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Hotspot analysis of COVID-19 infection in Tokyo based on influx patterns

Multitude of glasses of water

Evidence of avian and human influenza A virus infection in farmed Siamese crocodiles (Crocodylus siamensis) in Thailand

Crocodilians are susceptible to a range of virus infection including influenza A virus (IAV). However, little is known about the ecology and epidemiology of IAV in crocodile species. This study aimed to investigate IAV infection in farmed Siamese crocodiles in central Thailand. We collected plasma samples and pharyngeal swab samples from Siamese crocodiles residing in 13 crocodile farms in 9 provinces of central Thailand during 2019. Additional archival plasma samples of Siamese crocodiles collected in 2012 and 2018 were also included in the study. Plasma samples were screened for influenza A antibodies by a hemagglutination inhibition (HI) assay and positive were evaluated by a cytopathic effect/hemagglutination based-microneutralization (MN) assay. Swab samples were tested for influenza viral RNA by a real-time RT-PCR assay targeting the influenza matrix (M) gene. Among 246 tested plasma samples, the overall seroprevalence of antibodies against IAV in farmed Siamese crocodiles was 17.5% (43/246). The most common hemagglutinin (HA) subtype was H2 (46.5%, 20/43) followed by H9 (39.5%, 17/43), human H1 (14%, 6/43) and H1 (7%, 3/43). Multiple HA subtypes were also detected in 7% (3/43) of infected crocodiles with combination of H1 and H2 subtypes. All 126 tested swab samples were negative for influenza viral RNA. In addition, we demonstrated the ability of wild-type IAV subtypes (H1, H2, H9 and human H1) to infect primary Siamese crocodile fibroblast cells. To our knowledge, this is the first report of serological evidences of avian and human IAV infection in Siamese crocodiles. Our findings highlighted the role of crocodile species in the ecology of IAV particularly the potential to serve as the reservoir or mixing vessel for the viruses that significantly threaten both human and animal health.

Elucidation of peptide screen for targeted identification of Yersinia pestis by nano-liquid chromatography tandem mass spectrometry

Deciphering the role of the MALT1–RC3H1 axis in regulating GPX4 protein stability

Ferroptosis, a unique form of iron-dependent cell death triggered by lipid peroxidation accumulation, holds great promise for cancer therapy. Despite the crucial role of GPX4 in regulating ferroptosis, our understanding of GPX4 protein regulation remains limited. Through FACS-based genome-wide CRISPR screening, we identified MALT1 as a regulator of GPX4 protein. Inhibition of MALT1 expression enhances GPX4 ubiquitination-mediated degradation by up-regulating the E3 ubiquitin ligase RC3H1. Using both rescue assays and functional genetic screening, we demonstrate that pharmacologically targeting MALT1 triggers ferroptosis in liver cancer cells. Moreover, we show that targeting MALT1 synergizes with sorafenib or regorafenib to induce ferroptosis across multiple cancer types. These findings elucidate the modulatory effects of the MALT1–RC3H1 axis on GPX4 stability, revealing a molecular mechanism that could be exploited to induce ferroptosis for cancer therapy.

A two-stage hybrid NSGA-III with BWO for path planning and task allocation in agricultural land preparation

Automated large-scale farmland preparation operations face significant challenges related to path planning efficiency and uniformity in resource allocation. To improve agricultural production efficiency and reduce operational costs, an enhanced method for planning land preparation paths is proposed. In the initial stage, unmanned aerial vehicles (UAVs) are employed to collect data from the field, which is then used to construct accurate farm models. For single-field operations, a path planning approach is developed that minimizes energy consumption. The approach combines the selection of optimal operational angles with the implementation of efficient turning strategies, aiming to achieve full coverage. In addressing the issue of scheduling multiple machines across multiple fields, a two-stage optimization method, referred to as the BNSGA-III algorithm, is introduced. This algorithm integrates the NSGA-III algorithm with Beluga Whale Optimization (BWO), adaptive parameter adjustment, and Adaptive Inversion Crossover (AIC). The proposed method tackles the inherent complexity of agricultural environments, balancing operational efficiency and resource allocation through multi-objective optimization. Experimental results demonstrate that, compared to random operation directions, the proposed method reduces the path length by 1.9% to 3.1%, decreases the turning frequency by 19.5% to 24.0%, and improves coverage by 1.0% to 1.4%. In the context of multi-machine scheduling, the BNSGA-III algorithm outperforms the NSGA-II, NSGA-III, and MOEA/D algorithms, achieving improvements in total travel distance (12.3% to 34.4%), path balance (60.9% to 66.2%), and workload distribution (78.7% to 92.9%). Further evaluation shows that BNSGA-III excels in key metrics such as convergence (IGD), solution quality (HV), and diversity (Spread), thereby confirming its superiority in solution quality, convergence, and diversity. The findings of this study provide strong support for the advancement of intelligent agriculture.

