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FaceScanPaliGemma multi-agent vision language models for facial attribute recognition. FaceScanPaliGemma多智能体视觉语言模型用于人脸属性识别。
IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-02-23 DOI: 10.1038/s41598-026-39584-3
Nouar AlDahoul, Myles Joshua Toledo Tan, Harishwar Reddy Kasireddy, Yasir Zaki

Technologies for recognizing facial attributes such as race, gender, age, and emotion from images of human faces have several applications, including personalized advertising, sentiment analysis, and the study of demographic trends and social behaviors. Analyzing face images and facial expressions presents several challenges due to the complexity of human facial attributes and the diversity in representation. While numerous attempts have been made to improve facial attribute classification performance, there remains a strong demand for enhanced accuracy. In this paper, we propose "FaceScanPaliGemma," a multi-agent vision language model (VLM) system consisting of four fine-tuned Google PaliGemma models, each specialized for a specific facial attribute classification. To evaluate the proposed solution, we used the public "FairFace" and "AffectNet" datasets. The results show high accuracy, reaching up to 81.1%, 95.8%, 80.0%, and 59.4% for race, gender, age group, and emotion classification, respectively, outperforming other VLMs such as OpenAI GPT, Google Gemini, LLaVA, and Google PaliGemma under zero-shot evaluation.

从人脸图像中识别人脸属性(如种族、性别、年龄和情感)的技术有多种应用,包括个性化广告、情感分析以及人口趋势和社会行为的研究。由于人类面部属性的复杂性和表征的多样性,人脸图像和面部表情分析面临着一些挑战。虽然已经进行了许多尝试来提高面部属性分类性能,但仍然需要提高准确性。在本文中,我们提出了“FaceScanPaliGemma”,这是一个多智能体视觉语言模型(VLM)系统,由四个微调的谷歌PaliGemma模型组成,每个模型专门用于特定的面部属性分类。为了评估提出的解决方案,我们使用了公共的“FairFace”和“AffectNet”数据集。结果显示,该方法在种族、性别、年龄组和情绪分类上的准确率分别达到81.1%、95.8%、80.0%和59.4%,优于OpenAI GPT、谷歌Gemini、LLaVA和谷歌PaliGemma等VLMs。
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引用次数: 0
Research and optimization of screening strategy for calcium-activated chloride channel modulators guided by electrophysiological characteristics. 基于电生理特性的钙活化氯离子通道调节剂筛选策略研究与优化。
IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-02-23 DOI: 10.1038/s41598-026-39762-3
Yanyan Wang, Kai Zheng, Liu Yang, Liying Liu, Haojian Han, Shuang Chen, Zhanning Qu, Kai Qin, Wansheng Zhang, Feng Hao

Calcium-activated chloride channels (CaCCs) are essential for epithelial secretion, neuronal transmission, and smooth muscle function. Among the Anoctamin family, Anoctamin 1 (ANO1) and Anoctamin 2 (ANO2) are classical CaCCs proteins. ANO1 has been identified as a potential therapeutic target due to its involvement in diseases such as cancer and cystic fibrosis. However, current high-throughput screening (HTS) systems face limitations in achieving subtype-specific detection and optimizing screening strategies. Stable HTS cell models expressing ANO1 or ANO2 were constructed via lentiviral transduction in Fischer mouse thyroid (FRT) cells. The models were validated using flow cytometry, Reverse Transcription Polymerase Chain Reaction(RT-PCR), and YFP-H148Q/I152L-based iodide fluorescence quenching assays. Patch-clamp electrophysiology was employed to characterize ANO1 and ANO2 current properties. Although these electrophysiological features have been previously reported, their application in HTS workflows had not been systematically evaluated. ANO1 displayed notable current rundown under sustained stimulation with high Ca2+ or agonist concentrations, whereas ANO2 maintained stable currents under identical conditions. Based on these findings, an optimized screening strategy was developed, incorporating agonist concentration gradients and the timing of inhibitor application. This approach improved the specificity and reliability of modulator detection. A robust and functionally validated cell-based HTS platform for CaCCs modulator discovery was established. By integrating the electrophysiological characteristics of ANO1 into the screening design, the optimized strategy enhances the accuracy of identifying selective ANO1 modulators. This work provides a methodological basis for future mechanism-driven screening of CaCCs-targeted compounds.

