Photothermal therapy (PTT) is a promising non-invasive approach for cancer trearment, while its clinical translation has been hindered by the limited targeting precision. Herein, we synthesized Fe(III)-coordinated dimeric indocyanine green nanoparticles (Fe-DICG NPs) via a method of metal coordination driven selfassembly. The resulting Fe-DICG NPs exhibit excellent colloidal stability and favorable photothermal performance upon 808 nm laser irradiation. Meanwhile, Fe-DICG NPs enable bimodal imaging, including Fe-guided T1weighted magnetic resonance imaging and DICG-assisted near infrared fluorescence imaging. Fe-DICG NPs allow precise therapeutic guidance through magnetic resonance imaging. In vitro and in vivo experimental results verify that Fe-DICG NPs can significantly promote tumor regression with alleviated systemic toxicity. Our work provides a facile and efficient preparation method for constructing a theranostic nanoplatform for tumors, and offers an insight into advancing the precise clinical translation of PTT.

BackgroundDiabetes mellitus has emerged as a global public health concern, boasting a high prevalence rate worldwide. Given this situation, accurately identifying type 2 diabetes mellitus (T2DM) holds great significance as it plays a pivotal role in enabling early intervention and facilitating more effective management of the disease. Against this backdrop, it becomes essential to explore the diagnostic value of radiomics features extracted from CT images of vertebral bodies (VB) and paravertebral muscles (PVM) in relation to type 2 diabetes mellitus (T2DM).MethodsA total of 160 cases of clinical and imaging data were retrospectively collected, including 80 patients with T2DM and 80 non-diabetic patients. Regions of interest (ROIs) of VB and PVM were delineated for all subjects, and radiomics features were extracted. Patients were divided into a training group (n=112) and a validation group (n=48) at a 7:3 ratio. Key radiomics features of VB and PVM were screened using independent samples t-test and least absolute shrinkage and selection operator (LASSO) algorithm. A k-nearest neighbor (KNN) classifier was used to establish radiomics models based on VB and PVM, and radiomics scores (Rad-scores) were calculated by weighting the coefficients of the selected features. Clinical risk factors were identified via univariate and multivariate logistic regression to construct a clinical model. A nomogram was then developed by integrating the Rad-score with the clinical model using multivariate logistic regression. The diagnostic performance of the models was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, and clinical decision curves, with the Delong’s test applied to compare performance among models.ResultsIn the training set, the AUCs of the VB radiomics model, PVM radiomics model, VB-PVM combined radiomics model, clinical model, and radiomics-clinical combined model were 0.902, 0.948, 0.952, 0.857, and 0.956, respectively; in the validation set, the corresponding AUCs were 0.873, 0.880, 0.894, 0.758, and 0.926. The radiomics-clinical combined model showed the best diagnostic performance. Calibration and decision curves indicated that the radiomics nomogram had good consistency and clinical applicability.ConclusionThe combined radiomics and clinical model based on CT images of VB and PVM has good diagnostic value for the differential diagnosis of T2DM.

Differentiating between parotid adenolymphoma and malignant tumors remains challenging. This study aims to improve preoperative diagnosis accuracy by evaluating the role of multimodal functional magnetic resonance imaging (MRI) and advanced radiomics analysis. We retrospectively analyzed 124 patients with adenolymphoma and malignant parotid tumors, divided into primary (n = 84) and test (n = 40) cohorts. Tumor regions were manually labeled on susceptibility-weighted imaging (SWI), diffusion-weighted imaging (DWI), and contrast-enhanced T1-weighted imaging (CE-T1WI). Seven radiomics models were constructed using logistic regression. We also incorporated intratumoral susceptibility signal (ITSS) grading and performed histogram analysis of apparent diffusion coefficient (ADC) maps. The united radiomics model combining SWI, DWI, and CE-T1WI showed the highest diagnostic performance (area under the curve (AUC) = 0.95, accuracy = 0.93, specificity = 0.93) in the primary cohort, outperforming single-sequence and double-sequence models. The test set validated the model’s good diagnostic performance (AUC = 0.9). ITSS grading significantly differed between adenolymphomas and malignant tumors (p < 0.001). ADC histogram analysis revealed significant differences in mean, 10th percentile, and kurtosis values between the two groups. The multisequence radiomics model combining DWI, SWI, and CE-T1WI provides a comprehensive and accurate noninvasive approach for differentiating parotid adenolymphoma from malignant tumors. This method helps avoid the risks associated with invasive procedures, such as tumor cell implantation and metastasis, while guiding personalized surgical decision-making. By offering a novel diagnostic tool, this study enhances the precision of preoperative tumor characterization and supports more effective treatment planning and prognosis assessment for patients with parotid gland tumors.

