bluuebunny/crossref_metadata_2025 huggingface dataset:
Regulatory T cells constrain T cells of shared specificity to enforce tolerance during infection
Authors: Klawon David E. J. , Pagane Nicole , Walker Matthew T. , Ganci Nicole K. , Miller Christine H. , Gai Eric , Rodriguez Donald M. , Ryan-Payseur Bridgett K. , Duncombe Ryan K. , Adams Erin J. , Maienschein-Cline Mark , Freitag Nancy E. , Germain Ronald N. , Wong Harikesh S. , Savage Peter A.
Published: February 2025

During infections, CD4
+
Foxp3
+
regulatory T (Treg) cells must control autoreactive CD4
+
conventional T (Tconv) cell responses against self-peptide antigens while permitting those against pathogen-derived “nonself” peptides. We defined the basis of this selectivity using mice in which Treg cells reactive to a single prostate-specific self-peptide were selectively depleted. We found that self-peptide-specific Treg cells were dispensable for the control of Tconv cells of matched specificity at homeostasis. However, they were required to control such Tconv cells and prevent autoimmunity toward the prostate following exposure to elevated self-peptide during infection. Importantly, the Treg cell response to self-peptide did not impact protective Tconv cell responses to a pathogen-derived peptide. Thus, self-peptide-specific Treg cells promoted self-nonself discrimination during infection by selectively controlling Tconv cells of shared self-specificity.
Plant pathogenic fungi hijack phosphate signaling with conserved enzymatic effectors
Authors: McCombe Carl L. , Wegner Alex , Wirtz Louisa , Zamora Chenie S. , Casanova Florencia , Aditya Shouvik , Greenwood Julian R. , de Paula Samuel , England Eleanor , Shang Sascha , Ericsson Daniel J. , Oliveira-Garcia Ely , Williams Simon J. , Schaffrath Ulrich
Published: February 2025

Inorganic phosphate (Pi) is essential for life, and plant cells monitor Pi availability by sensing inositol pyrophosphate (PP-InsP) levels. In this work, we describe the hijacking of plant phosphate sensing by a conserved family of Nudix hydrolase effectors from pathogenic
Magnaporthe
and
Colletotrichum
fungi. Structural and enzymatic analyses of the Nudix effector family demonstrate that they selectively hydrolyze PP-InsP. Gene deletion experiments of Nudix effectors in
Magnaporthe oryzae
,
Colletotrichum higginsianum
, and
Colletotrichum graminicola
indicate that PP-InsP hydrolysis substantially enhances disease symptoms in diverse pathosystems. Further, we show that this conserved effector family induces phosphate starvation signaling in plants. Our study elucidates a molecular mechanism, used by multiple phytopathogenic fungi, that manipulates the highly conserved plant phosphate sensing pathway to exacerbate disease.
Too much of a good thing: Lessons from compromised rootworm Bt maize in the US Corn Belt
Authors: Ye Ziwei , DiFonzo Christina , Hennessy David A. , Zhao Jinhua , Wu Felicia , Conley Shawn P. , Gassmann Aaron J. , Hodgson Erin W. , Jensen Bryan , Knodel Janet J. , McManus Bradley , Meinke Lance J. , Michel Andrew , Potter Bruce , Seiter Nicholas J. , Smith Jocelyn L. , Spencer Joseph L. , Tilmon Kelley J. , Wright Robert J. , Krupke Christian H.
Published: February 2025

Widespread use of genetically engineered maize targeting the corn rootworm complex (
Diabrotica
species) has raised concerns about insect resistance. Twelve years of university field trial and farm survey data from 10 US Corn Belt states indicate that maize hybrids expressing toxins derived from the bacterium
Bacillus thuringiensis
(Bt maize) exhibited declining protection from rootworm feeding with increased planting while pest pressures simultaneously decreased. The analysis revealed a tendency to overplant Bt maize, leading to substantial economic losses; this was particularly striking in eastern Corn Belt states. Our findings highlight the need to go beyond the “tragedy of the commons” perspective to protect sustainable use of Bt and other crop biotechnology resources. We propose moving toward a more diversified and transparent seed supply.
Liver ALKBH5 regulates glucose and lipid homeostasis independently through GCGR and mTORC1 signaling
Authors: Ding Kaixin , Zhang Zhipeng , Han Zhengbin , Shi Lei , Li Xinzhi , Liu Yutong , Li Zhenzhi , Zhao Chongchong , Cui Yifeng , Zhou Liying , Xu Bolin , Zhou Wenjing , Zhao Yikui , Wang Zhiqiang , Huang He , Xie Liwei , Chen Xiao-wei , Chen Zheng
Published: February 2025

Maintaining glucose and lipid homeostasis is crucial for health, with dysregulation leading to metabolic diseases such as type 2 diabetes mellitus (T2DM) and metabolic dysfunction–associated fatty liver disease (MAFLD). This study identifies alkylation repair homolog protein 5 (ALKBH5), an RNA N
6
-methyladenosine (m
6
A) demethylase, as a major regulator in metabolic disease. ALKBH5 is up-regulated in the liver during obesity and also phosphorylated by protein kinase A, causing its translocation to the cytosol. Hepatocyte-specific deletion of
Alkbh5
reduces glucose and lipids by inhibiting the glucagon receptor (GCGR) and mammalian target of rapamycin complex 1 (mTORC1) signaling pathways. Targeted knockdown of hepatic
Alkbh5
reverses T2DM and MAFLD in diabetic mice, highlighting its therapeutic potential. This study unveils a regulatory mechanism wherein ALKBH5 orchestrates glucose and lipid homeostasis by integrating the GCGR and mTORC1 pathways, providing insight into the regulation of metabolic diseases.
Isotopic and compositional constraints on the source of basalt collected from the lunar far side
Authors: Che Xiaochao , Long Tao , Nemchin Alexander , Xie Shiwen , Qiao Le , Li Zengsheng , Ban Yiyi , Fan Runlong , Yang Chun , Liu Dunyi
Published: February 2025