An optimized eDNA protocol for fish tracking in estuarine environments

CryoSeek II: Cryo-EM analysis of glycofibrils from freshwater reveals well-structured glycans coating linear tetrapeptide repeats

Despite the recent breakthrough in structure determination and prediction of proteins, the structural investigation of carbohydrates remains a challenge. Here, we report the cryo-EM analysis of a glycofibril found in the freshwater in the Tsinghua Lotus Pond. The fibril, which we name TLP-4, is made of a linear chain of tetrapeptide repeats coated with >4 nm thick glycans. In each repeat, two glycans are O-linked to a 3,4-dihydroxyproline and another glycan attaches to the adjacent Ser or Thr. The fibril structure is entirely maintained through glycan packing. Bioinformatic analysis confirms the conservation of the TLP-4 repeats across species, suggesting the existence of a large number of glycofibrils to be discovered. Our findings not only provide valuable insights into the structural roles of glycans in bio-assemblies but also demonstrate the potential of our recently formulated research strategy of CryoSeek to find bioentities and establish prototypes for structural studies of carbohydrates.

The impact of achievement goals on college students’ English performance—A moderated mediation model

The study investigated the relationship between learning engagement and achievement goals, and English performance among college students. With the increasing popularity of online teaching methods, exploring how different teaching modes (online and classroom teaching) might influence students’ learning outcomes is important. The researcher sought to understand how adopting different achievement goals such as mastery and performance-avoidance approaches could impact English performance and learning engagement. By examining this factor, the study aimed to provide insights into effective teaching strategies and interventions that could enhance students’ academic success in English language learning. The survey included 953 college students assessed using the Achievement Goal Questionnaire and Learning Engagement Scale. Their IELTS English scores were also recorded to study the relationship between learning engagement and achievement goals, and English performance. Additionally, the researcher utilized statistical analysis tools such as SPSS and the PROCESS Marco programme to explore the moderated mediation model and to uncover the complex relationships among the variables in the study. The results revealed that adopting a mastery approach positively influenced English performance, while the performance-avoidance approach negatively influenced English performance. Additionally, learning engagement partially mediated the connection between the mastery approach, performance-avoidance approach, and English performance. Teaching mode influenced the initial phase of the mediating effect between the mastery approach and English performance. More importantly, compared to online teaching, classroom teaching with a focus on mastery approach had a stronger predictive effect on learning engagement. Lastly, there was a moderated mediating effect between English achievement and the mastery approach, whereas the performance-avoidance approach showed a simple mediating effect on English achievement. The findings from this research could potentially inform educators and policymakers on how to optimize teaching practices to promote student engagement and improve English language proficiency.

Prediction analysis of human brucellosis cases in Ili Kazakh Autonomous Prefecture Xinjiang China based on time series

Stochastic morphological swings in <i>Hydra</i> regeneration: A manifestation of noisy canalized morphogenesis

Animal morphogenesis, the development of an organism’s body form, is commonly perceived as a directed and almost deterministic process. However, noise and stochastic fluctuations are ubiquitous in biological systems. The questions on the role of fluctuations in morphogenesis and what ensures the robustness of this process under noisy conditions remain elusive. Here, we utilize Hydra regeneration, subjected to an external electric field, to provide unique insights into these questions. We found that during Hydra morphogenesis, a phase can be induced where fluctuations lead to stochastic morphological swings, back and forth, between a nearly spherical structure (the incipient tissue’s state) and an elongated cylindrical shape (the final body form of a mature Hydra ). Despite these prolonged swings, the tissue regenerates into a normal Hydra . The stochastic transitions between two well-defined shapes imply that morphological development occurs through an activation process. Indeed, by introducing a periodic perturbation through modulation of the electric field, we were able to demonstrate morphogenesis dynamics with characteristics of stochastic resonance —the tissue’s response to the perturbation displayed a resonance-like behavior as a function of the noise level. Our findings add a dynamic layer to the problem of morphogenesis and offer an unconventional physical framework based on an activation transition in a slowly varying double-well potential that ensures a canalized regeneration of the body form under fluctuations.

