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Optimizing lung cancer diagnosis through computed tomography: A radiological perspective 通过计算机断层扫描优化肺癌诊断:放射学角度
IF 2.5 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-03-01 Epub Date: 2025-12-08 DOI: 10.1016/j.jrras.2025.102105
Yazeed I. Alashban

Objectives

Lung cancer remains a major global health burden with high mortality rates, primarily due to late-stage diagnosis and limitations in accessible, rapid screening techniques. This study proposes a novel deep learning framework leveraging a hybrid Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Random Forest classification (RF) mode (CNN-LSTM-RF) architecture for the automated detection and classification of lung cancer using radiological Computed Tomography (CT) scan imaging.

Materials and methods

For this study, DICOM (.dcm) images were obtained from The Cancer Imaging Archive (TCIA) containing a total of 355 subjects and a total of 251,135 CT scan images which was divided into 4 major classes of Adenocarcinoma, Small Cell Carcinoma, Large Cell Carcinoma, and Squamous Carcinoma. However, the study uses 249 out of 355 sample patient files containing only lung CT datasets, ignoring all other irrelevant or mixed radiology scans. Moreover, the Large Cell Carcinoma class had a very less sample size (5 patients), and thus was omitted from this study, leaving behind a total sample size of 244 patients which was considered for classification. These slices were normalized and resized to a consistent input dimension after which data augmentation (including rotations, flips, and intensity shifts) was applied to balance the dataset across classes. A custom hybrid CNN was integrated with LSTM for temporal encoding across CT slice sequences, followed by RF classification. At a distribution ratio of 70:20:10, the data was separated into training, testing, and validation datasets.

Results

The custom CNN-LSTM-RF model classified three cancer types – Adenocarcinoma, Small Cell Carcinoma, and Squamous Cell Carcinoma – with a validation accuracy of 97 % and an AUC exceeding 0.95 indicating a well-balanced and highly effective model. In addition to lung cancer classification, histological grading was evaluated among smoking patients, revealing that even aggressive G3 tumors do not occur with excessively higher frequency in smokers, suggesting multifactorial etiologies of lung cancer. Moreover, Early, Intermediate, and Advanced Stage T-Stage tumors were also graphically represented for different age groups. This framework demonstrates promising clinical potential for early-stage lung cancer detection, offering a scalable tool to support radiologists and reduce diagnostic delays.
肺癌仍然是全球主要的健康负担,死亡率高,主要是由于晚期诊断和可获得的快速筛查技术的限制。本研究提出了一种新的深度学习框架,利用混合卷积神经网络(CNN)、长短期记忆(LSTM)和随机森林分类(RF)模式(CNN-LSTM-RF)架构,利用放射计算机断层扫描(CT)扫描成像自动检测和分类肺癌。材料和方法本研究的DICOM (.dcm)图像来源于The Cancer Imaging Archive (TCIA),共355名受试者,共251,135张CT扫描图像,分为腺癌、小细胞癌、大细胞癌和鳞状癌4大类。然而,该研究使用了355个样本患者档案中的249个只包含肺部CT数据集,忽略了所有其他不相关或混合的放射学扫描。此外,大细胞癌类别的样本量非常少(5例),因此从本研究中省略,留下244例患者的总样本量作为分类考虑。这些切片被归一化并调整为一致的输入维度,之后应用数据增强(包括旋转、翻转和强度变化)来平衡跨类的数据集。将自定义混合CNN与LSTM相结合,对CT切片序列进行时间编码,然后进行RF分类。按照70:20:10的分布比,将数据分为训练、测试和验证数据集。结果自定义CNN-LSTM-RF模型对腺癌、小细胞癌和鳞状细胞癌三种癌症类型进行了分类,验证准确率为97%,AUC超过0.95,表明该模型是一个平衡良好、高效的模型。除肺癌分类外,对吸烟患者的组织学分级进行了评估,发现即使是侵袭性G3肿瘤也不会在吸烟者中出现过高的频率,提示肺癌的多因素病因。此外,不同年龄组的早期、中期和晚期t期肿瘤也用图表表示。该框架展示了早期肺癌检测的临床潜力,提供了一个可扩展的工具来支持放射科医生并减少诊断延误。
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引用次数: 0
Botulinum toxin type A alleviates chronic post-thoracotomy pain by inhibiting the HMGB1-mediated TLR4/NF-KB signaling pathway in rats A型肉毒毒素通过抑制hmgb1介导的TLR4/NF-KB信号通路减轻大鼠开胸术后慢性疼痛
IF 2.5 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-03-01 Epub Date: 2026-01-27 DOI: 10.1016/j.jrras.2026.102199
Fuwang Wei , Bingyang Lv , Dan Liu , Xiaoming Zou

Introduction

The purpose of this study was to establish a chronic pain model after thoracotomy in rats and investigate the effects of BTX-A on spinal inflammation and the chronic hyperalgesia of rats.