Volcanism on the Moon has produced surface basalt deposits, which record lunar interior processes. The Chang’e-6 mission retrieved samples from the South Pole-Aitken basin (SPA) on the Moon’s far side. We analyze basalt fragments collected by Chang’e-6, finding their composition resembles low-Ti basalts previously sampled by the Apollo missions. U-Pb dating indicates a basalt age of 2823.0 ± 5.9 Ma and a source
238
U/
204
Pb ratio (μ-value) of 480 ± 56. This high μ-value indicates that the source contained materials that formed during late stages of lunar magma ocean (LMO) crystallization. The results are consistent with the LMO model, but the Chang’e-6 basalt deviates from the trend in Apollo mission samples of younger basalts having higher μ-values. We suggest this indicates post-LMO modification of the mantle by the SPA impact.
Assessing market failures driving pesticide resistance
Authors: Brown Zachary , Reisig Dominic
Published: February 2025

Some US farms’ use of transgenic Bt corn raises questions
Tessellated with tiny dumbbells
Authors: Korgel Brian A.
Published: February 2025

Concave and convex surfaces direct nanocrystals to assemble into complex patterns
Virtual reality rewrites rules of the swarm
Authors: Buhl Camille , Simpson Stephen J.
Published: February 2025

Study of locusts in a virtual environment challenges models of collective behavior
Infrared space telescope will probe ‘inflation’ after Big Bang
Authors: Clery Daniel
Published: February 2025

SPHEREx hopes to explain our “boring” uniform universe
U.S. cuts support for IPCC report
Authors: Voosen Paul
Published: February 2025

U.N. climate panel meets without U.S. leadership
Multi-omics analysis reveals associations between gut microbiota and host transcriptome in colon cancer patients
Authors: Qin Yuling , Wang Qiang , Lin Qiumei , Liu Fengfei , Pan Xiaolan , Wei Caibiao , Chen Junxian , Huang Taijun , Fang Min , Yang Weilong , Pan Linghui
Published: February 2025

Colon cancer (CC) is one of the most common cancers globally, which is associated with the gut microbiota intimately. In current research, exploring the complex interaction between microbiomes and CC is a hotspot. However, the information on microbiomes in most previous studies is based on fecal, which does not fully display the microbial environment of CC. Herein, we collected mucosal and tissue samples from both the tumor and normal regions of 19 CC patients and clarified the composition of mucosal microbiota by 16S rRNA and metagenomic sequencing. Additionally, RNA-Seq was also conducted to identify the different expression genes between tumor and normal tissue samples. We revealed significantly different microbial community structures and expression profiles to CC. Depending on correlation analysis, we demonstrated that 1,472 genes were significantly correlated with CC tumor microbiota. Our study reveals a significant enrichment of
Campylobacter jejuni
in the mucosa of CC, which correlates with bile secretion. Additionally, we observe a negative correlation between
C. jejuni
and immune cells CD4+ Tem and mast cells. Finally, we discovered that metabolic bacterial endosymbiont of
Bathymodiolus
sp.,
Bacillus wiedmannii
, and
Mycobacterium tuberculosis
had a significant survival value for CC, which was ignored by previous research. Overall, our study expands the understanding of the complex interplay between microbiota and CC and provides new targets for the treatment of CC.

IMPORTANCE

This study contributes to our understanding of the interaction between microbiota and colon cancer (CC). By examining mucosal and tissue samples rather than solely relying on fecal samples, we have uncovered previously unknown aspects of CC-associated microbiota. Our findings reveal distinct microbial community structures and gene expression profiles correlated with CC progression. Notably, the enrichment of
Campylobacter jejuni
in CC mucosa, linked to bile secretion, underscores potential mechanisms in CC pathogenesis. Additionally, observed correlations between microbial taxa and immune cell populations offer new avenues for immunotherapy research in CC. Importantly, this study introduces CC-associated microbiota with survival implications for CC, expanding therapeutic targets beyond conventional strategies. By elucidating these correlations, our study not only contributes to uncovering the potential role of gut microbiota in colon cancer but also establishes a foundation for mechanistic studies of gut microbiota in colon cancer, emphasizing the broader impact of microbiota research on cancer biology.
A novel double-antibody sandwich ELISA based on monoclonal antibodies against the viral spike protein detects porcine deltacoronavirus infection
Authors: Bai Yingjie , Yu Ruiming , Zhou Guangqing , Zhang Liping , Wang TianTian , Liu Ya , Wang Dongsheng , Zhang Zhongwang , Wang Yonglu , Guo Huichen , Pan Li , Liu Xinsheng
Published: February 2025

