bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploration of Antioxidative, Antidiarrheal, and Antihyperglycemic Properties of Artocarpus chama Leaves Along With In Silico Analysis
Authors: Hossen Md. Shahriar , Refat K. M. Nazmul Hasan , Faruque Muaz , Kundu Pritam , Karmakar Utpal Kumar
Published: January 2025

Artocarpus chama is a rare member of the Moraceae family that is found in some Asian countries. This plant has some therapeutic uses in folk medicine. This project was carried out on the leaves of this plant to explore some of its pharmacological importance. This plant revealed the presence of different phytochemical groups such as reducing sugars, tannins, flavonoids, alkaloids, gums, glycosides, terpenoids, and steroids. This plant has antioxidant compounds, and the total content of phenolic, flavonoid, and tannin was measured at 38.7 mg GAE/g, 298.37 mg QE/g, and 43.9 mg GAE/g, respectively. In the 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH), H2O2, and superoxide scavenging tests, SC50 values were found to be 232.2, 131.67, and 192.12 μg/mL, respectively. In the FeCl3 reducing assay, the RC50 was 79.71 μg/mL. The n-hexane fraction showed a good antidiarrheal effect, while defecation inhibition was 54.42% and 66.29% at 250 and 500 mg/kg doses, respectively. Both n-hexane and ethyl acetate fractions exhibited a good antihyperglycemic effect in the oral glucose tolerance test in the experimental mice. In α‐glucosidase inhibition, the IC50 value was 25.043 mg/mL. This extract did not show any promising responses in the diuretic, analgesic, and anthelmintic tests. From gas chromatography–mass spectrometry (GC‐MS) investigation, we have found 25 compounds that are displayed in this extricate. After conducting absorption, distribution, metabolism, excretion, and toxicity (ADMET) and molecular coupling analysis, we finally selected four compounds which may be further tested in order to isolate newer antidiarrheal and antihyperglycemic compounds from this plant in the future.
Let the Customers Speak Their Hearts Out: The Role of Verbosity and Emotions in Online Viewer‐to‐Viewer Engagement
Authors: Pasha Fahad Mansoor , Habib Fatima , Kamran Komal , Azam Akbar , Ali Zeeshan , Hussain Dildar
Published: January 2025

This study examines the combined impact of emotions, emojis, and verbosity on online viewer‐to‐viewer engagement, focusing on their interaction in shaping engagement behaviors. Using sentiment analysis with the Syuzhet package in R Studio and logistic regression on over 15,000 YouTube comments from the “YouTube Ads Leaderboard: 2021 Cannes Edition,” this research identifies key drivers of replies to initial comments. Results reveal that verbosity significantly enhances engagement, while emojis generally diminish it. Arousal‐inducing emotions, such as anticipation and anger, positively influence engagement but are moderated by comment length. These findings extend the understanding of digital engagement by integrating textual, emotional, and stylistic elements into a unified framework. The study provides actionable insights for marketers to optimize user interaction and opens avenues for further exploration of engagement strategies across digital platforms.
Intelligent Recognition for Operation States of Hydroelectric Generating Units Based on Data Fusion and Visualization Analysis
Authors: Wang Yongfei , Liu Yu , Li Xiaofei , Wang Tong , Xu Zhuofei , Guo Pengcheng , Liao Bo
Published: January 2025

This paper proposes a novel recognition approach for operation states of hydroelectric generating units based on data fusion and visualization analysis. First, the principal component analysis (PCA) is employed to simplify signals from multiple channels into a single fused signal, thereby reducing data computation for multiple‐channel signals. To reflect the features of fused signals under different operation states, the Gramian angular field (GAF) method is applied to convert the fused signals into image formats, including Gramian angular differential field (GADF) images and Gramian angular summation field (GASF) images, then a depthwise separable convolution neural network (DSCNN) model is established to achieve the operation state recognition for the unit by GADF and GASF images. Based on the operation data from a Kaplan hydroelectric unit at a hydropower station in Southwest China, an experiment on operation recognition is conducted. The proposed PCA–GAF–DSCNN method achieves an accuracy rate of 95.21% with GADF images and 96.41% with GASF images, which were higher than the results obtained using original signals with the GAF–DSCNN method. The results indicate that the fused signal with PCA demonstrates superior performance in the operation recognition compared to the original signals, and PCA–GAF–DSCNN can be used for hydroelectric units effectively. This approach accurately identifies abnormal states in units, making it suitable for monitoring and fault diagnosis in the daily operations of hydroelectric generating units.
Prediction of COD Degradation in Fenton Oxidation Treatment of Kitchen Anaerobic Wastewater Based on IPSO‐BP Neural Network
Authors: Zhang Tianpeng , Ji Pengfei , Tian Dayong , Xu Rui
Published: January 2025