Methods

SD rats were used to established animal model of chronic post-thoracotomy pain (CPTP) by Buvanendran method, and a control group and sham group were established. On the third day postoperatively, the rats were given subcutaneous injection of BTX-A. Pain behavior tests of rats, including Mechanical withdrawal threshold (MWT) and cold hyperalgesia threshold, were performed before operation and postoperatively. Finally, the rats were killed to collect spinal cord tissue samples for pathological examination or protein expression detection.

Results

After the operation, all model rats showed a decrease in MWT values and an increase in the number of positive reactions to cold acetone stimulation, the model was successfully established. In contrast to the model group, the MWT in the M + BTX-A group was significantly higher, and the number of positive reactions of cold acetone stimulation was also significantly decreased. HE staining results showed that the nucleus of spinal cord tissue was abnormally enlarged and inflammatory cells were increased in the model group. The cell morphology of M + BTX-A group was close to normal. In addition, BTX-A significantly decreased the levels of OX-42, HMGB1, TLR4, IL-10, TNF-α, p-P65 and p-IKB-α in tissues.

Conclusion

BTX-A was able to effectively relieve chronic post-thoracotomy pain and decrease spinal inflammation in CPTP model rats by suppressing microglial activation in spinal cord by inhibiting HMGB1-mediated TLR4/NF-κB signaling pathway.
本研究旨在建立大鼠开胸后慢性疼痛模型,探讨BTX-A对大鼠脊柱炎症和慢性痛觉过敏的影响。方法采用布vanendran法建立大鼠慢性开胸术后疼痛(CPTP)动物模型,并建立对照组和假手术组。术后第3天皮下注射BTX-A。术前和术后分别对大鼠进行疼痛行为测试,包括机械戒断阈值(MWT)和冷痛过敏阈值。最后处死大鼠,采集脊髓组织标本进行病理检查或蛋白表达检测。结果术后各模型大鼠MWT值下降,冷丙酮刺激阳性反应次数增加,模型建立成功。与模型组比较,M + BTX-A组MWT明显升高,冷丙酮刺激阳性反应次数也明显减少。HE染色结果显示,模型组大鼠脊髓组织核异常增大,炎症细胞增多。M + BTX-A组细胞形态接近正常。BTX-A还能显著降低组织中OX-42、HMGB1、TLR4、IL-10、TNF-α、p-P65、p-IKB-α的水平。结论btx - a通过抑制hmgb1介导的TLR4/NF-κB信号通路,抑制脊髓小胶质细胞活化,可有效缓解CPTP模型大鼠开胸术后慢性疼痛,减轻脊髓炎症反应。
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引用次数: 0
Sound-based navigation system for visually impaired individuals 视障人士的声音导航系统
IF 2.5 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-03-01 Epub Date: 2026-01-05 DOI: 10.1016/j.jrras.2026.102160
Emad Malaekah , Othman Alfahad , Mohsen Bakouri , Adel Gadallah , Suvad Selman , Ahmed Al Rashdi , Husham Saied
Millions of people worldwide have impaired vision for various reasons, such as cataracts, glaucoma, AMD, diabetic retinopathy, trauma, infections, genetic disorders, and amblyopia. Visual impairment ranges from normal vision to complete blindness, with varying severities that affect daily life. This study presents a sound-based navigation system to improve indoor mobility for visually impaired individuals. The system combines voice recognition, LED-guided floor paths, and real-time haptic feedback to help users follow predefined routes. Users issue voice commands to activate illuminated floor strips, which a robot cart follows using light-dependent resistor (LDR) sensors. An electromechanical compass provides accurate orientation, while a vibrating handle delivers haptic alerts for real-time directional adjustments. Bluetooth Low Energy (BLE) determines the user's location and destination to guide them along the correct route. Experimental results show high accuracy: 91.04 % voice recognition, 4 % navigation error due to sensor noise, and 3 % speed regulation error from electrical fluctuations. The proposed solution is cost-effective and user-friendly, promoting greater independence and safety for visually impaired individuals.