Porcine deltacoronavirus (PDCoV) is a significant emerging pathogen that causes severe enteric disease in swine, and therefore significant economic losses in the pig farming industry. Here, we developed a novel double-antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA) based on two monoclonal antibodies directed against the PDCoV spike protein. These two monoclonal antibodies were obtained through hybridoma fusion and screening, and they can specifically react with the PDCoV spike protein. The detection limits of the DAS-ELISA for the recombinant spike protein and viral titer were approximately 0.12 ng/mL and 1.96 × 10³ copies/μL, respectively. The DAS-ELISA did not cross-react with other swine enteric coronaviruses, including porcine epidemic diarrhea virus, transmissible gastroenteritis virus, or porcine rotavirus. A total of 145 rectal swab samples were collected and tested for the presence of PDCoV with the DAS-ELISA and reverse transcription-quantitative PCR (RT-qPCR). The coincidence rate between the DAS-ELISA and RT-qPCR was 91.03%, with a kappa value of 0.814, indicating that the DAS-ELISA is a reliable method for viral antigen detection in clinical samples. DAS-ELISA had a sensitivity of 92.85% and a specificity of 89.89%. The positive predictive value and negative predictive value of this method are 85.25% and 95.24%, respectively. Furthermore, the DAS-ELISA can also be used to detect the spike protein in PDCoV vaccines, making it a valuable tool for assessing the efficacy of PDCoV vaccines.

IMPORTANCE

Since 2014, porcine deltacoronavirus (PDCoV) has spread widely across multiple countries and regions, causing significant economic losses to the global livestock industry. Currently, no commercially available vaccine exists for the prevention of PDCoV infection; therefore, accurate and effective diagnostic methods are crucial for its control and prevention. In this study, the PDCoV S protein expressed in Chinese Hamster Ovary (CHO) cells was used to immunize mice, and a novel double-antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA) was established based on two monoclonal antibodies. The DAS-ELISA had high sensitivity, good repeatability, strong specificity, and high consistency for detecting clinical samples and spike protein in PDCoV vaccines. Therefore, the DAS-ELISA established in this study may be a reliable and effective tool for detecting PDCoV infection and the efficacy of PDCoV vaccines.
Disorganisation of inner retinal layers in diabetic macular oedema: is it time to standardise this OCT biomarker?
Authors: Danieli Luca , Midena Giulia , Frizziero Luisa , Midena Edoardo
Published: February 2025

Disorganisation of inner retinal layers (DRIL) is an optical coherence tomography (OCT) biomarker in patients with diabetic macular oedema. Different ways of quantification of DRIL have been proposed, without final agreement. We found a significant difference in DRIL length if measured with different techniques. Our data highlight that DRIL needs to be measured in a standardised way to provide comparable clinical results. Whereas an international consensus is needed, DRIL measurement as mean of five central OCT scans spaced 120 µm seems better than a single scan and comparable to seven scans, which needs a longer assessment time.
Glucagon-like peptide-1 receptor agonists and risk of suicidality among patients with type 2 diabetes: active comparator, new user cohort study
Authors: Shapiro Samantha B , Yin Hui , Yu Oriana Hoi Yun , Rej Soham , Suissa Samy , Azoulay Laurent
Published: February 2025

Objective

To determine whether the use of glucagon-like peptide-1 (GLP-1) receptor agonists is associated with an increased risk of suicidal ideation, self-harm, and suicide among patients with type 2 diabetes compared with the use of dipeptidyl peptidase-4 (DPP-4) inhibitors or sodium-glucose cotransporter-2 (SGLT-2) inhibitors.

Design

Active comparator, new user cohort study.

Setting

Primary care practices contributing data to the UK Clinical Practice Research Datalink linked to the Hospital Episodes Statistics Admitted Patient Care and Office for National Statistics Death Registration databases.

Participants

Patients with type 2 diabetes.

Exposures

Two cohorts were assembled, with the first composed of patients who started and continued on GLP-1 receptor agonists or DPP-4 inhibitors between 1 January 2007 and 31 December 2020 and the second composed of patients who started and continued on GLP-1 receptor agonists or SGLT-2 inhibitors between 1 January 1 2013 and 31 December 2020. Both cohorts were followed until 29 March 2021.

Main outcome measures

The primary outcome was suicidality, defined as a composite of suicidal ideation, self-harm, and suicide. Secondary outcomes were each of these events considered separately. Propensity score fine stratification weighted Cox proportional hazards models were fitted to estimate hazard ratios and 95% confidence intervals (CIs) to estimate the average treatment effect among the treated patients.

Results

The first cohort included 36 082 GLP-1 receptor agonist users (median follow-up 1.3 years) and 234 028 DPP-4 inhibitor users (median follow-up 1.7 years). In crude analyses, GLP-1 receptor agonist use was associated with an increased incidence of suicidality compared with DPP-4 inhibitors (crude incidence rates 3.9
v
1.8 per 1000 person years, respectively; hazard ratio 2.08, 95% CI 1.83 to 2.36). This estimate decreased to a null value after confounding factors were accounted for (hazard ratio 1.02, 95% CI 0.85 to 1.23). The second cohort included 32 336 GLP-1 receptor agonist users (median follow-up 1.2 years) and 96 212 SGLT-2 inhibitor users (median follow-up 1.2 years). Similarly, GLP-1 receptor agonist use was associated with an increased risk of suicidality compared with SGLT-2 inhibitors in crude analyses (crude incidence rates 4.3
v
2.7 per 1000 person years; hazard ratio 1.60, 95% CI 1.37 to 1.87) but not after confounding factors were accounted for (0.91, 0.73 to 1.12). Similar findings were observed when suicidal ideation, self-harm, and suicide were analysed separately in both cohorts.

