Qualitätsentwicklung im Gesundheitswesen: Sind wir schon so weit,wie wir wollten?

Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz -     

Nanotherapy: New Approach for Impeding Hepatic Cancer Microenvironment via Targeting Multiple Molecular Pathways

Objective: Hepatocellular carcinoma (HCC) microenvironment has been recognized as a key contributor for cancer progression, metastasis, and drug resistance. The crosstalk between tumor cells, the vascular endothelial growth factor (VEGF), and the chemokine (C-C motif) ligand 2 (CCL2) signaling networks mediates immunoinhibitory impact and facilitates tumor angiogenesis. The current investigation aimed at exploring the potent anti-cancer activity of the newly designed nano-based anti-cancer therapy comprising anti-VEGF drug, avastin (AV), and CCR2 antagonist (CR) to counteract HCC and tracking its mode of action in vivo. Methods: The prepared AV, CR, and AVCR nanoprototypes were characterized by nanoscale characterization techniques in our previous work. Here, they are applied for unearthing their anti-cancer properties / mechanisms in hepatic cancer-induced rats via analyzing protein levels and genetic expression of the elements incorporated in the angiogenesis, apoptosis, and metastasis signalling pathways. Results: The present results revealed a significant down-regulation in the angiogenesis, survival and metastasis indices along with up-regulation in the pro-apoptotic mediators upon treatment of hepatic cancer-bearing rats with the novel synthesized nanomaterials when compared with the untreated counterparts. We showed across HCC model that anti-VEGF in combination with CCR2 antagonism therapy leads to sensitization and enhanced tumor response over anti-VEGF or CCR2 antagonism monotherapy, particularly in its nanoscale formulation. Conclusion: The present approach provides new mechanistic insights into the powerful anti-hepatic cancer advantage of the novel nanoprototypes which is correlated with modulating critical signal transduction pathways implicated in tumor microenviroment such as angiogenesis, apoptosis and metastasis. This research work presents a substantial foundation for future studies focused on prohibiting cancer progression and recovery by targeting tumor microenviroment.     

Sickle cell nephropathy: A review of novel biomarkers and their potential roles in early detection of renal involvement

Whether the underlying mutations are homozygous, heterozygous, or co-inherited with other hemoglobinopathies, sickle cell disease is known to afflict the kidneys, leading to the clinical entity known as sickle cell nephropathy (SCN). Although common, SCN remains diagnostically elusive. Conventional studies performed in the context of renal disorders often fail to detect early stage SCN. This makes the quest for early diagnosis and treatment more challenging, and it increases the burden of chronic kidney disease-related morbidity among patients. Novel diagnostic tools have been employed to overcome this limitation. In this study, we discuss various biomarkers of SCN, including those employed in clinical practice and others recently identified in experimental settings, such as markers of vascular injury, endothelial dysfunction, tubulo-glomerular damage, and oxidative stress. These include kidney injury molecule-1, monocyte chemoattractant protein-1, N-acetyl-B-D-glucosaminidase, ceruloplasmin, orosomucoid, nephrin, and cation channels, among others. Furthermore, we explore the potential of novel biomarkers for refining diagnostic and therapeutic approaches and describe some obstacles that still need to be overcome. We highlight the importance of a collaborative approach to standardize the use of promising new biomarkers. Finally, we outline the limitations of conventional markers of renal damage as extensions of the pathogenic process occurring at the level of the organ and its functional subunits, with a discussion of the expected pattern of clinical and biochemical progression among patients with SCN.     