钙活化的氯离子通道(CaCCs)对上皮分泌、神经元传递和平滑肌功能至关重要。在Anoctamin家族中,Anoctamin 1 (ANO1)和Anoctamin 2 (ANO2)是典型的CaCCs蛋白。ANO1已被确定为潜在的治疗靶点,因为它与癌症和囊性纤维化等疾病有关。然而,目前的高通量筛选(HTS)系统在实现亚型特异性检测和优化筛选策略方面面临局限性。通过慢病毒转导,在Fischer小鼠甲状腺(FRT)细胞中构建了表达ANO1或ANO2的稳定HTS细胞模型。采用流式细胞术、逆转录聚合酶链反应(RT-PCR)和基于YFP-H148Q/ i152l的碘化物荧光猝灭实验对模型进行验证。膜片钳电生理技术表征了ANO1和ANO2的电流特性。虽然这些电生理特征以前已经报道过,但它们在HTS工作流程中的应用尚未得到系统的评估。在高Ca2+或激动剂浓度的持续刺激下,ANO1显示出明显的电流损耗,而ANO2在相同条件下保持稳定的电流。基于这些发现,我们开发了一种优化的筛选策略,结合激动剂浓度梯度和抑制剂应用时间。该方法提高了调制器检测的特异性和可靠性。建立了一个鲁棒且功能验证的基于cell的HTS平台,用于CaCCs调制器的发现。通过将ANO1的电生理特性整合到筛选设计中,优化策略提高了识别选择性ANO1调制器的准确性。这项工作为未来机制驱动的caccs靶向化合物筛选提供了方法学基础。
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引用次数: 0
Potential urine NMR Metabolomic signatures for early diagnosis of paediatric tuberculosis. 小儿结核病早期诊断的潜在尿核磁共振代谢组学特征。
IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-02-23 DOI: 10.1038/s41598-026-40619-y
Andrea López-Suárez, Patricia Comella-Del-Barrio, Pilar Alonso-Moreno, Yaiza Marín, Palmira Villa-Valverde, Mar Santos-Sebastián, Antoni Noguera-Julian, Anna Gamell, Paula Rodríguez-Molino, Jara Hurtado-Gallego, Daniel Blázquez-Gamero, Ana Belén Jiménez-Jiménez, Adriana Navas, Elena Del Castillo, Marta Llorente, Talía Sainz, José Domínguez, José Luis Izquierdo-García, Begoña Santiago-García

Early diagnosis of tuberculosis (TB) in children is hampered by non-specific symptoms, low bacillary loads, and difficulties in obtaining respiratory samples. We evaluated urinary metabolomics using high-resolution nuclear magnetic resonance (HR-1H-NMR) spectroscopy as a non-invasive tool to discriminate TB disease, TB infection (TBI), and healthy controls (HC). Urine samples from 101 children enrolled in the Spanish Paediatric TB Network (pTBred) were retrospectively analysed, including 62 TB cases (26 microbiologically confirmed [cTB]), 17 TBI, and 22 HC. Metabolic fingerprints were generated via1 H-NMR spectroscopy. Group discrimination was assessed using partial least squares discriminant analysis (PLS-DA) with cross-validation. Metabolites were selected using VIP > 2 and p < 0.05. Validated PLS-DA models (TB vs. HC, cTB vs. HC and cTB vs. TBI) achieved ≥ 70% accuracy (AUC-ROC 0.867-0.971), with sensitivities ranging from 69.1% to 90.0% and specificities from 77.3% to 86.7%. Discrimination was strongest for cTB vs. TBI (AUC-ROC 0.971; sensitivity 90.0%; specificity 86.7%). A set of discriminatory metabolites was identified across validated comparisons. Compared with HC, TB disease was characterized by increased levels of phenylalanine and two unidentified NMR signals, together with reductions in several energy and nitrogen-related metabolites; benzoate and histidine showed borderline differences. In contrast, TBI was associated with higher levels of isoleucine, N-acetylglutamine, glutamine, creatinine and 2-hydroxyvalerate. Urine HR-1H-NMR metabolomics suggests potential distinct metabolic signatures across TB states. While not yet suitable as a confirmatory test, these preliminary findings show potential as a triage tool to help prioritise children for microbiological testing and may eventually reduce the need for invasive sampling.

