials. However, there is a relatively high sensitivity of their resonant characteristics to sub-mm deviations in geometry, pushing the limits of additive manufacturing. One way of overcoming this is via active control of device resonance. Here, an acoustic metamaterial cell with adjustable resonance is demonstrated for the sub-100 Hz regime. A functionally superparamagnetic membrane—devised to facilitate the fabrication process by eliminating magnetic poling requirements—is engineered using stereolithography, and its mechanical and acoustic properties are experimentally measured using laser Doppler vibrometry and electret microphone testing, with a mathematical model developed to predict the cell response. It is demonstrated that an adjustable magnetic acoustic metamaterial can be fabricated at ultra-subwavelength dimensions (

$$\le \lambda$$

≤
λ

/77.5), exhibiting adjustable resonance from 88.73 to 86.63 Hz. It is anticipated that this research will drive new innovations in adjustable metamaterials, including wider frequency ranges.
Exploring stroke discourse on Twitter through content and network analysis among Indian users
Authors: Ramamoorthy Thilagavathi , Kulothungan Vaitheeswaran , Mappillairaju Bagavandas
Published: July 2024

The study aimed to understand stroke-related Twitter conversations in India, focusing on topics, message sources, reach, and influential users to provide insights to stakeholders regarding community needs for knowledge, support, and interventions. Geo-tagged Twitter posts focusing on stroke originating from India and, spanning from November 7, 2022, to February 28, 2023, were systematically obtained via the Twitter application programming interface, using keywords and hashtags sourced through Symplur Signals. Preprocessing involved the removal of hashtags, stop words, and URLs. The Latent Dirichlet Allocation (LDA) topic model was used to identify recurring stroke-related topics, while influential users were identified through social network analysis. About half of the tweets about stroke in India were about seeking support and post-stroke bereavement sharing and had the highest reachability. Four out of 10 tweets were from the individual twitter users. Tweets on the topic risk factors, awareness and prevention (14.6%) constituted the least proportion, whereas the topic management, research, and promotion had the least retweet ratio. Twitter demonstrates significant potential as a platform for both disseminating and acquiring stroke-related information within the Indian context. The identified topics and understanding of the content of discussion offer valuable resources to public health professionals and organizations to develop targeted educational and engagement strategies for the relevant audience.
Enhancing tunnel crack detection with linear seam using mixed stride convolution and attention mechanism
Authors: Lang Lang , Chen Xiao-qin , Zhou Qiang
Published: July 2024

Cracks in tunnel lining structures constitute a common and serious problem that jeopardizes the safety of traffic and the durability of the tunnel. The similarity between lining seams and cracks in terms of strength and morphological characteristics renders the detection of cracks in tunnel lining structures challenging. To address this issue, a new deep learning-based method for crack detection in tunnel lining structures is proposed. First, an improved attention mechanism is introduced for the morphological features of lining seams, which not only aggregates global spatial information but also features along two dimensions, height and width, to mine more long-distance feature information. Furthermore, a mixed strip convolution module leveraging four different directions of strip convolution is proposed. This module captures remote contextual information from various angles to avoid interference from background pixels. To evaluate the proposed approach, the two modules are integrated into a U-shaped network, and experiments are conducted on Tunnel200, a tunnel lining crack dataset, as well as the publicly available crack datasets Crack500 and DeepCrack. The results show that the approach outperforms existing methods and achieves superior performance on these datasets.
Synergistic effect of benzo triazole with polyethoxylated sorbitan monooleate in inhibiting corrosion of rebars and chloride diffusion through mortars
Authors: Hussain Raja Rizwan , Alhozaimy Abdulrahman , Al-Negheimish Abdulaziz , Singh D. D. N. , Ahmed Mshtaq
Published: July 2024