早孕期监测子宫动脉多普勒参数在预测低危人群不良妊娠结局的价值

目的 建立妊娠11~13+6周子宫动脉多普勒参数在低危人群中的正常参考值，同时评估其对不良妊娠结局的预测价值。方法 收集2019年6月至2021年6月于我院行产前超声检查的妊娠11~13+6周孕妇，根据妊娠结局分组。收集两侧子宫动脉多普勒指标，包括搏动指数（PI）、阻力指数（RI）、舒张早期是否有切迹，以及孕妇基本临床资料和胎儿出生信息，将以上相关参数进行统计学分析。结果 最终纳入800例孕妇，包括正常妊娠结局组740例和不良妊娠结局组60例。两组孕妇体质量指数（BMI）、分娩孕周和胎儿出生体质量比较，差异均有统计学意义（均P＜0.05）。随着孕周的增加，子宫动脉两侧平均搏动指数（mPI）、平均阻力指数（mRI）和两侧舒张早期切迹检出率均呈逐渐下降的趋势。ROC曲线分析显示，mPI、mRI及两侧舒张早期切迹预测妊娠结局的曲线下面积（AUC）分别为0.542、0.574、0.521，三者联合预测妊娠结局的AUC为0.648；孕妇BMI、年龄mPI、mRI及两侧舒张早期切迹预测妊娠结局的AUC为0.751。结论 建立了低危人群在妊娠11~13+6周子宫动脉多普勒参数的正常参考值范围。在妊娠11~13+6周单纯应用子宫动脉多普勒参数预测妊娠结局的价值有限，将子宫动脉参数与临床相关指标结合可提高对不良妊娠结局的预测价值。     

Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning

Arterial spin labeling (ASL) imaging is a powerful magnetic resonance imaging technique that allows to quantitatively measure blood perfusion non-invasively, which has great potential for assessing tissue viability in various clinical settings. However, the clinical applications of ASL are currently limited by its low signal-to-noise ratio (SNR), limited spatial resolution, and long imaging time. In this work, we propose an unsupervised deep learning-based image denoising and reconstruction framework to improve the SNR and accelerate the imaging speed of high resolution ASL imaging. The unique feature of the proposed framework is that it does not require any prior training pairs but only the subject's own anatomical prior, such as T1-weighted images, as network input. The neural network was trained from scratch in the denoising or reconstruction process, with noisy images or sparely sampled k-space data as training labels. Performance of the proposed method was evaluated using in vivo experiment data obtained from 3 healthy subjects on a 3T MR scanner, using ASL images acquired with 44-min acquisition time as the ground truth. Both qualitative and quantitative analyses demonstrate the superior performance of the proposed txtc framework over the reference methods. In summary, our proposed unsupervised deep learning-based denoising and reconstruction framework can improve the image quality and accelerate the imaging speed of ASL imaging.     

Functional estrogen receptor signal transduction pathway activity and antihormonal therapy response in low-grade ovarian carcinoma

Background

Advanced low-grade ovarian carcinoma (LGOC) is difficult to treat. In several studies, high estrogen receptor (ER) protein expression was observed in patients with LGOC, which suggests that antihormonal therapy (AHT) is a treatment option. However, only a subgroup of patients respond to AHT, and this response cannot be adequately predicted by currently used immunohistochemistry (IHC). A possible explanation is that IHC only takes the ligand, but not the activity, of the whole signal transduction pathway (STP) into account. Therefore, in this study, the authors assessed whether functional STP activity can be an alternative tool to predict response to AHT in LGOC.

Methods

Tumor tissue samples were obtained from patients with primary or recurrent LGOC who subsequently received AHT. Histoscores of ER and progesterone receptor (PR) were determined. In addition, STP activity of the ER STP and of six other STPs known to play a role in ovarian cancer was assessed and compared with the STP activity of healthy postmenopausal fallopian tube epithelium.

Results

Patients who had normal ER STP activity had a progression-free survival (PFS) of 16.1 months. This was significantly shorter in patients who had low and very high ER STP activity, with a median PFS of 6.0 and 2.1 months, respectively (p < .001). Unlike ER histoscores, PR histoscores were strongly correlated to the ER STP activity and thus to PFS.

Conclusions

Aberrant low and very high functional ER STP activity and low PR histoscores in patients with LGOC indicate decreased response to AHT. ER IHC is not representative of functional ER STP activity and is not related to PFS.