bluuebunny/crossref_metadata_2025 huggingface dataset:
In Vitro Fertilization with Dichorionic-Diamniotic Twin Pregnancies: A Retrospective Study Comparing Pregnancy Outcomes of Advanced Maternal Age and Age-Appropriate nulliparous women
Authors: Zhao Kaisun , Yuan Chunlan , He Shimei , He Meirong , Jian Wenqian , Yan Jian , Huang Jianchun
Published: November 2024

Objective and Significance:
This study aims to compare the pregnancy outcomes of advanced maternal age and age-appropriate nulliparous women undergoing in vitro fertilization (IVF) with dichorionic-diamniotic twin pregnancies (DCDA).
Methods
A total of 141 nulliparous women who underwent cesarean section due to IVF DCDA twin pregnancies at the Second People's Hospital of Nanning between January 2020 and August 2024 were analyzed. The advanced maternal age group consisted of 47 cases, while the age-appropriate group comprised 94 cases, with propensity score matching (PSM) applied. We observed parameters including body mass index (BMI), parity, age at menarche, gestational week at delivery, preterm birth (PTB), premature rupture of membranes (PROM), low birth weight (LBW), twin growth discordance, intraoperative blood loss, hemoglobin levels in early and late pregnancy, placenta previa, placental abruption, hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus (GDM), intrahepatic cholestasis of pregnancy (ICP), and postpartum hemorrhage (PPH).
Results
The advanced maternal age group exhibited higher rates of twin growth discordance and intraoperative blood loss compared to the age-appropriate group, with statistically significant differences (P < 0.05). However, no significant differences were observed between the groups regarding PTB, LBW, placenta previa, placental abruption, GDM, HDP, ICP, and PPH.
Conclusion
Advanced maternal age nulliparous women undergoing IVF with DCDA twin may face higher risks of twin growth discordance and intraoperative blood loss, but there are no significant differences in other pregnancy complications and outcomes compared to age-appropriate nulliparous women. This suggests that with proper monitoring during pregnancy, favorable outcomes can be achieved in advanced maternal age nulliparous women undergoing IVF with DCDA twin pregnancies.
ADEP‎: ‎A Novel Approach Based on Discriminator-Enhanced Encoder-Decoder Architecture for Accurate Prediction of Adverse Effects in Polypharmacy
Authors: Kobraei Katayoun , Baradaran Mehrdad , Sadeghi Seyed Mohsen , Masumshah Raziyeh , Eslahchi Changiz
Published: November 2024

Background: Unanticipated drug-drug interactions (DDIs) pose a significant risk of severe bodily harm, emphasizing the importance of predicting adverse effects in polypharmacy. Recent advancements in computational methods have aimed to tackle this critical challenge.
Results: We introduce ADEP, a novel approach that integrates a discriminator and an encoder-decoder model to address data sparsity and improve feature extraction accuracy. ADEP utilizes a three-part model including a multiple classification method to predict adverse effects in polypharmacy. Performance evaluation on three benchmark datasets demonstrates that ADEP outperforms several well-known methods, including GGI-DDI, SSF-DDI, LSFC, DPSP, GNN-DDI, MSTE, MDF-SA-DDI, NNPS, DDIMDL, Random Forest (RF), K-Nearest-Neighbor (KNN), Logistic Regression (LR), and Decision Tree (DT). Comprehensive analysis of ADEP’s performance on these datasets highlights key metrics such as Accuracy (ACC), Area Under the Receiver Operating CharacteristicCurve (AUROC), Area Under the Precision-Recall Curve (AUPRC), F-score, Recall, Precision, False Negatives (FN), and False Positives (FP). The results demonstrate that ADEP achieves a more accurate prediction of adverse effects associated with polypharmacy. Furthermore, a case study conducted with real-world patient data illustrates the practical application of ADEP in identifying potential drug-drug interactions and preventing adverse effects.
Conclusions: ADEP represents a significant advancement in predicting adverse effects of polypharmacy, offering improved accuracy and reliability. Its innovative architecture and alternative classification methods contribute to better representation and feature extraction from sparse medical data, thereby enhancing medication safety and patient outcomes. The source code and datasets are available at https://github.com/m0hssn/ADEP.
14-3-3ζ: An Optimal Housekeeping Protein for Western Blot Analysis in Swine Rotator Cuff Tendon Studies
Authors: Rajalekshmi Resmi , Rai Vikrant , Agrawal Devendra K.
Published: November 2024

Healthy biomechanics of the shoulder involving rotator cuff muscles and rotator cuff tendon (RCT) is pivotal for joint stability, yet co-morbid conditions like hyperlipidemia and hyperglycemia can lead to degenerative changes jeopardizing tendon integrity. A change in protein expression, the functional moiety for molecular events, may result in altered healing of RCT and prolonged morbidity. Expression and activity of proteins are critical while investigating the underlying molecular and cellular changes involved in tendinopathy. While investigating the changes in the protein expression of various inflammatory mediators, we observed that the Western Blot bands for commonly used housekeeping genes (GAPDH, β-actin, and α-tubulin) were not uniform in different tendon samples. Therefore, we investigated for an optimal housekeeping gene for Western blot analysis in swine RCT under normal and hyperlipidemic conditions, as this is essential for accurate normalization of protein expression. The study evaluated several housekeeping genes—GAPDH, beta-actin, alpha and beta-tubulin, Ubiquitin C, Cyclophilin A, TATA-box binding protein, and 14-3-3ζ—to ensure robust normalization across experimental setups. The results revealed that the protein expression of 14-3-3ζ was uniform in all samples, thereby validating its suitability as a stable housekeeping protein. The findings are important while studying the RCT pathology in a clinically relevant animal model, like swine, which mimics human RCT and provides translationally significant findings. Thus, the 14-3-3ζ protein will be an ideal housekeeping gene in the design of experiments utilizing musculoskeletal tissues.
A delayed response in area-concentrated search can improve foraging success.
Authors: Chaianunporn Thotsapol , Hovestadt Thomas
Published: November 2024