BackgroundOral squamous cell carcinoma is a highly invasive tumor. The degree of histological differentiation and lymph node metastasis are important factors in the treatment and prognosis of patients. There is a lack of non-invasive and accurate preoperative risk prediction model in the existing clinical work.ObjectiveThis study sought to develop and validate a combined model including MRI radiomics and morphological analysis to predict lymph node metastasis and degree of tumor differentiation prior to surgical intervention for oral squamous cell carcinoma (OSCC).MethodsThis study retrospectively included 119 patients which were divided into a training cohort (n=83) and a validation cohort (n=36). To predict lymph node metastasis (LNM) and degree of tumor differentiation, both univariate and multivariate analyses were performed to identify significant features and develop morphological prediction models. Radiomics features were extracted from T2-FS and DWI sequences, followed by feature selection and the establishment of Rad-scores using the LASSO method. Two nomograms was constructed by integrating MRI morphological features with radiomics features. The performance of the models was assessed using the AUC and the Delong test. Calibration curves and DCA were employed to further evaluate the models’ practical applicability.ResultsNine radiomics features were selected to develop the Rad-scores. The morphological features for predicting LNM are depth of invasion and tumor thickness. The morphological features for predicting the degree of tumor differentiation are ADC value and intratumoral necrosis.In the validation cohort, the nomogram for predicting LNM achieved an area under the curve (AUC) of 0.90 (95% CI: 0.84, 0.97), while the nomogram for tumor grade prediction achieved an AUC of 0.87 (95% CI: 0.76, 0.98), demonstrating excellent diagnostic performance. Calibration curve and decision curve further confirmed the accuracy of nomograms prediction.ConclusionNomograms derived from MRI radiomics and morphological characteristics offer a noninvasive and precise method for predicting degree of tumor differentiation and LNM in OSCC preoperatively. The combined model is an accurate risk prediction model with good clinical benefits and prediction accuracy.

BACKGROUND:this study was designed to analyse patient outcomes using a combination of PCI and exercise-based cardiac rehabilitation compared with PCI alone. METHODS:PCI can improve the survival rate of patients with coronary artery disease, but it can also cause vascular endothelial cell injury, thrombosis, and even restenosis. Early cardiac rehabilitation exercise is crucial for patients with coronary heart disease after PCI. Five databases were examined for randomised controlled trials involving early cardiac rehabilitation exercise and standard treatment in patients with coronary heart disease after PCI. The search period lasted from the creation of the database (2006) until December 2022. The outcomes including angina, arrhythmia, coronary restenosis, left ventricular ejection fraction, left ventricular end diastolic diameter, 6-min walk distance, total cholesterol, heart rate, systolic blood pressure and diastolic blood pressure. RevMan 5.3 was used to analyse the data, and the Cochrane Collaboration was used to assess the quality of evidence. RESULTS:A total of 1231 patients were enrolled in this study. Angina pectoris (RR = 0.24, 95% CI [0.10, 0.57], p = 0.001), Arrhythmia (RR = 0.17, 95% CI [0.05, 0.55], p = 0.003), Coronary artery restenosis (RR = 0.10, 95% CI [0.01, 0.76], p = 0.03). CONCLUSION:Exercise after PCI improves LVEF, enhances 6MWD, lowers HR and minimises the risk of angina, arrhythmia and coronary artery restenosis in CHD patients. Exercise had no discernible effect on LVEDD, TC, SBP, or DBP.

