bluuebunny/crossref_metadata_2025 huggingface dataset:
Association Between Reactive Strength Index and Metabolic Cost of Running in Male Master Athletes
Authors: Tanneau Maxence , Berryman Nicolas , Mujika Iñigo , Nguyen Anh P. , Cappa Darío , Barraud Jeanne , Bosquet Laurent
Published: February 2025

Purpose: To examine the association between reactive strength index (RSI) and metabolic cost of running (MCr) in master athletes. We hypothesized that individuals with a higher RSI would exhibit a lower MCr, that both variables would be associated, and that age would moderate this relationship. Methods: Forty-five male master athletes participated to this study. A median split was performed to constitute 2 age groups (group 1, 47.7 [1.7] y old; group 2, 56.3 [4.6] y old). Participants underwent a single 45-minute session during which RSI was assessed with drop jumps, and MCr, during a continuous exercise of submaximal intensity performed on a treadmill. Results: A small negative association was found between net MCr and RSI in the overall sample (RSI mean r = −.38, P < .05; RSI max r = −.38, P < .05). Group 1 exhibited a lower net MCr (P < .01, d = −0.84) and higher RSI (P < .01, d > 0.82) than group 2. However, the association between the 2 measures was verified specifically in group 2 (RSI from a 20-cm drop jump, r = −.53, P < .01; RSI mean, r = −.50, P < .05; RSI maximum, r = −.57, P < .01). Conclusions: RSI is associated with net MCR in master athletes, particularly in older participants. Additional intervention studies are now required to further explore this association.
Effects of Postactivation Performance Enhancement From Upper-Body Flywheel Overload on Tennis-Serve Performance
Authors: Baiget Ernest , Fernández-Fernández Jaime , Díaz Martina , Colomar Joshua
Published: February 2025

Purpose: (1) To analyze the effects of postactivation performance enhancement (PAPE) induced by upper-limb flywheel resistance training on serve velocity and accuracy in tennis players, (2) to compare the effects of 2 different protocols (low load [LL] vs high load [HL]), and (3) to examine whether PAPE effects are influenced by tennis players’ neuromuscular performance. Methods: Fifteen young competitive tennis players completed 1 familiarization and 3 testing sessions in a randomized order. In the control session, participants performed a warm-up protocol followed by serve-velocity and -accuracy tests. The experimental sessions included 3 sets of 6 repetitions of LL (0.02 kg·m2) or HL (0.08 kg·m2) flywheel shoulder internal rotation prior to the serve-velocity and -accuracy tests. Serve velocity and accuracy were measured at 30 seconds and 3 and 6 minutes after each protocol. Results: There were moderately significant serve-velocity differences between baseline and LL protocols at 3 (P = .009; 5.4% [5.8%]; effect size = 0.927) and 6 minutes in both LL (P = .025; 5.7% [7.2%]; effect size = 0.793) and HL (P = .026; 5.4% [6.8%]; effect size = 0.787) protocols. Serve accuracy remained stable in both protocols and recovery times. No associations were found between mechanical outcomes and percentage changes. Conclusions: Low volume and multiple sets of shoulder internal-rotation flywheel resistance training induced serve-velocity PAPE in competitive tennis players without serve-accuracy impairment in time windows from 3 to 6 minutes. Better neuromuscular performance did not seem to favor PAPE effects.
Physical Exercise Time and Depression Among Adolescents: A Nonlinear Dose–Response Association
Authors: Ge Meng-Wei , Shen Lu-Ting , Hu Fei-Hong , Jia Yi-Jie , Tang Wen , Zhang Wan-Qing , Chen Hong-Lin , Yu De-Jun
Published: February 2025

Background: Although physical exercise has been proven to yield beneficial outcomes for individual health, the dose–response association between physical exercise time and depression among adolescents remains unclear. This study aimed to investigate the association between exercise time and depression among adolescents, as well as the dose–response relationship. Methods: A logistic regression analysis was conducted to determine the correlation between physical exercise time and depression among adolescents. The model controlled for age, ethnicity, economic status, parental relationship, divorce, being an only child, and sleep time. A restricted cubic spline model was used to examine the nonlinear dose–response relationship. Results: A significant inverse correlation was demonstrated between adolescents’ physical exercise time and depression (P = .014). Both insufficient exercise (odds ratios = 1.27; 95% CI, 0.98–1.65; P = .072) and excessive level (odds ratios = 2.14; 95% CI, 1.03–4.47; P = .041) showed positive associations with depression. Restricted cubic spline analysis indicated that appropriate exercise (2.0–9.5 h/wk) may prevent depression, while excessive exercise (>9.5 h/wk) may exacerbate it (P-nonlinear < .001, P-overall < .001). Conclusions: Low physical exercise time is associated with higher risk for depressive symptoms in adolescents, whereas excessive exercise is also associated with higher risk of depression, particularly in boys. The findings of this study underscore the importance of adolescents increasing their physical exercise time, but also maintaining a balance to avoid excessive exercise.
Laboratory observation of ion drift acceleration via reflection off laser-produced magnetized collisionless shocks
Authors: Tang Hui-bo , Hao Yu-fei , Hu Guang-yue , Lu Quan-ming , Ren Chuang , Zhang Yu , Guo Ao , Hu Peng , Wang Yu-lin , Wang Xiang-bing , Zhang Zhen-chi , Yuan Peng , Liu Wei , Si Hua-chong , Yu Chun-kai , Zhao Jia-yi , Wang Jin-can , Zhang Zhe , Yuan Xiao-hui , Yuan Da-wei , Xie Zhi-yong , Xiong Jun , Fang Zhi-heng , Xu Jian-cai , Ju Jing-Jing , Zhang Guo-qiang , Zhu Jian-Qiang , Li Ru-xin , Xu Zhi-zhan
Published: February 2025

