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The role of oxidative stress-related genes in idiopathic pulmonary fibrosis
A glucose-enriched lung pre-metastatic niche triggered by matrix stiffness-tuned exosomal miRNAs in hepatocellular carcinoma
Altered resting-state amplitudes of low-frequency fluctuations in offspring of parents with a diagnosis of bipolar disorder or major depressive disorder
Offspring of parents with bipolar disorder (BD) or major depressive disorder (MDD) are at high biological risk (HR) of these disorders given their significant heritability. Thus, studying neural correlates in youths at HR-MDD and HR-BD appears essential to understand the development of mood disorders before their onset. Resting-state amplitudes of low-frequency fluctuations (ALFF) and fractioned ALFF (fALFF) shows moderate to high test-retest reliability which makes it a great tool to identify biomarkers. However, this avenue is still largely unexplored. Using the Healthy Brain Network biobank, we identified 150 children and adolescents HR-MDD, 50 HR-BD and 150 not at risk of any psychiatric disorder (i.e., the control group). We then examined differences in relative ALFF/fALFF signals during resting-state. At a corrected threshold, participants HR-MDD displayed lower resting-state ALFF signals in the dorsal caudate nucleus compared to the control group. The HR-BD group showed increased fALFF values in the primary motor cortex compared to the control group. Therefore, robust differences were noted in regions that could be linked to important symptoms of mood disorders, namely psychomotor retardation, and agitation. At an uncorrected threshold, differences were noted in the central opercular cortex and the cerebellar. The database is a community-referred cohort and heterogeneous in terms of children’s psychiatric diagnosis and symptomatology, which may have altered the results. ALFF and fALFF results for the comparison between both HR groups and the control group overlapped, suggesting good convergence. More studies measuring ALFF/fALFF in HR are needed to replicate these results.
Future climate change and the distributional shift of the common vampire bat, Desmodus rotundus
Abstract Interactions among humans, livestock, and wildlife within disturbed ecosystems, such as those impacted by climate change, can facilitate pathogen spillover transmission and increase disease emergence risks. The study of future climate change impacts on the distribution of free-ranging bats is therefore relevant for forecasting potential disease burden. This study used current and future climate data and historic occurrence locations of the vampire bat species Desmodus rotundus, a reservoir of the rabies virus to assess the potential impacts of climate change on disease reservoir distribution. Analyses included a comprehensive comparison of different climate change periods, carbon emission scenarios, and global circulation models (GCMs) on final model outputs. Models revealed that, although climatic scenarios and GCMs used have a significant influence on model outputs, there was a consistent signal of range expansion across the future climates analyzed. Areas suitable for D. rotundus range expansion include the southern United States and south-central portions of Argentina and Chile. Certain areas in the Amazon Rainforest, which currently rests at the geographic center of D. rotundus’ range, may become climatically unsuitable for this species within the context of niche conservatism. While the impacts of rabies virus transmitted by D. rotundus on livestock are well known, an expansion of D. rotundus into novel areas may impact new mammalian species and livestock with unexpected consequences. Some areas in the Americas may benefit from an assessment of their preparedness to deal with an expected D. rotundus range expansion.
Correction for Sun et al., JFK, a Kelch domain-containing F-box protein, links the SCF complex to p53 regulation
Doublecortin restricts neuronal branching by regulating tubulin polyglutamylation
Analysis of the network structure characteristics and influencing factors of regional tourism economy
The tourism economic network is a crucial factor influencing regional tourism interrelations and economic behaviors. This study selects Sichuan Province, China, as the research area and employs social network analysis to evaluate the spatial network structure of its tourism economy from 2015 to 2022. Additionally, the Quadratic Assignment Procedure (QAP) analysis method is used to explain the influencing factors of the tourism economic spatial network structure. The results show that: (1) The volume of regional tourism economic connections is on a rapid growth trajectory, with the radiation capacity and spillover effects of core node areas continuously strengthening. (2) The density of spatial networks in regional tourism economics remains low, showing a trend from loose to tight connections, essentially forming a spatial distribution pattern of “one axis with multiple branches” in tourism economic connections. (3) There are differences in the centrality of tourism economic connection networks among various cities and prefectures within the region, with differing statuses and roles in the tourism economic spatial network. (4) Geographic proximity, tourism resource endowment, economic development levels, and tourism reception capacity positively promote inter-regional tourism economic connections, while the shortest road distance negatively impacts regional tourism economic connections.