Objective: To explore the value of 1.5T magnetic resonance (MR) fat saturation-T2-weighted imaging (FS-T2WI) and apparent diffusion coefficient (ADC) imaging texture features in distinguishing the renal changes of patients with stage III type 2 diabetic kidney disease (DKD) from healthy people.Methods: This study collected 55 patients with stage III DKD (39 males and 16 females) and 33 healthy controls (13 males and 20 females) from December 2021 to June 2022 in the China-Japan Union Hospital of Jilin University. All subjects were randomly divided in a ratio of 6:4 to extract and screen the FS-T2WI and ADC texture features of the right kidney of the subjects. The area under the curve (AUC) was used to assess the diagnostic accuracy of each model. Results: There were significant differences between urea, creatinine and sex (p<0.05) of the two groups in the training and test set, and no significant difference in age and body mass index (BMI). We extracted 1409 imaging features from the original ADC sequence and selected them by wavelet and Laplace-Gaussian filter and LASSO algorithm, and using the same methods of FS-T2WI. Finally, FS-T2WI and ADC models were selected to construct the united model, including 3 first-order features and 8 texture features. The AUC values of the training set of FS-T2WI, ADC, FS-T2WI+ADC combined logistic regression model were 0.96, 0.91, 0.98; the AUC values of the test set were 0.91, 0.89 and 0.93, and the specificity and accuracy values of the united model were 0.90 and 0.89, respectively. Conclusion: FS-T2WI and ADC imaging features based on 1.5 T MR had diagnostic value in the early diagnosis of DKD stage III, and the combined model of FS-T2WI and ADC had high diagnostic efficiency.

The purpose of this study was to identify neurogenic tumours and pleomorphic adenomas of the parapharyngeal space based on the texture characteristics of MRI-T2WI. MR findings and pathological reports of 25 patients with benign tumours in the parapharyngeal space were reviewed retrospectively (13 cases with pleomorphic adenomas and 12 cases with neurogenic tumours). Using PyRadiomics, the texture of the region of interest in T2WI sketched by radiologists was analysed. By using independent sample t-tests and Mann‒Whitney U tests, the selected texture features of 36 Gray Level Co-Occurrence Matrix (GLCM) and Gray Level Dependence Matrix (GLDM) were tested. A set of parameters of texture features showed statistically significant differences between the two groups, which were selected, and the diagnostic efficiency was evaluated via the operating characteristic curve of the subjects. The differences in the three parameters – small dependence low level emphasis (SDLGLE), low level emphasis (LGLE) and difference variance (DV) of characteristics – between the two groups were statistically significant (P < 0.05). No significant difference was found in the other indices. ROC curves were drawn for the three parameters, with AUCs of 0.833, 0.795, and 0.744, respectively. There is a difference in the texture characteristic parameters based on magnetic resonance T2WI images between neurogenic tumours and pleomorphic adenomas in the parapharyngeal space. For the differential diagnosis of these two kinds of tumours, texture analysis of significant importance is an objective and quantitative analytical tool.

腺样囊性癌(ACC)是来源于涎腺组织的罕见恶性肿瘤,占所有口腔颌面部恶性肿瘤的 1％,占所有涎腺上皮性肿瘤的 22％[1].本病的特点是肿瘤缓慢而进行性生长,有神经周围浸润和局部复发的倾向,常导致颅面浸润[2].目前关于头颈部ACC的MRI表现报道较少.本文回顾性分析 2017-2021年吉林大学中日联谊医院经手术病理确诊的 4 例ACC患者资料,分析 MRI 信号特点,并就其临床、病理及治疗方面作一简短的文献回顾.