It is found that mixture of 1,2,3 benzo triazole (BTAH) with polyethoxylated sorbitan monooleate, a non-ionic surface-active agent (NIS) effectively improves the properties of the cast concrete as well as significantly reduces the chloride induced corrosion of steel reinforced bars, when added in freshly prepared paste of mortar mixture. The addition of this mixture in the cast mortars is noted to reduce the water absorption in comparison to the control mortars cast using identical materials and under similar cast conditions. Electrochemical impedance spectroscopy and polarization studies of the rebars embedded in mortars and exposed in cement slurry have been performed to study the role of synergistic mixture on kinetics and mechanism of corrosion of rebars. The characterisation of corrosion products formed on the surface of rebars was carried out by X-ray diffraction, Scanning electron microscopy and EDX analysis. It is proposed that the synergistic boosting in protection is caused due to the shielding of NIS around anionic BTA−, thus minimizing their electrostatic repulsion. This facilitates the migration of additional ionic BTA towards the double layer which increases their concentration at the corroding interface leading to reduced susceptibility to corrosion.
Association between parental decisions regarding abortion and severity of fetal heart disease
Authors: Nakao Masahiro , Kuwabara Masanari , Saito Mika , Horiuchi Chinami , Morisaki Hiroko , Kishiki Kanako , Hamamichi Yuji , Orui Izumi , Ono Ryoko , Suzuki Ryo , Izawa Miho , Maeda Yoshiki , Ohmori Azumi , Uyeda Tomomi , Yazaki Satoshi , Yoshikawa Tadahiro , Wada Naoki , Hosoda Toru , Nii Masafumi , Tanaka Kayo , Tanaka Hiroaki , Kondo Eiji , Takahashi Yukihiro , Ikeda Tomoaki
Published: July 2024

The prenatal diagnosis of fetal heart disease potentially influences parental decision-making regarding pregnancy termination. Existing literature indicates that the severity, whether in complexity or lethality, significantly influences parental decisions concerning abortion. However, questions remain as to how fetal heart disease severity impacts parental decisions, given recent advancements in postsurgical outcomes. Therefore, we investigated risk factors associated with parents’ decision-making regarding abortion following a prenatal diagnosis of fetal heart disease. Our analysis included 73 (terminated: n = 37; continued: n = 36) pregnancies with a fetal heart disease diagnosed before 22 weeks of gestation. Increased gestational age at diagnosis reduced the likelihood of parents’ decision on termination (Model 1: adjusted odds ratio, 0.94; 95% confidence interval 0.89–0.99; Model 2: 0.95 0.90–0.997). Critical disease (5.25; 1.09–25.19) and concurrent extracardiac or genetic abnormalities (Model 1: 4.19, 1.21–14.53; Model 2: 5.47, 1.50–19.96) increased the likelihood of choosing abortion. Notably, complex disease did not significantly influence parental decisions (0.56; 0.14–2.20). These results suggest that parental decision-making regarding abortion may be influenced by earlier gestational age at diagnosis, the lethality of heart disease, and extracardiac or genetic abnormalities, but not its complexity if prenatal diagnosis and parental counseling are provided at a cardiovascular-specialized facility.
Neuropeptide natalisin regulates reproductive behaviors in Spodoptera frugiperda
Authors: Gong Wei , Linghu Jun-Hong , Xu Hui-Min , Luo Li-Lin , Smagghe Guy , Liu Tong-Xian , Gui Shun-Hua
Published: July 2024

