Prognosis factors of respiratory syncytial virus reinfection in hospitalized pediatric inpatients: A retrospective cohort study

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf Herbivory is one of the main biotic processes modulating plant diversity and productivity. In tropical forests, insects may remove up to 30% of total leaf biomass, but the effects on vegetation structure/productivity and biodiversity are poorly understood. Insect herbivory might promote or suppress plant growth, first reducing the photosynthetic area but also providing a rather direct path from nutrients in leaves to the plant-available soil pool. In this study, we used a trait-based Dynamic Global Vegetation Model (LPJ-GUESS-NTD), parameterized with unique field data from a tropical mountain forest gradient in southern Ecuador, to analyze how observed leaf-trait dependent insect herbivory influences the functional diversity and productivity of vegetation. According to the model, insect herbivory decreases net primary production by 6% and vegetation carbon storage by 26%. Herbivory also causes a vegetation community trait shift related to the leaf and wood economic spectrum, since with it specific leaf area (SLA) is reduced by 34% and wood specific gravity (WSG) increases by 10% respectively. This herbivory-induced change implies a shift towards a vegetation community with more conservative growth strategies, with negative effects on litter quality and nutrient availability. Accordingly, and in contrast to our expectations, herbivory reduces nutrient availability in the model. Finally, the inclusion of herbivory re-enforces gradients in nutrient availability and increases the community trait dissimilarity across altitudes (beta diversity). Our results suggest that insect herbivory has profound negative impacts on vegetation productivity and biomass in our study area, partly driven through feedbacks between soil processes and changes in plant traits. Furthermore, insect herbivory might be an important factor in shaping vegetation functional diversity.

Microbial interactions evolve simultaneously with the evolution of microorganisms. Although building Earth co-occurrence network offers valuable insights into the complex connectivity of the global microbiome, the evolutionary feature of these networks remains largely uncharacterized. Here, we simulated the evolution of the Earth microbial co-occurrence network using the Earth Microbiome Project datasets. We found that the Earth microbial co-occurrence network evolved following the Bianconi-Barabasi model, suggesting that inherent traits of microbial taxa shaped potential interaction patterns in microbial communities. The estimated degree growth exponent (β) was the major determinant of accumulated degree of taxa. The positive correlation between β and genome sizes suggested that genome sizes regulated the evolution of the Earth microbial co-occurrence network. The gamma distribution of β suggested that the taxa with low topological fitness were prone to extinction, even though link acquisition by hub nodes was not affected by node extinction and decay. This study provides a framework for predicting evolution trends of microbial co-occurrence network and sheds light on the evolutionary features of the Earth microbial co-occurrence network.

Accurately predicting gross primary productivity (GPP) is crucial for understanding carbon cycling; however, many studies have predominantly investigated GPP using environmental metrics, overlooking the pivotal role of functional traits as intermediaries between environment and GPP and the predictive potential of GPP. Therefore, this study proposes and employed a three-dimensional ”engine” framework to predict GPP and tested it by leveraging functional traits from 2040 plant communities on the Tibetan Plateau, incorporating environmental factors and the length of the plant growing season. Our results challenged the conventional emphasis that the environment plays a predominant role in predicting GPP dynamics, showing that while the environment exerts a minor direct effect, density traits of leaf and length of plant growing season significantly contributed to GPP predictions. With a prediction accuracy close to 0.90, this study underscores the feasibility of the three-dimensional engine framework in GPP prediction However, incorporating nitrogen-to-phosphorus ratio to the framework diminished the model’s predictive accuracy. Within the stoichiometric dimension alone, the prediction accuracy significantly increased with the number of input traits, indicating a substantial potential for enhancing predictive capability. Our research facilitates the dynamic, continuous, and relatively accurate monitoring of GPP, contributing to a better understanding of carbon cycle dynamics and supporting informed ecosystem planning and management.

A document by Rene Steinmann. Click on the document to view its contents.