Fermi acceleration is believed to be the primary mechanism to produce high-energy charged particles in the Universe, where charged particles gain energy successively from multiple reflections. Here, we present the direct laboratory experimental evidence of ion energization from single reflection off a supercritical collisionless shock, an essential component of Fermi acceleration, in a laser-produced magnetized plasma. A quasi-monoenergetic ion beam with two to four times the shock velocity was observed, which is consistent with the fast ion component observed in the Earth’s bow shock. Our simulations reproduced the energy gain and showed that ions were accelerated mainly by the motional electric field during reflection. The results identify shock drift acceleration as the dominant ion energization mechanism, which is consistent with satellite observation in the Earth’s bow shock. Our observations pave the way for laboratory investigations of the cosmic accelerators, also be beneficial to laser fusion and laser-driven ion accelerator.
The role of electronic excited states in the spin-lattice relaxation of spin-1/2 molecules
Authors: Mariano Lorenzo A. , Nguyen Vu Ha Anh , Petersen Jonatan B. , Björnsson Magnus , Bendix Jesper , Eaton Gareth R. , Eaton Sandra S. , Lunghi Alessandro
Published: February 2025

Magnetic resonance is a prime method for the study of chemical and biological structures and their dynamical processes. The interpretation of many of these experiments relies on understanding how the spin of unpaired electrons exchanges energy with their environment, or lattice, and relaxes to equilibrium. Here, we overcome the common use of effective spin Hamiltonians to describe spin-lattice relaxation in spin-1/2 and apply ab initio open quantum systems theory to their full molecular electronic wavefunction. Simulations for two Cr(V) coordination compounds under this framework show a marked improvement in accuracy and demonstrate that relaxation in spin-1/2 molecules is enabled by virtual transitions to molecular excited states with energy approaching 20,000 cm
–1
. This work establishes a connection between the original theory of Van Vleck and modern electronic structure methods, ultimately exemplifying the urgency of further advancing an ab initio approach to spin-lattice relaxation.
Blue light restores functional circadian clocks in eyeless cave spiders
Authors: Wang Jinhui , Chang Jian , Wang Kai , Liang Bing , Zhu Yang , Liu Zhihua , Liang Xitong , Chen Jian , Peng Yu , Agnarsson Ingi , Li Daiqin , Liu Jie
Published: February 2025

Evolution in profound darkness often leads to predictable, convergent traits, such as the loss of vision. Yet, the consequences of such repeated evolutionary experiments remain obscure, especially regarding fundamental regulatory behaviors like circadian rhythms. We studied circadian clocks of blind cave spiders and their sighted relatives. In the field, cave spiders exhibit low
per
expression and maintain constant activity levels. Curiously, their clocks are not permanently lost; exposure to monochromatic blue light restores both circadian gene expression and behavioral rhythms. Conversely, blocking blue light in sighted relatives induces an arrhythmic “cave phenotype.” Our RNA interference experiments suggest that clock genes regulate the rhythmicity of the huddle response, establishing a link between circadian gene networks and this behavioral rhythm. We demonstrate that circadian regulation is readily toggled and may play a latent role, even in constant darkness. Overall, our study expands understanding of circadian clock variations and paves the way for future research on the maintenance of silent phenotypes.
Reduced RG-II pectin dimerization disrupts differential growth by attenuating hormonal regulation
Authors: Jewaria Pawan Kumar , Aryal Bibek , Begum Rifat Ara , Wang Yaowei , Sancho-Andrés Gloria , Baba Abu Imran , Yu Meng , Li Xiaojuan , Lin Jinxing , Fry Stephen C. , Verger Stephane , Russinova Eugenia , Jonsson Kristoffer , Bhalerao Rishikesh P.
Published: February 2025

Defects in cell wall integrity (CWI) profoundly affect plant growth, although, underlying mechanisms are not well understood. We show that in
Arabidopsis mur1
mutant, CWI defects from compromising dimerization of RG-II pectin, a key component of cell wall, attenuate the expression of auxin response factors
ARF7-ARF19
. As a result, polar auxin transport components are misexpressed, disrupting auxin response asymmetry, leading to defective apical hook development. Accordingly,
mur1
hook defects are suppressed by enhancing
ARF7
expression. In addition, expression of brassinosteroid biosynthesis genes is down-regulated in
mur1
mutant, and supplementing brassinosteroid or enhancing brassinosteroid signaling suppresses
mur1
hook defects. Intriguingly, brassinosteroid enhances RG-II dimerization, showing hormonal feedback to the cell wall. Our results thus reveal a previously unrecognized link between cell wall defects from reduced RG-II dimerization and growth regulation mediated via modulation of auxin-brassinosteroid pathways in early seedling development.
Turning antagonists into allies: Bacterial-fungal interactions enhance the efficacy of controlling
Fusarium
wilt disease
Authors: Li Tuo , Shi Xiaoteng , Wang Jiaguo , Zhou Yihao , Wang Tuokai , Xu Yan , Xu Zhihui , Raza Waseem , Liu Dongyang , Shen Qirong
Published: February 2025