Vaccine hesitancy among health paraprofessionals: A mixed methods study

Background The World Health Organization (WHO) defines vaccine hesitancy as “a delay in acceptance or refusal of vaccines despite availability of vaccination services”. Vaccine hesitancy has also been declared a top threat to global health. Some employers imposed vaccine mandates during the Covid-19 pandemic resulting in health care employees resigning or being fired rather than receive a vaccine. Healthcare paraprofessionals such as certified nursing assistants, dietary and home health aides are among the most patient facing of all health care providers. Their beliefs and attitudes about vaccines are critical to how they communicate about vaccines with their patients. Objective The objective of this project was to survey health care paraprofessionals to explore their thoughts and opinions about vaccines in general, and Covid-19 vaccines specifically. Methods This was a 25 question, mixed methods, cross sectional email survey. Subjects were recruited from the mailing list of a non-profit organization in the Midwest. This organization is dedicated to bringing a face and a voice to healthcare paraprofessionals engaged in direct patient care. Results Most respondents were reasonably well informed about vaccines; had received one or more doses of indicated vaccines; used credible resources to learn about vaccines and believed physicians and pharmacists were the most trusted information sources. Qualitative results indicated that respondents expressed support for vaccines but that the support was often qualified in that a respondent may have had both pro and anti-vaccine opinions in the same response. They also expressed that communications about vaccines were often problematic. Additional vaccine-related continuing professional development for healthcare paraprofessionals appears to be indicated. Conclusions Although attitudes towards vaccines were generally positive, respondents had concerns about the quality of vaccine information. Additional vaccine-related continuing professional development for healthcare paraprofessionals appears to be indicated.

Enhanced hemocompatibility, antimicrobial and anti-inflammatory properties of biomolecules stabilized AgNPs with cytotoxic effects on cancer cells

Daily briefing: Why did Europe’s first cities disappear? Uncovering the mysterious Cucuteni–Trypillia culture

Moiré magnetism and moiré excitons in twisted CrSBr bilayers

Moiré excitons and moiré magnetism are essential to semiconducting van der Waals magnets. In this work, we perform a comprehensive first-principles study to elucidate the interplay of electronic excitation and magnetism in twisted magnetic CrSBr bilayers. We predict a twist-induced quantum phase transition for interlayer magnetic coupling and estimate the critical twist angle below which moiré magnetism with mixed ferromagnetic and antiferromagnetic domains could emerge. Localized one-dimensional moiré excitons are stable if the interlayer coupling is ferromagnetic and become unstable if the coupling turns to antiferromagnetic. Exciton energy modulation by magnons is estimated and dependence of exciton oscillator strength on the twist angle and interlayer coupling is analyzed. An orthogonally twisted bilayer is revealed to exhibit layer-dependent, anisotropic optical transitions. Electric field is shown to induce net magnetic moments in moiré excitons, endowing them with exceedingly long lifetimes. Our work lays the foundation for using magnetic moiré bilayers in spintronic, optoelectronic, and quantum information applications.

Mobile Sleep Lab: Comparison of polysomnographic parameters with a conventional sleep laboratory

In remote areas, visiting a laboratory for sleep testing is inconvenient. We, therefore, developed a Mobile Sleep Lab in a bus powered by fuel cells with two sleep measurement chambers. As the environment in the bus could affect sleep, we examined whether sleep testing in the Mobile Sleep Lab was as feasible as in a conventional sleep laboratory (Human Sleep Lab). We tested 15 healthy adults for four nights using polysomnography (the first two nights at the Human Sleep Lab or Mobile Sleep Lab with a switch to the other facility for the next two nights). Sleep variables of the four measurements were used to assess the discrepancy of different places or different nights. No significant differences were found between the laboratories other than the percentage of total sleep time in stage N3. Next, we analyzed the intraclass correlation coefficient to evaluate the test-retest reliability. The intraclass correlation coefficient between these two measurements: the Human Sleep Lab and Mobile Sleep Lab showed similar reliability for the same sleep variables. The intraclass correlation coefficient revealed that several sleep indexes, such as total sleep time, sleep efficiency, wake after sleep onset, percentage of stage N1, and stage R latency, showed poor reliabilities (&lt;0.5) based on Koo and Li’s criteria. In contrast, the percentage of stage N3 showed moderate (0.5–0.75) or good (0.75–0.9) reliabilities. As almost all sleep variables showed no difference and same level of test-retest reliability between the Mobile Sleep Lab and Human Sleep Lab, the Mobile Sleep Lab might be suitable for conducting polysomnography as a conventional sleep laboratory. The reduction in N3 in the Mobile Sleep Lab should be scrutinized in the larger sample, including sleep disorders. Practical application of the Mobile Sleep Lab can transform sleep medicine in remote areas.

Numerical simulation of coal particle motion characteristics in the envelope region of spiral drum based on discrete element method

