PYCR3 modulates mtDNA copy number to drive proliferation and doxorubicin resistance in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) poses significant challenges in treatment due to its aggressive nature and limited therapeutic targets. Understanding the underlying molecular mechanisms driving TNBC progression and chemotherapy resistance is imperative for developing effective therapeutic strategies. Thus, in this study, we aimed to elucidate the role of pyrroline-5-carboxylate reductase 3 (PYCR3) in TNBC pathogenesis and therapeutic response. We observed that PYCR3 is significantly upregulated in TNBC specimens compared to normal breast tissues, correlating with a poorer prognosis in TNBC patients. Knockdown of PYCR3 not only suppresses TNBC cell proliferation but also reverses acquired resistance of TNBC cells to doxorubicin, a commonly used chemotherapeutic agent. Mechanistically, we identified the mitochondrial localization of PYCR3 in TNBC cells and demonstrated its impact on TNBC cell proliferation and sensitivity to doxorubicin through the regulation of mtDNA copy number and mitochondrial respiration. Importantly, Selective reduction of mtDNA copy number using the mtDNA replication inhibitor 2', 3'-dideoxycytidine effectively recapitulates the phenotypic effects observed in PYCR3 knockout, resulting in decreased TNBC cell proliferation and the reversal of doxorubicin resistance through apoptosis induction. Thus, our study underscores the clinical relevance of PYCR3 and highlight its potential as a therapeutic target in TNBC management. By elucidating the functional significance of PYCR3 in TNBC, our findings contribute to a deeper understanding of TNBC biology and provide a foundation for developing novel therapeutic strategies aimed at improving patient outcomes.

Unsupervised OCT image despeckling with ground-truth- and repeated-scanning-free features.

Optical coherence tomography (OCT) can resolve biological three-dimensional tissue structures, but it is inevitably plagued by speckle noise that degrades image quality and obscures biological structure. Recently unsupervised deep learning methods are becoming more popular in OCT despeckling but they still have to use unpaired noisy-clean images or paired noisy-noisy images. To address the above problem, we propose what we believe to be a novel unsupervised deep learning method for OCT despeckling, termed Double-free Net, which eliminates the need for ground truth data and repeated scanning by sub-sampling noisy images and synthesizing noisier images. In comparison to existing unsupervised methods, Double-free Net obtains superior denoising performance when trained on datasets comprising retinal and human tissue images without clean images. The efficacy of Double-free Net in denoising holds significant promise for diagnostic applications in retinal pathologies and enhances the accuracy of retinal layer segmentation. Results demonstrate that Double-free Net outperforms state-of-the-art methods and exhibits strong convenience and adaptability across different OCT images.

STK32C modulates doxorubicin resistance in triple-negative breast cancer cells via glycolysis regulation.

Understanding the mechanisms underlying doxorubicin resistance in triple-negative breast cancer (TNBC) holds paramount clinical significance. In our study, we investigate the potential of STK32C, a little-explored kinase, to impact doxorubicin sensitivity in TNBC cells. Our findings reveal elevated STK32C expression in TNBC specimens, associated with unfavorable prognosis in doxorubicin-treated TNBC patients. Subsequent experiments highlighted that STK32C depletion significantly augmented the sensitivity of doxorubicin-resistant TNBC cells to doxorubicin. Mechanistically, we unveiled that the cytoplasmic subset of STK32C plays a pivotal role in mediating doxorubicin sensitivity, primarily through the regulation of glycolysis. Furthermore, the kinase activity of STK32C proved to be essential for its mediation of doxorubicin sensitivity, emphasizing its role as a kinase. Our study suggests that targeting STK32C may represent a novel therapeutic approach with the potential to improve doxorubicin's efficacy in TNBC treatment.

Toward ground-truth optical coherence tomography via three-dimensional unsupervised deep learning processing and data.

