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High mortality rates and long-term complications in children with infectious brainstem encephalitis: A study of sixteen cases

Objective Brainstem encephalitis (BE) can cause sudden death in children. Fewer studies have been conducted on the incidence, clinical manifestations, pathogens and post-infectious sequelae of pediatric infectious BE. Methods Pediatric patients diagnosed with BE in our Medical Center from 01 January 2015 to 31 July 2024 were retrospectively reviewed. The clinical data of these children were obtained from the hospital’s medical database on 15 August 2024. The number of outpatient and inpatient patients at our Medical Center during that period were provided by the hospital data center. Data analysis was conducted using Excel 2019. Results A total of twenty-eight cases were diagnosed with BE in our National Children′s Medical Center over the past decade. Among them, 57.1% (16/28) cases were diagnosed with infectious BE. The incidence of infectious BE was estimated to be 16 cases per 30 million outpatient visits and 13 cases per 500,000 hospitalized patients. Fever, consciousness disorders and seizures were observed in 75.0% (12/16), 68.8% (11/16) and 62.5% (10/16) of the cases, respectively. Among them, 31.3% (5/16) cases were diagnosed as human enterovirus infections, 12.5% (2/16) cases were confirmed to be influenza B virus infections, while one case each was diagnosed with herpes simplex virus 1 and human herpesvirus 6 infection. The mortality rate during hospitalization was 12.5% (2/16). Among the surviving patients, 50.0% (7/14) of them had follow-up records, 85.7% (6/7) of the survivors suffered from sequelae such as motor disorders. Conclusion Fever, consciousness disorders and seizures were the major clinical manifestations in patients with infectious BE visited our Medical Center. These rare cases exhibited a notably high mortality rate and a significant frequency of long-term complications.

Author Correction: Calibration of miniature air quality detector monitoring data with PCA–RVM–NAR combination model

On the road to Mecca: Branding discourses and national identity on coffee shop signage

Commercial branding stands as a discursive and cultural facet of the contemporary global era where competing brands construct their own identities. From a discourse perspective, a brand is discursively constructed on commercial signs. Accordingly, this study examines the interplay between coffee shop branding and national identity in Saudi Arabia. In so doing, the study investigates the competing branding discourses associated with coffee as well as the space given to national identity. To achieve this task, the study developed a conceptual framework grounded on critical discourse analysis (CDA) and linguistic landscape (LL). The data consists of 88 commercial signs of coffee shops collected by driving on a road from Najran to Mecca, Saudi Arabia. The research site was then verified through Google Maps. The data built a communicative event for an empirical mixed-method research design. CDA linguistic and multimodal toolbox was utilized. The analysis showed that three names of coffee are found on the road to Mecca: qahwa (Arabic), coffee (English), and kufi (transliteration). With these names, four discourse are in competition. For globalization, English-Arabic glocal discourse (34%), and English global discourse (8%) are competing to construct coffee branding. For national identity, Arabic local discourse (42%) and Arabic-English glocal discourse (16%) are associated with qahwa; something that gives substantial space (58%) for national identity. These findings enhance our understanding of the linguistic and multimodal dimensions of globalized spaces and their discursive construction of branding at the local scale of globalization. The study recommends further research and suggests some cultural and pedagogical implications for authorities, translation, bilingual awareness, teaching, and learning.

Exploiting question-answer framework with multi-GRU to detect adverse drug reaction on social media

Correction for Humbert et al., Functional SARS-CoV-2 cross-reactive CD4 ⁺ T cells established in early childhood decline with age

The protein interactome of Escherichia coli carbohydrate metabolism

We investigate how protein-protein interactions (PPIs) can regulate carbohydrate metabolism in Escherichia coli. We specifically investigated the stoichiometry of 378 PPIs involving carbohydrate metabolic enzymes. In 48 interactions, the interactors were much more abundant than the enzyme and are thus likely to affect enzyme activity and carbohydrate metabolism. Many of these PPIs are conserved across thousands of bacteria including pathogens and microbial species. E. coli adapts to different cellular environments by adjusting the quantities of the interacting proteins (25 PPIs) in a way that the protein-enzyme interaction (PEI) is a likely mechanism to regulate its metabolism in specific environments. We predict 3 PPIs (RpsB-AdhE, DcyD-NanE and MinE-Yccx) previously not known to regulate metabolism.