Natalisin (NTL) is a conserved neuropeptide, only present in insects, that has been reported to regulate their sexual activity. In this study, we investigated the involvement of NTL in the reproductive behaviors of a major invasive pest, Spodoptera frugiperda. We identified NTL precursor-encoded transcripts, and evaluated their transcript levels in different stages and tissues of S. frugiperda. The results showed that the NTL transcript level was expressed in both male and female pupae and both male and female adults in the later stage. It was highly expressed in male pupae, 3-day-old male and female adults, and 5-day-old male adults. In different tissues, the expression level is higher in the male and female adult brain and male testis. Immunohistochemical staining of the brain of S. frugiperda female and male adults revealed that three pairs of brain neurons of S. frugiperda adults of both sexes secreted and expressed NTL. To study the role of NTL in reproductive behaviors, NTL was silenced in S. frugiperda male and female adults by RNA interference (RNAi) technology, the results showed that silencing NTL could significantly affect the sexual activity behavior of the adults, reducing the calling rate of females, the courtship rate of males, and the mating rate. In summary, this study emphasizes the important role of NTL in regulating the mating behavior and sexual activity of S. frugiperda in both male and female adults, potentially laying a foundation to employ NTL as a new insect-specific target to control populations of pest insects.
A method for calculating vector forces at human-mattress interface during sleeping positions utilizing image registration
Authors: Gao Ying , Zhang Jing , Zou Chengzhao , Bi Liwen , Huang Chengzhen , Nie Jiachen , Yan Yongli , Yu Xinli , Zhang Fujun , Yao Fanglai , Ding Li
Published: July 2024

The vector forces at the human-mattress interface are not only crucial for understanding the distribution of vertical and shear forces exerted on the human body during sleep but also serves as a significant input for biomechanical models of sleeping positions, whose accuracy determines the credibility of predicting musculoskeletal system loads. In this study, we introduce a novel method for calculating the interface vector forces. By recording indentations after supine and lateral positions using a vacuum mattress and 3D scanner, we utilize image registration techniques to align body pressure distribution with the mattress deformation scanning images, thereby calculating the vector force values for each unit area (36.25 mm × 36.25 mm). This method was validated through five participants attendance from two perspectives, revealing that (1) the mean summation of the vertical force components is 98.67% ± 7.21% body weight, exhibiting good consistency, and mean ratio of horizontal component force to body weight is 2.18% ± 1.77%. (2) the predicted muscle activity using the vector forces as input to the sleep position model aligns with the measured muscle activity (%MVC), with correlation coefficient over 0.7. The proposed method contributes to the vector force distribution understanding and the analysis of musculoskeletal loads during sleep, providing valuable insights for mattress design and evaluation.
Mosquitocidal toxin-like islands in Bacillus thuringiensis S2160-1 revealed by complete-genome sequence and MS proteomic analysis
Authors: Zhou Yan , Zhang Wenfei , Wan Yusong , Jin Wujun , Zhang Yan , Li Youzhi , Chen Baoshan , Jiang Mingguo , Fang Xuanjun
Published: July 2024

Here, we present the whole genome sequence of Bt S2160-1, a potential alternative to the mosquitocidal model strain, Bti. One chromosome genome and four mega-plasmids were contained in Bt S2160-1, and 13 predicted genes encoding predicted insecticidal crystal proteins were identified clustered on one plasmid pS2160-1p2 containing two pathogenic islands (PAIs) designed as PAI-1 (Cry54Ba, Cry30Ea4, Cry69Aa-like, Cry50Ba2-like, Cry4Ca1-like, Cry30Ga2, Cry71Aa-like, Cry72Aa-like, Cry70Aa-like, Cyt1Da2-like and Vpb4C1-like) and PAI-2 (Cyt1Aa-like, and Tpp80Aa1-like). The clusters appear to represent mosquitocidal toxin islands similar to pathogenicity islands. Transcription/translation of 10 of the 13 predicted genes was confirmed by whole-proteome analysis using LTQ-Orbitrap LC–MS/MS. In summary, the present study identified the existence of a mosquitocidal toxin island in Bacillus thuringiensis, and provides important genomic information for understanding the insecticidal mechanism of B. thuringiensis.
Characterising the Tasmanian devil (Sarcophilus harrisii) pouch microbiome in lactating and non-lactating females
Authors: Ockert Lucy E. , McLennan Elspeth A. , Fox Samantha , Belov Katherine , Hogg Carolyn J.
Published: July 2024