Intense microbial competition in soil has driven the evolution of resistance mechanisms, yet the implications of such evolution on plant health remain unclear. Our study explored the conversion from antagonism to coexistence between
Bacillus velezensis
(
Bv
) and
Trichoderma guizhouense
(
Tg
) and its effects on
Fusarium
wilt disease (FWD) control. We found a bacilysin transmembrane transporter (
Tg
MFS4) in
Tg
, critical during cross-kingdom dialogue with
B
v. Deleting
Tgmfs4
(Δ
Tgmfs4
) mitigated
Bv
-
Tg
antagonism, reduced bacilysin import into
Tg
, and elevated its level in the coculture environment. This increase acted as a feedback regulator, limiting overproduction and enhancing
Bv
biomass. Δ
Tgmfs4
coinoculation with
Bv
demonstrated enhanced FWD control relative to wild-type
Tg
(
Tg
-WT). In addition, the
Tg
-WT+
Bv
consortium up-regulated antimycotic secretion pathways, whereas the Δ
Tgmfs4
+
Bv
consortium enriched the CAZyme (carbohydrate-active enzyme) family gene expression in the rhizosphere, potentiating plant immune responses. This study elucidates the intricacies of bacterial-fungal interactions and their ramifications for plant health.
Compositional shifts and co-occurrence patterns of topsoil bacteria and micro-eukaryotes across a permafrost thaw gradient in alpine meadows of the Qilian Mountains, China
Authors: Wang Zhu , Liu Yang , Wang Fang
Published: February 2025

Soil microorganisms play a pivotal role in the biogeochemical cycles of alpine meadow ecosystems, especially in the context of permafrost thaw. However, the mechanisms driving microbial community responses to environmental changes, such as variations in active layer thickness (ALT) of permafrost, remain poorly understood. This study utilized next-generation sequencing to explore the composition and co-occurrence patterns of soil microbial communities, focusing on bacteria and micro-eukaryotes along a permafrost thaw gradient. The results showed a decline in bacterial alpha diversity with increasing permafrost thaw, whereas micro-eukaryotic diversity exhibited an opposite trend. Although changes in microbial community composition were observed in permafrost and seasonally frozen soils, these shifts were not statistically significant. Bacterial communities exhibited a greater differentiation between frozen and seasonally frozen soils, a pattern not mirrored in eukaryotic communities. Linear discriminant analysis effect size analysis revealed a higher number of potential biomarkers in bacterial communities compared with micro-eukaryotes. Bacterial co-occurrence networks were more complex, with more nodes, edges, and positive linkages than those of micro-eukaryotes. Key factors such as soil texture, ALT, and bulk density significantly influenced bacterial community structures, particularly affecting the relative abundances of the Acidobacteria, Proteobacteria, and Actinobacteria phyla. In contrast, fungal communities (e.g.,
Nucletmycea
,
Rhizaria
,
Chloroplastida
, and
Discosea
groups) were more affected by electrical conductivity, vegetation coverage, and ALT. This study highlights the distinct responses of soil bacteria and micro-eukaryotes to permafrost thaw, offering insights into microbial community stability under global climate change.

IMPORTANCE

This study sheds light on how permafrost thaw affects microbial life in the soil, with broader implications for understanding climate change impacts. As permafrost degrades, it alters the types and numbers of microbes in the soil. These microbes play essential roles in environmental processes, such as nutrient cycling and greenhouse gas emissions. By observing shifts from bacteria-dominated to fungi-dominated communities as permafrost thaws, the study highlights potential changes in these processes. Importantly, this research suggests that the stability of microbial networks decreases with permafrost degradation, potentially disrupting the delicate balance of these ecosystems. The findings not only deepen our understanding of microbial responses to changing climates but also support the development of strategies to monitor and potentially mitigate the effects of climate change on fragile high-altitude ecosystems.
Complete genome sequences of
Klebsiella pneumoniae
,
Klebsiella quasipneumoniae
, and
Klebsiella variicola
clinical isolates from an epidemiology study
Authors: Peralta-Macotela Pedro , Flores-Monzón Bibiana , Lira de León Karla Isabel , Sánchez-Tusie Ana Alicia , Rodríguez-Medina Nadia , Alvarado-Delgado Alejandro , Aguilar-Vera Edgar , Zumaya-Estrada Federico , Garza-Ramos Ulises , García-Gutiérrez Maria Carlota
Published: February 2025

An epidemiology study of
Klebsiella spp
. causing infections was carried out. In the study,
K. pneumoniae
was identified with a prevalence of 94.6%,
K. quasipneumoniae
with 3.8%, and
K. variicola
with 1.6%. Here, we report the draft genome sequence of four selected
Klebsiella pneumoniae
species complex (KpSC) clinical isolates obtained from different sources.
The effects of small geographical resolution and age on the phyllosphere microbial diversity of
Castanopsis eyrei
in subtropical forest
Authors: Xie Lei , Bao XuXu , Chen Shuifei , Ding Hui , Fang Yanming
Published: February 2025