Application of in-silico docking for green electrochemical quantification of prucalopride succinate in pharmaceutical, urine, and milk matrices
Abstract The development of ion-selective sensors as green and energy-efficient substitutes is a promising trend in today’s analytical techniques. So, three distinct polyvinyl chloride sensors modulated by ionophores of cyclodextrins (α-, β-, and γ-cyclodextrins) were built, and their composition was optimized for rapid in-situ estimation of prucalopride succinate in different matrices. The experimental work was backed up by applying molecular docking, whose results were consistent with the practical findings, offering a creative strategy to reduce the experiment’s costs and duration. According to findings, the α-cyclodextrin sensor outperformed the other proposed sensors in terms of Nernstian slope (56.87 mV/decade), linearity range (1 × 10−6 M – 1 × 10−2 M), and detection limit (7.50 × 10−7 M). For the first time and with minimal sample pre-treatment, prucalopride was quantified with excellent recoveries in dissolution media, human urine, and formula milk samples employing the proposed α-cyclodextrin sensor. The proposed three sensors were validated following IUPAC guidelines. The proposed technique, represented by the proposed three sensors, has the following merits: high sample throughput, quick analysis, high selectivity, wide linearity ranges, and low detection limits, making it apt for routine prucalopride assessment, either in QC centers or in bioavailability units, at the most affordable price. Concerning the statistical assessment, there weren’t palpable disparities in functioning between the suggested technique and the published one. Concerning green assessment, the proposed technique surpassed the published techniques in both GAPI and analytical eco-scale metrics.
Scalable production of muscle and adipose cell-laden microtissues using edible macroporous microcarriers for 3D printing of cultured fish fillets
An integrated approach for advanced vehicle classification
This study is dedicated to addressing the trade-off between receptive field size and computational efficiency in low-level vision. Conventional neural networks (CNNs) usually expand the receptive field by adding layers or inflation filtering, which often leads to high computational costs. Although expansion filtering was introduced to reduce the computational burden, the resulting receptive field is only a sparse sampling of the tessellated pattern in the input image due to the grid effect. To better trade-off between the size of the receptive field and the computational efficiency, a new multilevel discrete wavelet CNN model (DWAN) is proposed in this paper. The DWAN introduces a four-level discrete wavelet transform in the convolutional neural network architecture and combines it with Convolutional Block Attention Module (CBAM) to efficiently capture multiscale feature information. By reducing the size of the feature maps in the shrinkage subnetwork, DWAN achieves a wider sensory field coverage while maintaining a smaller computational cost, thus improving the performance and efficiency of visual tasks. In addition, this paper validates the DWAN model in an image classification task targeting fine categories of automobiles. Significant performance gains are observed by training and testing the DWAN architecture that includes CBAM. The DWAN model can identify and accurately classify subtle features and differences in automotive images, resulting in better classification results for the automotive fine-grained category. This validation result further demonstrates the effectiveness and robustness of the DWAN model in vision tasks and lays a solid foundation for its generalization to practical applications.