Wildlife harbour a diverse range of microorganisms that affect their health and development. Marsupials are born immunologically naïve and physiologically underdeveloped, with primary development occurring inside a pouch. Secretion of immunological compounds and antimicrobial peptides in the epithelial lining of the female’s pouch, pouch young skin, and through the milk, are thought to boost the neonate’s immune system and potentially alter the pouch skin microbiome. Here, using 16S rRNA amplicon sequencing, we characterised the Tasmanian devil pouch skin microbiome from 25 lactating and 30 non-lactating wild females to describe and compare across these reproductive stages. We found that the lactating pouch skin microbiome had significantly lower amplicon sequence variant richness and diversity than non-lactating pouches, however there was no overall dissimilarity in community structure between lactating and non-lactating pouches. The top five phyla were found to be consistent between both reproductive stages, with over 85% of the microbiome being comprised of Firmicutes, Proteobacteria, Fusobacteriota, Actinobacteriota, and Bacteroidota. The most abundant taxa remained consistent across all taxonomic ranks between lactating and non-lactating pouch types. This suggests that any potential immunological compounds or antimicrobial peptide secretions did not significantly influence the main community members. Of the more than 16,000 total identified amplicon sequence variants, 25 were recognised as differentially abundant between lactating and non-lactating pouches. It is proposed that the secretion of antimicrobial peptides in the pouch act to modulate these microbial communities. This study identifies candidate bacterial clades on which to test the activity of Tasmanian devil antimicrobial peptides and their role in pouch young protection, which in turn may lead to future therapeutic development for human diseases.
Density functional theory study of doped coronene and circumcoronene as anode materials in lithium-ion batteries
Authors: Geetha Sadasivan Nair Remya , Narayanan Nair Arun Kumar , Sun Shuyu
Published: July 2024

Density functional theory calculations are carried out to investigate the adsorption properties of Li+ and Li on twenty-four adsorbents obtained by replacement of C atoms of coronene (C24H12) and circumcoronene (C54H18) by Si/N/BN/AlN units. The molecular electrostatic potential (MESP) analysis show that such replacements lead to an increase of the electron-rich environments in the molecules. Li+ is relatively strongly adsorbed on all adsorbents. The adsorption energy of Li+ (Eads-1) on all adsorbents is in the range of − 42.47 (B12H12N12) to − 66.26 kcal/mol (m-C22H12BN). Our results indicate a stronger interaction between Li+ and the nanoflakes as the deepest MESP minimum of the nanoflakes becomes more negative. A stronger interaction between Li+ and the nanoflakes pushes more electron density toward Li+. Li is weakly adsorbed on all adsorbents when compared to Li+. The adsorption energy of Li (Eads-2) on all adsorbents is in the range of − 3.07 (B27H18N27) to − 47.79 kcal/mol (C53H18Si). Assuming the nanoflakes to be an anode for the lithium-ion batteries, the cell voltage (Vcell) is predicted to be relatively high (> 1.54 V) for C24H12, C12H12Si12, B12H12N12, C27H18Si27, and B27H18N27. The Eads-1 data show only a small variation compared to Eads-2, and therefore, Eads-2 has a strong effect on the changes in Vcell.
Risk of stress cardiomyopathy associated with selective serotonin reuptake inhibitors and serotonin and norepinephrine reuptake inhibitors: a real-world pharmacovigilance analysis
Authors: Tan Boyu , Chen Li , Yan Sulan , Pan Huijie , Zhang Jingxian , Wei Hongyan
Published: July 2024