Kitchen anaerobic wastewater contains a high concentration of insoluble organic matter, and the degradation of organic matter in the wastewater is the key to treating kitchen anaerobic wastewater. The Fenton oxidation process is used to treat kitchen anaerobic wastewater, and the effects of H2O2 dosage, Fe2+ dosage, reaction time and pH value on chemical oxygen demand (COD) degradation efficiency are explored. The improved particle swarm optimization (IPSO) algorithm is used to optimize the back propagation (BP) neural network, and a prediction model of COD degradation is established based on IPSO‐BP neural network. H2O2 dosage, Fe2+ dosage, reaction time and pH value are selected as the main influencing factors of the COD degradation, and 30 groups of experimental data are selected to train the IPSO‐BP neural network. The results predicted by the trained IPSO‐BP neural network on 10 groups of test data are compared with the actual values, and the results predicted by BP model and genetic algorithm‐BP (GA‐BP) model are compared. The IPSO‐BP model has the highest fitting accuracy. The root mean square error (RMSE), RMSE coefficient of variation (CV‐RMSE), and coefficient of determination (R2) were used to evaluate the prediction performance of the model. The indicators of the IPSO‐BP model were significantly better than those of the GA‐BP model and the BP model, indicating that IPSO‐BP model had better generalization ability and could predict COD concentration more effectively. The optimal conditions for Fenton oxidation obtained from IPSO‐BP model are as follows: the dosage of H2O2 is 2000 mg/L, the dosage of Fe2+ is 1200 mg/L, the pH value is 2.8, the reaction time is 75 min, and the COD removal rate is 80.125%, which is consistent with the experimental results. Through gas chromatography‐mass spectrometry (GC‐MS) analysis, most organic compounds in kitchen anaerobic wastewater are oxidized and decomposed, indicating that the IPSO‐BP model has good predictive quality.
Focusing on Rare Variants Related to Maturity‐Onset Diabetes of the Young in Children
Authors: Ding Yu , Zhang Qianwen , Gao Shiyang , Li Juan , Chang Guoying , Wang Yirou , Wang Libo , Li Xin , Chen Yao , Yao Ru-en , Yu Tingting , Li Niu , Lou Dan , Wang Xiumin
Published: January 2025

Background: In this study, we analysed the clinical and genetic characteristics and follow‐up data of patients with maturity‐onset diabetes of the young (MODY).

Methods: From January 2015 to December 2022, patients with persistent hyperglycaemia suspected of having monogenic diabetes or diabetes syndrome were recruited, and next‐generation sequencing (NGS) was performed at the Shanghai Children’s Medical Center. Patients’ clinical and laboratory findings were recorded preceding follow‐ups. Candidate variants were verified using Sanger sequencing. Variant pathogenicity was evaluated according to the American College of Medical Genetics and Genomics (ACMG) guidelines.

Results: Genetic testing was performed in 175 children. MODY‐related pathogenic or likely pathogenic gene variants were identified in 30 patients from different families. Of these, 11 were diagnosed with GCK‐MODY (36.7%), six with INS‐MODY (20%), five with HNF1A‐MODY (16.7%), five with ABCC8‐MODY (16.7%), two with HNF1B‐MODY (6.7%) and one with HNF4A‐MODY (3.3%). There was one shift variant and seven splice‐site variants, and the rest were missense variants. We discovered six novel variants. Of the 30 patients, 63.3% had a family history of diabetes, 13.3% had diabetic ketoacidosis (DKA), and 16.7% had positive diabetes‐associated autoantibodies. The diabetes phenotype of patients with the INS variant was similar to that of patients with type 1 diabetes. All patients, including those having positive autoantibodies, required long‐term insulin therapy during follow‐ups. Four patients with the ABCC8 variant were unable to switch to oral sulfonylurea therapy and continued insulin therapy.

Conclusion: Genetic testing is helpful for the precise diagnosis and treatment of patients with MODY, including those with DKA history and positive diabetes autoantibody. GCK‐MODY is the most common type of MODY, and patients with INS variant account for a relatively large proportion of MODY cases in our cohort.
Figure S1 from Serially Quantifying TERT Rearrangement Breakpoints in ctDNA Enables Minimal Residual Disease Monitoring in Patients with Neuroblastoma
Authors: Hollander Jan F. , Szymansky Annabell , Wünschel Jasmin , Astrahantseff Kathy , Rosswog Carolina , Thorwarth Anne , Thole-Kliesch Theresa M. , Chamorro González Rocío , Hundsdörfer Patrick , Hauptmann Kathrin , Schmelz Karin , Gürgen Dennis , Rogasch Julian M.M. , Henssen Anton G. , Fischer Matthias , Schulte Johannes H. , Eckert Cornelia , Eggert Angelika , Lodrini Marco , Deubzer Hedwig E.
Published: January 2025

Figure S1
Figure 4 from Serially Quantifying TERT Rearrangement Breakpoints in ctDNA Enables Minimal Residual Disease Monitoring in Patients with Neuroblastoma
Authors: Hollander Jan F. , Szymansky Annabell , Wünschel Jasmin , Astrahantseff Kathy , Rosswog Carolina , Thorwarth Anne , Thole-Kliesch Theresa M. , Chamorro González Rocío , Hundsdörfer Patrick , Hauptmann Kathrin , Schmelz Karin , Gürgen Dennis , Rogasch Julian M.M. , Henssen Anton G. , Fischer Matthias , Schulte Johannes H. , Eckert Cornelia , Eggert Angelika , Lodrini Marco , Deubzer Hedwig E.
Published: January 2025