PCR-based detection of Botryosphaeria canker pathogens in fig trees

Spatial risk modelling of highly pathogenic avian influenza in France: Fattening duck farm activity matters

In this study, we present a comprehensive analysis of the key spatial risk factors and predictive risk maps for HPAI infection in France, with a focus on the 2016–17 and 2020–21 epidemic waves. Our findings indicate that the most explanatory spatial predictor variables were related to fattening duck movements prior to the epidemic, which should be considered as indicators of farm operational status, e.g., whether they are active or not. Moreover, we found that considering the operational status of duck houses in nearby municipalities is essential for accurately predicting the risk of future HPAI infection. Our results also show that the density of fattening duck houses could be used as a valuable alternative predictor of the spatial distribution of outbreaks per municipality, as this data is generally more readily available than data on movements between houses. Accurate data regarding poultry farm densities and movements is critical for developing accurate mathematical models of HPAI virus spread and for designing effective prevention and control strategies for HPAI. Finally, our study identifies the highest risk areas for HPAI infection in southwest and northwest France, which is valuable for informing national risk-based strategies and guiding increased surveillance efforts in these regions.

Sulfur partitioning between aqueous fluids and felsic melts at high pressures: Implications for sulfur migration in subduction zones

A comprehensive analysis of time investment in skid trail planning for forest access

Properly planned skid trails form an important basis for sustainable timber production. They affect cost-effectiveness and the environmental impact of the harvesting process to a large extent. Here, we conducted an economic analysis to understand the skid trail planning process and to generate an initial model to estimate the time and costs involved. We investigated in detail how the planning process of skid trails is carried out in practice, what time is required for the planning work, and what factors influence its performance. Through an online survey conducted in 2022, we asked practitioners in Germany and Switzerland about their time and effort required for the planning process and the determining factors, such as the planning method and the terrain and stand conditions. Based on this survey, we calculated statistical indicators of time consumption, considered possible rationalization options, and developed an initial estimation model. The effort required to identify and evaluate skid trails planned for distances of 20 to 40 m amounts to around 3 to 4 hours of productive working time per hectare, with deviations expected depending on the specific situation in the forest. The costs corresponding to this investment amount to less than one euro per cubic meter of harvested timber, depending primarily on the extent of wood use. Our in-depth insight into the planning process enables its economic evaluation and the development of improvements.

Automatic cervical lymph nodes detection and segmentation in heterogeneous computed tomography images using deep transfer learning

Illusory finger stretching and somatosensory responses in participants with chronic hand-based pain

Current pharmaceutical interventions for chronic pain are reported to be minimally effective, leading researchers to investigate non-pharmaceutical avenues for chronic pain treatment. One such avenue is resizing illusions delivered using augmented reality. These illusions resize the affected body part through stretching or shrinking manipulations and have been shown to give analgesic effects; however, the neural underpinnings of these illusions remain undefined. Steady-state evoked potentials (SSEPs) have been studied within populations without chronic pain undergoing hand-based resizing illusions, finding no convincing differences in SSEP amplitudes during illusory stretching. Here, we present comparable findings from a sample with chronic pain, who are thought to have blurred cortical representations of painful body parts, but again find no clear differences in SSEP amplitude during illusory stretching. However, no significant decreases in pain ratings were found following illusory resizing, and changes in SSEP amplitudes are thought to possibly reflect experiences of illusory analgesia. Despite a lack of illusory analgesia across the sample, several participants experienced clinically meaningful levels of pain reduction following illusory resizing, highlighting the potential of resizing illusions as an analgesia treatment avenue. Subjective illusory experience data showed significantly greater experiences of the illusion in the multisensory (visuotactile) condition compared to non-illusion conditions and a unimodal visual condition, replicating findings from participants without chronic hand-based pain. Exploratory analyses using subjective disownership data show that the multisensory condition did not elicit significant disownership experiences, demonstrating that the pain reductions seen in the multisensory condition do not arise from disownership of the limb, but more likely as a direct result of the illusory resizing manipulations.