Selective serotonin reuptake inhibitors (SSRIs) and serotonin and norepinephrine reuptake inhibitors (SNRIs) are reported to cause stress cardiomyopathy (SC). This study evaluated the association between SSRI/SNRI use and the occurrence of cardiomyopathy in the publicly available U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) database. Disproportionate analysis and likelihood ratio tests were used to identify risk associated with SSRIs or SNRIs and the incidence of SC, using data from between from 2012 to 2022 acquired from the FAERS database. The study identified 132 individual case safety reports (ICSRs) of SC associated with SSRIs or SNRIs. Venlafaxine (48%) and fluoxetine (27%) were the most common antidepressants of the ICSRs. Approximately 80% of SC cases were reported in females, with individuals aged 45–65 years identified as a high-risk population. Both venlafaxine (ratio-scale information component [RSIC] 2.54, 95% CI 2.06–3.04) and fluoxetine (RSIC 3.20, 95% CI 2.31–4.47) were associated with SC, with likelihood ratio estimates of 3.55 (p = 0.02) for venlafaxine and 4.82 (p = 0.008) for fluoxetine. The median time to cardiomyopathy onset was 20 days, with hospitalization reported in 48.33% of patients. Venlafaxine and fluoxetine were associated with SC risk, particularly in middle-aged women. Caution should be exercised when using SSRIs or SNRIs combined with other serotonergic medications.
Exploring self-reported visual function and vision-related anxiety in patients with RPGR-associated retinal degeneration
Authors: Gouveia Nuno , Chukwunalu Oluji , Oliveira Carolina , Alves C. Henrique , Silva Rufino , Murta Joaquim , Marques João Pedro
Published: July 2024

Variants in the retinitis pigmentosa GTPase regulator (RPGR) gene are responsible for the majority of X-linked retinitis pigmentosa cases, which not only affects male patients but also some heterozygous females. Vision-related disability and anxiety of patients with RPGR-associated retinal degeneration have never been explored before. This study aimed to evaluate self-reported visual function and vision-related anxiety in a Portuguese cohort of male and female patients with RPGR-associated retinal degeneration using two validated patient-reported outcome measures. Cross-sectional data of thirty-two genetically-tested patients was examined, including scores of the Michigan retinal degeneration questionnaire (MRDQ) and Michigan vision-related anxiety questionnaire. Patients were classified according to retinal phenotypes in males (M), females with male phenotype (FM), and females with radial or focal pattern. Both M and FM revealed higher rod-function and cone-function anxiety scores (p < 0.017). Most MRDQ disability scores were higher in M and FM (p < 0.004). Overall, positive correlations (p < 0.004) were found between every MRDQ domain and both anxiety scores. In RPGR-associated retinal degeneration, males and females with male phenotype show similar levels of increased vision-related anxiety and disability. Every MRDQ visual function domain showed a strong correlation with anxiety scores.
Research on the influencing factors of promoting flipped classroom teaching based on the integrated UTAUT model and learning engagement theory
Authors: Pan Yufan , He Wang
Published: July 2024

With the rapid advancement of educational technology, the flipped classroom approach has garnered considerable attention owing to its potential for enhancing students’ learning capabilities. This research delves into the flipped classroom teaching methodology, employing the Unified Theory of Acceptance and Use of Technology (UTAUT), learning engagement theory, and the 4C skills (comprising communication, collaboration, creativity, and critical thinking) to investigate its effects on learning capabilities. The research surveyed 413 students from three universities in Jiangxi Province, employing stratified random sampling. SPSS 24.0 and Amos were used for structural equation modeling and hypothesis testing analysis. The findings indicate that: (1) Performance expectancy, effort expectancy, and peer influence significantly enhance students’ learning engagement in the flipped classroom. (2) Students’ learning engagement in the flipped classroom notably promotes their learning capabilities. (3) Performance expectancy, effort expectancy, and peer influence can significantly boost learning capabilities by increasing learning engagement. (4) Personality traits significantly moderate the effect of peer influence on learning engagement, highlighting the crucial role of individual differences in learning. (5) The level of students’ learning engagement is differentially influenced by performance expectancy and peer influence across various academic disciplines. Ultimately, this research provides valuable insights for educational policymakers and guides improvements in teaching practices, collectively advancing educational quality and equity.
Defect detection of photovoltaic modules based on improved VarifocalNet
Authors: Jia Yanfei , Chen Guangda , Zhao Liquan
Published: July 2024