Longitudinal TERT breakpoint monitoring in ctDNA detects molecular relapse of high-risk neuroblastoma in patient P4. TERT breakpoint copies (top) and ALK copy numbers (bottom; both detected by ddPCR in purified ctDNA and genomic DNA) as well as selected clinical case information (below time line) are shown for longitudinally collected samples (type and time indicated in the graphical display) from patient P4. Light yellow and white backgrounds represent different treatment modules. BM, bone marrow; CR, complete remission; HSCT, hematopoietic stem cell transplantation; HVA, homovanillic acid in urine/g creatinine; INRC, International Neuroblastoma Response Criteria; max, maximum; mIBG, [123I]meta-iodobenzylguanidine; NDD, no detectable disease; PD, progressive disease; RECIST, response evaluation criteria in solid tumors; RIST, molecularly targeted multimodal therapy consisting of metronomic courses of rapamycin/dasatinib and irinotecan/temozolomide; S, surgery; SIOPEN, The European Association for Neuroblastoma Research; VMA, vanillylmandelic acid in urine/g creatinine.
Expression Patterns of DLL3 across Neuroendocrine and Non-neuroendocrine Neoplasms Reveal Broad Opportunities for Therapeutic Targeting
Authors: Lozada John R. , Elliott Andrew , Evans Mark G. , Wacker James , Storey Kathleen M. , Egusa Emily A. , Zorko Nicholas A. , Kumar Akhilesh , Crymes Anthony , Heath Elisabeth I. , Carneiro Benedito A. , Soares Heloisa P. , Cichocki Frank , Miller Jeffrey S. , Lou Emil , Beltran Himisha , Antonarakis Emmanuel S. , Ryan Charles J. , Hwang Justin H.
Published: January 2025

Neuroendocrine neoplasms (NEN) encompass a diverse set of malignancies with limited precision therapy options. Recently, therapies targeting DLL3 have shown clinical efficacy in aggressive NENs, including small cell lung cancers and neuroendocrine prostate cancers. Given the continued development and expansion of DLL3-targeted therapies, we sought to characterize the expression of DLL3 and identify its clinical and molecular correlates across diverse neuroendocrine and non-neuroendocrine cancers. Here, we interrogated paired DNA and RNA-sequencing from 1,589 NENs across 29 sites, as well as 203,252 tumors across 47 cancer types. We found that high transcriptomic levels of DLL3 correlated with more aggressive histologic and mutational patterns in NENs, with adverse survival outcomes being reflected in NENs originating from the lung, pancreas, stomach, and small bowel. The heterogeneity in DLL3 expression across NENs was largely explained by site of origin, with lung, prostate, and bladder NENs exhibiting relatively high levels of DLL3, whereas gastroenteropancreatic NENs displayed relatively low expression levels. Although the therapeutic targeting of DLL3 may be less applicable for gastroenteropancreatic NENs, we did find an upregulation of alternative targets such as SEZ6, CELSR3, and SSTR2 in these settings. Lastly, expanding our investigation into non-neuroendocrine cancers, we detected an enrichment of DLL3 in both low-grade and high-grade gliomas, Merkel cell carcinomas, medulloblastomas, and melanomas, with such enrichment being associated with prolonged overall survival in gliomas, but worse overall survival in melanomas. Altogether, we demonstrate that DLL3 represents an attractive target for subsets of neuroendocrine and non-neuroendocrine cancers and uncover opportunities for future therapeutic strategies.

Significance:

DLL3-targeted therapies have recently shown robust clinical efficacy in aggressive neuroendocrine cancers, positioning them to fulfill a great unmet need in these settings. Here, we examine the clinical and biological correlates of DLL3 expression in both neuroendocrine and non-neuroendocrine cancers. Our findings may stimulate the development and application of DLL3-targeted therapies, as well as other precision therapies, in neuroendocrine cancers and beyond.
Modeling Heart Failure With Preserved Ejection Fraction Using Human Induced Pluripotent Stem Cell–Derived Cardiac Organoids
Authors: Haim Idan Refael , Gruber Amit , Kazma Noam , Bashai Caroline , Lichtig Kinsbruner Hava , Caspi Oren
Published: January 2025

BACKGROUND:

The therapeutic armamentarium for heart failure with preserved ejection fraction (HFpEF) remains notably constrained. A factor contributing to this problem could be the scarcity of in vitro models for HFpEF, which hinders progress in developing new therapeutic strategies. Here, we aimed at developing a novel, comorbidity-inspired, human, in vitro model for HFpEF.

METHODS:

Human induced pluripotent stem cells–derived cardiomyocytes were used to produce cardiac organoids. The generated organoids were then subjected to HFpEF-associated, comorbidity-inspired conditions, such as hypertension, diabetes, and obesity-related inflammation. To assess the development of HFpEF pathophysiological features, organoids were thoroughly evaluated for their structural, functional, electrophysiological, and metabolic properties.

RESULTS:

Exposure to the combination of all comorbidity-mimicking conditions resulted in the largest cellular volume of 1692±52 versus 1346±84 µm
3
in RPMI (Roswell Park Memorial Institute medium) control group (
P
=0.003), while lower in obesity, hypertension, and diabetes groups: 1059±40 µm
3
(
P
=0.014), 1276±35 µm
3
(
P
=0.940), and 1575±70 µm
3
(
P
=0.146), respectively. Similarly, ultrastructural fibrosis was most significantly observed after exposure to the combination of all HFpEF-inducing conditions 14.6±1.2% compared with single condition exposure 5.2±1.3% (obesity), 6.7±3.5% (hypertension), and 9.0±1.1% (diabetes;
P
<0.001). Moreover, HFpEF-related conditions led to an increase in passive force compared with control (7.52±1.08 versus 2.33±0.46 mN/mm,
P
<0.001), whereas no significant alterations were noted in active contractile forces. Relaxation constant τ was significantly prolonged after exposure to HFpEF conditions showing a prolongation of 95.9 ms (36.4–106.4;
P
=0.028) compared with a shortening of 35.6 ms (43.3–67.3;
P
=0.80) in the control. Finally, organoid exposure to HFpEF conditions led to a significant increase in oxidative stress levels and a significant decline in oxygen consumption rate.