Objective The objective of the study was to explore the value of MRI texture features based on T1WI, T2-FS and diffusion-weighted imaging (DWI) in differentiation of renal changes in patients with stage III type 2 diabetic nephropathy (DN) and normal subjects. Materials and Methods A retrospective analysis was performed to analyze 44 healthy volunteers (group A) and 40 patients with stage III type 2 diabetic nephropathy (group B) with microalbuminuria. Urinary albumin to creatinine ratio (ACR) <30 mg/g, estimated glomerular filtration rate (eGFR) in the range of 60–120 ml/(min 1.73 m2), and randomly divided into primary cohort and test cohort. Conventional MRI and DWI of kidney were performed using 1.5 T magnetic resonance imaging (MRI). The outline of the renal parenchyma was manually labeled in fat-suppressed T2-weighted imaging (FS-T2WI), and PyRadiomics was used to extract radiomics features. The radiomics features were then selected by the least absolute shrinkage and selection operator (LASSO) method. Results There was a significant difference in sex and body mass index (BMI) (P <0.05) in the primary cohort, with no significant difference in age. In the final results, the wavelet and Laplacian–Gaussian filtering are used to extract 1,892 image features from the original T1WI image, and the LASSO algorithm is used for selection. One first-order feature and six texture features are selected through 10 cross-validations. In the mass, 1,638 imaging extracts features from the original T2WI image.1 first-order feature and 5 texture features were selected. A total of 1,241 imaging features were extracted from the original ADC images, and 5 texture features were selected. Using LASSO-Logistic regression analysis, 10 features were selected for modeling, and a combined diagnosis model of diabetic nephropathy based on texture features was established. The average unit cost in the logistic regression model was 0.98, the 95% confidence interval for the predictive efficacy was 0.9486–1.0, specificity 0.97 and precision 0.93, particularly. ROC curves also revealed that the model could distinguish with high sensitivity of at least 92%. Conclusion In consequence, the texture features based on MR have broad application prospects in the early detection of DN as a relatively simple and noninvasive tool without contrast media administration.

腮腺是人体颌面部最大的腺体,其在颌面部肿瘤发生率中约占80％,腺淋巴瘤是仅次于多形性腺瘤第二位腮腺常见肿瘤,并有逐年上升趋势.腺淋巴瘤又称为乳头状淋巴囊腺瘤、Warthin肿瘤,即良性囊性肿瘤,其中含有上皮成分及丰富的淋巴基质.它以病理学家Aldred Scott Warthin的名字命名为Warthin肿瘤.从临床角度看,它似乎是一种缓慢生长的肿瘤[1-2].该肿瘤以吸烟男性患者多见,其治疗方式与恶性肿瘤不同.

Herein, a ratiometric fluorescent sensor based on MoS2 quantum dots (QDs) and glutathione-capped gold nanoclusters (AuNCs) was developed for determination and imaging of alkaline phosphatase (ALP). The sensor was developed by covalently linking QDs with AuNCs to form stable MoS2@AuNCs nanohybrids that exhibited the blue fluorescence of MoS2 QDs and the red fluorescence of AuNCs. In the presence of Ce3+, the fluorescence intensity of AuNCs was increased due to the aggregation-induced emission enhancement (AIEE), while that of MoS2 QDs remained unchanged, thus could be used as a reference signal. After adenosine 5'-monophosphate (AMP) and ALP were introduced into the system, AMP was hydrolyzed to adenosine and phosphate ions (PO43-). Owing to higher affinity between Ce3+ and PO43-, the AIEE effect was inhibited, in turn resulting in the decrease of AuNCs fluorescence. The developed ratiometric fluorescent sensor had a linear response to ALP concentration ranging from 0.5 to 50 U L-1 with a detection limit (LOD) of 0.08 U L-1. Moreover, the sensor had low cytotoxicity and was successfully employed in lysosome localization and bioimaging of intracellular ALP in living cells. (C) 2021 Elsevier B.V. All rights reserved.

OBJECTIVE In this review, we aim to provide an overview of the imaging techniques most commonly used to study Alzheimer's disease (AD). BACKGROUND Neuroimaging biomarkers can be used to evaluate these abnormalities, improve the ability of early diagnosis and help predict disease progression. These signs mainly include local brain atrophy on structural MRI, hypometabolic foci, and amyloid plaque deposition in the brain detected by specific imaging. These techniques not only have their unique advantages, but can complement each other in multimodal imaging evaluation of patients with cognitive impairment and dementia. METHODS A literature search was performed on PubMed using the search term combinations "Alzheimer's disease", "Amyloid-beta plaques", and "MRI". We discuss various magnetic resonance imaging (MRI) based techniques, including direct imaging, indirect imaging, amyloid-beta (Aβ) plaque and radiomics, Hybrid PET/MRI and MRI imaging technology in the future, placing a special emphasis on multimodal imaging, and focus our review on the MRI features of Aβ plaques (AD biomarkers). CONCLUSIONS After a lot of research and reasonable selection, multimodal imaging composed of MRI and PET can significantly improve the diagnosis and treatment of AD patients, and the complementary information can be obtained by the new PET/MR instrument at the same time. The findings of this review emphasize that multimodal imaging is likely to be the preferred method for future AD research and clinical practice.