Detecting and replacing defective photovoltaic modules is essential as they directly impact power generation efficiency. Many current deep learning-based methods for detecting defects in photovoltaic modules focus solely on either detection speed or accuracy, which limits their practical application. To address this issue, an improved VarifocalNet has been proposed to enhance both the detection speed and accuracy of defective photovoltaic modules. Firstly, a new bottleneck module is designed to replace the first bottleneck module of the last stage convolution group in the backbone. This new module includes both standard convolution and dilated convolution, enabling an increase in network depth and receptive field without reducing the output feature map size. This improvement can help to enhance the accuracy of defect detection for photovoltaic modules. Secondly, another bottleneck module is also designed and used to replace the original bottleneck module used in the fourth stage convolution group of the backbone. This new module has smaller parameters than the original bottleneck module, which is useful to improve the defect detection speed of the photovoltaic module. Thirdly, a feature interactor is designed in the detection head to enhance feature expression in the classification branch. This helps improve detection accuracy. Besides, an improved intersection over union is proposed and introduced into the loss function to measure the difference between the predicted and ground truth boxes. This is useful for improving defect detection accuracy. Compared to other methods, the proposed method has the highest detection accuracy. Additionally, it also has a faster detection speed than other methods except for the DDH-YOLOv5 method and the improved YOLOv7 method.
Risk practices and awareness of leptospirosis amongst residents of Zaria, Nigeria
Authors: Udechukwu Collins Chimezie , Kudi Caleb Ayuba , Abdu Paul Ayuba , Mamman Paul Habila , Pilau Nicholas Nathaniel , Jolayemi Kelvin Olutimilehin , Okoronkwo Magdalene Ogbonneya
Published: July 2024

This study evaluated the level of risk practices and awareness of leptospirosis among residents of Zaria, Nigeria. A pre-tested questionnaires were administered via face-to-face interview to 100 residents. The data was analyzed using chi-square and multivariate analysis to identify risk factors for leptospirosis. The demography showed that the majority of the respondents were male, aged 21–40 years, and majorly crop farmers. The risk factors identified showed that males were 4.14 times more likely to be affected by leptospirosis (OR 4.14, 95% CI [1.93–5.37],p = 0.02) and the source of animal’s water was 5.56 times more likely to be contaminated byLeptospiraspp. (OR 4.14, 95% CI [2.88–8.03],p = 0.01) and these relationships were significant. The majority of respondents were not aware of the disease (OR 1.87, 95% CI [1.22–4.57],p = 0.01) with 78% of the respondents not sure of which of the animal species leptospirosis affected (OR 1.67, 95% CI [1.07–2.62],p = 0.02). This study has demonstrated the existence of risk behaviors, and paucity of knowledge about leptospirosis in the study area. It is therefore recommended to organize an enlightenment program and the need for protective clothing for individuals occupationally at risk of infection byLeptospiraspp.
Retrieval of hourly aerosol single scattering albedo over land using geostationary satellite data
Authors: Jiang Xingxing , Xue Yong , de Leeuw Gerrit , Jin Chunlin , Zhang Sheng , Sun Yuxin , Wu Shuhui
Published: July 2024