CONCLUSIONS:

We established a novel, human, in vitro model for HFpEF, based on comorbidity-inspired conditions. The model faithfully recapitulated the structural, functional, and mechanistic features of HFpEF. This model holds the potential to provide mechanistic insights and facilitate the identification of novel therapeutic targets.
Test-retest repeatability of intravoxel incoherent motion (IVIM) measurements in the cervical cord
Authors: Lebret Anna , Lévy Simon , Freund Patrick , Callot Virginie , Seif Maryam
Published: January 2025

Intravoxel incoherent motion (IVIM) measurements allow to probe tissue microcirculation non-invasively. Spinal cord perfusion has been shown to be altered following different neurological pathologies. A non-invasive imaging protocol to assess perfusion in the cervical cord is, therefore, clinically relevant. This work aimed at assessing the reliability of IVIM parameters sensitive to perfusion changes in the cervical cord by determining the test-retest variability across subjects and different post-processing fitting algorithms. IVIM test-retest scans were acquired in the cervical cord (C1-C3) of 10 healthy subjects on a 3T MRI scanner, with a 15-minute break in-between. IVIM parameters, including microvascular volume fraction (F), pseudo-diffusion coefficient (D*), blood flow-related coefficient (F·D*), and diffusion coefficient (D), were derived using voxel-wise and region of interest (ROI)-wise fits. The reliability of each IVIM parameter was determined with coefficients of variation (CV), intraclass correlation coefficients (ICC), Bland-Altman analysis, and linear regression. To assess the effects of the different fitting approaches, a two-way repeated-measures analysis of variance (ANOVA) was conducted on the CVs calculated across fitting algorithms. Mean CVs of IVIM parameters calculated across subjects using the voxel-wise fit were lower in the white matter (WM) and grey matter (GM): (WM: 2.6% to 15.6%; GM: 2.2% to 16.4%) compared with those calculated using the ROI-wise fit approach (WM: 4.5% to 32.2%; GM: 3.4% to 53.4%). The voxel-wise fit in the WM yielded higher ICC values (good-to-excellent, 0.71–0.97) compared to the ROI-wise fit approach (poor-to-excellent, 0.49–0.90). IVIM parameters, derived using the voxel-wise fitting approach, demonstrated a high reliability in the cervical cord. Results highlight the high variability of IVIM parameter values depending on the fitting approach, underlining the importance of characterizing the reliability of IVIM acquisition and fitting configuration in the relevant organ of interest. Robust IVIM metrics using a voxel-wise one-step approach, observed across scans and subjects, can facilitate studies targeting perfusion impairment and pave the way to future clinical trials assessing perfusion impairment as a potential quantitative biomarker.
Bundle-specific tractography approach for identifying white matter microstructural changes following traumatic brain injury in rats: An EpiBioS4Rx study
Authors: Sharma Akul , Cabeen Ryan , Harris Neil G. , Wright David K. , Tohka Jussi , Grohn Olli , Bennett Alexis , Alba Celina , Bhagavatula Sweta , Garner Rachael , Asifriyaz Tuba , Ndode-Ekane Xavier Ekolle , Andrade Pedro , Immonen Riikka , Manninen Eppu , Puhakka Noora , Heiskanen Mette , Ali Idrish , Jones Nigel C. , Shultz Sandy R. , Casillas-Espinosa Pablo M. , Hudson Matthew R. , Silva Juliana , Yamakawa Glenn , Braine Emma L. , Smith Gregory D. , Santana-Gomez Cesar E. , Staba Richard J. , O’Brien Terence J. , Pitkanen Asla , Duncan Dominique
Published: January 2025

Traumatic brain injury (TBI) presents a major global health concern, characterized by a variety of negative long-term neurological outcomes. Current diagnostic tools lack the sensitivity to fully capture the complex pathophysiology of TBI and predict long-term consequences, underscoring the need for robust methods for biomarker detection. This study, conducted within the multicenter Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) framework, used a standardized lateral fluid-percussion injury (FPI) model to produce TBI in the left hemisphere of adult male Sprague-Dawley rats across three sites: University of Eastern Finland, Monash University, and the University of California, Los Angeles. This study utilized a novel kernel regression method for improved estimation of fiber orientations and streamline tractography to derive diffusion tensor imaging (DTI) metrics of 36 white matter tracts which were used as features to classify TBI versus sham-operated rodents scanned at 2 days (30 sham, 87 TBI), 9 days (29 sham, 84 TBI), 1 month (28 sham, 81 TBI), and 5 months (25 sham, 65 TBI) post-injury using elastic net regression regularization. A mean area under the curve (AUC) of 0.92 was achieved in correctly classifying the TBI rats in a leave-one-out cross-validation (LOOCV) framework. The results revealed delayed, region-specific effects on the microstructure of the left fimbria and left thalamic subcortical projections at 5 months following TBI. By integrating multi-compartment modeling, tractography, and harmonization, this study advances our understanding of the temporal evolution of TBI pathogenesis, paving the way for development of translational prognostic biomarkers for the risk of post-traumatic epilepsy (PTE).
Parodies of Epicureanism on the Road to Brundisium (Horace, Satire 1.5)
Authors: Paul Joshua M.
Published: January 2025

I argue that Horace Satire 1.5 presents a day in the life of a bumbling, inept Epicurean, one who constantly succumbs to the pitfalls and stereotypes associated with his philosophical school of choice. I draw attention to the narrator’s eager memorization of doctrine, aspirations towards Lucretian scientific analysis, idealization of friendship, constant sickness, exaggerated reaction to “death”, and obsession over food. I then demonstrate how these caricatures help explain the narrator’s complete apathy towards the political embassy, defang the vitriol of potential detractors, and facilitate in-group bonding among fellow Epicureans within the Circle of Maecenas.
Introduction to Fabiola Escárzaga’s ‘The EGTK (Tupac Katari Guerrilla Army): Aymara Insurgency in Bolivia’
Authors: Cabell Patrick
Published: January 2025