Optimization of multiple sampling for solving network boundary specification problem

BCL6 (B-cell lymphoma 6) expression in adenomyosis, leiomyomas and normal myometrium

Adenomyosis and leiomyomas are common benign uterine disorders characterized by abnormal cellular proliferation. The BCL6 protein, a transcriptional repressor implicated in cell proliferation and oncogenesis, has been linked to the pathogenesis of endometriosis. This study investigates BCL6 expression in adenomyosis, leiomyomas, and normal myometrium using immunohistochemistry and deep learning neural networks. We analyzed paraffin blocks from total hysterectomies performed between 2009 and 2017, confirming diagnoses through pathological review. Immunohistochemistry was conducted using an automated system, and BCL6 expression was quantified using Fiji-ImageJ software. A supervised deep learning neural network was employed to classify samples based on DAB staining. Our results show that BCL6 expression is significantly higher in leiomyomas compared to adenomyosis and normal myometrium. No significant difference in BCL6 expression was observed between adenomyosis and controls. The deep learning neural network accurately classified samples with a high degree of precision, supporting the immunohistochemical findings. These findings suggest that BCL6 plays a role in the pathogenesis of leiomyomas, potentially contributing to abnormal smooth muscle cell proliferation. The study highlights the utility of automated immunohistochemistry and deep learning techniques in quantifying protein expression and classifying uterine pathologies. Future studies should investigate the expression of BCL6 in adenomyosis and endometriosis to further elucidate its role in uterine disorders.

UniLF: A novel short-term load forecasting model uniformly considering various features from multivariate load data

Unraveling multimodality of digital health records by comparing mortality trajectories of diagnoses of diseases from over 12 million patients

Understanding the multimodality of digital health data, including the scope of death records, is essential for adequate data acquisition to build a research framework for the health sciences. In this study, I leveraged the diverse healthcare records of over 12 million patients to reconstitute mortality trajectories that navigate the sequence of disease processes shared among patients from initial presentation through interim conditions that ultimately terminate in fatal outcomes. I conducted a comprehensive analysis of longitudinal discharge records for 10.4 million patients from US hospitals, utilizing the US State Inpatient Data (USSID) including 290,253 records of deaths in clinics. I also scrutinized the cross-sectional records of Korea from the billing reviews, specifically the National Inpatients Set of Korea (NISK), encompassing 2.1 million patients. By tracing the diagnostic timelines of patients diagnosed with significant comorbid diseases (False Discovery Rate (FDR) <0.1), I built mortality trajectories, mapping the temporal progression of disease diagnoses resulting in death. My trajectory model rewired 705 significant mortality trajectories across both datasets (USSID and NISK). The presented mortality trajectories successfully recapitulated established patterns of mortality for each country, while also revealing different trajectories leading to death, influenced by the modality of data. For example, viral hepatitis, a known predisposing feature of liver cancer in Asia, was observed to initiate in younger Koreans. Interestingly, owing to the collection of hospital records, the modeled mortality trajectories derived from the USSID converged towards sepsis. Although a substantial sequence of diagnostic processes is shared between USSID and NISK, the multimodality of these two datasets highlights different diagnoses preceded by fatal outcomes. Unraveling mortality patterns is feasible with an appropriate understanding of the multimodality of digital health data.