Cervical cancer or cervical intraepithelial neoplasia (CIN) remain a major public health problem among women globally. Traditional methods such as surgery are often associated with possible complications which may impact future pregnancies and childbirth especially for young female patients. Vagina with a high contact surface is a suitable route for the local and systemic delivery of drugs but its abundant mucus in continuous exchange presents a barrier for the popularization of conventional vaginal formulations including suppositories, gel, patch, creams and so on. So the development of new pharmaceutical forms based on nanotechnology became appealing owing to its several advantages such as mucosa penetration, bioadhesion, controlled drug release, and decreased adverse effects. This review provided an overview of the development of topical treatment of cervical cancer or CIN through vaginal drug delivery ranging from conventional vaginal formulations to new nanocarriers to the newly developed phototherapy and gene therapy, analyzing the problems faced by current methods used, and advising the developing trend in future. The methods of establishing preclinical animal model are also discussed.

With the rapid development of the nuclear industry, how to deal with radioactive iodine waste in a timely and effective manner has become an important issue to be solved urgently. Herein, the defect-engineering strategy has been applied to develop a metal-organic framework (MOF)-based solid adsorbent by using the classical UiO-type Hf-UiO-66 as an example. After simple acid treatment, the produced defect-containing Hf-UiO-66 (DHUN) not only retains its topological structure, high crystallization, and regular shape but also shows a great increase in the Brunauer-Emmett-Teller value and pore size in comparison with the original Hf-UiO (HUN). These formed defects within DHUN have been demonstrated to be important for the great enhancement of the iodine capture and following application in computed tomography imaging in vitro. This present work gives a new insight into the control and formation of defect sites, and this simple and efficient defect-engineering strategy also shows great promise for the development of novel solid adsorbents and other functional MOF materials.

Ultrastructural features of histospecific differentiation were found in early cleavage stage ascidian embryos treated with cytochalasin B and held thereby in cleavagearrest until hatching time. Markers characteristic of tissue differentiation during normal embryonic and larval stages ofCiona intestinalis were expressed in muscle and two brain cell lineages of cleavage-arrested whole embryos and in epidermal and notochordal cell lineages of cleavage-arrested partial embryos. These features were muscle myofilaments and myofibrils, melanosomes of the brain pigment cells, cilium-derived structures present in a “proprioceptive” brain cell, extracellular test material of epidermal cell origin, and the sheath filaments, membrane leaflets, and vacuolar colloid associated with notochord cells. All of these ultrastructural markers of differentiation were blocked in their development by treatment of gastrula stage embryos with actinomycin D, an inhibitor of RNA synthesis, and presumably result from the expression of new gene activity. At the time of cleavage-arrest the five cell lineages studies still contained two or more unsegregated lineage pathways. Subsequent developmental autonomy within the lineages is consistent with the hypothesis of segregation during early development of functionally independent gene regulatory factors.

多形性透明变性血管扩张性肿瘤又名多形性玻璃样变血管扩张性肿瘤(Pleomorphic hyaline vasodilator tumor,PHAT)由Smith等[1]于1996年发现,并将其描述为一种类似神经鞘瘤的低级别肿瘤.PHAT是发生在软组织、分化不确定的间叶源性肿瘤.此病较为罕见,在有限的报道中显示,其常见于中年人,多发生于下肢[2].现报告我院1例踝部PHAT患者,并分析此例患者的相关资料,汇总PHAT的临床、影像及病理特点.