This Introduction presents Escárzaga’s essay on the Ejercito Guerrillero Tupac Katari (Tupac Katari Guerrilla Army), presented here for the first time in English translation (https://doi.org/:10.1163/1569206X-00001978). Context for Anglophone readers is given regarding the group’s significance within the broad sweep of Bolivia’s history, as well as noting the scope of this chapter and where it fits within Escárzaga’s 2017 work La comunidad indígena insurgente.
Nymphanthus adenophorus, a new species of Phyllanthaceae from Vietnam
Authors: YAMAMOTO TAKENORI , DANG VAN-SON , SOULADETH PHETLASY , TAGANE SHUICHIRO
Published: January 2025

A new species of Nymphanthus (Phyllanthaceae), N. adenophorus from Ninh Thuan Province, central Vietnam, is described and illustrated, along with its vernacular name and preliminary conservation status. The new species is similar to N. pireyi and N. nanellus, but distinguished by its terete and shorter floriferous branchlets with fewer leaves, larger leaf blades, faintly visible lateral veins, longer pedicels of male flowers, and accordion-folded discs of pistillate flowers.
Puya vallis-colcaensis (Bromeliaceae) a new species from the Peruvian Andes
Authors: TREVIÑO-ZEVALLOS ITALO F. , GOUDA ERIC J. , QUIPUSCOA VICTOR , BRAVO CINTHIA
Published: January 2025

A new Puya species, Puya vallis-colcaensis (Bromeliaceae, Puyopsis), that inhabits the high Andean region of Arequipa in southern Peru, is described and illustrated. This species has greenish-black petals, a compound inflorescence with branches measuring 11–15 cm long, floral bracts that turn dark when dry, and sepals with dense stellate trichomes, carinate toward the apex. This species was locally mistaken for the similar P. weberbaueri, but a comparative and detailed analysis of its morphology reveals that it should be considered a new taxon.
A new species of Siphoneugena and a new combination in Plinia (Myrtaceae)
Authors: CALDAS DIANA K.D. , STADNIK ALINE M.S. , SOUZA MARCELO DA C. , ROSÁRIO ALESSANDRO S. DO , BAUMGRATZ JOSÉ FERNANDO A.
Published: January 2025

Siphoneugena itatiaiensis, endemic to the Itatiaia National Park, in the Brazilian southeastern state of Rio de Janeiro, is proposed as a new species, and is described and illustrated. This new species is morphologically close to S. densiflora, but differs by the combination of oblong leaf blades, pilose flowers with hypanthium not constricted above the ovary, and ovaries with 3 ovules per locule. Additionally, there is proposed, for the southeastern Brazilian species until now named Plinia anonyma, the new combination Plinia sulcata, based in Paramitranthes sulcata.
INDOFLOODS: A Comprehensive Database for Flood Events in India Enhanced with Catchment Attributes
Authors: Kuntla Sai Kiran , Saharia Manabendra
Published: January 2025

Despite floods causing significant loss of life and property, datasets to characterize flooding events in developing countries such as India are not widely available, hampered by limited hydrometric records. Current flood databases are limited to continental river basins, case studies, and government reports, which do not represent the diversity of flooding in terms of climate, basin morphometry, and triggering mechanisms. This first-of-its-kind flood event database called Indian Observational Flood Events Database (INDOFLOODS) is developed using a unique approach of combining long-term station discharge observations with official flooding thresholds for warning and danger water level. Flooding information include start and end time, peak flood level and discharge and its date of occurrence, flood volume, event duration, time to peak, and recession time. Along with metadata such as upstream catchment area, coordinates, shapefiles, and river and tributary names, the database is augmented with a large number of geomorphological, climatological, event-scale precipitation, land-cover, soil, lithology, and anthropogenic characteristics derived at the catchment scale. Preliminary data analysis based on envelope curves shows that the magnitude of extreme floods in India is higher than that reported in the United States. While every dataset has limitations, this collation of flooding events with a plethora of causative hydrogeomorphic factors in a standardized format will be a major asset for the community and serve as an example for how inconsistent data records in developing countries can be turned into useful flood event databases for data-driven studies. This large sample database is expected to cater to a wide range of applications advancing flood research and management, such as trend analysis, hazard and severity assessment, calibration and validation of hydrological and hydraulic models, and developing new metrics for impact assessment.
The Global Seasonal Relationship between Satellite-Observed Cold Pools and Rainfall
Authors: Orenstein Patrick , Sobel Adam H. , Camargo Suzana J. , Elsaesser Gregory S. , Garg Piyush
Published: January 2025