全世界有数百万人因各种原因而视力受损,如白内障、青光眼、黄斑变性、糖尿病性视网膜病变、创伤、感染、遗传疾病和弱视。视力障碍的范围从正常视力到完全失明,影响日常生活的严重程度不一。本研究提出一种以声音为基础的导航系统,以改善视障人士的室内行动能力。该系统结合了语音识别、led引导的地板路径和实时触觉反馈,以帮助用户遵循预定义的路线。用户发出语音命令来激活照明的地板条,机器人手推车使用光依赖电阻(LDR)传感器跟随。机电罗盘提供准确的方向,而振动手柄提供实时方向调整的触觉警报。低功耗蓝牙(BLE)可以确定用户的位置和目的地,引导他们沿着正确的路线前进。实验结果表明,该系统的语音识别精度为91.04%,由传感器噪声引起的导航误差为4%,由电波动引起的调速误差为3%。建议的解决方案具有成本效益和用户友好性,促进视障人士更大的独立性和安全性。
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引用次数: 0
A state-of-the-art statistical method with properties: Its utilization using the industrial investment funds and radiation data 一种最先进、最具特色的统计方法:利用产业投资基金和辐射数据
IF 2.5 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-03-01 Epub Date: 2025-11-29 DOI: 10.1016/j.jrras.2025.102085
Chunlian Xia , Liwe Cao , Maysaa Elmahi Abd Elwahab , Adel M. Widyan , Bassant Elkalzah
Understanding fundamental demographic and environmental dynamics is crucial for accurate data analysis and prediction, particularly when confronting diverse geographical, economic, and physical challenges. In this context, we propose a state-of-the-art statistical model, specifically an improved family of estimators for the population distribution function, which incorporates auxiliary information to enhance estimation accuracy. This model leverages known distribution functions of auxiliary variables to construct efficient estimators for the distribution function of a target study variable. Building on established statistical techniques such as ratio, product, and classical regression estimators, our approach introduces refined alternatives that demonstrate superior statistical properties. These include reduced mean square error (MSE) and increased percentage relative efficiency (PRE) across a wide range of scenarios. Through theoretical justification and empirical validation, we show that our estimators consistently outperform traditional methods in terms of precision and robustness. To demonstrate the model’s versatility, we apply it to two complex, real-world datasets: industrial investment funds and environmental radiation data. In the financial domain, the model effectively captures trends and distributional characteristics critical to fund allocation and risk assessment. For environmental analysis, particularly radiation monitoring, the model identifies distributional shifts and anomalies, providing critical insights for ecological safety and policy-making. Our findings confirm that the proposed family of estimators constitutes a statistically powerful and adaptable modeling framework. It offers significant advancements in distribution function estimation and is well-suited for multidisciplinary applications that demand reliable inference under uncertainty. This research thus contributes to both the theory and application of modern statistical estimation in industrial and environmental sciences.