AbstractIn order to study the movement characteristics of coal particles in the coal loading process of spiral drums, the spiral drum of a certain type of shearer was taken as the research object, and the intrinsic parameters of the materials were calibrated through the determination results of coal sample properties, the relevant parameters of coal particle adhesion were determined, and a discrete element model of spiral drum coal loading was established. The distribution of coal particle movement subsequent to the fracture of the coal wall was derived through simulation. By spatially dividing the envelope region of the spiral drum along the radial and axial directions, the number and velocity distribution of coal particles in different envelope regions were obtained. The study revealed that the number of coal particles in radial regions III and IV was significantly higher than that in regions I and II. Most of the coal particles in regions III and IV moved outward along the drum axis under the action of the spiral blades, while a small portion moved from regions III and IV towards regions I and II. The coal particles in the axial region near the outer side of the coal wall have a strong ability to flow towards the scraper conveyor, and the probability of coal particles being thrown towards the rear of the spiral drum is higher in the region near the end plate. The increase in traction speed has little effect on the velocity of coal particles in all directions within the envelope region, while the increase of drum rotation speed can significantly improve the velocity of coal particles in each region. Through statistical analysis, it was found that the coal loading rate decreases with the increasing of traction speed. As the drum speed increases, the coal loading rate first increases and then decreases. By comparing the results of industrial experiments and numerical simulations underground, the accuracy of the discrete element method used in this paper to analyze the particle motion in the envelope region of the spiral drum has been confirmed. The research results provide reference for the selection of motion parameters of coal shearer and the improving of coal loading efficiency of spiral drums.

Molecular basis of Spns1-mediated lysophospholipid transport from the lysosome

Spns1 mediates the rate-limiting efflux of lysophospholipids from the lysosome to the cytosol. Deficiency of Spns1 is associated with embryonic senescence, as well as liver and skeletal muscle atrophy in animal models. However, the mechanisms by which Spns1 transports lysophospholipid and proton sensing remain unclear. Here, we present a cryogenic electron microscopy structure of human Spns1 in lysophosphatidylcholine (LPC)-bound lumen-facing conformation. Notably, LPC snugly binds within the luminal-open cavity, where the molecular dynamics simulations reveal that LPC presents a propensity to enter between transmembrane-helices (TM) 5 and 8. Structural comparisons and cell-based transport assays uncover several pivotal residues at TM 5/8 that orchestrate the transport cycle, which are unique to Spns1. Furthermore, we identify a five-residue network that is crucial for proton-sensing by Spns1. Transference of these network residues to Spns2, a sphingosine-1-phosphate uniporter, causes the chimeric Spns2 to be low pH dependent. Our results reveal molecular insights into lysosomal LPC transport and the proton-sensing mechanism by Spns1.

Fault tolerance in distributed systems using deep learning approaches

Recently, distributed systems have become the backbone of technological development. It serves as the foundation for new trends technologies such as blockchain, the internet of things and others. A distributed system provides fault tolerance and decentralization, where a fault in any component does not result in a whole system failure. In addition, deep learning model enables processing data to find patterns, which helps in classification, regression, prediction, and clustering. This work employs deep learning to handle faults within distributed systems in three scenarios. Firstly, a faulty processor may not be able to produce the right output. Therefore, deep learning model uses the inputs and outputs of other processors to find patterns and produces the proper output of the faulty processor. Secondly, if a faulty possessor corrupts its inputs as well, then the deep learning model learns from the inputs and the outputs of successful processors and produces the proper output of the faulty processor, even with corrupted inputs. Thirdly, for unrelated data, in which the patterns of the input of the faulty processors differ from the patterns of the inputs of successful ones. In this case, the model is able to discover the new pattern and to be labeled as unknown. In the experiments, we use deep learning models like VGG16, VGG19, AlexNet LSTM and ResNet34, to investigate the performance of the deep learning in the three mentioned scenarios. For unstructured datasets, the accuracy of the models is affected by the size of the faulty data. The accuracy of all models lies between 60% when the size of the faulty data is 90%, and 96%, when the size of the faulty data is 90%. The structured datasets are not significantly affected by the portion of the faulty data and the accuracy reaches 99%.

Identification of new reference genes with stable expression patterns for cell cycle experiments in human leukemia cell lines

AbstractCell cycle-dependent gene expression analysis is particularly important as numerous genes show tightly regulated expression patterns at different phases of the cell cycle. For cancer cells, analysis of cell cycle-related events is of paramount significance since tumorigenesis is characteristically coupled to cell cycle perturbations. RT-qPCR is a highly sensitive technique to investigate cell cycle-dependent transcriptional regulation. However, for reliable evaluation of qPCR data reference genes with stable mRNA expression are required. Although several studies investigating cell cycle-dependent gene expression employ frequently used reference genes, the suitability of these reference genes has not been thoroughly investigated so far. Moreover, such potential reference genes for cell cycle analysis have not been described in the literature. Therefore, we aimed to identify reference genes characterized with stable expression throughout the cell cycle in MOLT4 and U937 human leukemia cell lines synchronized with RO-3306 CDK1 inhibitor using RT-qPCR. Here we show that for cell cycle-dependent gene expression analysis the commonly used TBP is suitable, while the recently recognized reference genes SNW1 and CNOT4 are applicable in a cell line-dependent manner. We also suggest that proper selection of reference genes for each experimental condition is crucial for reliable normalization as these aspects can severely compromise conclusions.