Our understanding of the mechanisms that maintain phyllosphere microbial diversity in natural systems remains far less developed than our understanding of belowground microbiomes. This knowledge gap hinders our comprehension of growth dynamics in the Fagaceae, a predominant tree family in subtropical regions, and the critical role it plays as a major forest community assembly. Here, we tested leaves from
Castanopsis eyrei
, a widespread subtropical Fagaceae species in south-eastern China, sampled across multiple ages within a forest dynamics plot on Mt. Huangshan. Using third-generation sequencing of full-length bacterial 16S rRNA genes and fungal ITS regions, we characterized the associated phyllosphere microbiota. We found that phyllosphere fungal diversity was high, dominated by Teratosphaeriaceae, Trimorphomycetaceae, and Bulleribasidiaceae, while bacterial diversity was lower and primarily comprised Beijerinckiaceae, Isosphaeraceae, and Acidobacteriaceae. Habitat, rather than host age, emerged as the principal factor influencing fungal and pathogen diversity. Linear mixed-effects models revealed a negative relationship between
C. eyrei
biomass and phyllosphere pathogen diversity. Co-occurrence network analysis showed that
C. eyrei
saplings supported the most complex network structure, with
Recuromyces
acting as a key pathogenic fungus, serving as both a module hub and a connector across all age classes. Overall, these findings highlight the ecological importance of habitat in shaping phyllosphere microbial diversity and underscore the interplay between host function and the maintenance of microbial diversity.

IMPORTANCE

Plant surfaces host diverse microbial communities that significantly impact host health and overall forest productivity. However, mechanisms maintaining phyllosphere microbial diversity and their consequences for host plants remain poorly understood. Employing a three-generation high-throughput sequencing approach, we investigated the phyllosphere fungal and bacterial diversity across different microhabitats and ages of
Castanopsis eyrei
, a common species in subtropical forest, China. Our results underscore the presence of exceptionally high microbial diversity on the plant surface, elucidating the taxonomic composition at the family level of key host microorganisms. Furthermore, our observation of a negative correlation between host performance and phyllosphere pathogens underscores the potential self-limiting ability of plants.
A model based cost-utility analysis of Embedding referral to structured self-management education into standard practice (Embedding) compared to usual care for people with type 2 diabetes diagnosis in the last 12 months in England
Authors: Pollard Daniel John , Keetharuth Anju , Brennan Alan , Bodicoat Danielle H , Glab Agnieszka , Hadjiconstantinou Michelle , Mensa Joesph P , Northern Alison , Davies Melanie J
Published: February 2025

Objectives

To conduct a cost-utility analysis of an implementation package that has been developed aiming to embed the referral of people with type 2 diabetes mellitus (T2DM) to structured self-management education (SSME) from primary care into routine practice compared with usual care.

Design

Model-based cost-effectiveness analysis using the School for Public Health Research type 2 diabetes treatment model. With costs and effectiveness parameters coming from analyses of data from a cluster randomised control trial.

Setting

English National Health Service.

Participants

People with T2DM from 64 GP practices in England.

Interventions

Embedding SSME implementation package Usual care.

Primary and secondary outcome measures

The primary outcome measure was the incremental cost-effectiveness ratio. Secondary outcome measures included the probability of Embedding implementation package being cost-effective and value of information.

Results

The estimated cost of the intervention was £40 316 across the study sites, which equates to £0.521 per patient across all practices. For the base case, the estimated mean discounted incremental lifetime cost of the intervention per patient is £48.19. This is associated with a mean per patient incremental quality-adjusted life-year (QALY) estimate of 0.006, producing an incremental cost-effectiveness ratio of £8311 per QALY gained. This has a 73.1% probability of the intervention being cost-effective at a funding threshold of £20 000 per QALY gained. Scenario analyses indicate that alternative parameterisations can lead to this finding being overturned.

Conclusions

The effectiveness of the Embedding packages was hampered by the COVID-19 pandemic. However, our base case analysis shows that Embedding could be cost-effective for this patient population, but this was subject to significant structural uncertainty. This suggests that while implementation initiatives can be highly cost-effective in this population, more robust evidence or further incentivisation will be required before widespread adoption can be recommended.

Trial registration number

NCT23474120
, registered 05/04/2018.
Protocol for a randomised phase 3 trial evaluating the role of Finasteride in Active Surveillance for men with low and intermediate-risk prostate cancer: the FINESSE Study
Authors: Cumberbatch Marcus , North Bernard , Kealy Roseann , Smith Samuel , Hubbard Rachel , Kennish Steven , Bhattrai Selina , Cross William , Chahal Rohit , Bryant Richard , Lamb Alastair D , Dooldeniya Mohantha , Faulkner Simon , Sasieni Peter , Catto James
Published: February 2025

Background

Prostate cancer (PCa) is the most common male malignancy in the western world. Many men (40%) are diagnosed with localised low or intermediate-risk PCa, which is suitable for active surveillance (AS). AS affords careful monitoring to identify changes in otherwise non-life-threatening cancers. While AS reduces overtreatment (and quality of life impact), long-term compliance can be poor, with many men undergoing radical treatment after starting AS.