Convective cold pools are important modulators of the onset and evolution of deep convection in the tropics. This work leverages a dataset derived from the Advanced Scatterometer (ASCAT) satellite instrument to quantify seasonal variations in cold-pool activity and their relationship to deep convection across tropical ocean basins. The dataset identifies gradient features (GFs) in the surface wind field, which have been shown to serve as reliable proxies for the boundaries of atmospheric cold pools. We examine the relationship between GFs and climatologies of precipitation, column relative humidity (CRH), and bulk vertical wind shear. We also collocate GFs with precipitation and CRH. High GF frequency, precipitation, and CRH coincide in many regions of the tropics, consistent with our understanding of the physical connections between precipitation and cold-pool generation. On the other hand, climatological bulk wind shear is often low in convective regions, and there is a weak inverse correlation between GF frequency and bulk wind shear, while our prior expectation might have been that shear promotes cold-pool formation. Compared to GF frequency, GF size shows a weaker relationship with the convective environment, with some of the largest GF sizes occurring at lower CRH values for a given rainfall rate. In a few exceptional regions and seasons, such as the Indian Ocean in Northern Hemisphere summer, the region of greatest precipitation does not coincide with the region of greatest GF frequency. These cases also have very high seasonal mean CRH, suggesting that in these regions cold-pool formation is suppressed by reduced evaporation of precipitation.
Evaluation of the Atmospheric Circulation of CMIP6 Models for Extreme Temperature Events Using Latent Dirichlet Allocation
Authors: Malhomme Nemo , Podvin Bérengère , Faranda Davide , Matheli Lionel
Published: January 2025

For climate models to continue improving, we need to uncover as many discrepancies they have with reality as possible. In particular, evaluating the representation of extreme events is important but challenging owing to their rarity. Here, we study how general circulation models reproduce large-scale atmospheric circulation associated with extreme temperature events. To this end, we apply latent Dirichlet allocation (LDA), a dimensionality reduction method, to a set of sea level pressure ERA5 maps over the North Atlantic region. LDA provides a basis of sparse latent modes called “motifs” that consist of localized objects at the synoptic scale. Any pressure map can be approximated by a generally sparse combination of motifs, whose coefficients are called the weights, containing local information about large-scale circulation. Weight statistics can be used to locally characterize circulation patterns, in general and during extreme events, allowing for detailed comparison of datasets. For four CMIP6 models and reanalyses, we quantify local circulation errors and identify model-agnostic and model-specific biases. On average, large-scale circulation is well predicted by all models, but model errors are increased for heat waves and cold spells. Significant errors were found to be associated with Mediterranean motifs for all models in all cases. In addition, the combination of motif and temperature error can discriminate between models in the general and cold spell cases, while models perform similarly on heat waves. The sparse characterization provided by the LDA analysis is, therefore, well suited for the model preselection for the study of extreme events.
Cellular immune response against rabies vaccination in laboratory-bred dogs: A systematised review
Authors: Rathnadiwakara Hasanthi , Amarasekara Sachini , Cliquet Florence , Thibault Jean-Christophe , Jalaldeen Roshan N , Gunatilake Mangala
Published: January 2025

The immunogenicity of rabies vaccines is commonly measured by serological testing, which includes measuring rabies virus-neutralising antibody titre levels in the serum. Apart from humoral immunity, cellular immunity measurements are also helpful in assessing the immunogenicity and efficacy of rabies vaccinations. Recently, there has been an increased emphasis on cellular immunity measurements against rabies in humans and animals. This review aimed to systematically analyse the literature on the composition of cellular immune responses against rabies vaccination in laboratory dogs. A literature survey was conducted to collect suitable articles by searching the research databases PubMed, Web of Science and Scopus. Subsequently, a two-person screening was conducted to identify suitable articles based on predetermined inclusion and exclusion criteria. Data extraction was performed by two authors independently. A total of 1396 studies were identified from the initial search. Following the screening, six studies were selected for final review. Different methods of detecting immune parameters from peripheral blood mononuclear cells were identified from the studies. Reports have demonstrated positive outcomes of the use of adjuvants for cellular immunity development. Even though the lack of specific immunological techniques and the specific reagents have negatively affected these types of cellular immunity measurements, it was evident that combining both humoral and cellular immune parameters against the rabies antigen would provide a clearer picture of the level of responsiveness in animals towards vaccinations and the protection against the disease. The protocol for this review was published in the International Prospective Register of Systematic Review (CRD42022380023).
Ageism and Loneliness in People Over 50: Understanding the Role of Self-Perception of Aging and Social Isolation in a Chilean Sample
Authors: Terán-Mendoza Oscar , Cancino Vicente
Published: January 2025

Population aging represents a global challenge. In this context, loneliness has positioned itself as a critical problem with adverse effects on the physical and mental health of the elderly. This study aimed to explore the role of negative self-perception of aging (SPA) and social isolation as mediators in the relationship between ageism and loneliness. Structural equation modeling (SEM) was used in a sample of 307 people over 50 in Chile. The results show that both age discrimination and ageist stereotypes are directly associated with higher levels of loneliness. Negative SPA significantly mediated the relationships between discrimination and loneliness, as well as between stereotypes and loneliness. These findings highlight the importance of psychological and cultural variables in objective and subjective outcomes of interpersonal relationships, suggesting the need for interventions to mitigate the effects of ageism and improve SPA to favor healthy aging.
Association Between Diabetes Mellitus Education and Self-Management Pre- and Post-COVID-19
Authors: Kim Yejin , Kim Bomgyeol , Rajaguru Vasuki , Lee Sang Gyu , Kim Tae Hyun
Published: January 2025

Purpose

This study explored the association between diabetes education and self-management during different COVID-19 periods.

Design

Cross-sectional study.

Setting

Korea Community Health Survey (2019, 2021, and 2022) and the data from Korea Centers for Disease Control and Prevention Agency.

Participants

78, 860 individuals with diabetes who participated in the 2019, 2021, and 2022 KCHS.

Measure

Diabetes education was categorized according to whether individuals received education on how to manage the disease. Diabetes self-management was assessed using self-checking and screening of HbA1c levels.

Analysis

Multiple logistic regression analysis and a subgroup analysis examined the regional impact of COVID-19 on this association.