Conclusions

In this large cohort study, the use of GLP-1 receptor agonists was not associated with an increased risk of suicidality compared with the use of DPP-4 inhibitors or SGLT-2 inhibitors in patients with type 2 diabetes.
Patient safety incident reporting systems and reporting practices in African healthcare organisations: a systematic review and meta-analysis
Authors: Fekadu Gelana , Muir Rachel , Tobiano Georgia , Ireland Michael J , Engidaw Melaku Tadege , Marshall Andrea P
Published: February 2025

Background

Patient safety incident reporting and learning systems are crucial for improving the safety and quality of healthcare. However, comprehensive evidence of their availability and use in African healthcare organisations is lacking. Therefore, this review aims to synthesise the existing literature on these systems and reporting practices within African healthcare organisations.

Methods

A systematic review and meta-analysis were conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Five electronic databases, including PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL) via EBSCOhost, Scopus, Web of Science and the Excerpta Medica Database (Embase), were searched to identify relevant records. Peer-reviewed articles and guidelines published in English were included in this review. Quality appraisal was performed using the Joanna Briggs Institute and Quality Assessment with Diverse Studies tool. A random effects model was used to compute the pooled prevalence using Stata V.17.0.

Results

A systematic search retrieved 9279 records, of which 39 (36 articles and 3 guidelines) were included in this review. Eight patient safety incident reporting and learning systems were identified, with compliance rates ranging from low (16%) to high (87%) based on the WHO criteria. The pooled prevalence of patient safety incident reporting practices was 48% (95% CI 40% to 56%). However, the studies exhibited high heterogeneity (I²=98.75%, p<0.001).

Conclusion

In African healthcare organisations, it is imperative to establish robust patient safety incident reporting and learning systems, as none of the existing systems fully meet WHO criteria. In addition, optimising the existing systems and encouraging healthcare professionals to improve reporting practices will enhance patient safety and outcomes.

PROSPERO registration number

CRD42023455168.
E-twenty-six-specific sequence variant 5 (ETV5) facilitates hepatocellular carcinoma progression and metastasis through enhancing polymorphonuclear myeloid-derived suppressor cell (PMN-MDSC)-mediated immunosuppression
Authors: Zhang Zerui , Huang Wenjie , Hu Dian , Jiang Junqing , Zhang Jiaqian , Wu Zhangfan , Wen Junjie , Luo Xiangyuan , Wang Yijun , Sun Mengyu , Li Siwen , Wang Yufei , Liu Danfei , Chen Xiaoping , Zhang Bixiang , Liang Huifang , Li Yiwei , Liu Bifeng , Wang Shuai , Xu Xiao , Nie Yongzhan , Wu Kaichun , Fan Daiming , Xia Limin
Published: February 2025

Background

Despite the success of immune checkpoint blockade, a lack of understanding of the hepatocellular carcinoma (HCC) immune microenvironment impedes its development.

Objective

We aim to elucidate the essential function of E-twenty-six-specific sequence variant 5 (ETV5) in regulating the immune microenvironment in HCC.

Design

Humanised mouse models, murine orthotopic models and diethylnitrosamine/carbon tetrachloride (DEN/CCl4)-induced HCC models were used to examine the function of ETV5. The downstream targets of ETV5 were screened using chromatin immunoprecipitation sequencing, CUT&Tag and RNA sequencing. Immune cells were examined using flow cytometry and immunofluorescence. S100 calcium-binding protein A9 (S100A9) was targeted by neutralising antibodies.

Results

Overexpression of ETV5 in HCC cells facilitated HCC metastasis and immune escape by recruiting and enhancing the immunosuppressive capabilities of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs). Mechanistically, ETV5 transactivated programmed death ligand 1 (PD-L1) and S100A9 expression. Inhibition of S100A9 or myeloid-specific knockout of toll-like receptor 4 (TLR4)/receptor for advanced glycation endproducts (RAGE), the receptors of S100A9, impeded ETV5-induced PMN-MDSC recruitment. Meanwhile, S100A9 within the tumour microenvironment elevated ETV5 expression via the extracellular signal-regulated kinase (ERK)/nuclear factor-kappa B pathway. Additionally, ETV5 transcriptionally upregulated PD-L1 in MDSCs as well, thereby augmenting their immunosuppressive functions. Myeloid-specificEtv5knockout attenuated HCC progression. We developed monoclonal neutralising-S100A9 antibodies that effectively inhibited ETV5-mediated PMN-MDSC infiltration. Synergistic application of anti-S100A9 or TLR4/RAGE inhibitors with anti-PD-L1 therapy significantly suppressed ETV5-mediated HCC progression.

Conclusion

ETV5 facilitates HCC progression and metastasis by promoting the recruitment, infiltration and activation of PMN-MDSCs. Synergistic application of anti-S100A9 or TLR4/RAGE inhibitors with anti-PD-L1 therapy holds great promise as an effective combinational treatment strategy for ETV5-positive HCC.
If you provide them, they will come: an observational study of online pathology report access by patients at a large, academic, tertiary care hospital in Canada
Authors: Ranot Jacob , Noghani Pedram , Rothwell Deanna , Wasserman Jason K
Published: February 2025

Aims

Patients of The Ottawa Hospital (TOH) are given immediate access to their pathology reports via an online patient portal. The purpose of this study was to determine how often patients accessed their reports, the sociodemographic and pathologic variables associated with access and the latency between sign out and access.

Methods

This retrospective cross-sectional observational study was conducted on the first 250 consecutive pathology reports published in 2023 from 10 different subspecialties in anatomical pathology at TOH. Data regarding date/time of report publication and access, as well as demographic data, and variables related to the individual report contents were extracted from the hospital’s electronic health records.