Background Area-concentrated search (ACS) is a simple movement rule implying that an animal searches for resources using a 'state-dependent correlated random walk'. Accordingly, a forager increases its searching intensity by reducing the directionality of movement ('intensive search mode' or ISM) when it detects a resource item, but if it searches unsuccessfully for a while, it returns to a more straight-line movement to search for new resource locations elsewhere ('extensive search mode' or ESM). In this study, we propose a modified ACS, called delayed-response ACS (dACS), which would be more efficient in resource collecting than the standard ACS.
Methods Instead of immediately switching from ESM to ISM upon encountering a resource as done in the standard ACS, an individual foraging in the dACS mode delays this switch for x steps (the delay parameter) so that it continues moving in a straight line for a while before switching to ISM. We simulated the movement paths of an individual with ACS compared with dACS in a continuous landscape with a single resource cluster and varied two different movement parameters, that is x and the half-saturation constant h that affects how quickly the forager returns to straight line movement, and two landscape parameters, i.e., cluster size and resource density.
Results Our results show that an individual with a suitable delay parameter x for the dACS achieves substantially higher foraging success than an individual with standard ACS (x=0). Optimal foraging success occurs when x is approximately similar to the patch radius r. This is because, with dACS, an individual can penetrate deeper into a cluster and stay longer within it, ultimately increasing the number of resources collected. Modifying the half-saturation constant h also affects foraging success but effects depend on resource density and cluster size. Generally, h modulates the optimal x value only slightly.
Conclusions An individual following a dACS with an adequate delay x can collect more resources from a patch than one using standard ACS; this hold in particular if patches are small or resource density is low. dACS can be interpreted as a survey movement within a resource cluster before switching from ESM to ISM. The dACS rule does not rely on complex spatial memory but only on memorizing whether resources were found or not. It may thus occur also in a wide range of taxa, from organisms without a central nervous system to animals with complex brain systems.
Squamous cell lung cancer coexisting with pulmonary MALT lymphoma: a rare case report
Authors: Li Ao , Jiang Lei , Hu Yin-Ting , Liu Zhi-Hua , Jiang Ben-Yuan
Published: November 2024

Background Mucosa-associated lymphoid tissue (MALT) lymphoma is a type of non-Hodgkin lymphoma that originates from MALT, most commonly in the stomach. However, primary pulmonary MALT lymphoma is particularly rare, and concomitant squamous cell lung cancer is even rarer. Herein, we report a rare case of squamous cell lung cancer coexisting with pulmonary MALT lymphoma. Case presentation A 67-year-old elderly male presented with chest pain and was found to have a lesion approximately 32×14 mm in the left upper lung during health examination. A biopsy confirmed squamous cell lung cancer, with negative EGFR and ALK driver genes, and PD-L1 expression < 1%. 18F-FDG-PET/CT indicated multiple mediastinal lymph node metastases. After three cycles of neoadjuvant immunochemotherapy, the patient underwent left upper lobectomy and radical lymph node dissection. Histopathological and molecular examinations confirmed that the lesion combined with a pulmonary MALT lymphoma, and the neoadjuvant therapy efficacy evaluation of pulmonary squamous cell carcinoma achieved pathological complete response (pCR). Postoperatively, the patient received only two cycles of adjuvant immunotherapy due to interstitial pneumonia. Follow-up a year post-surgery showed no signs of tumor recurrence or metastasis. Conclusion For patients with concurrent primary pulmonary lymphoma (PLL) and lung squamous cell carcinoma, there are currently no definitive treatment guidelines for this scenario. Our case suggests that the treatment strategy should prioritize lung cancer management. Further cases are needed to elucidate the underlying mechanisms and potential treatment options.
NCOR1 Deficiency in Macrophages Aggravates Aortic Aneurysm Formation via the ANGPTL4-ALDOA-MMP2 Axis
Authors: Zhang Deshuai , Zhu Hong , Fu Wenxia , Yitong Pan , Li Ruogu
Published: November 2024