Methods and analysis

Finasteride in Active Surveillance for men with low and intermediate-risk prostate cancer (FINESSE) is a prospective, open-label, two-arm, phase 3 trial, in which men with low or intermediate PCa are randomised (1:1) to receive AS with or without finasteride (5 mg once a day for 2 years). Randomisation is stratified by age and PCa risk. AS includes regular prostate-specific antigen testing, MRI scans and the offer of repeat biopsy (at 3 years, or if imaging suggests progression). Additional MRI scans and/or biopsies will be performed for biochemical or clinical indications. We aim to recruit 550 men (aged 50 to 75 years) from up to eight sites. Active outpatient follow-up will be for 3–5 years (depending on date recruited), followed by passive registry-based follow-up for up to 10 years. Primary outcome is adherence to AS. Secondary outcomes include rates and type of disease progression, treatments received (for PCa and benign prostatic enlargement), overall and PCa-specific mortality, an understanding of patients/professionals views of this approach and health-related quality of life. An external panel of experts blinded to allocation will review all AS cessation and progression events. Trial pathologist’s and radiologist’s, blinded to allocation, will review representative cases. Analysis is Intention to Treat.

Ethics and dissemination

The study received Health Research Authority and South-Central Oxford Research Ethics Committee (14/12/2021: 21/SC/0349) and CTA/MHRA (29/12/2021: 21304/0274/001–0001) approvals. Results will be made available to providers and researchers via publicly accessible scientific journals.

Trial registration number

NCT16867955
Gut cannabinoid receptor 1 regulates alcohol binge-induced intestinal permeability
Authors: Maccioni Luca , Dvorácskó Szabolcs , Godlewski Grzegorz , Cinar Resat , Iyer Malliga R , Gao Bin , Kunos George
Published: February 2025

Background

Endocannabinoids acting via cannabinoid receptor 1 (CB1R) can elicit increased intestinal permeability (a condition also called ‘leaky gut’). Alcohol binge can adversely affect digestive functions, including intestinal permeability; however, the underlying mechanisms remain incompletely understood. The current study aimed at examining whether CB1R is involved in alcohol binge-induced intestinal permeability.

Methods

We developed intestinal epithelial-specific CB1R knockout (CB1IEC−/−) mice and evaluated thein vivocontribution of gut CB1R in alcohol binge-induced intestinal permeability.

Results

Alcohol binge increased anandamide levels in the proximal small intestine in association with increased intestinal permeability. Radioligand binding and functional assays confirmed that the genetic deletion of intestinal epithelial CB1R did not alter the density or functionality of CB1R in the brain. Additionally, a peripheral CB1R antagonist, (S)-MRI-1891 (INV-202/monlunabant), exhibited comparable binding affinity to CB1R in brain homogenates. An acute oral administration of (S)-MRI-1891 (3 mg/kg) reduced alcohol binge-induced intestinal permeability in littermate control CB1f/f(CB1 floxed/floxed) mice but had no effect in CB1IEC−/−mice, underscoring the role of intestinal CB1R in this phenomenon. Mechanistically, we found that alcohol activated intestinal epithelial CB1R-ERK1/2 pathway with subsequent downregulation of tight junction proteins and reduction in villi length. In addition, targeting intestinal CB1R and downstream ERK1/2 was able to reverse this process, with subsequent upregulation of tight junction proteins and increased villi length, thus improving gut barrier function. Despite the effects on intestinal permeability, deletion of intestinal CB1R did not significantly affect metabolic parameters and liver disease.

Conclusion

Our findings suggest that alcohol promotes leaky gut via the activation of gut epithelial CB1R and demonstrate that inhibition of CB1R with peripheral-restricted selective CB1R antagonists can prevent alcohol binge-induced intestinal permeability.
Association between ambient temperature and years of life lost of external causes of death in 16 prefecture-level regions of Yunnan Province
Authors: Wang Kai , Chen Yang , Zha Yuanyi , Lu Lvliang , Wang Yujin , Guo Pi , Zhang Qingying
Published: February 2025

Background

Many injury deaths are related to the environment. This study examined the impact of ambient temperature on external causes of death in Yunnan Province.

Methods

Data on external causes of death and meteorological information were collected from 2014 to 2020 across 129 counties and districts of Yunnan Province. We estimated associations of the years of life lost (YLL) and its attributable fraction (AF) with temperature using a distributed lag non-linear model in each city and then pooled them in a multivariate meta-regression.

Results

This study included 191 115 external causes of death and daily YLL was 2338.1 years. The relationship between mean temperature and YLL was found to be U-shaped. The AF of the YLL was 12.65% (95% empirical CI (eCI) 7.80% to 16.45%), 18.54% (95% eCI 8.91% to 23.56%) and 15.79% (95% eCI 8.83% to 20.07%) for external causes of death, traffic accidents and other external causes, respectively. Most of the disease burden was attributed to heat temperature. In the disease burden caused by temperature, males, individuals under 75 years old and those of Han ethnicity were mainly affected by heat temperature; individuals over 75 years old and minority populations were mainly affected by cold temperatures. Non-farmers are more affected by temperature than farmers.

Conclusions

The findings suggest that ambient temperature impacts external causes of death, and the results vary by gender, age, ethnicity and occupation. The study shows the importance of implementing preventive measures targeting both the general population and vulnerable groups in order to address external causes of death in future adaptation policies.
Characteristics and clinical outcomes of patients with systemic lupus erythematosus initiating anifrolumab in a real-world setting in Spain (AZAHAR study): an observational study protocol
Authors: Galindo-Izquierdo María , Bahamontes-Rosa Noemí , Sarto-Ferres Berta , Galvez-Fernandez Marta , Cortés-Hernández Josefina
Published: February 2025

Introduction

Anifrolumab (Saphnelo) is approved for adult patients with moderate-severe systemic lupus erythematosus (SLE). Considering its commercialisation in Spain in 2023, observational studies describing the use of anifrolumab in routine clinical practice are limited. The aim of the AZAHAR study is to describe the characteristics and clinical outcomes of patients with SLE who initiated anifrolumab during its first year of marketing in Spain.