Integrative morphological, phytochemical, and molecular identification of three invasive and medicinal Reynoutria species
Abstract The three highly invasive Reynoutria species – R. japonica Houtt., Reynoutria sachalinensis (F.Schmidt) Nakai, and a hybrid of them – R. x bohemica J. Chrtek & A. Chrtková are rich sources of biologically active compounds. However, only R. japonica is accepted as an herbal drug source in the pharmacopeias as Polygoni cuspidati rhizoma et radix , while R. sachalinensis is used in folk phytotherapy. The hybrid species can be misidentified as R. japonica due to its morphological resemblance. This study intended to explore genetic identity, diversity, and population structure using sequence-related amplified polymorphisms (SRAP) and start codon targeted (SCoT) markers correlated with morphological characteristics and metabolic profiles in fifteen accessions of Reynoutria species from invasive populations in Central Europe (Wroclaw, south-west Poland). The results suggest that morphological identification based on leaf morphology is clear for R. sachalinensis but fails to distinguish between R. japonica and R . × bohemica unambiguously. The qualitative HPLC/DAD/ESI-HR-QTOF-MS analysis determined the chemical composition of collected samples, revealing 117 compounds belonging to carbohydrates, stilbenes, flavan-3-ols, procyanidins, anthraquinones, organic acids, and naphthalenes. Out of these, the six compounds were quantitated. Based on LC-MS data for 117 compounds, the cluster analysis categorized the fifteen accessions into two distinctive clusters. All SCoT and SRAP markers showed medium (0.1 to 0.25) to high (0.30 to 0.40) levels of PIC, high levels of polymorphic bands (85 and 89%, respectively) and relatively high mean values for Rp (6.42 and 7.0) and were considered informative and differentiating. Partitioning the genetic diversity with AMOVA showed that variation within the populations was higher than among them, as seen in the combined data from SCoT and SRAP (53.04% vs. 46.96%, respectively) and the analyses of individual markers. Genetic diversity indices revealed that chosen genetic markers efficiently assess the variability within the genus Reynoutria . Na varied from 1.57 in R. sachalinensis to 3.34 in R. x bohemica , and Ne was low and almost identical for all species (~ 1.6). Nei’s diversity (H) indicated low genetic diversity (< 0.2) in all species, with the highest value for hybrid (0.184). Despite low H values, Shannon’s index (I) remains high and similar ( R. japonica − 5.21, R. x bohemica – 5.28, and R. sachalinensis − 5.45). The number (NPL) and percentage of polymorphic loci (PPL) for the hybrid (160 and 52.98%) were almost twice as high as for the parent species. The populations exhibited moderate G ST values (0.159) and a gene flow (Nm = 1.317). Genetic structure analysis with the Evanno test (ΔK = 2) reveals two genetic groups with the highest admixture in the hybrid population. The cluster analysis dendrograms based on LC-MS data, genetic distance, and leaf morphology categorized the fifteen accessions into three clusters, revealing unequivocal separation of the R. sachalinensis from both other taxa. According to Baker’s methodology, the highest correlation between dendrograms was observed between genetic and morphological data, with values of 0.85. Lower correlations were noted between molecular markers and phytochemical profile, as well as between morphology and phytochemical profile. The study suggests the effectiveness of combined morphological, phytochemical, and SCoT and SRAP molecular marker systems in assessing the identity of plant material. This approach can also be used in further studies on the population structure, spread, diversity, and evolution of invasive species such as Reynoutria spp.
Phase transformation in lead titanate based relaxor ferroelectrics with ultra-high strain
Abstract The reverse piezoelectric effect allows for the conversion of an electrical input signal into mechanical displacement and forms the basis for the operation of positioners and actuators. Addressing the practical need for cost-effective sensitive materials, we introduce erbium-doped lead magnesium niobium titanate ceramics which exhibit exceptionally high strain (3.19% bipolar and 0.8% unipolar) under a very low applied field of 2 kV mm−1, resulting in record-breaking piezoelectric coefficients (d 33* values of 15,950 and 4014 pm V−1, respectively). These exceptional properties stem from a combination of factors including the sensitivity of polar nanoregions to the applied field in this relaxor ferroelectric system, the thickness of the sample, and the energetic availability of polymorphs with different polar structures where a change in polarisation direction occurs at the field induced phase transition. Surpassing the performance of single crystal materials, our findings establish a benchmark in piezoelectric performance with implications for many diverse applications.