An aortic aneurysm (AA) is a life-threatening cardiovascular condition characterized by progressive aortic dilation and potential rupture. In this study, we determined the function of nuclear receptor corepressor 1 (NCOR1) in macrophages in AA development. First, macrophage-specific NCOR1 knockout (MNKO) mice were generated, followed by treatment with β-aminopropionitrile to induce AA. AA formation was exacerbated in MNKO mice, with increased aortic dilation, elastin degradation, and inflammatory cell infiltration. Furthermore, NCOR1 deficiency promoted M1 macrophage polarization and upregulated the expression of proinflammatory cytokines and matrix metalloproteinases (MMPs). Mechanistically, NCOR1 regulates the ANGPTL4-ALDOA-MMP2 signaling axis in macrophages. Particularly, NCOR1 directly binds to the ANGPTL4 promoter, suppressing its transcription. ANGPTL4 knockdown attenuates NCOR1 deficiency-induced ALDOA and MMP2 upregulation. These findings suggest that macrophage-specific NCOR1 deficiency exacerbates AA formation via enhanced inflammatory responses and extracellular matrix degradation. The identification of the NCOR1-ANGPTL4-ALDOA-MMP2 axis provides new insights into the molecular mechanisms underlying AA development and highlights the essential role of epigenetic regulation in maintaining aortic wall integrity. This discovery may serve as therapeutic targets for preventing and treating AA.
Wideband ratiometric measurement of tonic and phasic dopamine release in the striatum
Authors: Hamid Arif , Gottschalk Amy , Menees Haley , Bogner Celine , Zewde Semele , Jibin Joanna , Gamam Asma , Flink Dylan , Mosissa Meea , Bonneson Faith , Wehelie Hibo , Alonso-Caraballo Yanaira
Published: November 2024

Reward learning, cognition, and motivation are supported by changes in neurotransmitter levels across multiple timescales. Current measurement technologies for various neuromodulators (such as dopamine and serotonin) do not bridge timescales of fluctuations, limiting the ability to define the behavioral significance, regulation, and relationship between fast (phasic) and slow (tonic) dynamics. To help resolve longstanding debates about the behavioral significance of dopamine across timescales, we developed a novel quantification strategy, augmenting extensively used carbon-fiber Fast Scan Cyclic Voltammetry (FSCV). We iteratively engineered the FSCV scan sequence to rapidly modify electrode sensitivity within a sampling window and applied ratiometric analysis for wideband dopamine measurement. This allowed us to selectively eliminate artifacts unrelated to electrochemical detection (i.e., baseline drift), overcoming previous limitations that precluded wideband dopamine detection from milliseconds to hours. After extensive characterization and validation in vitro and in vivo with simultaneous microdialysis, pharmacological, reward, and optogenetic manipulations, we demonstrate the utility of ratiometric FSCV to resolve key questions about how phasic DA transients contribute to setting striatal DA tone. We identify specific DA frequency bands that correlate with canonical microdialysis-defined “tonic” DA levels while also uncovering a paradoxical constraint on the accumulation of phasic DA into tonic levels. Our approach can extend to additional analytes, including serotonin, empowering the emperical testing of contrasting predictions from theories about neuromodulator circuit and computaional mechanisms that support behavioral flexibility.
Secure Novel Hybrid PUF Design For Key Generation and Authentication Applications Of IoT
Authors: Narayanapuram Bhagyalakshmi , Panda Jeebananda
Published: November 2024

This paper presents proposed multi mode memory PUF design for high speed 5G IOT nodes. Since in conventional IOT nodes keys are used to be stored in non volatile memory, This will cause the side channel vulnerability and compromise the integrity. Silicon PUFs are used as feasible solution for this. However there is vulnerabilities in existed PUF architectures. To overcome these a new multi mode memory PUF was designed. This new PUF can be operated in two modes i.e Weak PUF(W) mode Strong(S) PUF mode. Authentication by Strong mode and weak Mode are discussed. The performance evolution metrics of proposed PUFs are close to ideal responses. The vulnerability analysis and possible side channel attacks such as data remanance attack and modeling attacks already performed in the existed memory PUFS were discussed and counter measures are used to design novel PUF of this work. The work is implemented on Artix-7 FPGA The authentication by S mode PUF and W mode PUF for IOT is implemented. The key generation by using W mode is implemented. The propose PUF has uniqueness is 49.96 %, uniformity is 49.87%, BER is 0.41
Biphasic Lubrication Theory of Hydrogels: Transient Response and Sample Size Effects
Authors: Yamaguchi Tetsuo , Sawae Yoshinori
Published: November 2024

Hydrogels are soft and wet materials with remarkable properties. Among such properties, low friction has attracted much attention from scientists and engineers. While many studies investigated the correlation between material properties and frictional behavior, little attention has been paid to other effects, such as sample sizes. In this study, we developed a theoretical model based on the biphasic lubrication theory to describe the frictional behavior of hydrogels against a glass substrate in the rotational shear test. Consequently, we obtained analytical solutions for the time evolutions of friction coefficient, hydrostatic pressure, and elastic stress. To validate our model, we prepared cylindrical PVA (Polyvinyl alcohol) hydrogels with different radii and thicknesses and conducted friction experiments. We confirmed reasonable agreements with theoretical predictions for the transient responses and their size dependences. Interestingly, we found that the friction coefficient at the initial phase decreased drastically with decreasing thickness. Our results indicate the fundamental importance of bulk transport in surface friction of hydrogels, and the controllability of friction by varying the geometry of hydrogels.
Quantitation of the Interplay between Economic Growth and Atmospheric Environment in China's Transition to Green Economy
Authors: Zhang Dan , Li Ziwei , Hu Hao , Wu Jiayuan , Wu Chaohui
Published: November 2024