了解基本的人口和环境动态对于准确的数据分析和预测至关重要,特别是在面对不同的地理、经济和物理挑战时。在这种情况下,我们提出了一个最先进的统计模型,特别是一个改进的总体分布函数估计器族,它包含辅助信息以提高估计精度。该模型利用已知的辅助变量的分布函数来构造目标研究变量的分布函数的有效估计。基于已建立的统计技术,如比率、乘积和经典回归估计器,我们的方法引入了精细的替代方案,展示了优越的统计特性。这包括在广泛的场景中降低均方误差(MSE)和提高相对效率百分比(PRE)。通过理论论证和实证验证,我们表明我们的估计器在精度和鲁棒性方面始终优于传统方法。为了证明该模型的通用性,我们将其应用于两个复杂的真实世界数据集:工业投资基金和环境辐射数据。在金融领域,该模型有效地捕获了对资金分配和风险评估至关重要的趋势和分布特征。对于环境分析,特别是辐射监测,该模型可以识别分布变化和异常,为生态安全和政策制定提供重要见解。我们的研究结果证实,所提出的估计器家族构成了一个统计上强大且适应性强的建模框架。它在分布函数估计方面取得了重大进展,非常适合需要在不确定性下进行可靠推断的多学科应用。因此,本研究对现代统计估计在工业科学和环境科学中的理论和应用作出了贡献。
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引用次数: 0
Investigation of gamma-attenuation and optical behavior in La-doped phosphate glasses for electronic shielding materials 电子屏蔽材料中掺la磷酸盐玻璃的γ衰减和光学行为研究
IF 2.5 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-03-01 Epub Date: 2025-12-20 DOI: 10.1016/j.jrras.2025.102133
Gharam A. Alharshan , Nasra M. Ebrahem , Shaaban M. Shaaban , A.M.A. Mahmoud , R.A. Elsad
Phosphate glasses with a composition of 60 P2O5-20 Li2O-15ZnO- 5Bi2O3 and (60-(x+0.5)) P2O5-20 Li2O-15ZnO- 5Bi2O3- 0.5 Er2O3-xLa2O3 with x = 0:1 mol% were formed via a quick melt-quench process in addition to casting. The produced phosphate glass samples exhibit a rise in density as well as molar volume upon substitution of P2O5 with a specific ratio of Er2O3 and La2O3. The UV–visible domain absorption spectra were analyzed to determine optical characteristics of the manufactured glasses. The Davis-Mott method is employed to find the Urbach energy and optical energy band gaps. The refractive index of each created glass sample is also evaluated, and these results are used to calculate the corresponding molar refraction, the metallization criterion and non-linear optical susceptibilities of all samples, using the appropriate formulae. Phy-X/PSD software was utilized to compute the mass attenuation coefficient (MAC) and linear attenuation coefficient (LAC) throughout an energy range of 0.01–15 MeV. Additionally, LAC was detected experimentally at particular energies, and there was good agreement between both experimental and theoretical findings. The accuracy of the findings was confirmed by the same outcomes that both methods produced. Furthermore, transmission factors (TF), radiation protection efficiency (RPE), (half- and tenth-value layers HVL, and TVL were estimated to evaluate the shielding effectiveness of the glass samples. As the quantity of rare earth oxides in mol% increased, radiation shielding items declared a notable enhancement, with an order of S4 > S3 > S2 > S2 > S1 found at all photon energies.
在浇铸的基础上,采用快速熔淬工艺制备了60 P2O5-20 Li2O-15ZnO- 5Bi2O3和(60-(x+0.5)) P2O5-20 Li2O-15ZnO- 5Bi2O3- 0.5 Er2O3-xLa2O3的磷酸盐玻璃,其质量分数为x = 0:1 mol%。用特定比例的Er2O3和La2O3取代P2O5后,制备的磷酸盐玻璃样品的密度和摩尔体积都有所增加。分析了所制玻璃的紫外-可见吸收光谱,确定了其光学特性。采用Davis-Mott方法计算了乌尔巴赫能和光能带隙。对每个玻璃样品的折射率进行了评估,并利用这些结果计算出相应的摩尔折射率、金属化判据和所有样品的非线性光学磁化率。利用Phy-X/PSD软件计算了0.01-15 MeV能量范围内的质量衰减系数(MAC)和线性衰减系数(LAC)。此外,在特定能量下对LAC进行了实验检测,实验结果与理论结果吻合良好。两种方法产生的相同结果证实了结果的准确性。利用透射系数(TF)、辐射防护效率(RPE)、半值层和十值层HVL和TVL来评价玻璃样品的屏蔽效果。随着稀土氧化物摩尔%含量的增加,辐射屏蔽项明显增强,在所有光子能量下均为S4 >; S3 > S2 > S2 > S1。
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引用次数: 0
KLK5 promotes anoikis resistance in non-small cell lung cancer by activating PI3K/AKT signaling pathway KLK5通过激活PI3K/AKT信号通路促进非小细胞肺癌的anoikis耐药
IF 2.5 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-03-01 Epub Date: 2026-01-13 DOI: 10.1016/j.jrras.2026.102162
Lei Zhang , Qingqing Sun , Qingyong Cai , Mingqiang Shen , Zhijun Zhu , Tengfang Zhang , Baolei Liang , Jinjiao Zhang