Investigation of severe dengue outbreak in Maumere, East Nusa Tenggara, Indonesia: Clinical, serological, and virological features
Background Dengue, an acute febrile disease caused by dengue virus (DENV) infection, is endemic to Indonesia. During early 2020, an outbreak of severe dengue occurred in Maumere, East Nusa Tenggara province, a region with low dengue endemicity with limited data on the characteristics of the circulating DENV. By 18 March 2020, 1396 cases were reported with 14 fatalities. Investigation was conducted to understand the cause and characteristics of the outbreak. Methods Sera were collected from 133 patients with dengue-like symptoms through random sampling at TC Hillers Hospital, Maumere during outbreak between February and June 2020. Dengue was confirmed using NS1 and/or RT-PCR detection. Serological status was determined using IgG/IgM ELISA and plaque reduction neutralization test (PRNT). DENV serotyping and genome sequencing were performed to identify the DENV serotype and genotype. Results We recruited suspected dengue patients attending the hospital during the outbreak. Dengue was confirmed in 72.2% (96/133), while 18.8% (25/133) were diagnosed as probable dengue. Children under 18 years old accounted for 85.1% (103/121) of dengue cases. Severe dengue accounted for 94.2% (81/86) of cases. Secondary infections made up 92.6% (112/121) of cases. Serotyping detected 87.3% (62/71) as DENV-3, 7.0% (5/71) as DENV-4, 2.8% (2/71) as DENV-1, and 2.8% (2/71) as DENV-2. Phylogenetic analysis revealed close evolutionary relationship of Maumere DENV to viruses from other Indonesian regions, especially Bali and Kupang. PRNT on DENV-3 secondary infections patients detected the presence of DENV-2 and DENV-4 neutralizing antibodies. Conclusion The severe dengue outbreak in Maumere is caused by DENV-3 introduced from nearby islands. The high proportion of secondary infections likely contributes to the severity of the disease. The high percentage of anti-dengue neutralizing antibodies for multiple serotypes and the high proportion of anti-dengue IgG in young children suggests a history of dengue transmission with a high infection rate in the area.
Non-dikarya fungi share the TORC1 pathway with animals, not with Saccharomyces cerevisiae
Abstract Target of rapamycin (TOR), discovered in Saccharomyces cerevisiae, is a highly conserved serine/threonine kinase acting as a regulatory hub between the cell and its environment. Like mammals, in fungi, the TOR complex 1 (TORC1) pathway is essential for coordinating cell growth in response to nutrient availability. The activation of TORC1 is similar in yeast and mammals, while its inhibition is more complex in mammals. This divergence of TORC1 regulation opens the question of how common are the yeast and mammalian variants in the fungal kingdom. In this work, we trace the evolutionary history of TORC1 components throughout the fungal kingdom. Our findings show that these fungi contain the mammalian-specific KICSTOR complex for TORC1 inhibition. They also possess orthologs of serine, arginine and methionine sensors of TORC1 pathway that orchestrate the response to nutrient starvation in mammals. The Rheb-TSC mediated activation of mammalian TORC1 that was lost in Saccharomycotina was also conserved in non-Dikarya. These findings indicate that the TORC1 pathway in non-Dikarya fungi resembles mammalian TORC1. Saccharomycotina lost many of the inhibitory components and evolved alternate regulatory mechanisms. Furthermore, our work highlights the limitations of using S. cerevisiae as a fungal model while putting forward other fungi as possible research models.