Results

Of the 2500 patients included in this study, 1315 (52.6%) accessed their report online. Patients under 65 years of age, female patients and those residing within Ottawa were more likely to access their reports. Biopsies and reports with malignant diagnoses were accessed at higher rates than resections and benign cases, respectively. 463 (36.0%) patients accessed their reports within 24 hours; 822 (68.5%) accessed them within the first week. In 53% of cases, the patient accessed their report before the treating physician.

Conclusions

These findings highlight that while over half of patients accessed their pathology reports online, significant differences in access rates were observed based on age, gender, location and report type. The high proportion of patients reviewing their reports before their treating physician underscores the need for patient-centred strategies to enhance understanding and support timely communication of results.
Transradial cerebral angiography: predicting left ICA selective angiography success using pre-diagnostic aortic arch factors
Authors: Eun Jin , Song Seung Yoon , Im Sang Hyuk , Park Hae Kwan
Published: February 2025

Background

Transradial cerebral angiography (TRA) is a convenient but challenging procedure, particularly for selecting the left internal carotid artery (ICA) and vertebral artery.

Objective

To predict the selection of the left ICA using CT and MR images acquired before TRA.

Methods

Overall, 306 patients with TRA were enrolled and divided into either the group with success (264 patients) or the failure (42 patients) group. The following anatomical factors were measured: A1 (subclavian artery angle), A2 (right subclavian–innominate artery angle), A3 (innominate–left common carotid artery angle), D1 (aorta to right subclavian artery length), and D2 (innominate-to-left common carotid artery length).

Results

The median values for A1, A2, A3, D1, and D2 were 81.57° (IQR 69.26–94.14), 147.03° (125.73–161.09), 24.73 (15.85–37.72°), 34.73 mm (29.68–38.48), and 13.15 mm (11.33–15.64), respectively, with significant differences observed between the successful and failure groups in A3 (26.88° vs 15.50°; P<0.001), D1 (34.24 mm vs 37.62 mm; P<0.001), and D2 (12.78 mm vs 14.91 mm; P<0.001). The aortic arch type did not affect success (P=0.134), while patients in the failure group were significantly older (P<0.001). A predictive logistic regression model was developed, revealing differing factor impacts when controlling variables. The model (area under the curve 0.87) highlights data complexity and enables user-friendly prediction of left ICA-selective TRA success (https://je0000000342227505.shinyapps.io/icatra/).

Conclusion

This study demonstrated that the success of left ICA selective angiography can be predicted using aortic arch images, providing a basis for the extension of TRA.
Long-term maintenance of mycophenolate mofetil in anti-NMDA receptor encephalitis (LEARN): a multicentre, open-label, blinded-endpoint, randomised controlled trial
Authors: Gong Xue , Liu Yue , Ma Yaru , Yan Bo , An Dongmei , Guo Yonghua , Liu Xu , Li Xingjie , Cai Linjun , Deng Xiaolin , Zhou Dong , Li Jin-Mei , Hong Zhen
Published: February 2025

Background

Anti-N-methyl-D-aspartate receptor encephalitis (NMDARE) is a severe autoimmune disorder with high morbidity and mortality. Current treatments have limitations including relapse, highlighting the need for effective maintenance therapy. This study evaluates the efficacy and safety of mycophenolate mofetil (MMF) as long-term adjunctive therapy to first-line treatment in newly diagnosed patients with NMDARE.

Methods

We conducted a prospective, randomised, open-label trial in four academic centres in China. Patients aged 14 and older with acute NMDARE, who received first-line treatments within 2 weeks of presentation to the hospital and had a modified Rankin scale (mRS) score of 2 or more, were recruited. Participants were randomly assigned to receive first-line treatment with or without MMF (0.5 g two times per day for 24 months). Primary outcomes included relapse rates and time to relapse, with secondary outcomes including cognitive deficits, treatment response (the proportion of patients with≥1 point improvement in mRS within 4 weeks) and adverse events (AEs).

Results

Of 100 patients (52% female; median age 27), those in the MMF group had fewer relapses (5.9% vs 26.5%; p=0.006) and better treatment response (84.3% vs 65.3%; p=0.03). No significant difference was found in long-term functional prognosis at 12 and 24 months. However, MMF patients had less fatigue, cognitive impairment, depression and seizures. AEs were mild-to-moderate, with no deaths or anaphylactic reactions.

Conclusions

This study provides Class II evidence that long-term adjunctive treatment of MMF to first-line treatment of NMDARE resulted in a lower risk of relapse and was well tolerated beyond the 24 months of treatment.

Trial registration number

ChiCTR2100044362.
Online retailer noncompliance to e-cigarette excise tax and tobacco licensing laws
Authors: Mejorado Tomas , Ellis Shannon , Harati Raquel M , Satybaldiyeva Nora , Benitez Gustavo , Austin Emily A C , Leas Eric C
Published: February 2025

Introduction

Tax non-compliance by online vaping retailers undermines excise taxes designed to reduce vaping rates and fund prevention efforts. Despite California’s 12.5% Electronic Cigarette Excise Tax and federal mandates under the Prevent All Cigarette Trafficking Act, online vaping retailers’ adherence to excise taxes remains unclear. This study assessed excise tax compliance among online vaping retailers shipping products to California consumers.