Methods and analysis

This is an observational retrospective study including ~120 patients with moderate-severe SLE who received anifrolumab in Spain in 20 centres from 1 June 2023 to 31 May 2024. Patients will be followed up every 6 months after the first infusion of anifrolumab for a period between 6 and 18 months until the end of the study (31 December 2024). Data will be obtained through the review of medical records, considering as primary outcomes disease activity measured by Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) 2000, clinical SLEDAI, Physician Global Assessment and Lupus Low Disease Activity State and remission, defined by Definitions of Remission in SLE-21, and as secondary outcomes, SLE treatment, flare incidence, anifrolumab adherence and persistence (time on treatment) and healthcare resources utilisation.

Ethics and dissemination

The final protocol of the study will be approved by ethics committees/institutional review boards (IRB)/independent ethics committees at each site.

Trial registration number

NCT06626945.
Investigating the potential uptake of microplastic-derived carbon into a boreal lake food web using carbon-13 labelled plastic
Authors: Graves Stephanie , Chen Shao-Min , McNamee Rachel , Rodrigues Tazi H. , Hayden Brian , Rochman Chelsea M. , Provencher Jennifer F. , Rennie Michael D. , Layton-Matthews Daniel , Leybourne Matthew , Sherwood Owen A. , Orihel Diane M.
Published: February 2025

Microplastics degrade slowly over time, leaching carbon (C) that could be subsequently incorporated into aquatic food webs. Current estimates of microplastic degradation vary, and little is known about microplastic-derived C fate under natural environmental conditions. To investigate whether microplastics leach C that is subsequently incorporated into aquatic food webs, we added isotopically enriched microplastics to Lake 378 at the Experimental Lakes Area in Ontario, Canada. In an ∼1100 L limnocorral (in situ open-bottom enclosure), we added 99% 13C-labelled polystyrene (8–216 µm in longest dimension) at a nominal concentration of 3268 particles/L. A second limnocorral without microplastics served as a negative control. Monthly measurements of δ13C-DIC and δ13C-DOC in filtered water revealed no detectable leaching of 13C from the plastic. Compound-specific isotope analysis of δ13C in amino acids of bulk plankton and periphyton revealed a slight (0.5‰) enrichment in 13C, within the range of natural variability for these organisms. Under the natural conditions of temperate oligotrophic lakes, degradation of microplastics is likely a very slow process that was not possible to detect in this 4-month experiment. Future studies should focus on assessing degradation of microplastics under realistic field scenarios to improve estimates of degradation pathways and associated time scales.
An ensemble machine learning bioavailable strontium isoscape for Eastern Canada
Authors: Le Corre Mael , Dargent Felipe , Grimes Vaughan , Wright Joshua , Côté Steeve D. , Reich Megan S. , Candau Jean-Noël , Miller Marrissa , Holmes Brent , Bataille Clement P. , Britton Kate
Published: February 2025

Bioavailable strontium isotope ratios (87Sr/86Sr) distribution across the landscape mainly follow the underlying lithology, making 87Sr/86Sr baseline maps (isoscapes) powerful tools for provenance studies. 87Sr/86Sr has already been used in Eastern Canada (EC) to track food and human remains origins, or to reconstruct animal mobility. While bioavailable 87Sr/86Sr isoscapes for EC can be extrapolated from global datasets using random forest modelling (RF), no regionally calibrated isoscape exists. Here, we produce a regionally calibrated bioavailable 87Sr/86Sr isoscape by analysing plants collected at 136 sites across EC, incorporating updated geological variables and applying a novel ensemble machine learning (EML) framework. We generated and compared isoscapes generated by the traditional RF and the EML approaches. Adding local bioavailable 87Sr/86Sr to a global dataset significantly improved the model prediction with a drastic increase of predicted 87Sr/86Sr and increased spatial uncertainty in the northern Canadian craton. EML produced similar 87Sr/86Sr predictions but with tighter spatial uncertainty distribution. Regionally calibrated RF and EML isoscapes significantly outperformed the global bioavailable RF isoscape, confirming the requirement for collecting local data in data-poor regions. This isoscape provides a baseline in EC to monitor and manage the movements and provenance of agricultural products, natural resources, endangered/harmful migratory species, and archaeological human remains and artifacts.
Design and Analysis of Electricity Anomaly Detection and Diagnosis Models Based on Generative Adversarial Networks
Authors: Sun Ying , Dang Sanlei , Fang Wenchong , Huang Wan , Xu Yanhao
Published: February 2025