Background

Metastasis and recurrence remain the principal causes of mortality in non-small cell lung cancer (NSCLC) patients. A critical prerequisite for tumor cell invasion and metastasis is the development of resistance to anoikis. In NSCLC, high levels of KLK5 are linked to lymphatic metastasis and unfavorable patient survival. This study was designed to investigate the role of KLK5 in anoikis and hypothesized that KLK5 promotes NSCLC metastasis by conferring anoikis resistance via the PI3K/AKT pathway.

Methods

We established and characterized an anoikis-resistant stable cell line, AR-H1299. KLK5 expression in these cells was measured using RT-qPCR and Western blot. Functional assessments of AR-H1299 cells, including CCK-8 assay, colony formation assay, flow cytometry, wound healing assay, and Transwell assay, were performed, and the levels of epithelial-mesenchymal transition (EMT) and metastasis signaling-related proteins were examined. The mechanism by which KLK5 confers anoikis resistance was further investigated through Western blot analysis and functional rescue experiments.

Results

Our results show that KLK5 expression is closely associated with anoikis resistance in NSCLC cells. Genetic knockdown of KLK5 inhibited, while its overexpression enhanced, the proliferation, migration, invasion, and EMT process of AR-H1299 cells. Mechanistic studies revealed that KLK5 promotes the expression of downstream apoptotic regulators Bcl-2 and Bad by activating the PI3K/AKT pathway. Rescue experiments confirmed that the PI3K/AKT inhibitor LY294002 could counteract the pro-metastatic effects induced by KLK5 upregulation.

Conclusion

This study elucidates a previously unreported mechanism by which KLK5 confers anoikis resistance through the PI3K/AKT signaling pathway to promote metastasis in NSCLC.
背景:转移和复发仍然是非小细胞肺癌(NSCLC)患者死亡的主要原因。肿瘤细胞侵袭和转移的一个关键先决条件是对肿瘤产生耐药性。在非小细胞肺癌中,高水平的KLK5与淋巴转移和不利的患者生存有关。本研究旨在探讨KLK5在anoikis中的作用,并假设KLK5通过PI3K/AKT通路赋予anoikis抗性,从而促进NSCLC转移。方法建立一株抗异臭稳定细胞系AR-H1299,并对其进行鉴定。采用RT-qPCR和Western blot检测KLK5在这些细胞中的表达。对AR-H1299细胞进行功能评估,包括CCK-8实验、集落形成实验、流式细胞术、伤口愈合实验和Transwell实验,并检测上皮-间质转化(EMT)和转移信号相关蛋白的水平。通过Western blot分析和功能拯救实验进一步研究了KLK5赋予anoikis抗性的机制。结果KLK5表达与非小细胞肺癌耐药密切相关。KLK5基因敲低抑制AR-H1299细胞的增殖、迁移、侵袭和EMT过程,而过表达增强。机制研究表明,KLK5通过激活PI3K/AKT通路,促进下游凋亡调节因子Bcl-2和Bad的表达。救援实验证实PI3K/AKT抑制剂LY294002可以抵消KLK5上调诱导的促转移作用。本研究阐明了一种以前未报道的机制,即KLK5通过PI3K/AKT信号通路赋予anoikis抗性,从而促进NSCLC的转移。
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引用次数: 0
Impact of case management on chemotherapy adherence, complications, and quality of life post-bladder tumor resection 病例管理对膀胱肿瘤切除术后化疗依从性、并发症和生活质量的影响
IF 2.5 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-03-01 Epub Date: 2026-01-17 DOI: 10.1016/j.jrras.2026.102178
Qiumei Huang, Yudui Xia, Jingfen Cui, Xinli Wang

Purpose

Successful management of non-muscle-invasive bladder cancer (NMIBC) following transurethral resection of bladder tumor (TURBT) depends critically on compliance with intravesical chemotherapy. This study evaluates the impact of a case management model on patient adherence and prognosis.

Methods

This retrospective cohort analysis enrolled NMIBC patients who underwent intravesical chemotherapy after TURBT from June 2022 to June 2024. Subjects were allocated to either a case management cohort (n = 47) or a conventional care cohort (n = 43). Evaluations conducted at 6 and 12 months post-intervention encompassed adherence to therapy, scores from the Functional Assessment of Cancer Therapy – Bladder (FACT-BL), incidence of complications, rates of bladder tumor recurrence, results from the Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS), as well as outcomes from the European Organization for Research and Treatment of Cancer Quality of Life Questionnaires (EORTC QLQ-C30 and QLQ-BLS24).

Results

The case management group showed higher overall treatment adherence (100 % vs 83.72 %, p = 0.013), calculated for all 47 patients who completed the one-year study period with no dropouts or exclusions due to protocol deviation, and lower complication rates during instillation (21.28 % vs 46.51 %, p = 0.011). FACT-BL scores in all four domains were higher in the case management group (all p < 0.05). SAS (41.77 vs 49.32, p < 0.001) and SDS (44.66 vs 47.82, p = 0.001) scores were lower. QLQ-BLS24 indicated reduced future concerns and improved gastrointestinal symptoms, while QLQ-C30 showed better cognitive, emotional, and social functioning. No difference in bladder tumor recurrence rates was observed (p > 0.05).