儿童结核病(TB)的早期诊断受到非特异性症状、低细菌载量和难以获得呼吸道样本的阻碍。我们使用高分辨率核磁共振(HR-1H-NMR)光谱来评估尿液代谢组学,作为区分结核病、结核病感染(TBI)和健康对照(HC)的非侵入性工具。回顾性分析了西班牙儿科结核病网络(pTBred)登记的101名儿童的尿液样本,包括62例结核病(26例微生物确诊[cTB]), 17例TBI和22例HC。通过H-NMR生成代谢指纹图谱。采用交叉验证的偏最小二乘判别分析(PLS-DA)评估群体歧视。使用VIP >2和p1h - nmr代谢组学选择代谢物,表明不同结核状态的潜在不同代谢特征。虽然还不适合作为确认性测试,但这些初步发现显示了作为分诊工具的潜力,可以帮助优先进行微生物测试的儿童,并可能最终减少侵入性采样的需要。
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引用次数: 0
Plant based synthesised silver nanoparticles delivering enhanced antifungal activity and synergistic environmental remediation. 基于植物的合成纳米银提供增强的抗真菌活性和协同环境修复。
IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-02-23 DOI: 10.1038/s41598-026-40674-5
Shani Raj, Rohini Trivedi

This study delves into the antifungal capabilities and catalytic dye degradation efficiency of silver nanoparticles (AgNPs) synthesised using Enicostemma axillare leaf extract. Highlighting the pressing need for sustainable agriculture and pollution mitigation strategies, our investigation demonstrates the dual utility of phyto-synthesised AgNPs. Antifungal assays revealed substantial inhibition of mycelial growth and spore germination in Alternaria alternata and Fusarium oxysporum, with inhibition rates peaking at 83% and 82.79%, respectively, at a concentration of 120 µg/ml. Additionally, AgNPs showcased remarkable catalytic degradation of hazardous dyes methylene blue, methyl orange, and Congo red, achieving over 90% degradation within minutes, underlying their potential in environmental remediation. The catalytic reduction showcased not only the high efficiency of these nanoparticles in breaking down complex organic molecules but also positioned them as viable candidates for treating industrial effluents. The increased phenolic and proline contents in treated tomato plants suggest an enhanced stress response, potentially contributing to disease resistance. These findings underscore the versatility of phyto-synthesised AgNPs, offering promising avenues for the development of eco-friendly solutions in agriculture and environmental management.

本研究探讨了用竹叶提取物合成的银纳米颗粒(AgNPs)的抗真菌能力和催化染料降解效率。强调可持续农业和污染缓解战略的迫切需要,我们的调查证明了植物合成AgNPs的双重效用。抗真菌实验表明,当浓度为120µg/ml时,对交替稻瘟菌和尖孢镰刀菌的菌丝生长和孢子萌发有明显的抑制作用,抑制率分别为83%和82.79%。此外,AgNPs对亚甲基蓝、甲基橙和刚果红等有害染料具有显著的催化降解作用,在几分钟内降解率达到90%以上,具有潜在的环境修复潜力。催化还原不仅展示了这些纳米颗粒在分解复杂有机分子方面的高效率,而且使它们成为处理工业废水的可行候选者。处理过的番茄植株酚和脯氨酸含量增加,表明胁迫反应增强,可能有助于抗病。这些发现强调了植物合成AgNPs的多功能性,为农业和环境管理中生态友好解决方案的开发提供了有希望的途径。
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引用次数: 0
Quantum linear solvers for scientific computing: a comparison of VQLS, HHL and quantum annealing on time-fractional diffusion problems. 科学计算的量子线性解算:VQLS、HHL和量子退火在时间分数扩散问题上的比较。
IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-02-23 DOI: 10.1038/s41598-026-40910-y
Amir Hossein Salehi Shayegan