Effective energy management and optimal utilization of assets are crucial for a nation’s progress and prosperity. However, as electricity travels from power plants to end users, it incurs two types of losses: Technical Losses (TL) and Non-Technical Losses (NTL). TLs arise from outdated or inefficient technologies, whereas NTLs result from abnormal electricity usage, including electricity theft, which is often conducted to reduce expenses. These losses pose significant challenges to maintaining grid reliability and result in reduced profits for utility operators. Although the implementation of Automatic Metering Infrastructure (AMI) has improved grid predictability, it has also created new vulnerabilities for NTLs through Cyber-Physical Theft Attacks (CPTA). Machine learning techniques have been applied to identify and mitigate CPTA; however, they often fail to capture comprehensive Energy Consumption Patterns (ECPs), limiting their effectiveness in detecting malicious activities. Generative Adversarial Networks (GANs) have shown remarkable success in various anomaly detection applications. In the context of electricity anomaly identification and diagnosis, GANs are particularly effective in modeling typical energy usage patterns and detecting deviations. Building on this foundation, this study introduces an Adaptive GAN (AGAN) model to detect and diagnose electricity anomalies. The AGAN dynamically optimizes key parameters, such as the number of hidden neurons, epochs and steps per epoch, using the Improved Honey Badger Algorithm (IHBA). This optimization enhances the model’s performance, particularly in terms of Detection Accuracy, Critical Success Index (CSI) and False Omission Rate (FOR). The proposed model demonstrates its capability to accurately identify electricity anomalies and has been rigorously evaluated against existing anomaly detection methods. Results highlight AGAN’s superior effectiveness and robustness, establishing it as a reliable solution for improving the reliability and efficiency of electricity grid systems.
Automatic Detection and Location of Energy Metering Anomalies Based on Graph Convolutional Neural Network
Authors: Wu Min , Chen Xiaoyu , Xie Ruibiao , Chen Yongfa , Jiang Zetao
Published: February 2025

In order to improve the service quality of the power grid and ensure the safe and stable operation of the power grid, an in-depth study is carried out on the automatic detection and positioning of abnormal power metering. First, the data clustering algorithm is used to cluster the electric energy metering data. Next, the graph convolutional neural network algorithm is used to automatically detect and locate the abnormal data of electric energy metering. A graph is constructed, and the subgraphs are divided. These subgraphs are then sent to the graph convolutional neural network for processing. Feature extraction is carried out on the points and edges of the graph. This process completes the automatic detection and location of the electric energy metering anomaly based on the graph convolutional neural network. The experimental results show that the proposed algorithm can effectively improve the efficiency and accuracy of automatic detection and positioning of electric energy metering anomalies, and can better meet the needs of actual power work.
Landscape Evaluation of Bohe Fishing Port in Maoming City, China Based on Analytic Hierarchy Process
Authors: Wu Jiawei , Qiu Nengjie , Li Haibo , Pan Chen
Published: February 2025

This study took Bohe Ancient Fishing Port in Maoming City, China as the research object and adopted the analytic hierarchy process (AHP) to construct a landscape evaluation system including 4 criterion layers and 14 index factor layers for this fishing port. The evaluation results indicated that: (1) The weights in the criterion layer in descending order were: weaving and combing life networks B1 (0.3164), straightening out the governance mechanism B4 (0.2872), awakening the cultural base B2 (0.2274), and injecting vitality through innovations B3 (0.1689). (2) The highest and lowest importance values in the indicator factor layer were: ecological improvement (0.1221) and implanting market elements (0.0134) in B1, multi-party participation under the leadership of the government (0.1656) and bottom-up public participation (0.0549) in B4, functional regeneration of historical buildings (0.0929) and creation of historical and cultural corridors (0.0577) in B2, and functional regeneration of historical buildings (0.0929) and creation of historical and cultural corridors (0.0577) in B3. (3) Based on the results obtained from the evaluation system, this paper proposed to strengthen the traffic management of the fishing port, optimize the architectural renewal of the sea-facing section of the fishing port, and improve the cultural connotations of the fishing port.
Torus and Hyperchaos in 3D Lotka–Volterra Map
Authors: Muni Sishu Shankar
Published: February 2025

In this study, we investigate the occurrence of a three-frequency quasi-periodic torus in a three-dimensional Lotka–Volterra map. Our analysis extends to the observation of a doubling bifurcation of a closed invariant curve, leading to a subsequent transition into a state of hyperchaos. The absorption of various saddle periodic orbits into the hyperchaotic attractor is demonstrated through distance computation, and we explore the dimensionality of both stable and unstable manifolds. Various routes to cyclic and disjoint quasi-periodic structures are presented. Specifically, we showcase the transition from a saddle-node connection to a saddle-focus connection, leading to the formation of quasi-periodic closed cyclic disjoint curves, as revealed by the computation of one-dimensional unstable manifold. Additionally, we show an unusual transition from a period-2 orbit to a period-6 orbit and uncover the mechanism related to two subsequent bifurcations: (a) sub-critical Neimark–Sacker bifurcation, and (b) saddle-node bifurcation. Our approach involves the use of computational methods for constructing one-dimensional manifolds, extending saddle periodic orbits through a one-parameter continuation, and employing a multidimensional Newton–Raphson approach for pinpointing the saddle periodic orbits in the three-dimensional map.
Level of Maturity of Competitive Intelligence and Decision-Making in Software Industry: A Knowledge Management Approach
Authors: Bressan André , Tenório Nelson , Brambilla Marcos
Published: February 2025