Methods

156 purchase attempts were made from n=78 online vaping retailers shipping to San Diego residential addresses. 16 buyers used their personal billing information and residential addresses. Receipts obtained from their purchases were analysed to determine if retailers charged the required 12.5% tax. Retailer licensing status was verified by comparing retailer information to the state’s licensed business list using geolocation and approximate string matching. Differences in compliance rates were compared using χ2and Fisher’s exact tests.

Results

Of the n=58 retailers with receipts, 84.5% did not charge the required excise tax. In-state retailers were more likely to be (p<0.001) licensed than out-of-state (4.0%) or international (0.0%), but tax compliance rates did not significantly differ by retailer location (p=0.57)—intrastate (19.2%), interstate (16.7%) or international (0.0%). Licensed retailers had higher tax compliance (27.3%) than unlicensed ones (9.1%); however, overall compliance was low.

Discussion

Many online vape retailers fail to comply with California’s excise tax and licensing laws. Low compliance rates indicate existing enforcement mechanisms are not optimised for online sales. Enhancing oversight and enforcement of excise tax laws for online retailers is crucial to reduce tax non-compliance, prevent revenue loss and support public health.
Predicting Human Perceptions of Robot Performance During Navigation Tasks
Authors: Zhang Qiping , Tsoi Nathan , Nagib Mofeed , Choi Booyeon , Tan Jie , Chiang Hao-Tien Lewis , Vázquez Marynel
Published: February 2025

Understanding human perceptions of robot performance is crucial for designing socially intelligent robots that can adapt to human expectations. Current approaches often rely on surveys, which can disrupt ongoing human-robot interactions. As an alternative, we explore predicting people’s perceptions of robot performance using non-verbal behavioral cues and machine learning techniques. We contribute the SEAN TOGETHER Dataset consisting of observations of an interaction between a person and a mobile robot in Virtual Reality, together with perceptions of robot performance provided by users on a 5-point scale. We then analyze how well humans and supervised learning techniques can predict perceived robot performance based on different observation types (like facial expression and spatial behavior features). Our results suggest that facial expressions alone provide useful information; but in the navigation scenarios that we considered, reasoning about spatial features in context is critical for the prediction task. Also, supervised learning techniques outperformed humans’ predictions in most cases. Further, when predicting robot performance as a binary classification task on unseen users’ data, the

\(F_{1}\)

-Score of machine learning models more than doubled that of predictions on a 5-point scale. This suggested good generalization capabilities, particularly in identifying performance directionality over exact ratings. Based on these findings, we conducted a real-world demonstration where a mobile robot uses a machine learning model to predict how a human who follows it perceives it. Finally, we discuss the implications of our results for implementing these supervised learning models in real-world navigation. Our work paves the path to automatically enhancing robot behavior based on observations of users and inferences about their perceptions of a robot.
Selected Chemical Engineering Applications in Nuclear-Waste Processing at the Savannah River Site
Authors: Crouse Steven H. , Prasad Rupanjali , Maharjan Nischal , Ocampo Viviana Cardenas , Woodham Wesley H. , Lambert Dan P. , Rousseau Ronald W. , Grover Martha A.
Published: February 2025

The Savannah River Site has been successfully processing and immobilizing nuclear waste since 1996. However, recent developments in both the scientific understanding of chemical principles and the engineering of immobilizing nuclear-waste systems demand a review of the state of the art. These recent advances have significance to other locations that immobilize nuclear waste. The subject matter of this review may find special applicability to chemical engineers interested in hazardous chemical processes (such as processing toxic and radioactive nuclear waste) and to those in the nuclear industry curious about current research in nuclear-waste processing at a site that has eclipsed the quarter-century mark of large-scale (136 million L total) nuclear-waste processing.
Entropic Bonding—Not Quite So Simple Behaviors from Simple Hard Particles
Authors: Vo Thi
Published: February 2025

Advances in experimental synthesis and computer simulations have led to the proliferation of anisotropy and particle geometry as popular handles for directed self-assembly. This paradigm employs entropy to direct building block organization into desired spatial and orientational orderings. Yet, how does a metric associated primarily with disorder give rise to ordered assemblies? We first explain the governing principles behind entropic crystallization and entropy maximization processes. We then show how entropic forces can produce emergent, attractive, and bond-like interactions between otherwise sterically repulsive particles. Building on these ideas, we establish entropy as a mediator of interparticle attraction in hard particle systems that relies on extrinsic, systems-level behaviors as opposed to intrinsic, particle-level properties. Finally, we present a theory of entropic bonding that formalizes the phenomena discussed into a rigorous mathematical framework and discuss relevant next steps for its development and applications of entropic crystallization in materials design.
An Invisibility/Hypervisibility Paradox: The Sociology of Middle Eastern and North African (MENA) Americans
Authors: Maghbouleh Neda
Published: February 2025

Research on Middle Eastern and North African (MENA) populations in the United States has been shaped by a fundamental paradox: MENAs are statistically invisible in the administrative data infrastructure yet socially hypervisible in other domains. This review outlines key demographic characteristics of the MENA American population and argues that by addressing the invisibility/hypervisibility paradox through innovative research questions and methods, previous scholarship has advanced sociology in three areas: identity, racialization, and integration. As upcoming changes to federal race and ethnicity standards take effect, the invisibility/hypervisibility paradox may shift as sociologists more easily collect and analyze data about MENA Americans. However, this information may be misused, misinterpreted, or handled unethically without sufficient background context and responsibility to community members. Future research will require data disaggregation to explore intersectional and intragroup minority issues, examination of the evolving content and meaning of MENA panethnicity, and ongoing assessment of the MENA group's relative racial position.
SOC Estimation in Lithium Ion Batteries using a Hybrid Gated Residual Wavenet with LSTM-GRU Network Across Varying Temperatures
Authors: Sridharan Supriya , Venkataraman Swaminathan , Raja S. P.
Published: February 2025