Quantifying the interplay between economic growth and atmospheric environment (EG-AE) is crucial for the transition of green economy in China. The Aerosol Optical Depth (AOD) variation under GDP growth index (AVGGI) is suggested to measure the air pollutant emissions per unit of economic growth. Geographically weighted regression (GWR) model is used to analyze the spatio-temporal patterns of EG-AE. The results show that: (1) Taking the Hu line as the boundary, AVGGI values present obvious spatio-temporal differences. High AVGGI values are mainly distributed in the Beijing-Tianjin-Hebei urban agglomeration and the Central Plains urban agglomeration. (2) The local R2 shows a striped distribution in the east of the Hu line. There are two distinct symmetrical U-shapes in the region of R2 > 0.6. The local R2 in the west is a low-value zone with poor correlation between GDP and AOD. (3) In 2007 - 2017, the trajectory of the barycenter shift of high-value, medium-value, and low-value zones in China's EG-AE showed a trend of moving westward. China's economic growth pattern has affected the dynamic change of atmospheric environment over the past decade. Therefore, policymakers should formulate urban economic growth patterns which helps reduce urban air pollution, to achieve green economy development.
Gonadal miRNomes and transcriptomes in infected fish reveal sexually dimorphic patterns of the immune response
Authors: Gelderen Tosca A. van , Debnath Pinky , Joly Silvia , Bertomeu Edgar , Duncan Neil , Furones Dolors , Ribas Laia
Published: November 2024

Background
Fish disease outbreaks caused by bacterial burdens are responsible for decreasing productivity in aquaculture. Unraveling the molecular mechanisms activated in the gonads after infections is pivotal for enhancing husbandry techniques in fish farms, ensuring disease management, and selecting the most resistant phenotype.
Methods
Here, an experiment with European sea bass (Dicentrarchus labrax), an important commercial species in Europe, was conducted to study the miRNome and transcriptome through sequencing analysis 48 hours after an intraperitoneal infection with Vibrio anguillarum.
Results
The findings indicate that following infection, testes exhibited more pronounced alterations in both the miRNome and transcriptome. Specifically, males showed approximately 26% more differentially expressed genes in testicular genes compared to females (2,624 vs. 101 DEGs). Additionally, four miRNAs (miR-183-5p, miR-191-3p, miR-451-5p, and miR-724-5p) were significantly expressed post-infection in males, while none were identified in females. Interestingly, upon deep analysis of sexual dimorphic gene modules, a larger number of miRNAs were identified in infected females targeting genes related to the immune system compared to infected males. These results suggest that fish ovaries demonstrate greater resilience in response to infections by suppressing genes related to the immune system through a post-transcriptional mechanism performed by miRNAs. In contrast, testes activate genes related to the immune system and repress genes related to cellular processes to cope with the infection. In particular, the crosstalk between the miRNome and transcriptome in infected males revealed a pivotal gene, namely, insulin-like growth factor binding protein (igfbp), acting as a gene network hub in which miR-192-3p was connected.
Conclusions
The current study elucidated the need to comprehend the basic immune regulatory responses associated with miRNAs and gene regulation networks that depend on fish sex. The data reveal the importance of considering sex as a factor in interpreting the immune system in fish to generate efficient protocols to prevent outbreaks in fish farms.
AEJaya+DE: A Hybrid Feature Selection Methodfor Machine Learning-Based Network IntrusionDetection on Cybersecurity Datasets
Authors: Albasheer Fawzia Omer , Kalaimannan Ezhil , Agarwal Mayank
Published: November 2024

The exponential growth of network traffic in recent years has intensified the need for robust and sustainable security measures. Intrusion Detection Systems (IDS) play a crucial role in maintaining network security but face significant challenges due to the increasing volume and complexity of data. The high dimensionality of network traffic data makes it difficult to efficiently identify and process the most relevant features for effective intrusion detection. To address these challenges and enhance IDS performance, we propose AEJaya+DE, an adaptive optimization technique that combines the Adaptive Enhanced Jaya Algorithm (AEJaya) with Differential Evolution (DE) for effective feature selection in IDS. Unlike the basic Jaya algorithm, which can get trapped in local optima due to its single learning strategy, AEJaya improves local search ability by utilizing local attractors for exploitation and historical population for enhanced global exploration. AEJaya+DE incorporates dynamic parameter adjustment and adaptive probabilistic strategy selection to maintain a balanced exploration and exploitation process. We evaluated the method on two benchmark datasets: UNSW-NB15 and NSL-KDD. AEJaya+DE reduced the feature set from 42 to 21 on UNSW-NB15, achieving 96.10% accuracy with the XGBoost classifier, and from 41 to 24 on NSL-KDD, achieving 99.93% accuracy with the CatBoost classifier. These results demonstrate AEJaya+DE’s ability to significantly enhance IDS performance by selecting a minimal yet highly informative feature set, improving both accuracy and computational efficiency. This novel approach offers a robust and efficient solution for intrusion detection across diverse network environments, contributing to advancements in the field of network security.
Towards Efficient, Fair and Interpretable Neural Dynamic Data Valuation
Authors: Liang Zhangyong , Gao Huanhuan , Zhang Ji
Published: November 2024

