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Global Effect of Cardiovascular Risk Factors on Lifetime Estimates

A circulating microRNA panel enhances the diagnosis of cholangiocarcinoma

Background and aim Cholangiocarcinoma (CCA), a malignancy with a high incidence in regions endemic for the liver fluke Opisthorchis viverrini, is frequently characterized by alterations in the p53 tumor-suppressor gene, a process often modulated by microRNAs. Our study aimed to identify circulating miRNAs as potential diagnostic biomarkers for CCA. Methods We sequenced small RNAs to identify differentially expressed microRNAs (miRNAs) in two CCA cell lines (one p53-mutant, one p53-wildtype) relative to an immortalized cholangiocyte cell line. Candidate miRNAs exhibiting significant upregulation with a log2 fold change > 4.5 were selected for validation via RT-qPCR in serum samples from patients with CCA. The diagnostic utility of these serum miRNAs was subsequently evaluated using receiver operating characteristic (ROC) analysis to assess their ability to distinguish CCA from normal controls and hepatocellular carcinoma (HCC). This performance was assessed for the miRNAs as standalone markers and in combination with conventional tumor markers. Results Analysis of miRNA expression profiles identified seven upregulated candidates for validation. Among these, serum levels of miR-99a-5p, miR-516a-5p, and miR-526b-5p were significantly elevated in patients with CCA compared to both normal controls (all area under the curve, AUC > 0.79, p < 0.0001) and patients with HCC (all AUC > 0.80, p < 0.0001). A diagnostic panel combining these three miRNAs demonstrated high accuracy in distinguishing CCA from normal controls (AUC = 0.899) and from HCC (AUC = 0.937). The panel’s performance was further enhanced by incorporating conventional tumor markers, achieving an AUC of 0.928 when combined with CA19−9, and rising to 0.959 with the inclusion of both CA19−9 and CEA. Conclusions These findings indicate that a panel comprising miR-99a-5p, miR-516a-5p, and miR-526b-5p, alone or with established tumor markers, offers high accuracy as a minimally invasive diagnostic tool for CCA, and can effectively distinguish it from HCC.

Nonoperative Management of Mismatch Repair–Deficient Tumors

Large-scale carbon and nitrogen isotopic investigations into caprine diet and management at Tepe Yahya, southeastern Iran

Tepe Yahya, a small urban center in southeastern Iran, was embedded in cross-cultural exchange with the many entities of southwestern Asia. Besides an understanding that caprines dominated the animal economy, we have little knowledge of how these animals were managed. The site was discontinuously occupied from the Neolithic to Sassanian periods (6500 BCE to 200 CE). As one of the longest occupied archaeological sites in Iran, Tepe Yahya provides a unique opportunity to examine whether diversity in caprine management accompanied the site’s development and expanded need for provisioning. We examine the diet of 254 sheep and goats between 6500 and 2000 BCE, the Neolithic to Bronze Age, using carbon (δ13C) and nitrogen (δ15N) stable isotopic analysis, and estimate the percentage of C3 plants in animal diets using a custom isotopic mixing model developed in R with “simmr.” While isotopic averages indicate diet was consistent through time, dietary outliers demonstrate the simultaneous presence of multiple management strategies, with certain animals receiving limited access to the full variety of plants available in the landscape. Goats and sheep show statistically significant differences in the percentage of C3 plants in their diets, with goats always eating higher portions of C3 plants than sheep. These differences are likely a result of human interference rather than substantial environmental changes, which are not reflected in the isotopic values. Increasing isotopic variability over time points to a broader array of caprine management strategies, through greater environmental use or more discrete herds, as well as the introduction of nitrogen-fixing plants into select animal diets. The Tepe Yahya caprines continue to reveal the multifaceted nature of managerial strategies and their relation to urban centers.