Soil microbiota can colonise plant roots via a two-step selection process, which involves the recruitment of microbiota first from bulk soil into plant rhizospheres, then into root endospheres. This process is poorly understood in all but a few model species, which is surprising given its fundamental role in plant and soil ecology. Here we examined the microbial assembly processes across the rhizospheres and root endospheres in eight natural populations of the pan-palaeotropical C4 grass, Themeda triandra, in southern Australia. We assessed whether root endosphere colonisation patterns aligned with the two step-selection process. We also assessed the degree to which the assembly patterns of these rhizospheres and endospheres were influenced by deterministic processes. We show that two-step selection was the dominant recruitment dynamic across these natural T. triandra populations, and present clear evidence that host plants influenced microbial assembly via deterministic pressures that produced strong convergence of endospheres. Both endospheres and rhizospheres were influenced by local environmental filtering, including aridity. Our study improves our understanding of assembly processes of root endospheres, which is central to plant-soil interactions yet poorly understood in non-model species. We show that endospheres of native populations of a widely distributed, keystone grass (T. triandra) were strongly shaped by the host plant and displayed patterns consistent with the two-step selection process. These findings raise intriguing questions about the functions of this ‘core’ microbial endosphere, but our limited understanding of their ecology hinders our ability to harness these important relationships to, for example, improve plant propagation and revegetation practices.

Efficient streaming media caching policies help improve the request hit rate of Content Delivery Networks (CDNs), which leads to reduced service latency and enhanced service qual- ity. Existing research on caching policies primarily relies on the popularity of media content for decision-making. Me- dia servers face constraints in storage and computational re- sources, along with frequently changing service requests, mak- ing it challenging to determine the cached content and co- optimize caching and computational resources. We propose an innovative architecture for efficient CDN service caching policies to address this challenge. This architecture utilizes a hierarchical adaptive caching strategy (HACS) that deter- mines the computational resources to be allocated by pre- dicting the network resource consumption of each edge and cloud node. Next, we analyze the live and playback streams from each node using the Quantum Particle Swarm Opti- mization (QPSO) algorithm to extract features related to the playback streams. These features are used as inputs for pre- dicting potential hot content. Based on the prediction results and historical data, we dynamically adjust the caching pol- icy by monitoring resource consumption and user requests in real-time. Finally, experimental data demonstrate that, com- pared to existing schemes, our proposed architecture offers ∗Equally contributing authors. FIGURE 1 Scenarios of CDNs advantages in improving cache hit rates and reducing user latency.

Predator avoidance and antipredator mechanisms are ubiquitous in organisms affected by predation. One such mechanism, startle behavior, uses bright colors or contrasting patterns to intimidate a potential predator in such a way as to provide the prey with a slight escape advantage prior to the subjugation phase of a predation sequence. The extravagant coloration of Red-eyed Treefrogs (Agalychnis callydrias) is commonly explained as functioning in such a startle capacity, yet this hypothesis remains untested. We assessed the reaction of field-collected Red-eyed Treefrogs to simulated predation events from forceps and a model bird. Red-eyed Treefrogs opened their eyes rapidly and early during the predation sequence. Yet the orange feet and blue/yellow flanks of Red-eyed Treefrogs were flashed rarely and only in association with an escape jump. . To determine how the red eye color influences the tendency for a predator to attack, domestic chickens (Gallus gallus) were exposed to clay frogs with their eyes painted red or green. In a second experiment, chickens were exposed to clay frogs in which the eyes were replaced with red light emitting diodes (LED) that could be turned on, thus stimulating the “flash” of color that a potential predator would experience when disrupting a sleeping frog. Red eye color increased attack frequency and intensity on clay frogs. Model frogs in which red LED eyes were turned on during the initial interaction with chickens failed to induce a delayed reaction in subsequent strikes. While an evaluation of interactions involving wild avian predators are necessary, these results suggest that the bright coloration of Red-eyed Treefrogs may not function as a startle mechanism to prevent predation. Alternative hypotheses for the adaptive significance of Red-eyed Treefrog coloration include a role in sexual selection and an aposematic function.

Effective biodiversity conservation requires knowledge of species’ distributions across large areas, yet prevalence data for marine sessile species is scarce. As marine organism distributions generally depend on terrain heterogeneity, topographic variables derived from digital elevation models (DEMs) can be useful proxies in distribution modelling. However, the suitability of such variables depends on spatial resolution. Here, we (1) assess three high-resolution bathymetry DEMs for accuracy, (2) harness DEM-derived topographic variables for regional coral species distribution models (SDMs), and (3) develop a transferable framework to produce, select and integrate multi-resolution topographic variables into marine spatial modelling. We use a case study from three reef-building Acropora coral species sampled across 23 reefs of the Great Barrier Reef, Australia. Obtaining three open-source bathymetric DEMs (15m Allen Coral Atlas (ACA), 30m DeepReef, 100m DeepReef), we produce eight derived topographic variables generalised to multiple nested spatial resolutions (15m to 120m) to assess SDM sensitivity to bathymetry source and resolution. We found that the ACA and DeepReef DEMs had similar vertical accuracies, each producing topographic variables relevant to marine SDMs. Slope and vector ruggedness measure (VRM) explained most of the variance for all three species. Coral prevalence increased with slope to a moderate steepness before quickly decreasing with increasing steepness for two species, while the third species plateaued. The prevalence of all species was negatively associated with VRM. Topographic variables for coral SDMs were most relevant at 15–60m resolutions, where the optimal resolution depended on the variable type and species. Overall, we show that the finest resolution was unnecessary to achieve high-performing SDMs. Running SDMs with multi-resolution topographic variables provided insights into the importance of terrain attributes for distribution modelling of different species. We provide a transferrable framework to facilitate the adoption of multiscale SDMs for better-informed conservation and management planning.