目的:评价舌部病灶与病灶周围正常腺体表观弥散系数(ADC)的比值对于舌癌的诊断、病理分级、分期的应用价值及相关性.方法:收集2017年3月—2019年3月吉林大学中日联谊医院经手术病理证实的60例舌部病变患者的资料,术前行常规MRI及DWI序列扫描,测量瘤体及瘤体周围正常腺体的ADC值并计算出ADC比值,将其与术后病理结果进行对照分析.结果:①舌癌40例,舌良性病灶20例,舌癌对应的ADC比值为-0.13±0.17,舌良性病灶对应的ADC比值为0.09±0.10,二者比值间差异有统计学意义(t=5.129,P<0.05).②高分化组的ADC比值为0.02±0.07,中分化组的ADC比值为-0.14±0.17,低分化组的ADC比值为-0.26±0.09,三组间比较差异有统计学意义(F=3.593,P=0.047).③晚期舌癌组(T3+T4)的ADC比值(-0.20±0.13)低于早期舌癌组(Tis+T1+T2)的ADC比值(0.00±0.17)(t=3.314,P=0.03<0.05),T4与T1及T2比较差异有统计学意义(P<0.05),其他两两比较无显著差异(P>0.05).结论:ADC比值能够为舌良恶性病灶的鉴别诊断以及舌癌的病理分级、分期提供参考依据,具有重要的临床指导意义.

Correction for ‘BODIPY-containing nanoscale metal–organic frameworks as contrast agents for computed tomography’ by Tao Zhang et al., J. Mater. Chem. B, 2017, 5, 2330–2336, DOI: 10.1039/C7TB00392G.

目的:探讨腮腺良恶性肿瘤的磁共振弥散加权成像(DWI)表观扩散系数(ADC)和表观扩散系数比值(rADC)在鉴别腮腺良恶性肿瘤中的诊断价值.方法:选取经病理证实的腮腺肿瘤患者84例,根据患者术后病理类型分为腮腺良性肿瘤组和恶性肿瘤组,患者术前行常规MRI及DWI序列扫描,HE染色观察不同病理分型腮腺肿瘤组织病理形态表现,测定腮腺良恶性肿瘤及其临近腺体和腮腺良恶性肿瘤及其对侧腺体的ADC,计算相应rADC.结果:腮腺良性肿瘤60例,恶性肿瘤24例;良性肿瘤多边界清晰,混合瘤和腺淋巴瘤是最常见的类型.T2WI显示病灶呈等、低信号;恶性肿瘤以黏液表皮样癌较为多见,形态不规则,边界模糊,信号欠均匀,常伴周围结构的侵犯及颈部淋巴结的增大.与腮腺良性肿瘤比较,腮腺恶性肿瘤的ADC降低(P<0.05),腮腺恶性肿瘤对侧腺体rADC和邻近腺体rADC均降低(P<0.05).受试者工作特征(ROC)曲线检测,ADC、对侧腺体rADC和邻近腺体rADC曲线下面积(AUC)分别为0.859、0.874和0.894;多项指标联合并计算AUC结果显示ADC与对侧腺体rADC、ADC与邻近腺体rADC的AUC分别为0.874和0.894.结论:DWI的ADC和rADC能够为腮腺良恶性肿瘤的诊断及鉴别诊断提供参考依据,具有重要的临床指导意义.

Introduction: Apelin plays an important part in regulating blood pressure, metabolism, and the development of cancer. Recent studies have investigated the association of apelin polymorphisms and hypertension risk, but no meta-analysis has been conducted. Materials and methods: Five studies were included in this meta-analysis in total. The pooled odds ratio and its corresponding 95% confidence interval were calculated by the random-effect model. Results: The overall pooled odds ratio of the distribution of rs3761581 G allelic frequency was 0.90 (95% confidence interval: 0.82–1.00). In female participants, the pooled odds ratio of the frequency of G allele was 1.01 (95% confidence interval: 0.89–1.14). For males, the pooled odds ratio of the frequency of G allele was 0.69 (95% confidence interval: 0.46–1.03). As for rs56204867, the overall pooled odds ratio of the frequency of G allele was 1.09 (95% confidence interval: 0.86–1.37). In females, the pooled odds ratio of the frequencies of the G allele was 1.05 (95% confidence interval: 0.86–1.29). In male participants, the frequency of G allele did not show significant correlation with hypertension (pooled odds ratio=1.21 95% confidence interval: 0.81–1.79). Conclusion: This meta-analysis revealed that there was no correlation between apelin polymorphisms, rs3761581 and rs56204867, and the prevalence of hypertension.