In the modern data economy, data has emerged as a valuable form of property, driving the growth of data marketplaces and elevating the importance of data valuation. While existing methods have made progress in this field, they often struggle to simultaneously achieve efficiency, fairness, and interpretability. To address these challenges, we introduce a novel approach called Neural Dynamic Data Valuation (NDDV), which leverages the principles of optimal control theory. NDDV offers a comprehensive framework that accounts for the dynamic nature of data value and the intricate interactions between data points. By reformulating classical valuation criteria through the lens of stochastic optimal control, our method provides a fresh perspective on quantifying data worth. At its core, NDDV employs trajectory learning to accurately identify data value, supported by robust theoretical interpretations. We enhance the method's fairness through a data re-weighting strategy that captures unique features of individual data points, facilitating interactions between individual data states and the weighted mean-field state. Our results demonstrate NDDV's ability to unveil the dynamic process of data valuation while extending to an interpretable model. Importantly, NDDV achieves significant computational efficiency by requiring only a single training session to estimate the value of all data points. This advancement represents a substantial improvement over existing methods, potentially revolutionizing how we approach data valuation in complex, real-world scenarios.
IvoryOS: an interoperable operating system for flexible self-driving laboratories
Authors: Hein Jason , Zhang Wenyu , Hao Lucy , Reish Matthew , Greenwood Rebekah , Depner Noah , Min Jiyoon , El-khawldeh Rama , Prieto Paloma , Trushina Ekaterina
Published: November 2024

Graphical User Interfaces (GUIs) are essential for providing a user-friendly experience to chemists employing Self-Driving Laboratories (SDLs). However, building an interoperable GUI is challenging due to the diverse layouts, frameworks and functionalities of SDLs, which often limit the use of existing GUIs on these SDLs. In this work, we introduce ivoryOS, a configuration-free software that automatically generates a snapshot of an SDL Python script, capturing all device instances, functionalities and argument information. This snapshot allows for the automatic creation of interactive forms that enable visual programming for control and workflow design across any SDLs. We demonstrate an example use case with the Hein Group Purification Platform Optimizing Solubility based Experimentation (PurPOSE) platform. This plug-and-play operating system for SDLs streamlines robot and lab hardware interaction, democratizing access to advanced SDLs for a broader range of scientists.
Biogenesis, molecular characterization and dye degradation efficacy of alkaline protease from an estuarine associated actinobacterium Streptomyces variabilis using in-silico method
Authors: Balamurugan Pandiselvi , Tamilselvan Silambarasan
Published: November 2024

In this study, biogenesis, statistical optimization and molecular modeling of alkaline protease from an estuarine associated actinobacterium Streptomyces variabilis was carried out by Box-Behnken design. Initially, the biogenesis of alkaline protease from the selected actinobacterium was attained through submerged condition. Simultaneously, the actinobacterial mediated biogenesis of alkaline protease was statistically optimized through ‘one factor at a time approach’ using Box-Behnken design in a basal medium constitutes 2.5% w/v of NaCl concentration with pH 8.0, temperature 55°C and 2.50% of inoculum size for 94h of incubation. The analysis of variance (ANOVA) exhibited a maximum level of coefficient (R2 = 0.9720) with more significance (P < 0.0001). In purification step, the alkaline protease expressed 21.93% of recovery with 2.93 of purification fold at the last stage using Sephadex G-100 chromatography. Followed by, the molecular mass of the enzyme was calculated as 35kDa on 10% of SDS-PAGE. The three dimensional structure of purified alkaline protease was predicted with the encoded total amino acid content 481. The maximum stability range of purified alkaline protease was denoted at pH 8, temperature 60°C and the fermentation medium constituted with 1mM of Mg2+, 3.5% of NaCl and 2.5% of casein. The kinetic parameters like Km and Vmax of purified alkaline protease showed 5.158mg/ml and 484.90 ± 2.04µg/min/mg, respectively. Further, the degradation efficacy and the interaction between the alkaline protease as well as dye molecules like acridine orange and erythrosine pink were assessed by in-silico docking method using online Swiss modeling software tool. The decolouration of dyes were evaluated through first order kinetic study with the R2 values 0.9987 & 0.9953 respectively. By keeping this view, this study could be validated that the selected actinobacterium is a potent strain for the production of alkaline protease and also used as dye decoulouring agent.
Microclimate and dry years interfere with landscape structure effects on intraspecific trait variation
Authors: Jacome Santiago Ordonez , Deák Balázs , Valkó Orsolya , Szász Vivien , Neumann Krisztina Verbényiné , Csergő Anna Mária
Published: November 2024

Context
Predicting how changes in weather patterns and land use jointly impact populations is a pressing task in ecology. Microclimate may play a key role in species’ local persistence by modulating regional weather effects. We lack sufficient empirical evidence to understand the relative effects of landscape structure and habitat conditions on intraspecific trait variation.
Objectives
Using a spatially and temporally replicated demographic dataset, we tested the relative effect of landscape structure (area and connectivity of remnant habitat fragments), microclimate (heat load), and fluctuation in weather conditions (study year) on intraspecific plant trait variation, and we investigated whether the local heat load modulated the weather effects on the studied traits.
Methods
We performed repeated measurements of stem height, leaf area, number of stems, main inflorescence length and number of primary side inflorescences of 569 permanently marked individuals of the grassland specialist Salvia nemorosa L. We sampled 13 populations encompassing microhabitats exposed to different heat load levels, over three consecutive years.
Results
Mature individuals had fewer stems in isolated, and taller stems in small habitat fragments. High levels of heat load and dry years affected negatively all measured traits, and the negative effects of exposure to high heat load were generally exacerbated in dry years.
Conclusions
Exposure to strong environmental stressors could ultimately obscure the real effect of human impact on plant populations. Landscape planning for conservation of dry grassland species should ensure not only improved habitat connectivity but also high-quality habitats with heterogeneous microclimates able to buffer weather extremes.
Non-invasive prediction of KRAS mutation in rectal cancer using hybrid intravoxel incoherent motion and diffusion kurtosis model
Authors: YUAN Jie , Wang Ziyuan , Tan Wenli , Zhang Yun , Yan Huamei , Liu Mengxiao , Gong Hangjun , Zhan Songhua
Published: November 2024