A document by MEHADI HASAN. Click on the document to view its contents.

Background The patterns of circulation and burden of influenza and respiratory syncytial virus (RSV) in Singapore are affected by the COVID-19 pandemic containment measures. These patterns in relation to SARS-CoV-2 in a post-pandemic era are unclear. Methods Using data from 2015 to 2023, we estimated excess influenza-, RSV- and SARS-CoV-2-associated hospitalisation in Singapore, adjusted for rhinovirus/enterovirus activity in generalised additive models. The data includes pneumonia and influenza (P&I) hospitalisation from a national inpatient database and a community-wide acute respiratory infection (ARI) sentinel surveillance programme, stratified by age groups. Results Across all age groups, the proportion of hospitalisation associated with influenza, SARS-CoV-2 and RSV was 15.7% (95% CI 6.4%–25.0%), 16.5% (95% CI 10.5%–22.6%) and 6.3% (95% CI 2.2%–12.5%) in 2023. From 2019 to 2023, all-age influenza-associated hospitalisation declined from 129.8 per 100,000 person-years (95% CI 110.9–148.4) to 95.7 per 100,000 person-years (95% CI 38.9–152.2). In contrast, all-age RSV-associated hospitalisation after the pandemic was 38.4 per 100,000 person-years (95% CI 13.1-75.9), similar to pre-pandemic observations. Peak seasonal influenza occurred 3-8 weeks later as compared to the time of pre-pandemic peak influenza activity. Conclusion The overall burden of influenza has declined after the COVID-19 pandemic and its burden is comparable with SARS-CoV-2. Furthermore, shifts in the timing of peak influenza activity suggest a potential need to review the timing of vaccine recommendations in Singapore.

In the First Section of the lower Paraná River delta, Buenos Aires residents have created a large number of small-scale private artificial river beaches for recreational purposes. The nourishment used in these beaches mitigates the existing distributary channel bank erosion phenomena caused by river floods, storm surges and motorboat waves. This contribution aims to analyse the distribution of these river beaches in the above mentioned section and examine the characteristics and evolution of a case study. To achieve this, existing beaches were mapped on Google Earth using a satellite image from 2021. Subsequently, a selected case study was located in a high-traffic area, near the continent, along the Sarmiento Channel (Timón Dorado Beach), where samples were taken for grain-size analysis and beach cross sections were surveyed with a total station on two different occasions within six months of each other. Additionally, a webcam was installed on a tower to photograph the Sarmiento Channel and its motorboat traffic. Results revealed a total of 401 beaches in the studied area, with a total area of 62,848 m 2. The case study monitoring confirmed that this nourished sand is fine and well sorted. The beach cross section evolves as sand flows upward from upper foreshore to a stable berm on the backshore and downward to the lower foreshore. In conclusion, recharge at least every 4 years is recommended to maintain the beach as a recreational space and as a bank protection.