CD19 CAR T-Cell Therapy in Multidrug-Resistant Ulcerative Colitis

COVID-19 vaccinations among German university students: The role of fear of COVID-19 and risk assessment

Studies on the reasons why people have opted for COVID-19 vaccination have shown that a higher fear of COVID-19 and a higher risk assessment of developing a serious illness in case of a SARS-CoV-2 infection correlate positively with higher vaccine uptake. The present study examined whether this also holds true for university students who face a very low risk of developing a serious illness. Fear of COVID-19, risk assessment, and the number of received COVID-19 vaccinations was measured using an online questionnaire which could be completed from December 15, 2022 to the end of January 2023. In total, data from 419 German university students was analyzed. The results show that the vaccination rate among German university students (93.6%) was higher than the vaccination rate of the general population of the same age group. Even in the group of university students who reported having no fear of COVID-19 at all, the vaccination rate was still 83%, and already the experience of low fear and the estimation of low risk led to the vaccination rate rising to almost 100%. Fear of COVID-19 also increased with the willingness to receive additional vaccinations after the initial two doses, and even in this case, already the experience of low fear was associated with a substantial increase in the rate of double-vaccinated individuals who continued to receive further vaccinations. These findings underline the role of fear in people’s decision for COVID-19 vaccination and specifically show that fear can play a substantial role even in groups of people who actually have a very low risk of becoming seriously ill.

A Fizzy Fix

Re-emerging outbreaks of chikungunya virus infections of increased severity: A single-center, retrospective analysis of atypical manifestations in hospitalized children during the 2019 outbreak in Bangkok, Thailand

This retrospective observational study assesses the clinical characteristics, atypical manifestations, and treatment outcomes in pediatric patients hospitalized with chikungunya virus (CHIKV) infection during the Bangkok outbreak in 2019. Children <18 years old hospitalized from January 1 to December 31, 2019, and confirmed positive for CHIKV infection by RT-PCR or IgM antibodies were included in this study at a tertiary care center in Bangkok, Thailand. Patient demographics, clinical manifestations, and laboratory findings at the time of hospitalization were collected from de-identified medical records. Of 31 included children, seven (22.6%) were <1 year old, 22 (71.0%) were male, nine (29.0%) had underlying medical conditions, four (17.4%) tested positive for dengue coinfection, and four (12.9%) had multi-organ involvement. The median age was 9.5 (IQR 6.9–12.5) years. Most (90.3%) had atypical clinical manifestations, four (12.9%) had life-threatening manifestations. Two (6.5%) neonates had congenital CHIKV. The most common manifestations included fever (100.0%), rashes (77.4%), myalgia (41.9%), and arthralgia (35.5%). The three most involved organ systems presenting atypical manifestations included gastrointestinal (32.3%), dermatologic (32.3%), and neurological (22.6%) systems. Of those with dermatologic involvement, 67.7% had maculopapular rashes, 19.4% bullous skin lesions, and 6.5% generalized erythroderma. At the time of presentation, 25 (80.6%) children had lymphopenia, five (16.1%) had anemia, and none had thrombocytopenia. Five (16.1%) children required intensive care and four (12.9%) developed shock. Thirteen (41.9%) children, five with neurological involvement, fully recovered at discharge. Among the remaining children, five (16.1%) still had musculoskeletal conditions, 11 (35.5%) had skin lesions, and two (6.5%) with congenital CHIKV had skin lesions and neurological sequelae. Despite the small cohort, the observed frequency of neurological complications attributed to CHIKV infection justifies long-term follow-up in children with neurological manifestations and complications. CHIKV should be suspected in endemic countries and tested for in febrile children, particularly those with rash and neurological involvement.

Structural and Scientific Racism, Science, and Health — Evidence versus Ideology

Genetic suppression features ABHD18 as a Barth syndrome therapeutic target

Comparison of cellular responses of cultured fibroblasts from Iriomote wild cats and domestic cats exposure to polyinosinic:polycytidylic acid