Estimating the State of Charge in lithium-ion batteries is vital for enhancing efficiency, ensuring safety, and prolonging lifespan but remains complex due to temperature fluctuations, aging impacts, nonlinear behaviour, dynamic loads, and long-term precision requirements. To address these complexities, this study proposes a novel hybrid model combining Residual WaveNet, Gated Recurrent Units, and Long Short-Term Memory networks for SOC estimation. The model leverages lagged features to capture temporal dependencies, which are crucial for understanding how past states of the battery influence future behavior. By integrating both past and present data points, the model maximizes the use of time series information, allowing it to identify important patterns and trends that enhance predictive accuracy. Residual WaveNet captures complex temporal patterns and long-range dependencies, particularly those influenced by temperature variations, using dilated convolutions and residual connections. GRUs improve the efficiency of processing sequential data, while LSTMs handle long-term dependencies effectively, ensuring the model can accurately predict future SOC across varying conditions. The proposed model’s efficacy is evaluated using a LG18650HG2 Li-ion battery and the results indicate the proposed attains higher accuracy and minimum RMSE. The proposed model undergoes various performance analyses across different temperatures and its effectiveness surpasses that of other comparative methods.
Functional reprogramming of neutrophils within the brain tumor microenvironment by hypoxia-driven histone lactylation
Authors: Ugolini Alessio , De Leo Alessandra , Yu Xiaoqing , Scirocchi Fabio , Liu Xiaoxian , Peixoto Barbara , Scocozza Delia , Pace Angelica , Perego Michela , Gardini Alessandro , D'Angelo Luca , Liu James K C. , Etame Arnold B. , Rughetti Aurelia , Nuti Marianna , Santoro Antonio , Vogelbaum Michael A. , Conejo-Garcia Jose R. , Rodriguez Paulo C. , Veglia Filippo
Published: February 2025

Despite functional heterogeneity, high frequency of intratumoral neutrophils predicts poor clinical outcomes. The tumor microenvironment reprograms neutrophils into immunosuppressive subsets that hinder anti-cancer immunity, thereby contributing to tumor growth and resistance to immunotherapies. However, the mechanisms underlying neutrophil reprogramming remain elusive. Here, we report that the immunosuppressive ability of brain tumor-infiltrating neutrophils was restricted to a highly glycolytic and long-lived subset expressing CD71, which acquired immunosuppressive properties in response to hypoxia. Mechanistically, hypoxia boosted glucose metabolism in CD71+neutrophils, leading to high lactate production. Lactate caused histone lactylation, which subsequently regulated arginase-1 expression, required for T cell suppression. Targeting histone lactylation with the anti-epileptic drug isosafrole blocked CD71+neutrophil immunosuppressive ability, delayed tumor progression and sensitized brain tumors to immunotherapy. A distinctive gene signature characterizing immunosuppressive CD71+neutrophils correlated with adverse clinical outcomes across diverse human malignancies. This study identifies histone lactylation as a potential therapeutic target to counteract neutrophil-induced immunosuppression within tumors.
Intelligent voice control system for UAV with mobile robot
Authors: Atanov Sabyrzhan , Moldamurat Khuralay , Bakyt Makhabbat , Zinagabdenova Dariga , Moldamurat Aibek , Zhumazhanov Berik , Maidanov Adil
Published: February 2025

The article presents a voice control system for unmanned aerial vehicles (UAVs) and an integrated mobile robot, based on artificial intelligence (AI). The system recognizes voice commands in the Kazakh language, converted into Latin transliteration, providing intuitive control of the UAV and robot. The performance of the system in various scenarios including agriculture, environmental monitoring and search and rescue operations is investigated. The system showed high accuracy of command recognition (95%) and efficient control of the UAV and robot. The proposed system opens up new possibilities for the use of UAVs and robots in various fields, increasing their autonomy, flexibility and ease of use.
Enhancing uncollateralized loan risk assessment accuracy through feature selection and advanced machine learning techniques
Authors: Salahudin Shahrul Nizam , Dasril Yosza , Arisandy Yosy
Published: February 2025

Accuracy in evaluating the risk of credit applications is crucial for lenders, particularly when dealing with unsecured loans. Accuracy can be enhanced by selecting suitable features for a machine learning model. To better identify high-risk borrowers, this study applies an elaborate feature selection technique. This study uses the light gradient boosting machine (LGBM) Classifier model with boosting type gradient boosting decision tree (GBDT) algorithm and n_estimator value 100 for feature selection process. This work uses advanced machine learning techniques namely stacking to improve accuracy model perform. The dataset consists of 307,506 applicants from European lenders who have applied for loans in Southeast Asia. Each applicant is described by 126 different features. Using GDBT algorithm GBDT, 30 best features were selected based on their maximum accuracy compared to another feature. By employing a stacking technique that combines the LGBM, gradient boosting (GB), and random forest (RF) models, and utilizing logistic regression (LR) as the final estimator, an accuracy of 0.99637 was reached. This study demonstrates an improved the accuracy compared to previous research. This discovery indicates that utilizing feature selection and stacking method can provide one of the most precise choices for modelling the binary class classification among the current models.
Optimal land distribution for ambiguous profit vegetable crops using multi-objective fuzzy linear programming
Authors: Dixit Pranav , Tyagi Sohan Lal
Published: February 2025