Results

Participants who received education before and after COVID-19 were more likely to self-manage their diabetes than those without education (pre-COVID-19 aOR = 2.11, post-COVID-19, 2022 aOR = 2.04, and post-COVID-19, 2021 aOR = 1.94). Those in regions with lower COVID-19 incidence had slightly higher self-management rates (pre-COVID-19 aOR = 2.37; post-COVID-19 2022 aOR = 2.33; post-COVID-19 2021 aOR = 2.02) compared to participants in high-incidence regions (pre-COVID-19 aOR = 1.96; post COVID-19 2021 aOR = 1.89 and post COVID-19 2022 aOR = 1.89).

Conclusions

Diabetes education has a positive impact on self-management, which is especially important during public health crises such as the COVID-19 pandemic.
Orthogonal limited-angle CT reconstruction method based on anisotropic self-guided image filtering
Authors: Changcheng Gong , Qiang Song
Published: January 2025

Computed tomography (CT) reconstruction from incomplete projection data is significant for reducing radiation dose or scanning time. In this work, we investigate a special sampling strategy, which performs two limited-angle scans. We call it orthogonal limited-angle sampling. The X-ray source trajectory covers two limited-angle ranges, and the angle bisectors of the two angular ranges are orthogonal. This sampling method avoids rapid switching of tube voltage in few-view sampling, and reduces data correlation of projections in limited-angle sampling. It has the potential to become a practical imaging strategy. Then we propose a new reconstruction model based on anisotropic self-guided image filtering (ASGIF) and present an algorithm to solve this model. We construct adaptive weights to guide image reconstruction using the gradient information of reconstructed image itself. Additionally, since the shading artifacts are related to the scanning angular ranges and distributed in two orthogonal directions, anisotropic image filtering is used to preserve image edges. Experiments on a digital phantom and real CT data demonstrate that ASGIF method can effectively suppress shading artifacts and preserve image edges, outperforming other competing methods.
Study on the influence of square fiber diameter quality on the optical characteristics of lobster eye X-ray micro pore optics
Authors: Cao Yang , Wang Honggang , Wang Yanan , Li Longhui , Qian Yunsheng , Lang Yizheng
Published: January 2025

Background

The lobster eye micro pore optics (MPO) plays a pivotal role in X-ray focusing, composed of thousands of hollow square microfibers. The channel error in MPO can profoundly impact its focusing performance. Due to the complex manufacturing process of MPO, there are numerous factors that can contribute to channel errors.

Objective

This paper investigates the impact of two key quality indicators of fiber, i.e., diameter precision and ovality, on the focusing performance of flat MPO.

Methods

During the actual production process of MPO, fibers with varying diameter precision and ovality are utilized, and point-to-point vacuum X-ray focusing equipment is used to assess MPO's focusing performance. Channel error models related to fiber diameter accuracy and ovality are established in the simulation.

Results

Experiments show that both the diameter precision and ovality of fiber influence MPO focusing abilities, with diameter precision primarily affecting the intensity and uniformity of the central point focus and the parallelism of the line foci, while ovality mainly affects the intensity and continuity of the line foci. Numerical simulation results reveal that tilt channel errors significantly affect the X-ray focusing effects.

Conclusions

These findings hold important guiding significance for the preparation process of square fibers and high quality X-ray focusing device.
A multi-model machine learning framework for breast cancer risk stratification using clinical and imaging data
Authors: Miao Lu , Li Zidong , Gao Jinnan
Published: January 2025

Purpose

This study presents a comprehensive machine learning framework for assessing breast cancer malignancy by integrating clinical features with imaging features derived from deep learning.

Methods

The dataset included 1668 patients with documented breast lesions, incorporating clinical data (e.g., age, BI-RADS category, lesion size, margins, and calcifications) alongside mammographic images processed using four CNN architectures: EfficientNet, ResNet, DenseNet, and InceptionNet. Three predictive configurations were developed: an imaging-only model, a hybrid model combining imaging and clinical data, and a stacking-based ensemble model that aggregates both data types to enhance predictive accuracy. Twelve feature selection techniques, including ReliefF and Fisher Score, were applied to identify key predictive features. Model performance was evaluated using accuracy and AUC, with 5-fold cross-valida tion and hyperparameter tuning to ensure robustness.

Results

The imaging-only models demonstrated strong predictive performance, with EfficientNet achieving an AUC of 0.76. The hybrid model combining imaging and clinical data reached the highest accuracy of 83% and an AUC of 0.87, underscoring the benefits of data integration. The stacking-based ensemble model further optimized accuracy, reaching a peak AUC of 0.94, demonstrating its potential as a reliable tool for malignancy risk assessment.

Conclusion

This study highlights the importance of integrating clinical and deep imaging features for breast cancer risk stratification, with the stacking-based model.
Preparation and properties of acetylene-functional benzoxazines with comparative phenol sources
Authors: Wen Wei , Luo Wei , Chen Guiyong , Fang Xiong , Zhou Yixue , Ran Qichao
Published: January 2025