The Iriomote wild cat is endemic to Iriomote Island. The total population is only 100 cats. These cats are thus listed as critically endangered on the IUCN Red List. Infectious disease is a risk factor for further reducing the Iriomote wild cat population. RIG-I, MDA5 and TLR3 are important sensors that recognize host viral defense responses. IL6, Mx, and OAS are downstream genes of RIG-I and MDA5. Polyinosinic:polycytidylic acid (poly(I:C)) stimulates the RIG-I, MDA5 and TLR3 in many animals. In this study, we thus tried to compare RIG-I, MDA5, and TLR3 responses after exposure to the poly(I:C) in domestic cat- and Iriomote wild-cat-derived fibroblasts. This study also compared the expression of downstream gene (IL6, Mx, and OAS) of RIG-I and MDA5. This study analyzed the genes expressions of domestic cat- and Iriomote wild-cat-derived fibroblasts after exposure the poly(I:C), using real-time PCR and RNA-seq. In addition to these genes expression, this study compared the gene sequence of RIG-I and MDA5 between domestic cat and Iriomote wild cat with information of public database. RIG-I and MDA5 levels were increased in both domestic cat- and Iriomote cat-derived fibroblasts after poly(I:C) exposure, while TLR3 expression did not change dramatically after poly(I:C) exposure. A comprehensive gene expression analysis revealed that molecular responses of fibroblasts derived from domestic cats and those derived from Iriomote wild cats to poly(I:C) exposure were similar. Furthermore, RIG-I and MDA5 sequences are similar between domestic and Iriomote wild cat. Our results suggested that poly(I:C) mainly stimulates RIG-I and MDA5 among the three genes (RIG-I, MDA5 and TLR3) examined in this study, and the RIG-I and MDA5 mediated molecular responses to poly(I:C) exposure are similar in domestic and Iriomote wild cats fibroblasts. To the best of our knowledge, this is the first study to compare the RIG-I and MDA5 responses of Iriomote wild cats and domestic cats after poly(I:C) exposure. This study provides valuable insights into the cellular response mediated by RIG-I and MDA5 in the Iriomote wild cat.

No lectures, exams, essays: inside a twenty-first-century university

Deep time evolution of the Latitudinal Diversity Gradient: Insights from mechanistic models

The latitudinal diversity gradient (LDG) designates the increase in species richness toward the tropics. While geological and climatic changes are recognized as key drivers, the precise factors and their relative contributions to species richness gradients remain debated. Using a spatially explicit eco-evolutionary model, we simulate diversification over 125 million years. We validate the model with empirical mammalian richness patterns, and uncover a pivotal role of paleoclimate and paleogeography. This approach allows us to investigate both the mechanisms driving the LDG and space and time variations in species diversification rates across dynamic landscapes integrating changes in tectonic, climatic and surface processes. We show how scale-dependent surface processes are a key driver of regional diversity patterns and how LDG can emerge under a wide range of eco-evolutionary scenarios. Plate tectonics and the subsequent enduring uneven distribution of land masses within the North and South hemispheres imprinted an asymmetric pattern of species diversification rates, primarily shaped by paleoclimate and paleogeography and only to a lesser extent by surface processes. Our simulations also indicate that the LDG has persisted since the Cretaceous, steepened and stabilized from the early Cenozoic on. The modeled scenarios depict that species primarily originate in the tropics and disperse toward the poles without losing their tropical presence. The tropics not only served as a cradle, fostering the origination of new species, but also as a museum, preserving biodiversity over deep time.

Thangka super-resolution diffusion model based on discrete cosine transform domain padding upsampling and high-frequency focused attention

Thangka is a traditional Tibetan painting art form, possessing profound cultural significance and a unique artistic style. Image super-resolution technology, as an effective means of digital preservation and restoration, plays an important role in maintaining the integrity and heritage of Thangka art. However, existing image super-resolution methods cannot be used for Thangka images due to the following reasons: (1) Thangka images are large in size and rich in content, making it difficult for existing models to restore the original textures of degraded Thangka images. (2) Thangka images have intricate textures, so the high-resolution Thangka images reconstructed by existing methods, which perform well on objective metrics, perform poorly in terms of human visual perception. To overcome these challenges, a Frequency-Domain Enhanced Diffusion Super-Resolution (FDEDiff) is proposed, consisting of three parts: (1) a High-Frequency Focused Cross Attention Mechanism (HFC-Attention), which can separate high-frequency features of images to guide the attention mechanism, improving the reconstruction quality of high-frequency details in the diffusion model; (2) a DCT Domain Padding Upsampling (DCT-Upsampling), which performs upsampling in the Discrete Cosine Transform (DCT) domain and improves the reconstruction of dense line areas in Thangka images by fully utilizing global information; (3) for the first time, we construct a Thangka image super-resolution dataset, which contains 82,688 pairs of 512 × 512 images. Qualitative and quantitative experiments demonstrate that the proposed method achieves state-of-the-art performance on the Thangka dataset, attaining a LPIPS score of 0.0815 (lower indicates better perceptual quality) and showing a 20% improvement in perceptual quality over baseline methods. Although the proposed method requires longer inference time due to the iterative nature of diffusion models, this computational trade-off is justified by the critical need for artistic authenticity in cultural preservation applications. Dataset is available at https://github.com/cvlabdatasets/ThangkaDatasets.