Purpose: This study seeks to evaluate the efficacy of the hybrid intravoxel incoherent motion and diffusion kurtosis imaging (IVIM-DKI) model in predicting Sarcoma Viral Oncogene Homologue (KRAS) mutation status in rectal cancer patients.
Materials and Methods: Rectal cancer patients received hybrid IVIM-DKI MRI, surgery, and KRAS mutation status was assessed. The parameters derived from the hybrid IVIM-DKI model, including the apparent diffusion coefficient (ADC), true diffusion coefficient (D), diffusion kurtosis (K), perfusion fraction (f), and pseudo-diffusion coefficient (D*), were compared between the KRAS mutation group and wild-type group. The diagnostic performance was evaluated using the receiver operating characteristic (ROC) curve. The hybrid IVIM-DKI parameters and their association with clinicopathological features were also explored.
Results: In this prospective study, 73 patients (mean age, 66 ± 11 years) of 50 men and 23 women were included. Significant differences were observed between the KRAS mutation and wild-type groups for ADC, D, and K values (p < 0.05). The K value derived from the IVIM-DKI model demonstrated the highest area under the ROC curve (AUC = 0.779) in characterizing KRAS mutation status, with a sensitivity of 88.1% and specificity of 70.3%. The ADC value also showed satisfactory diagnostic performance (AUC = 0.702). Specific IVIM-DKI parameters, such as f and K, were associated with various clinicopathological features, suggesting their potential as imaging biomarkers.
Conclusion: The hybrid IVIM-DKI model, especially the K value, shows promise as a non-invasive tool for predicting KRAS mutation status in rectal cancer patients, potentially improving personalized treatment strategies.
Impact of comorbidity on the association between socioeconomic factors and long-term mortality of intensive care patients
Authors: Dannewitz Anna Aronsson , Svennblad Bodil , Michaëlsson Karl , Lipcsey Miklos , Gedeborg Rolf
Published: November 2024

Purpose

We aimed to estimate the association between socioeconomic status and long-term mortality after intensive care, with a particular focus on the impact of comorbidity.

Methods

First admissions to the ICU, registered in the national Swedish intensive care register between 2009 to 2012, were linked to information on education and income. We estimated the association between these socioeconomic factors and mortality, using Cox regression with follow-up until 2016. Comorbidity was measured with a multi-dimensional comorbidity measure based on hospital discharge diagnoses.

Results

We identified 101 745 ICU patients ≥30 years old. The group with only elementary school had a higher mortality rate than the group with the highest educational level (adjusted HR, 1.20; 95% CI 1.16-1.23). The association was not notably influenced by adjustment for comorbidity. In a landmark analysis, the association was weaker during the first year after ICU admission (adjusted HR, 1.14; 95% CI 1.09-1.18) than after the first year (adjusted HR, 1.28; 95% CI 1.23-1.35). The associations were stronger in patients with lower comorbidity burden than in patients with more severe comorbidity. The associations were largely consistent when income was used to indicate socioeconomic status.

Conclusion

Low educational level was associated with an increased long-term mortality rate after ICU admission, but the association was not notably related to comorbidity. The association was stronger after the first year of follow-up, suggesting that it may be more related to unmeasured background characteristics such as lifestyle factors that are not reflected in measurable comorbidity rather than the ICU admission.
Farmer’s Awareness on Climate Change and Needs for Adaptation. Case Study in Dinajpur and Feni District, Bangladesh
Authors: Chowdhury Rumman Mowla , Mahmud Chowdhury Arman , Alminara Mosammat
Published: November 2024

This study aims to analyze the farmer’s perception of weather pattern changes and their capability to change crop production according to climate alteration. This is one of the leading challenges affecting the performance of agriculture and the livelihood of farmers. They play a major role in the agricultural economy and face many problems during cultivation time mainly caused by the increasing climate change. Farmers are known how to take appropriate steps to cope with this situation and when they perceive change will have to be taken. In three different agroclimatic zones in Bangladesh identifying the main differences of temperature, rainfall, humidity, wind speed varies a lot and discusses with farmers to know their opinion and analyze the impact of these changes in crop production. Primary data collection was undertaken by a questionary survey with individual farmers, focused group discussions and key informant interviews. Analyzing the variance, secondary data of different weather parameters were collected from Bangladesh Meteorological Department (BMD), to cross-check according to farmer's perception and BMD data. Farmers perceived changes in temperature, rainfall, wind rate, frequent flood, drought, type of soil and quality of irrigation water affecting crop production. By analyzing primary data and secondary data, how farmers' perception and weather parameters hugely affect the agricultural system.
Detection of hepatic steatosis with ultrasound attenuation imaging compared to MRI
Authors: Postigliatti Alvaro , Aris Ricardo , Constenla Diego , Campos Oscar , Schiappacasse Giancarlo , Cea Jerson , González Felipe , Cavada Gabriel , Ginesta Alexandra , Silva Claudio
Published: November 2024