Conclusion

A structured case management model enhanced adherence, reduced complications, and improved quality of life for NMIBC patients receiving intravesical chemotherapy without negatively impacting short-term recurrence rates.
目的经尿道膀胱肿瘤切除术(TURBT)后非肌肉侵袭性膀胱癌(NMIBC)的成功治疗关键取决于膀胱内化疗的依从性。本研究评估病例管理模式对患者依从性和预后的影响。方法回顾性队列分析纳入2022年6月至2024年6月在TURBT术后接受膀胱化疗的NMIBC患者。受试者被分配到病例管理队列(n = 47)或常规护理队列(n = 43)。干预后6个月和12个月进行的评估包括治疗依从性、癌症治疗功能评估-膀胱(FACT-BL)评分、并发症发生率、膀胱肿瘤复发率、焦虑自评量表(SAS)和抑郁自评量表(SDS)的结果,以及欧洲癌症研究和治疗组织生活质量问卷(EORTC QLQ-C30和QLQ-BLS24)的结果。结果病例管理组显示了更高的总体治疗依从性(100% vs 83.72%, p = 0.013),所有47名患者完成了一年的研究期,没有因方案偏差而退出或排除,并且在注射期间并发症发生率较低(21.28% vs 46.51%, p = 0.011)。病例管理组在所有四个领域的FACT-BL得分均较高(p < 0.05)。SAS (41.77 vs 49.32, p < 0.001)和SDS (44.66 vs 47.82, p = 0.001)评分较低。QLQ-BLS24减少了对未来的担忧,改善了胃肠道症状,而QLQ-C30表现出更好的认知、情感和社交功能。两组膀胱肿瘤复发率无显著差异(p > 0.05)。结论结构化的病例管理模式提高了接受膀胱化疗的NMIBC患者的依从性,减少了并发症,改善了生活质量,而不会对短期复发率产生负面影响。
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引用次数: 0
Design of CKDNet and PMGFANet segmentation models for medical images considering accuracy improvement and data scarcity resolution 考虑精度提高和数据稀缺性分辨率的医学图像CKDNet和PMGFANet分割模型设计
IF 2.5 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-03-01 Epub Date: 2025-12-23 DOI: 10.1016/j.jrras.2025.102141
Tenghong Rong , Jingqi Sun

Introduction/objective

Medical image segmentation can raise the diagnostic efficiency of doctors and reduce their burden, which is of great significance. To raise the accuracy of medical image segmentation and solve the problem of scarce medical image data, corresponding segmentation algorithms are designed separately.

Methods

Firstly, a cascaded knowledge dissemination network model is designed to raise the accuracy of medical image segmentation through the collaborative work of three task subnets: initial segmentation, lesion classification, and fine segmentation, combined with a feature fusion module. Secondly, a semi-supervised segmentation model based on pseudo label guided feature aggregation network is designed, innovatively introducing pseudo label guided feature enhancement module and multi-scale multi-stage feature aggregation module, optimizing the teacher-student network architecture, and fully utilizing unlabeled data to supplement training samples, in order to solve the problem of data scarcity.

Results

The findings denoted that the average multi-category accuracy and segmentation accuracy of the cascaded knowledge dissemination network model were 86.7 % and 99.4 %. On the molecular nucleus segmentation dataset, when the proportion of annotated data was 10 % and 50 %, the maximum intersection to union ratios of the semi supervised segmentation model were 0.859 and 0.867, respectively.

Discussion

It can be seen that the cascaded knowledge dissemination network model has a segmentation accuracy of over 99.0 % on medical images, which can effectively improve the segmentation accuracy of medical images. The semi supervised segmentation model also has good intersection to union ratio and Dice coefficient in low annotated data ratios, and can complete segmentation tasks in medical image data scarcity. The two medical image segmentation models designed in the research have good effectiveness.