Latent representation of H&E images retains biological information in a breast cancer cohort

Imaging technologies and staining based pathology are important components of common practice cancer care. Specifically, H&E imaging is standard for almost all cancer patients. Traditionally, H&E images can serve, when used by experienced trained pathologists, to infer important biological properties of the samples. Recent work demonstrated that machine learning and machine vision analysis of H&E images can further expand the scope of the inference. However, H&E images are high-resolution, making them difficult to analyze and possibly noisy. In this work, we propose an autoencoder-based pipeline that greatly reduces the dimension of the data representation while maintaining valuable properties. In particular, we investigate how different latent space dimensions affect bulk label predictions from H&E. We use autoencoders applied to image tiles as a tool in this investigation and also examine other information that may be inferred from image tiles. For example, we show classification results for tiles, such as Luminal A versus Luminal B, with an F1 score larger than 0.85. We also show that Ki67 levels can be inferred from H&E tiles, as shown before on other cohorts, and that inference is still possible when working with lower dimensional latent representations. The two main contributions of this paper are as follows. First, demonstrating that the use of image tiles can be informative, both at the global classification level, and, more importantly, to support the assessment of heterogeneity. Second, reasonably accurate inference can be performed with lower dimensional latent representations of the H&E images.

A new investigation of nonalcoholic fatty liver disease: Effects of hypoxia on mitochondrial function and lipid droplet autophagy

An expanding body of research has highlighted the intimate connection between nonalcoholic fatty liver disease (NAFLD) and the dysregulation of hepatic lipid droplet autophagy as well as mitochondrial function. Nevertheless, the intricate interplay between lipid droplet autophagy and mitochondrial function under hypoxic conditions remains largely uncharted territory. Constructing NAFLD mouse models at altitudes of 2200 meters and 4500 meters and simultaneously culturing hepatocytes under oxygen concentrations of 21% and 1%, with the addition of oleic acid to induce lipid accumulation. A comprehensive evaluation of the NAFLD mice at different altitudes was conducted, including a combination of NMR, PAS, and Oil Red O staining, immunofluorescence, qPCR, flow cytometry, ELISA, electron microscopy, and cellular energy metabolism experiments. The high-altitude, high-fat diet group exhibited a reduction in lipid deposition and glycogen content, an increase in lipid droplet autophagy, and a decrease in mitochondrial damage and inflammatory injury when compared to the moderate-altitude, high-fat diet group. The 1% O2 + oleic acid group exhibited enhanced lipid droplet autophagy and increased cellular adaptation in comparison to the 21% O2 + oleic acid group. This study revealed that hypoxic conditions enhanced lipid droplet autophagy, reduced glycolipid accumulation, and alleviated mitochondrial damage in NAFLD mice.

The genomic origin of the unique chaetognath body plan

Abstract The emergence of animal phyla, each with their unique body plan, was a rapid event in the history of animal life, yet its genomic underpinnings are still poorly understood1. Here we investigate at the genomic, regulatory and cellular levels, the origin of one of the most distinctive animal phyla, the chaetognaths, whose organismal characteristics have historically complicated their phylogenetic placement2,3. We show that these characteristics are reflected at the cell-type level by the expression of genes that originated in the chaetognath lineage, contributing to adaptation to planktonic life at the sensory and structural levels4. Similarly to other members of gnathiferans (which also include rotifers and several other microscopic phyla)5,6, chaetognaths have undergone accelerated genomic evolution with gene loss and chromosomal fusions7,8. Furthermore, they secondarily duplicated thousands of genes9,10, without evidence for a whole-genome duplication, yielding, for instance, tandemly expanded Hox genes, as well as many phylum-specific genes. We also detected repeat-rich highly methylated neocentromeres and a simplified DNA methylation toolkit that is involved in mobile element repression rather than transcriptional control. Consistent with fossil evidence11,12, our observations suggest that chaetognaths emerged after a phase of morphological simplification through a reinvention of organ systems paralleled by massive genomic reorganization, explaining the uniqueness of their body plan.