Time-fractional diffusion equations have emerged as powerful models for describing anomalous transport phenomena in physics, biology and engineering. To address the computational challenges arising from their non-local operators, we employ the WEB-spline finite element method, which provides a flexible and accurate discretization framework. The resulting linear system of equations are then explored in the context of quantum computing. Specifically, we investigate three prominent quantum linear solvers: the variational quantum linear solver (VQLS), the Harrow-Hassidim-Lloyd (HHL) algorithm and quantum annealing (QA). VQLS leverages hybrid variational techniques and shallow circuits, making it well-suited for noisy intermediate-scale quantum (NISQ) devices, while HHL offers a theoretically exponential speedup for sparse systems but requires deep fault-tolerant circuits. QA, in contrast, reformulates the problem into a quadratic unconstrained binary optimization (QUBO) instance, enabling approximate solutions through energy minimization on specialized hardware. We present a comparative analysis in terms of circuit depth, noise resilience, scalability and solution extraction, including the role of quantum state tomography in reconstructing classical information. Numerical experiments on a time-fractional diffusion problem highlight the complementary strengths and limitations of each method. This study bridges advanced numerical discretization with emerging quantum algorithms, providing insights into the feasibility and future potential of quantum-enhanced solvers for fractional partial differential equations.

时间分数扩散方程已成为描述物理、生物和工程中异常输运现象的有力模型。为了解决它们的非局部算子带来的计算挑战,我们采用了web样条有限元方法,它提供了一个灵活和准确的离散化框架。然后在量子计算的背景下探索由此产生的线性方程组。具体来说,我们研究了三种著名的量子线性求解器:变分量子线性求解器(VQLS)、Harrow-Hassidim-Lloyd (HHL)算法和量子退火(QA)。VQLS利用混合变分技术和浅电路,使其非常适合有噪声的中等规模量子(NISQ)设备,而HHL为稀疏系统提供理论上的指数加速,但需要深度容错电路。相比之下,QA将问题重新表述为二次无约束二进制优化(QUBO)实例,通过在专用硬件上最小化能量来实现近似解。我们在电路深度、噪声弹性、可扩展性和解提取方面进行了比较分析,包括量子态层析成像在重建经典信息中的作用。对一个时间分数扩散问题的数值实验突出了每种方法的互补优势和局限性。本研究将先进的数值离散化与新兴的量子算法相结合,为分数阶偏微分方程的量子增强求解器的可行性和未来潜力提供了见解。
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引用次数: 0
Favorable research environment is a key determinant of research integrity according to a ten-country survey across Central and Eastern Europe. 根据中欧和东欧十国的调查,有利的研究环境是研究诚信的关键决定因素。
IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-02-23 DOI: 10.1038/s41598-026-39928-z
Renata Veselska, Jan Sirucek, Eugenijus Gefenas, Ana Borovecki
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引用次数: 0
Enhanced adaptive zebra optimization algorithm optimized kernel extreme learning machine for bankruptcy prediction problems. 增强自适应斑马优化算法优化核极值学习机破产预测问题。
IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-02-23 DOI: 10.1038/s41598-026-40651-y
Wenan Liu, Yu Zhang, Mengxuan Du
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引用次数: 0
Retraction Note: Elevated FDP levels independently predict poor outcomes in HBV-ACLF patients treated with artificial liver support system therapy. 注:FDP水平升高独立预测接受人工肝支持系统治疗的HBV-ACLF患者预后不良。
IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-02-23 DOI: 10.1038/s41598-026-41022-3
Xu Yang, Xiaoqi Zhou, Dachuan Cai, Junli Wang, Shiying Li
{"title":"Retraction Note: Elevated FDP levels independently predict poor outcomes in HBV-ACLF patients treated with artificial liver support system therapy.","authors":"Xu Yang, Xiaoqi Zhou, Dachuan Cai, Junli Wang, Shiying Li","doi":"10.1038/s41598-026-41022-3","DOIUrl":"https://doi.org/10.1038/s41598-026-41022-3","url":null,"abstract":"","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"16 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147277160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Porous structure analysis of coconut shell-derived activated carbons prepared under different conditions. 不同条件下椰壳活性炭的多孔结构分析。
IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-02-23 DOI: 10.1038/s41598-026-39432-4
Mirosław Kwiatkowski, Xin Hu
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引用次数: 0
Pre-trained multi-scale RWKV-GCN for multivariate time series forecasting. 多元时间序列预测的预训练多尺度RWKV-GCN。
IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-02-23 DOI: 10.1038/s41598-026-41091-4
Jianhua Hao, Fangai Liu, Weiwei Zhang
{"title":"Pre-trained multi-scale RWKV-GCN for multivariate time series forecasting.","authors":"Jianhua Hao, Fangai Liu, Weiwei Zhang","doi":"10.1038/s41598-026-41091-4","DOIUrl":"https://doi.org/10.1038/s41598-026-41091-4","url":null,"abstract":"","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147277239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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