Background and Purpose: No drugs targeting the core social features of autism spectrum disorder (ASD) have been approved. Although clinical trials with oxytocin (OT) and vasopressin (AVP) have yielded mixed results, targeting their receptors remains the most promising pharmacological strategy for addressing social impairments in ASD. This study aims to identify which receptors and signalling pathways within this family can sustainably improve social impairments. Experimental Approach: We used dose-response and kinetic analyses, along with mathematical modelling, to evaluate OT, AVP, their homologs, and novel synthetic ligands on G protein coupling, β-arrestins recruitment, and internalisation of mouse oxytocin (OTR) and vasopressin (V1A, V1B, V2) receptors in Neuro-2a cells. We tested acute and subchronic administration of OTR agonists and the novel V1A receptor antagonist, alongside OT and AVP, for their effects on social interaction in Fmr1 KO mice, a model exhibiting ASD-like features. Key Results: While OT, AVP and most compounds were non-selective across the four receptors, the OTR agonists TGOT or RO6958375 and the V1A antagonist RO6893074 were selective. TGOT or RO6958375, favouring Gαq signalling, enhanced social interactions in Fmr1 KO mice while showing minimal effects in wild-type mice. In contrast, OT, AVP or RO6893074 exhibited limited efficacy in Fmr1 KO mice. Conclusion and Implications: Selective OTR agonists, unlike OT and AVP, effectively improved social impairments in Fmr1 KO mice after acute and subchronic treatment. These findings highlight the necessity for developing highly selective OTR Gαq-biased agonists to achieve clinical outcomes in ASD.

Mixed Connective Tissue Disease with Overlapping Features of SLE and Dermatomyositis Complicated by Endocrine Abnormalities

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf Long-term use of the immunosuppressant tacrolimus (Tac) is limited due to its nephrotoxic, hepatotoxic and diabetogenic effects. Up to 33.6% of solid organ transplantation patients receiving Tac treatment develop hyperglycemia; however, the underlying mechanisms remain poorly elucidated. Here, using a mouse model of Tac-induced hyperglycemia, we found that Tac-induced body-weight loss, hyperglycemia, hypoinsulinemia, glucose intolerance and insulin resistance were improved by a renin-angiotensin system (RAS) inhibitor (valsartan). Morphologic and immunofluorescence observation uncovered that the pancreatic islet areas and β cell mass were reduced in Tac-treated mice. Besides, in isolated islets from Tac-treated mice, markers of cell proliferation (Ki67, Ccna2 and Ccnd1) were downregulated but markers of cell apoptosis (DNA fragmentation, Bax and Caspase3) were upregulated compared with control mice. Hypoxia-related markers in pancreas, including hypoxia-inducible factor-1 (HIF-1) and its downstream factors (Adm, Hmox1 and Vegfa), CD31 and pimonidazole adducts were augmented by Tac. Treatment with Tac leaded to vascular dysfunction in pancreatic arteries. All of these adverse effects could be partly or fully restored by valsartan. Tac also increased levels of renin in renal tissue (1.00±0.06 vs 1.31±0.02, p<0.05) and serum (28.35±4.29 ng/mL vs 51.99±4.95 ng/mL, p<0.05). Inhibition of RAS by valsartan protected against vascular dysfunction induced by Tac in renal interlobar arteries. Collectively, our data illustrate a previously undescribed mechanism that Tac-induced vascular dysfunction in renal interlobar arteries leads to RAS activation. Blocking RAS by valsartan alleviated vascular dysfunction in dorsal pancreatic arteries and hypoxia in islets, which in turn prevents Tac-induced β-cell dysfunction and glucose metabolism disorder.

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf As climate change progresses and severe disturbances become routine, understanding rates and mechanisms of recovery in habitat forming species is central to predicting the broader response of ecosystems to climate change. Here, we combined acute experimental heat stress and RNA sequencing to explore patterns of transcriptome plasticity and resilience to heat stress in a common Acropora coral from the World Heritage-listed Ningaloo Reef. Our data showed that corals subjected to sub-bleaching temperatures (33 ºC) elicited a large transcriptional response during heat stress, but quickly recovered to baseline levels of expression 16 hours after temperatures returned to pre-treatment conditions, with no evidence of bleaching. In contrast, corals exposed to a one degree increase (34 ºC) from the sub-bleaching heat treatment, mounted a transcriptional response nearly twice that of the sub-bleaching temperature, showed a lingering stress response in their transcriptome, and eventually bleached. Moreover, variation in the severity of bleaching among colonies was linked to patterns of transcriptome recovery – individuals that bleached heavily showed a larger lag in transcriptional recovery than those with lower levels of bleaching. Together, these findings provide new insight into the genetic mechanisms of heat stress recovery in coral and highlight the role of transcriptional plasticity in the resilience of coral to increasing disturbances.