Conclusion

The contribution of the research is the design of a semi supervised model consisting of a cascaded knowledge dissemination network model and a pseudo label guided feature aggregation network, which improves the accuracy of medical image segmentation and solves the problem of data scarcity.
医学图像分割可以提高医生的诊断效率,减轻医生的负担,具有重要意义。为了提高医学图像分割的精度,解决医学图像数据稀缺的问题,分别设计了相应的分割算法。方法首先,设计层叠式知识传播网络模型,结合特征融合模块,通过初始分割、病灶分类和精细分割三个任务子网协同工作,提高医学图像分割的准确率;其次,设计了基于伪标签引导特征聚合网络的半监督分割模型,创新引入伪标签引导特征增强模块和多尺度多阶段特征聚合模块,优化师生网络架构,充分利用未标记数据补充训练样本,解决数据稀缺性问题。结果发现,级联知识传播网络模型的平均多类准确率和分割准确率分别为86.7%和99.4%。在分子核分割数据集上,当标注数据比例为10%和50%时,半监督分割模型的最大交联比分别为0.859和0.867。可以看出,级联知识传播网络模型对医学图像的分割准确率达到99.0%以上,可以有效提高医学图像的分割精度。该半监督分割模型在低标注数据比例下具有良好的交联比和Dice系数,可以在医学图像数据稀缺的情况下完成分割任务。本文设计的两种医学图像分割模型均具有良好的分割效果。结论本研究的贡献在于设计了一种由级联知识传播网络模型和伪标签引导特征聚合网络组成的半监督模型,提高了医学图像分割的准确性,解决了数据稀缺性问题。
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引用次数: 0
ARHGAP11A promotes proliferation and invasion through RhoA/RAC1 in LUAD ARHGAP11A通过RhoA/RAC1在LUAD中促进增殖和侵袭
IF 2.5 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-03-01 Epub Date: 2025-12-18 DOI: 10.1016/j.jrras.2025.102123
Xinyu Liu , Xuesong Zhao , Haifeng Hu , Tianyu Zhang , Yi Qi , Bo Liu , Bing Lan , Bin Li

Background

Lung adenocarcinoma (LUAD) ranks among the most common subtypes of lung cancer, characterized by a poor prognosis due to the scarcity of effective treatment options. Functional role and underlying mechanisms of Rho GTPase-activating protein 11A (ARHGAP11A) in LUAD remain insufficiently characterized. The study aims to explore it, with the hypothesis that ARHGAP11A is a pivotal driver of tumor progression and a potential therapeutic target.

Methods

The research employed bioinformatics analysis to identify ARHGAP11A's overexpression in LUAD and its correlation with poor prognosis. To evaluate how reducing ARHGAP11A affects LUAD cell movement and invasion, various functional tests such as cell scratch and transwell cell invasion assays were conducted. Additionally, the study investigated ARHGAP11A's involvement in LUAD epithelial-mesenchymal transition and its regulation through the RhoA/RAC1 pathway using RAC1-specific inhibitor EHT-1864. In vivo tumor growth was assessed following ARHGAP11A knockdown, and the efficacy of the RAC1-specific inhibitor EHT-1864 in reducing tumor growth was tested.

Results

The bioinformatics investigation indicated that ARHGAP11A is upregulated in LUAD and correlates with unfavorable outcomes. Cell migration and invasion were inhibited after ARHGAP11A knockdown. The study also implicated ARHGAP11A in LUAD epithelial-mesenchymal transition and demonstrated its regulation through the RhoA/RAC1 pathway using a RAC1-specific inhibitor. In vivo tumor growth was significantly inhibited by ARHGAP11A knockdown, and treatment with EHT-1864 reduced tumor growth, indicating a potential therapeutic strategy.

Conclusion

The study's findings establish ARHGAP11A as a key factor in LUAD progression, enhancing cell proliferation and invasion. These results warrant further exploration of ARHGAP11A's mechanisms and clinical applications, potentially leading to new therapeutic strategies for LUAD treatment.
肺腺癌(LUAD)是最常见的肺癌亚型之一,由于缺乏有效的治疗方案,其预后较差。Rho gtpase激活蛋白11A (ARHGAP11A)在LUAD中的功能作用和潜在机制尚未得到充分的研究。本研究旨在对此进行探索,并假设ARHGAP11A是肿瘤进展的关键驱动因素和潜在的治疗靶点。方法采用生物信息学分析方法鉴定ARHGAP11A在LUAD中的过表达及其与不良预后的相关性。为了评估降低ARHGAP11A对LUAD细胞运动和侵袭的影响,我们进行了各种功能测试,如细胞划痕和transwell细胞侵袭试验。此外,本研究利用RAC1特异性抑制剂EHT-1864研究了ARHGAP11A参与LUAD上皮-间质转化及其通过RhoA/RAC1通路的调控。在ARHGAP11A基因敲除后评估体内肿瘤生长情况,并检测rac1特异性抑制剂EHT-1864抑制肿瘤生长的效果。结果生物信息学研究表明,ARHGAP11A在LUAD中表达上调,并与不良预后相关。敲低ARHGAP11A后,细胞迁移和侵袭受到抑制。该研究还发现ARHGAP11A参与LUAD的上皮-间质转化,并通过RAC1特异性抑制剂通过RhoA/RAC1通路进行调控。体内肿瘤生长被ARHGAP11A敲低显著抑制,用EHT-1864治疗可降低肿瘤生长,提示一种潜在的治疗策略。结论本研究结果证实ARHGAP11A在LUAD进展中起关键作用,可促进细胞增殖和侵袭。这些结果为进一步探索ARHGAP11A的作用机制和临床应用提供了依据,有可能为LUAD治疗提供新的治疗策略。
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引用次数: 0
Altered brain activation patterns in dyssynergic defecation: Investigating neural mechanisms through task-based fMRI analysis 失调排便的大脑激活模式改变:通过任务型功能磁共振成像分析研究神经机制
IF 2.5 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Pub Date : 2026-03-01 Epub Date: 2026-01-30 DOI: 10.1016/j.jrras.2026.102201
Sheng-fu Zhang , Li Wang , Tong Zeng , He-qiang Li , Qi-xin Tan , Fang Hu , Tao Wu , Shi-jun Qiu