Statistical framework for calling allelic imbalance in high-throughput sequencing data
Deformation monitoring and safety stability evaluation study of high-altitude limestone dumps
We employed synthetic aperture radar interferometry (InSAR) to assess the slope stability of a high-altitude landfill in Sangri County, Shannan, Tibet. To address the unique climatic conditions of high-altitude regions, the InSAR deformation monitoring model was enhanced to mitigate the effects of temperature and rainfall. The accuracy of InSAR monitoring in high-elevation slopes was validated by comparison with GNSS RTK measurements. Both Differential Interferometric Synthetic Aperture Radar (D-InSAR) and Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) techniques were applied to monitor and evaluate slope deformation at the landfill site. The findings indicate that the average error between the improved InSAR model and GNSS measurements is 0.28 mm, with no statistically significant difference. The maximum slope displacement exceeds 20 mm when rainfall exceeds 300 mm, reaching the blue warning threshold. From 2018 to 2022, the deformation rate of the high-altitude landfill ranged from 0 to − 9.00 mm/a, classified as slip category VII. Significant deformation was observed during the rainy season, while the slope remained stable during dry periods, suggesting that rainfall is a primary trigger for slope deformation. A certain hysteresis effect in the deformation response to rainfall was also identified. The results demonstrate that InSAR technology offers comprehensive and dynamic monitoring capabilities for high-altitude slopes and serves as an effective tool for slope stability management in challenging environments.
The relationship between estimated glucose disposal rate and cognitive function in older individuals
Monosaccharides drive Salmonella gut colonization in a context-dependent or -independent manner
Abstract The carbohydrates that fuel gut colonization by S. Typhimurium are not fully known. To investigate this, we designed a quality-controlled mutant pool to probe the metabolic capabilities of this enteric pathogen. Using neutral genetic barcodes, we tested 35 metabolic mutants across five different mouse models with varying microbiome complexities, allowing us to differentiate between context-dependent and context-independent nutrient sources. Results showed that S. Typhimurium uses D-mannose, D-fructose and likely D-glucose as context-independent carbohydrates across all five mouse models. The utilization of D-galactose, N-acetylglucosamine and hexuronates, on the other hand, was context-dependent. Furthermore, we showed that D-fructose is important in strain-to-strain competition between Salmonella serovars. Complementary experiments confirmed that D-glucose, D-fructose, and D-galactose are excellent niches for S. Typhimurium to exploit during colonization. Quantitative measurements revealed sufficient amounts of carbohydrates, such as D-glucose or D-galactose, in the murine cecum to drive S. Typhimurium colonization. Understanding these key substrates and their context-dependent or -independent use by enteric pathogens will inform the future design of probiotics and therapeutics to prevent diarrheal infections such as non-typhoidal salmonellosis.
Spatio-temporal analysis of human brucellosis distribution in Neyshabur, Iran from 2015 to 2022, a cross-sectional study
Background Human brucellosis is a global endemic disease and a significant public health concern. This cross-sectional study aims to explore the characteristics of human brucellosis, as well as its spatial and temporal clustering. Methods This cross-sectional study analyzed the population infected with human brucellosis in Neyshabur, Iran from 2015 to 2022. Data were obtained from the Neyshabur health center. Spatial analysis was conducted using Anselin Local Moran’s I and Global Moran’s I with ArcGIS 10.8.2. Descriptive statistical analyses were performed using SPSS 26. Results During the study period, a total of 4568 brucellosis patients were reported. The incidence of disease was higher in men with 55.37%. The majority of patients belonged to the 30 to 39-year-old age group. Temporal clustering analysis revealed a peak incidence between March and June. The highest incidence rates were observed in spring and summer, with 34.76% and 33.84% of cases, respectively. Spatial clustering analysis indicated a higher prevalence in the southern and southeast districts of Neyshabur. The results of Global Moran’s I analysis indicated that the distribution of brucellosis was not clustered in Neyshabur (P-value > 0.05). Conclusion The findings of this study highlight the importance of educational programs for mothers and animal vaccination strategies, particularly in the months leading up to the peak brucellosis season in high-incidence areas. Further research is needed to assess the coverage of livestock vaccination and its impact on human brucellosis rates.