Decisions in agriculture had been driven by methodical planning to increase yields to cater to the needs of overwhelming populations while also allowing farmers to prosper. Allocating land to various crops by making use of limited resources is becoming a crucial challenge for achieving higher profits. To make cropping pattern decisions, farmers traditionally rely on experience, instinct, and comparisons with their neighbors. Since profit varies depending on many factors, intuition and experience usually cannot guarantee optimal (maximum) profits. A number of research studies on linear programming (LP) have shown optimum cropping patterns when crop prices (profits) are fixed. Vegetable crops, also known as cash crops, are subject to a high degree of price volatility owing to the fact that their production is costly and they carry a significant risk of not being profitable, despite the fact that they provide higher earnings than food crops. The net returns of crops in agriculture are greatly impacted by price uncertainty. With the use of the optimization tool TORA, a step-by-step process is shown in this paper to solve the model and manage the volatility in vegetable crop profitability using fuzzy multi-objective linear programming (FMOLP).
Optimizing cloud tasks scheduling based on the hybridization of darts game hypothesis and beluga whale optimization technique
Authors: Chhabra Manish , E. Rajesh
Published: February 2025

This paper presents the hybridization of two metaheuristic algorithms which belongs to different categories, for optimizing the tasks scheduling in cloud environment. Hybridization of a game-based metaheuristic algorithm namely, darts game optimizer (DGO), with a swarm-based metaheuristic algorithm namely, beluga whale optimization (BWO), yields to the evolution of a new algorithm known as “hybrid darts game hypothesis – beluga whale optimization” (hybrid DGH-BWO) algorithm. Task scheduling optimization in cloud environment is a critical process and is determined as a non-deterministic polynomial (NP)-hard problem. Metaheuristic techniques are high-level optimization algorithms, designed to solve a wide range of complex, optimization problems. In the hybridization of DGO and BWO metaheuristic algorithms, expedition and convergence capabilities of both algorithms are combined together, and this enhances the chances of finding the higher-quality solutions compared to using a single algorithm alone. Other benefits of the proposed algorithm: increased overall efficiency, as “hybrid DGH-BWO” algorithm can exploit the complementary strengths of both DGO and BWO algorithms to converge to optimal solutions more quickly. Wide range of diversity is also introduced in the search space and this helps in avoiding getting trapped in local optima.
Artificial intelligence approaches for cardiovascular disease prediction: a systematic review
Authors: Hammadi Jasim Faraj , Abdul Latif Aliza Binti , Che Cob Zaihisma Binti
Published: February 2025

Cardiovascular disease (CVD) remains a top global cause of mortality, highlighting the critical need for precise prediction models to improve patient outcomes and optimize healthcare resource allocation. Accurate prediction of CVD is paramount for early diagnosis and reducing mortality rates. Achieving efficient CVD detection and prediction requires a deep understanding of health history and the underlying causes of heart disease. Harnessing the power of data analytics proves advantageous in leveraging vast datasets to make informed predictions, aiding healthcare clinics in disease prognosis. By consistently maintaining comprehensive patient-related data, healthcare providers can anticipate the emergence of potential diseases. Our study conducts a meticulous comparative analysis of CVD prediction methods, focusing on various artificial intelligence (AI) algorithms, particularly classification and predictive algorithms. Scrutinizing approximately sixty papers on cardiovascular disease through the prism of AI techniques, this study carefully assesses the selected literature, uncovering gaps in existing research. The outcomes of this study are expected to empower medical practitioners in proactively predicting potential heart threats and facilitating the implementation of preventive measures.
Measuring political influence during elections using a deep learning approach
Authors: Cherkaoui Abderrazzak , El Beqqali Omar
Published: February 2025

This contribution introduces a methodology for measuring political influence on Twitter during the 2020 U.S. presidential election campaign. The approach employs deep knowledge scores, which are generated through sentiment analysis of Tweets from users responding to influential users, coupled with an assessment of the strength of their interactions. The deep knowledge scores enable the categorization of three types of Twitter’s users engaging with influential users: influenced users, distrustful users, and connected users. Our approach, structured around a five-layer framework, effectively constructs networks of trust and distrust, and establishes the relationship between fluctuations in trust or distrust levels and the topics discussed by influential users.
Accurate segmentation of fruit based on deep learning
Authors: Elsoud Esraa Abu , Alidmat Omar , Abuowaida Suhaila , Alhenawi Esraa , Alshdaifat Nawaf , Aburomman Ahmad , Chan Huah Yong
Published: February 2025

In the last few years, deep learning has exhibited its efficacy and capacity in the field of computer vision owing to its exceptional precision and widespread acceptance. The primary objective of this study is to investigate an improved approach for segmentation in the context of various fruit categories. Despite the utilization of deep learning, the current segmentation techniques for various fruit items exhibit subpar performance. The proposed enhanced multiple fruit segmentation algorithm has the following main steps: 1) modifying the size of the filter, 2) the process of optimizing the ResNet-101 block involves selecting the most suitable count of repetitions. The multiple fruit dataset is split 80% in the training stage and 20% in the testing stage. These images were utilized to train a deep learning (DL) based algorithm, which aims to identify multiple fruit items within images accurately. The proposed algorithm has a lower training time compared to the other algorithms. The thresholds exhibit greater values compared to the thresholds of state-of-the-art algorithms.