Purpose: The main objective of this study was to evaluate the utility of a novel ultrasound technique, Attenuation Imaging (ATI), for detecting hepatic steatosis, comparing the results with magnetic resonance imaging (MRI) as the reference standard. ATI is a non-invasive, lower-cost, and potentially more available method with a shorter examination time than MRI.
Materials and Methods: A diagnostic test design was employed in a sample of 143 randomly selected patients who underwent both MRI and ATI. This diagnostic test study was conducted and reported in accordance with the STARD (Standards for Reporting of Diagnostic Accuracy) initiative. Pearson's correlation was used to compare the values obtained through ATI and MRI, and regression models was applied to assess interaction and confounding variables. Diagnostic performance was analyzed using receiver operating characteristic (ROC) curves and the area under the ROC curve (AUROC).
Results: The ATI and MRI measurements showed a strong correlation (R-squared = 0.9841, p < 0.001). The non-linear regression analysis generated a formula to estimate the percentage of steatosis in MRI based on the steatosis measured by ATI. The ROC analysis revealed an AUROC of 0.8251 (95% CI: 0.75457-0.89565).
Conclusion: The ATI technique demonstrated a strong correlation with MRI for the detection of hepatic steatosis. The non-linear regression used in the study allowed for generating a formula that estimates the percentage of steatosis in MRI based on the steatosis measured by ATI. This indicates that ATI may serve as a more accessible and cost-effective alternative to MRI in detecting and monitoring hepatic steatosis in patients with non-alcoholic liver disease. Clinical Relevance: ATI offers a cost-effective, non-invasive, and accurate diagnostic method for detecting hepatic steatosis, potentially improving access to early diagnosis and treatment.
Modelling transmission of Middle East respiratory syndrome coronavirus in camel populations and the potential impact of animal vaccination
Authors: Dighe Amy , Jombart Thibaut , Ferguson Neil
Published: November 2024

Outbreaks of Middle East Respiratory syndrome coronavirus (MERS-CoV) in humans are driven by recurring zoonotic spillover from camels, leading to demand for camel vaccination. With two vaccine candidates shown to reduce infectiousness, there is a need to better understand transmission of MERS-CoV in camels and assess the potential impact of vaccination. To help address this, we used age-stratified seroprevalence data and a combination of modelling methodologies to estimate key epidemiological quantities including MERS-CoV transmissibility in camels and to estimate vaccine impact on infection incidence. Transmissibility was higher in the Middle East (R0range 3–34) compared to Africa (2–15) and South Asia (2–4), highlighting the need for setting-specific vaccination strategies. Modelling suggested that even if the vaccine only reduced infectiousness rather than susceptibility to infection, vaccinating calves could achieve large reductions in incidence in moderate and high transmission settings, and interrupt transmission in low transmission settings, provided coverage was high (70–90%).
Agro-morphological Characterization Assessment of Rice (Oryza Sativa L.) Varieties
Authors: Howlader Nayan Chandra , Bulbul Mohammad Tanvir Ahmed , Arafat Easir , Rana Md. Sohel , Hasan Md. Ziaul
Published: November 2024

Rice (Oryza sativaL.) is an essential constituent of the global food chain. The goals of this study are to assess the field performance, character association and variability of 30 rice varieties (Oryza sativaL.) accessions collected from various locations of Bangladesh. To evaluate the morphological variability, yield variability and correlation, the study employed a randomized complete block design (RCBD) with three replications. ACC04 exhibited the highest yield (186.19 g), total number of grains per panicle (197.33), panicle length (29.1 cm), the number of filled grain (188.6), grain length (9.86 mm), grain width (3.34 mm), defective grain length (7.63 mm), defective grain breadth (2.92 mm) and 1000 seed weight (31.26 g) and gave lowest the number of unfilled grain (8.6). It can be concluded that rice accessions exhibit a diverse array of qualitative and morphological traits. The varieties were divided into six groups based on cluster. In Cluster I and III, ACC4 gave the highest performance followed by ACC01 and ACC22 in grain length, grain breadth defective grain length, defective grain breadth and 1000 seed weight. Therefore, ACC04, ACC01 and ACC22 would be best and promising variety for rice production.
Mechanism of Quiescent Nanoplastic Formation from Semicrystalline Polymers
Authors: Kumar Sanat , Mendez Nicholas , Sharma Vivek , Valsecchi Michele , Pai Vighnesh , Lee Johnny , Schadler Linda , Muller Alejandro , Watson-Sanders Shelby , Dadmun Mark , Kumaraswamy Guruswamy
Published: November 2024