The single scattering albedo (SSA) of aerosol particles is one of the key variables that determine aerosol radiative forcing. Herein, an Algorithm for the retrieval of Single scattering albedo over Land (ASL) is proposed for application to full-disk data from the advanced Himawari imager (AHI) sensor flying on board the Himawari-8 satellite. In this algorithm, an atmospheric radiative transfer model known as the USM (the top of the atmosphere reflectance as the sum of Un-scattered, Single-scattered, and Multiple-scattered components) is used to calculate the SSA instead of predetermining the aerosol model; the USM is constrained by the surface bidirectional reflectance distribution function shape and aerosol optical depth (AOD) in the retrieval process. Combining two consecutive observations and a 2 * 2 pixel window, the optimal estimation algorithm is adopted to obtain the optimal solution for the aerosol SSA. These SSA results are evaluated by comparing with aerosol robotic network (AERONET) data. Linear regression shows that SSAASL = 0.60*SSSAERONET + 0.38, with a correlation coefficient (0.7284), mean absolute error (0.0319), mean bias error (0.00324), root mean square error (0.0427), and ~80.11% of the ASL SSA data within an uncertainty of ±0.05 of the AERONET data. A comparison of the ASL SSA products with collocated Himawari-8 SSA products (Version 03, officially released by the Japan Meteorological Agency (JMA), referred to herein as JMA SSA) shows that the accuracy of the ASL SSA is better than that of the JMA SSA products. For the SSA retrieval in large AODs (>0.4), the validation metrics vs. AERONET data are better.
A climatology of stratospheric gravity waves induced by tropical cyclones on the northwest Pacific Ocean
Authors: Wang Xu , Wang Yuan , Zhang Lifeng , Zhang Yun , Guan Jiping
Published: July 2024

A climatology of stratospheric gravity waves (SGWs) induced by tropical cyclones (TC-SGWs) is necessary for stratospheric aviation safety and accurate numerical weather prediction. Few previous works have characterized the climatology of TC-SGWs, and the relative importance of the source and background wind for TC-SGWs has not been clearly established. Here we present the distribution of TC-SGWs formed over the northwest Pacific Ocean based on 30 years of ERA5 reanalysis data. Using explainable artificial intelligence, we found the background wind in the lower stratosphere to be more important than TCs in controlling the distribution pattern of TC-SGWs. The background wind shear can influence the direction of TC-SGW propagation by refraction and filtering, which influences the distribution pattern of the TC-SGWs. The TC intensity only influences the TC-SGW intensity. Our results provide information on TC-SGW hotspots and suggest the importance of the background wind shear.
Emerging topological multiferroics from the 2D Rice-Mele model
Authors: Vergara Patricio , Sáez Guidobeth , Castro Mario , Allende Sebastián , Núñez Álvaro S.
Published: July 2024

We introduce a two-dimensional dimerized lattice model that reveals a remarkable feature: the emergence of a complex, non-trivial topological multiferroic phase marked by zero Berry curvature and a significant Berry connection that influences the model’s bulk topology. This model extends the one-dimensional Rice-Mele Hamiltonian model to explore polarization-dependent topological properties in a 2D Su-Schrieffer-Heeger lattice, providing a detailed framework for studying the impact of symmetry-breaking and spatially varying potentials on electronic and spin properties. The findings are particularly relevant for spintronics, offering a foundation for topologically robust and electrically controlled spin-conducting edge states, with implications for developing advanced spin-dependent transport devices.
Stomach as the target organ of Rickettsia heilongjiangensis infection in C57BL/6 mice identified by click chemistry
Authors: Wang Juan , Du Li-Feng , Zhang Ming-Zhu , Wei Wei , Chen Zi-Yun , Zhang Xu , Xiong Tao , Wang Zhen-Fei , Xia Luo-Yuan , Jiang Jia-Fu , Li Wen-Jun , Zhu Dai-Yun , Jia Na , Cao Wu-Chun
Published: July 2024

Spotted fever group rickettsiae (SFGR) are obligate intracellular bacteria that cause spotted fever. The limitations of gene manipulation pose great challenges to studying the infection mechanisms of Rickettsia. By combining bioorthogonal metabolism and click chemistry, we developed a method to label R. heilongjiangensis via azide moieties and achieved rapid pathogen localization without complex procedures. Moreover, we constructed a C57BL/6 mice infection model by simulating tick bites and discovered that the stomach is the target organ of R. heilongjiangensis infection through in vivo imaging systems, which explained the occurrence of gastrointestinal symptoms following R. heilongjiangensis infection in some cases. This study offers a unique perspective for subsequent investigations into the pathogenic mechanisms of SFGR and identifies a potential target organ for R. heilongjiangensis.