High heat-resistant polymer materials are required urgently as the fast development of the aerospace field. The cross-linking characteristic of polymers with the acetylene group provides us with an effective strategy. Here, a series of acetylene-functional benzoxazine monomers with different phenolic compounds, TERT-apa, BA-apa and THPE-apa, were synthesized, and their chemical structures were confirmed by Fourier transform infrared (FTIR) and Nuclear magnetic resonance (NMR) spectra. Their curing behaviors and polymerization reactions were analyzed by differential scanning calorimetry (DSC) and FTIR technology, and possible cross-linking structures were proposed. Meanwhile, their gelation reaction activation energies were obtained by the gelation time test. After curing at 200°C, the thermal properties of these cured polybenzoxazines were studied by Dynamic mechanical analysis (DMA) and Thermogravimetric analysis (TGA). Among them, the glass transition temperature (Tg) of p(BA-apa) can reach as high as 428°C, while p(THPE-apa) had a weight loss temperature over 400°C and a char yield of 60% at 800°C under N2. Therefore, this study shows that the introduction of the acetylene groups is a effective strategy for the preparation of high-performance polymers, which provides some promising high heat resistant materials for the aerospace field.
An iteratively reweighted robust regression model for PV electrical and thermal performance using actual measurement data
Authors: Yaman Kaan , Dölek Sinan , Arslan Gökhan
Published: January 2025

The performance of photovoltaic (PV) modules is inherently dynamic, governed by a complex interplay of meteorological factors such as solar irradiance, temperature, and atmospheric conditions. Accurately and effectively predicting this performance remains a crucial area of research. This study aims to establish the correlation between meteorological parameters and power output as well as cell temperature. For this purpose, a prediction model was developed using iteratively reweighted robust regression to estimate both power output and cell temperature. Robust regression models were developed using real measurement data from the PV system and weather station established at the National Institute of Standards and Technology (NIST). The coefficient of determination (R2) and root mean square error (RMSE) of the proposed model for power output are 0.9870 and 0.0542, respectively. For cell temperature, these values are 0.8443 and 0.2194, respectively. The R2 and RMSE statistics of the proposed models indicate successful performance for the climatic conditions studied. Additionally, a series of experiments were conducted to evaluate the sensitivity of the proposed models to the variation in PV performance across regions. Therefore, the developed model is recommended as a powerful tool for predicting the electrical and thermal performance of PV systems.
Peptidomic Differences Between Natural Musk and Secretions from Forest Musk Gland Cells Cultured In Vitro
Authors: Huang Zhiying , Zhao Guijun , Zeng Dejun , Feng Xiaolan , Zhang Chenglu
Published: January 2025

Background

The Chinese forest musk deer, a solitary ungulate renowned for its musk secretion, is under extinction threat despite its extensive use in traditional Chinese medicine and perfumery. The demand for musk significantly outstrips its natural supply.

Purpose

This study aimed to explore the differences in peptide profiles between cultured musk gland cells and natural musk to develop sustainable alternatives for musk production and aid in the conservation of musk deer.

Materials and Methods

Musk samples from Chinese forest musk deer and cultured cells were collected and analyzed using the EASY-nLC 1000 system. Peptide extraction, nano LC–MS/MS analysis, and advanced peptidomics techniques were employed to identify and compare peptide compositions.

Results

The study found significant differences in secreted and natural musk peptide compositions. Cultured cells could partially replicate the complex peptide environment of natural musk, with some unique peptides identified in natural samples not present in cultured secretions.

Conclusion

While cultured musk gland cells show potential in mimicking natural musk synthesis, notable differences in peptide profiles suggest the importance of the gland’s microenvironment and the deer’s physiological conditions. This research establishes a foundation for optimizing culture techniques to enhance the therapeutic qualities of synthesized musk, contributing to the sustainable production of musk and the conservation of the species.
Comparison of 3 methods of quantification of phenobarbital in canine plasma: high-performance liquid chromatography, a point-of-care immunoassay, and the FDA-approved immunoassay analyzer
Authors: Thungrat Kamoltip , Gibson Ryan , Jukier Tom , Jenkins Alex , Cruz-Espindola Crisanta
Published: January 2025

Phenobarbital is a common antiseizure medication that has a relatively narrow therapeutic window. Therapeutic drug monitoring (TDM) is a helpful tool to guide dose adjustments for phenobarbital and avoid its toxicity. We investigated the agreement among 3 methods of quantifying phenobarbital in canine plasma: high-performance liquid chromatography (HPLC), point-of-care (POC) testing, and the FDA-approved immunoassay analyzer. We randomly selected 45 plasma samples obtained by the TDM service (College of Veterinary Medicine, Auburn University, Auburn, AL, USA). Passing–Bablok regression and Lin concordance correlation coefficients (CCCs) were used to determine the agreement of the results obtained for the 3 methods; Bland–Altman plots were used for bias analysis using the results from the HPLC method as a reference. The FDA-approved immunoassay analyzer and POC immunoassay method results agreed with the HPLC. The results from the FDA-approved immunoassay analyzer were better correlated than those from the POC method, with Lin CCCs of 0.96 (95% CI: 0.93–0.98) and 0.94 (95% CI: 0.90–0.97), respectively. The average biases of the FDA-approved and the POC immunoassay analyzers were 0.80 and −0.64 µg/mL, respectively. Based on the CIs of Lin CCCs, the commercial POC phenobarbital test is a good screening tool and agrees with the HPLC method. However, the FDA-approved immunoassay analyzer method allows for more accurate quantification of phenobarbital concentrations, which is required for appropriate dose adjustment of phenobarbital.
Improving High-Probability Request Sequence Implementation in Elementary School Through the Power of the Premack Principle
Authors: Maag John W.
Published: January 2025

Use of high-probability request sequences is a low-intensity intervention for increasing student compliance. There are several subtleties in implementing high-probability request sequences that make the process more complex. Review of supporting research raises concerns about how well the intervention translates into practice. This article presents foundational information that is critical for effective implementation of high-probability request sequences. The author discusses how use of the Premack principle can improve outcomes for the compliance-oriented intervention.