This study examines the correlation between Competitive Intelligence (competitive intelligence) maturity levels and organisational decision-making styles in software industry firms. For this purpose, we followed the competitive intelligence maturity model established by Zuquetto and Beltrame [(2012). Modelo de maturidade em inteligência competitiva. Global Manager Acadêmica, 1(2), 1–19] and the Organisational Decision-Making Perception Scale (ODMPS) model proposed by Nascimento and Gomide Jr [(2014). Tomada de decisão organizacional. In Novas medidas do comportamento organizacional: ferramentas de diagnóstico e de gestão, M. M. M. Siqueira (ed.), pp. 298–306. Porto Alegre: Artmed] was used to assess organisational decision-making styles. A quantitative study was carried out using a closed-ended questionnaire and a Likert scale, targeting managers of software companies. It is worth noting that technical abbreviations were clarified when first used. In addition, the language used in the study was objective, value-neutral and free of ornamental or figurative language. The structure of the study was clear and concise, with logical causality between each statement. The text followed scientifical guidelines for structure, terminology and footnoting. The results show that a significant number of companies have an intermediate level of competitive intelligence maturity and that the systematic approach to decision-making is ubiquitous. Hence, the Spearman Rank Correlation Coefficient (i.e. Spearman’s rho) indicates a positive correlation between competitive intelligence maturity and systematic decision-making in software companies. So, this research helps to understand the relationship between competitive intelligence and organisational decision-making in software companies. According to the findings, organisations with higher levels of competitive intelligence maturity are more likely to adopt a systematic decision-making style. This is noteworthy because systematic decision-making can lead to improved organisational outcomes. The research has implications for academics and practitioners alike. It provides new insights into the relationship between competitive intelligence and organisational decision-making. For practitioners, the findings suggest that investing in competitive intelligence and adopting a methodical approach to decision-making can improve organisational performance. The relationship between competitive intelligence maturity level and organisational decision-making styles in different industries should be explored in further research.
Supporting the Digital Safety of At-Risk Users: Lessons Learned from 9+ Years of Research & Training
Authors: Matthews Tara , Bursztein Elie , Kelley Patrick Gage , Kissner Lea , Kramm Andreas , Oplinger Andrew , Schou Andreas , Sleeper Manya , Somogyi Stephan , Szostak Dalila , Thomas Kurt , Turner Anna , Woelfer Jill Palzkill , You Lawrence L. , Zahorian Izzie , Consolvo Sunny
Published: February 2025

Creating information technologies intended for broad use that allow everyone to participate safely online—which we refer to as
inclusive digital safety
—requires understanding and addressing the digital-safety needs of a diverse range of users who face elevated risk of technology-facilitated attacks or disproportionate harm from such attacks—i.e.,
at-risk users
. This paper draws from more than nine years of our work at Google to understand and support the digital safety of at-risk users—including survivors of intimate partner abuse, people involved with political campaigns, content creators, youth, and more—in technology intended for broad use. Among our learnings is that designing for inclusive digital safety across widely varied user needs and dynamic contexts is a
wicked problem
with no ‘correct’ solution. Given this, we describe frameworks and design principles we have developed to help make at-risk research findings practically applicable to technologies intended for broad use and lessons we have learned about communicating them to practitioners.
Stop the Hate, Spread the Hope: An Ensemble Model for Hope Speech Detection in English and Dravidian Languages
Authors: Sharma Deepawali , Gupta Vedika , Singh Vivek Kumar , Chakravarthi Bharathi Raja
Published: February 2025

The rise of social media has led to vast amounts of user-generated content, with emotions ranging from joy to anger. Negative comments often target individuals, communities, or brands, prompting successful efforts to detect harmful speech such as hate speech, cyberbullying, and abuse. Recently, another type of speech referred to as ‘Hope Speech’ has gained attention from the research community. Hope speech consists of positive affirmations or words of reassurance, encouragement, consolation or motivation offered to the affected individual/ community during the lean periods of life. However, there has been relatively less research focused on the detection of hope speech, more particularly in low-resource languages. This paper, therefore, attempts to develop an ensemble model for detecting hope speech in some low-resource languages. Data for four different languages, namely English, Kannada, Malayalam and Tamil are obtained and experimented with different deep learning-based models. An ensemble model is proposed to combine the advantages of the better performing models. Experimental results demonstrate the superior performance of the proposed Ensemble (LSTM, mBERT, XLM-RoBERTa) model compared to individual models based on data from all four languages (weighted average F1-score for English is 0.93; for Kannada is 0.74; for Malayalam is 0.82; and for Tamil is 0.60). Thus, the proposed ensemble model proves to be a suitable approach for hope speech detection in the given low resource languages.
Rebalancing Discriminative Responses for Knowledge Tracing
Authors: Cui Jiajun , Qian Hong , Zheng Chanjin , Wang Lu , Yu Mo , Zhang Wei
Published: February 2025

Knowledge tracing (KT) is a crucial task in computer-aided education and intelligent tutoring systems, predicting students’ performance on new questions from their responses to prior ones. An accurate KT model can capture a student’s mastery level of different knowledge topics, as reflected in their predicted performance on different questions. This helps improve the learning efficiency by suggesting appropriate new questions that complement students’ knowledge states. However, current KT models have significant drawbacks that they neglect the imbalanced discrimination of historical responses. A significant proportion of question responses provide limited information for discerning students’ knowledge mastery, such as those that demonstrate uniform performance across different students. Optimizing the prediction of these cases may increase overall KT accuracy, but also negatively impact the model’s ability to trace personalized knowledge states, especially causing a deceptive surge of performance. Towards this end, we propose a framework to reweight the contribution of different responses based on their discrimination in training. Additionally, we introduce an adaptive predictive score fusion technique to maintain accuracy on less discriminative responses, achieving proper balance between student knowledge mastery and question difficulty. Experimental results demonstrate that our framework enhances the performance of three mainstream KT methods on three widely-used datasets.