Investigation of anxiety levels and associated factor analysis in breast cancer patients undergoing chemotherapy with implanted venous access ports during the stable phase of disease

Aims To analyze the occurrence of anxiety and its influencing factors in stable stage breast cancer patients after chemotherapy with Implanted Venous Access Port (IVAP). Methods A total of 776 female breast cancer patients who underwent IVAP and completed chemotherapy in a tertiary cancer hospital from February 2019 to December 2021 were selected as the study subjects. General condition survey scale, sociological data, disease data, infusion port situation, and SAS anxiety scale were used for investigation to assess their anxiety status. Factors with statistically significant differences in univariate analysis were used as independent variables, and anxiety scale scores were used as dependent variables for multiple linear regression analysis of anxiety-related factors. Results Among the 776 stable stage breast cancer patients after chemotherapy with IVAP, the average score of the anxiety scale was 50.35 ± 10.93, and the prevalence of anxiety was 58.51%, including 312 (40.21%) mild anxiety patients, 124 (15.98%) moderate anxiety patients, and 18 (2.32%) severe anxiety patients. The results of multivariate analysis showed that physical condition, wound dehiscence, pulling sensation, foreign body sensation, and the use of other venous channels and the order of chemotherapy and surgery were influencing factors of anxiety in stable stage breast cancer patients after implantable venous port chemotherapy (P < 0.05). Conclusions Anxiety is common in stable stage breast cancer patients after chemotherapy with IVAP. Healthcare professionals need to pay attention to patients’ psychological problems, strengthen psychological assessment, standardize and refine infusion port management, and promote patients’ physical and psychological recovery.

Universities are — and must continue to be — a force for good

A GAN-Based Approach for enhancing security in satellite based IoT networks using MPI enabled HPC

Satellite Internet of Things (IoT) networks based on satellites are becoming increasingly critical for mission-critical applications, including disaster recovery, environmental surveillance, and remote sensing. While becoming more widespread, they are also more vulnerable to various risks, particularly due to the heterogeneous communication technologies they support and the limited computing capacity on each device. When such IoT systems are connected with central HighPerformance Computing (HPC) clouds, particularly by satellite links, new security issues arise, the primary one being the secure transmission of confidential information. To overcome such challenges, this research proposes a new security framework termed DLGAN (Deep Learning-based Generative Adversarial Network), specially designed for satellite-based IoT scenarios. The model leverages the strengths of Convolutional Neural Networks (CNNs) for real-time anomaly detection, combined with Generative Adversarial Networks (GANs) to generate realistic synthetic attack data, thereby addressing the challenge of skewed datasets prevalent in cybersecurity research. Since training GANs may be computationally expensive, the model is optimized to run on an HPC system via the Message Passing Interface (MPI) to enable scalable parallel processing of huge IoT data. Fundamentally, the DLGAN model is based on a generator/discriminator mechanism for effectively distinguishing network traffic as either benign or malicious, with the capability to detect 14 different types of attacks. By harnessingAI-enabled GPUs in the HPC cloud, the system can provide fast and accurate detection while maintaining low computational costs. Experimental evaluations demonstrate that the framework significantly enhances detection accuracy, reduces training time, and scales well with large data volumes, making it highly suitable for real-time security operations. In total, this study highlights how integrating advanced deep learning technologies with HPC-based distributed environments can deliver an efficient and dynamic defense mechanism for contemporary IoT networks. The envisaged solution is unique in its ability to scale, maximize efficiency, and resist attacks while securing satellite-based IoT infrastructures.