Background

Dyssynergic Defecation (DD) is a functional disorder characterized by paradoxical contraction or insufficient relaxation of the pelvic floor muscles during defecation. While behavioral and physiological factors have been extensively investigated, the underlying central neural mechanisms remain inadequately understood. This study aims to elucidate the differences in brain activation patterns between individuals with DD and healthy controls (HC) during a simulated defecation task utilizing fMRI, thereby addressing the limited comprehension of its neural mechanisms.

Methods

We recruited eight patients diagnosed with DD and ten HC participants. All subjects underwent task-based fMRI while engaging in a validated simulated defecation paradigm. Additionally, the Constipation Scoring System (CSS), the Patient Assessment of Constipation Quality of Life (PAC-QOL), and Montreal Cognitive Assessment (MOCA) were utilized to assess Clinical indicators. The fMRI data were preprocessed and analyzed employing a general linear model (GLM) to identify brain regions exhibiting significant activation during the task. Comparisons between groups were conducted, along with correlation analyses with Clinical indicators.

Results

The DD cohort displayed diminished activation in the right thalamus and right cerebellum (VI), whereas the HC group exhibited activation in the right cerebellum (VI) and the right inferior parietal lobule. Notably, the DD group demonstrated negative activation in several brain areas, including the left fusiform gyrus and left parahippocampal gyrus, when compared to HC. Correlation analysis indicated positive relationships between brain activation in specific regions, such as the right cerebellum (VI) and the left cerebellum (III), with CSS scores and symptoms of straining and incomplete evacuation.

Conclusions

Individuals with DD manifest a distinct profile of dysfunctional brain activation during simulated defecation. These findings suggest a central neural pathophysiology characterized by impaired sensorimotor integration, excessive cognitive inhibition, and altered interoceptive processing. This provides a novel perspective for comprehending DD and may guide future neuromodulation-based therapeutic approaches.
背景:排便失调(DD)是一种以排便时盆底肌肉矛盾收缩或松弛不足为特征的功能性障碍。虽然行为和生理因素已被广泛研究,但潜在的中枢神经机制仍未得到充分了解。本研究旨在利用功能磁共振成像(fMRI)阐明DD患者和健康对照组(HC)在模拟排便任务中大脑激活模式的差异,从而解决对其神经机制的有限理解。方法我们招募了8例诊断为DD的患者和10例HC的参与者。所有的受试者在参与一个有效的模拟排便范例时都进行了任务型功能磁共振成像。此外,采用便秘评分系统(CSS)、患者便秘生活质量评估(PAC-QOL)和蒙特利尔认知评估(MOCA)对临床指标进行评估。对fMRI数据进行预处理,并采用一般线性模型(GLM)进行分析,以确定在任务期间表现出显著激活的大脑区域。组间比较,并与临床指标进行相关性分析。结果DD组在右侧丘脑和右侧小脑(VI)的激活减少,而HC组在右侧小脑(VI)和右侧顶叶下小叶(VI)的激活。值得注意的是,与HC相比,DD组在几个大脑区域表现出负激活,包括左侧梭状回和左侧海马旁回。相关分析显示,特定区域的大脑活动,如右小脑(VI)和左小脑(III),与CSS评分和紧张和不完全排空症状呈正相关。结论:DD患者在模拟排便过程中表现出明显的脑功能障碍。这些发现表明中枢神经病理生理以感觉运动整合受损、过度认知抑制和内感受加工改变为特征。这为理解DD提供了一个新的视角,并可能指导未来基于神经调节的治疗方法。
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引用次数: 0
期刊
Journal of Radiation Research and Applied Sciences
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