Experimental data suggest between population reversal in the condition dependence of two sexually selected traits

Abstract When viewing mate choice as a process of adaptive evolution, the condition-dependence of sexual ornaments represents a central pillar. Experimental tests of condition-dependence are few and refer to one population per species. The first brood size manipulation experiment aimed to test ornament condition-dependence had been reported from a Swedish population of collared flycatchers. Here we report a similar experiment conducted in a Hungarian population, examining the change of white plumage patch sizes of male parents by the next year and the patch sizes of male offspring in adulthood. The results consistently indicate that experimentally modified reproductive effort affects male wing, but not forehead patch size. To the contrary, previous results from the Swedish population indicated significant effects on forehead, but not wing patch sizes. Both patches are sexually selected in both populations, so the diverging results offer the first experimental suggestion of a trait by population crossover in the information content of two sexual ornaments. We conclude that explaining why some ornaments are condition-dependent is still far ahead, and further, preferably experimental population comparisons would be helpful.

Socioeconomic disparities in depression risk: Limitations of the moderate effect of physical activity changes in Korea

This study investigates the influence of changes in physical activity (PA) patterns on depression risk across different socioeconomic statuses (SES) in Korea. Utilizing National Health Insurance Data (NHID) from over 1.2 million individuals during 2013–2016, we matched medical aid beneficiaries with health insurance beneficiaries, excluding those with prior depression or incomplete PA data. Changes in moderate-to-vigorous PA (MVPA) were categorized into 16 groups, and depression incidence was tracked from 2019 to 2021. After adjustment, medical aid beneficiaries consistently showed higher risks of depression compared to health insurance enrollees with the same physical activity (PA) change patterns. For those consistently inactive, the risk was 1.68 times higher (aOR, 1.68; 95% CI, 1.37–2.05). Those who increased PA from inactivity to moderate-to-vigorous activity 3–4 times per week had a 3.33 times higher risk (aOR, 3.33; 95% CI, 1.72–6.43). Additionally, the risk was 2.64 times higher for those increasing from 1–2 times to ≥5 times per week (aOR, 2.64; 95% CI, 1.35–5.15), and 2.83 times higher for those consistently engaging in PA 3–4 times per week (aOR, 2.83; 95% CI, 1.35–5.94). Across the overall PA patterns, medical aid beneficiaries consistently faced higher depression risks, with risk increases of 1.80 times for increased activity, 1.68 times for continuous inactivity, and 1.34 times for decreased activity compared to health insurance beneficiaries with the same PA change patterns. However, in the consistently very active group, no significant difference in the risk of depression was observed between the two groups. Limitations include potential bias in self-reported PA and the NHIS data not fully capturing depression severity. The findings underscore the significant impact of SES on mental health, with consistently high PA levels potentially mitigating SES-related depression risk.

On the time lag between sea-level rise and basin infilling at tidal inlets

Spatio-temporal variation in pollen collected by honey bees (Apis mellifera) in rural-urban mosaic landscapes in Northern Europe

Pollen is a source of protein, lipids, vitamins and minerals for bees and other flower-visiting insects. The composition of macro- and micronutrients of pollen vary among different plant species. Honey bees are long-distance foragers, collecting nectar and pollen from plants within several kilometers of their hive. Availability of pollen within the foraging range of honey bees is highly dynamic, changing seasonally, and across different landscapes. In the present study, the aim was to investigate the composition of pollen collected by honey bees in rural-urban landscape mosaics typical of Northern Europe. Samples of corbiculate pollen were collected 3–9 times during the growing season by citizen scientist bee keepers from a total of 25 observation apiaries across Denmark in 2014–2015. Palynological analysis was conducted identifying 500 pollen grains per sample to pollen type (mostly plant genus). Pollen diversity denoted the number of different pollen types in a sample, while relative abundance was calculated as the proportional representation of a pollen type, if found in >1% of the sample. The quantity of pollen types across study years and sites was measured as the occurrence of each pollen type (number of samples with the pollen type present) and abundance (total number of pollen grains). Pollen diversity was highly variable, with effects of season, year, and area of green urban spaces. In terms of quantity, a few key pollen types occurred repeatedly and abundantly in the samples. Only 17 pollen types were present in >15 samples. These pollen types were consistent across study years and different landscapes. Pollen diversity may impact colony health, and hence foraging decisions by honey bees, especially in late summer. However, the bulk of the pollen collected by colonies came from a limited number of pollen sources, regardless of year and landscape context in the rural-urban landscape mosaics of Denmark.