Agricultural intensification is one of the major forces driving populations of many traditionally common native species into smaller, fragmented populations which are prone to isolation and loss of genetic diversity. Identifying the spatial extent and characteristics of rural systems that support gene flow and promote genetic diversity for these species is thus essential for their long-term conservation. Here we used asymmetric autosomal genetic structure between sexes to investigate current gene flow among four neighbouring suburban populations of hedgehogs (Erinaceus europaeus) in England, which are separated by agricultural land. Contrary to expectations, we found that individuals belonged to a single genetic population despite the populations being separated by unoccupied agricultural land. Spatial autocorrelation was significant in adult female hedgehogs, but non-significant in adult males, revealing male driven contemporary gene flow between local populations. The results suggest that male hedgehogs are capable of moving between population patches separated by at least 3 km across the agricultural matrix. This finding is crucial to aid the development of a conservation strategy for hedgehogs as, for the first time, it shows the extent that previously assumed isolated populations across a perceived inhospitable landscape are connected by current gene flow. Higher within patch relatedness, and lower allelic richness were found from smaller suburban patches, largely reflecting local population size, indicating an early stage of genetic diversity loss due to habitat loss and associated fragmentation. Our study illustrates that considering current gene flow and genetic diversity together is important to better understand habitat effects on genetic variation.

In this paper a method of Laser surface smoothing of 3D printed polymer material based on a nanosecond Laser is introduced. The adequate Laser enabled reducing surface roughness by 65% on a 25x25 mm² surface and therefore improving the printing quality of metal layer deposited on top to fabricate HF passive devices. This paper also examines the impact of Infrared (IR) sintering combined with thermal treatment in order to improve the electrical conductivity of printed silver layers by micro dispensing technique (nScrypt technology) up to 30.5 S/µm. A patch antenna was printed on smoothed PEEK substrate and gave promising results (gain of 5.4 dBi @ 6.8 GHz).

A novel treatment for thoracic hyperextension injury with opening wedge distraction fracture in DISH: A Case Report

Pleural Lipoma: A Case Report

A Case Report on Disseminated Mycobacterium Avium Complex Infection in an Otherwise Healthy Individual - A Diagnostic Challenge

KEY CLINICAL MESSAGEThis case report presents positive outcomes from deep brain stimulation (DBS) targeting bed nucleus of stria terminalis (BNST) in two patients with treatment-resistant depression and generalized anxiety disorder, while DBS targeting the medial forebrain bundle (MFB) was unclear. Further research into DBS’s efficacy when comorbid anxiety is present is required.Keywords: Deep brain stimulation, bed nucleus of the stria terminalis, medial forebrain bundle, depression, generalized anxiety disorder, clinical trial, neurosurgery

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf Understanding the processes that drive spatial genetic differentiation is essential for understanding how populations adapt to environmental change. By evaluating the relative influence of these drivers, we can gain insights into evolutionary dynamics and the potential for species to respond to shifting landscapes. Three well-accepted drivers of spatial patterns in genetic variation are isolation-by-distance (IBD), where individuals are more genetically similar the closer they are geographically; isolation-by-environment (IBE), where gene flow is reduced due to selection against migrants in unsuitable ecological conditions; and isolation-by-resistance (IBR), where landscape features limit dispersal. We employed a macrogenetic approach, conducting a multi-species, multi-driver, meta-analysis of published genomic SNP data to identify general patterns driving spatial genetic differentiation of mammals globally. Three species distribution models were built per species to test different aspects of IBR, using combinations of landscape and bioclimatic variables. Using two model selection techniques, we find that landscape resistance models better explain genetic differentiation than bioclimatic resistance models. Among the three drivers, IBR was most frequently selected as the best model of genetic differentiation in mammals across both model selection tests, with IBD a close second and IBE the worst performing model. However, the importance of IBE increased with increasing spatial scale, with populations spread over larger distances more likely to be diverging due to IBE than IBR or IBD. Our findings suggest that anthropogenic habitat fragmentation significantly shapes genetic variation in mammals worldwide, underscoring the importance of mitigating the impacts of habitat fragmentation to prevent isolation and extinction of mammalian species.

In order to improve the efficiency of electric energy measurement and verification, the CS5464 chip circuit is improved and applied. The CS5464 chip circuit includes amplifier circuit, modulation circuit, digital filtering circuit, and data communication circuit. When calculating electric energy, a 16 bit MSP430FG4619 MCU core computing circuit is used, and the computing power is improved through Dynamic Matrix Control (DMC) algorithm. When managing electric energy measurement data, the improved Min Max Ant System (MMAS) algorithm is used, and a classification algorithm model is integrated to classify various electric energy measurement data information, which improves the information management ability of electric energy measurement and verification. Through experiments, the error rate of the method in this study is less than 5%, greatly improving the efficiency of electric energy measurement and calibration.