Polymers are known to spontaneously produce micro (sizes 1μm - 5mm, MPL) and nanoplastics (10nm - 1μm, NPL), but the mechanisms by which environmentally-triggered Å-level random bond breaking events lead to the formation of these relatively large fragments are unclear. Significantly, ~70 % of commercial polymers are semicrystalline, with a morphology comprised of alternating crystalline and amorphous layers, each tens of nanometers thick. It is well-accepted that chain scission events accumulate in the amorphous phase. We show that this leads to mechanical failure of the semicrystalline morphology and the concurrent release of particulate NPL comprised of polydisperse stacks of lamellae even under quiescent conditions. Noncrystalline analogs, which do not have a well-defined microstructure, do not form NPL. While the amorphous phase of the semicrystalline NPL continues to degrade, crystal fragments do not and hence they temporally persist in the environment. These results stress the critical role of polymer microstructure and fracture mechanics on particulate NPL creation.
Synthetic Data for Accessible Learning in Healthcare: Improving Mortality Prediction with Longitudinal Data
Authors: Laribi Hakima , Raymond Nicolas , Taseen Ryeyan , Poenaru Dan , Vallières Martin
Published: November 2024

Accurate prediction of medium-term survival after admission is necessary for identifying end-of-life patients who may benefit from earlier goals of care (GOC) discussions. While previous studies have leveraged admission data from electronic health records (EHRs) to predict the hospital one-year mortality risk (HOMR) score, they focused on single admissions, without considering longitudinal patient history and its impact on prognostication. To address this gap, we developed the Ensemble Long Short-Term Memory (ELSTM) neural network, which learns from multiple visits of the same patient to improve the accuracy of the HOMR score. Furthermore, in this work, we generated a synthetic dataset and made it publicly available to encourage further research in this area while safeguarding patient privacy.
Investigating Percentage Depth Dose Curves in Proton Therapy: A Monte Carlo Geant4 Study on Beam Axis Behavior in Phantoms with Varied Clinical PTO Objects
Authors: Yuwei Zhang , Jinhai Liang
Published: November 2024

This study examines the accuracy of percentage depth dose (PDD) curves in proton therapy using Monte Carlo simulations through the Geant4 toolkit, focusing on beam axis behavior in various phantom models with clinical Proton Therapy Objects (PTOs). Proton therapy’s efficacy relies on precise dose distribution, especially in heterogeneous tissues that vary in density and atomic composition. Through simulated experiments, this research compares PDD curves across different PTO configurations to evaluate how these variations influence dose delivery accuracy. The findings aim to inform proton therapy optimization for enhanced clinical outcomes.
Somatostatin-expressing interneurons induce early NO-driven and late specific astrocyte-mediated vasodilation
Authors: Vo Thanh Tan , Jung Won Beom , Jin Tong , Im Geun Ho , Lee Soohyun , Kim Seong-Gi
Published: November 2024

Somatostatin-expressing (SST) interneurons modulate hemodynamic responses both directly and indirectly, but their precise role remains unclear. Here, we investigated how SST interneurons affect hemodynamics using a combination of electrophysiology, intrinsic optical imaging, calcium imaging, and fMRI with pharmacological, optogenetic, and chemogenetic manipulations. Prolonged optogenetic stimulation of SST neurons induces fast vasodilation through nitric oxide synthase-expressing neurons that co-express SST, and slow vasodilation mediated by astrocytes. Pharmacological blocking of SST receptors suppresses both astrocyte calcium activity and delayed vasodilation, while early vasodilation remains unchanged. Similar neurovascular coupling mechanisms are observed during prolonged sensory stimulation, which also induces both fast and delayed vasodilation. The delayed vasodilation, mediated by the SST-astrocyte pathway, enhances the specificity of cerebral blood volume-weighted fMRI signals to cortical layer 4, as confirmed by chemogenetic inhibition of SST neurons. Our findings suggest that the SST neuron-astrocyte-vascular pathway shapes hemodynamic responses to prolonged stimulation and is critical for achieving high-specificity, laminar-resolution fMRI, which is increasingly pursued in human cognitive studies.
Modelling the compressive strength of non-proprietary ultra-high-performance fiber-reinforced concrete: A D-optimal mixture design approach
Authors: JAMES IME EMMANUEL , Okafor Fidelis Onyebuchi , Mama Benjamin Okwudili
Published: November 2024

This study examines the compressive strength of an innovative non-proprietary ultra-high-performance fibre-reinforced concrete (UHPFRC) using an approach that combines experimental methods and mathematical modeling. The UHPFRC is developed using Portland limestone cement, river sand, rice husk ash, superplasticizer, recycled tire steel fibre, and water. This study aims to design, optimise, and develop prediction models that accurately predict the compressive strength of UHPFRC at 3, 7, 14, 28, 56, and 90 days, subjected to normal curing in water at 21 °C. A D-optimal mixture design approach was used to design the mixes. The laboratory test results of the mixes were studied, yielding prediction models that accurately predict the compressive strength of the UHPFRC with high values of the coefficient of multiple determinations (R2), insignificant lack of fit test results, low coefficient of variation and standard deviation indicate the precision, reliability and consistency of the models. Numerical optimisation revealed that UHPFRC can be designed with less amount of cement (36%), and recycled tire steel fibre (6.258%), yielding compressive strengths of 83.3 MPa, 91.84 MPa, 99.30 MPa, 105.44 MPa, 108.62 MPa, and 111.79 MPa at 3, 7, 14, 28, 56, and 90 days of curing, respectively. The research outcomes suggest that incorporating rice husk ash and recycled tire steel fibres in UHPFRC not only improves the compressive strength but also promotes sustainability in the construction industry, addresses the issue of standard construction material scarcity, reduces construction material costs, and supports local UHPFRC manufacturing.