Optical coherence tomography (OCT) can perform non-invasive high-resolution three-dimensional (3D) imaging and has been widely used in biomedical fields, while it is inevitably affected by coherence speckle noise which degrades OCT imaging performance and restricts its applications. Here we present a novel speckle-free OCT imaging strategy, named toward-ground-truth OCT (tGT-OCT), that utilizes unsupervised 3D deep-learning processing and leverages OCT 3D imaging features to achieve speckle-free OCT imaging. Specifically, our proposed tGT-OCT utilizes an unsupervised 3D-convolution deep-learning network trained using random 3D volumetric data to distinguish and separate speckle from real structures in 3D imaging volumetric space; moreover, tGT-OCT effectively further reduces speckle noise and reveals structures that would otherwise be obscured by speckle noise while preserving spatial resolution. Results derived from different samples demonstrated the high-quality speckle-free 3D imaging performance of tGT-OCT and its advancement beyond the previous state-of-the-art. The code is available online: https://github.com/Voluntino/tGT-OCT.

High-accuracy 3D segmentation of wet age-related macular degeneration via multi-scale and cross-channel feature extraction and channel attention.

Wet age-related macular degeneration (AMD) is the leading cause of visual impairment and vision loss in the elderly, and optical coherence tomography (OCT) enables revolving biotissue three-dimensional micro-structure widely used to diagnose and monitor wet AMD lesions. Many wet AMD segmentation methods based on deep learning have achieved good results, but these segmentation results are two-dimensional, and cannot take full advantage of OCT's three-dimensional (3D) imaging characteristics. Here we propose a novel deep-learning network characterizing multi-scale and cross-channel feature extraction and channel attention to obtain high-accuracy 3D segmentation results of wet AMD lesions and show the 3D specific morphology, a task unattainable with traditional two-dimensional segmentation. This probably helps to understand the ophthalmologic disease and provides great convenience for the clinical diagnosis and treatment of wet AMD.

High-precision Drosophila heart segmentation and dynamic cardiac parameter measurement for optogenetics-OCT-based cardiac function research.

Drosophila model has been widely used to study cardiac functions, especially combined with optogenetics and optical coherence tomography (OCT) that can continuously acquire mass cross-sectional images of the Drosophila heart in vivo over time. It's urgent to quickly and accurately obtain dynamic Drosophila cardiac parameters such as heartbeat rate for cardiac function quantitative analysis through these mass cross-sectional images of the Drosophila heart. Here we present a deep-learning method that integrates U-Net and generative adversarial network architectures while incorporating residually connected convolutions for high-precision OCT image segmentation of Drosophila heart and dynamic cardiac parameter measurements for optogenetics-OCT-based cardiac function research. We compared our proposed network with the previous approaches and our segmentation results achieved the accuracy of intersection over union and Dice similarity coefficient higher than 98%, which can be used to better quantify dynamic heart parameters and improve the efficiency of Drosophila-model-based cardiac research via the optogenetics-OCT-based platform.

Synthesis of hydroxyethyl starch 200/0.5-loaded albumin nanoparticles: biocompatibility and interaction mechanism.

We aimed to synthesize hydroxyethyl starch (HES) 200/0.5-loaded bovine serum albumin nanoparticles (HBNs) and investigate the compatibility and binding mechanism in simulated physiological environments. Here, to elucidate the morphology, biocompatibility, and formation mechanism of HBNs, techniques such as scanning electron microscopy, haemolysis test, fluorescence, and circular dichroism spectroscopy were applied. The thermodynamic parameters at body temperature (ΔS° = -26.7 J·mol-1 ·K-1 , ΔH° = -3.20 × 104 J·mol-1 , and ΔG = -2.35 × 104 J·mol-1 ) showed a 1:1 binding stoichiometry, which was formed by hydrogen bonds and van der Waals interactions. In addition, the conformational analysis showed that the microenvironment of fluorophores was altered with the adaptational protein secondary structural changes. Energy transfer occurred from the fluorophores to HES with a high possibility. All these results provided accurate and complete primary data for demonstrating the interaction mechanisms of HES with BSA, which helps to understand its pharmaceutical effects in blood.

SNR-Net OCT: brighten and denoise low-light optical coherence tomography images via deep learning.

Low-light optical coherence tomography (OCT) images generated when using low input power, low-quantum-efficiency detection units, low exposure time, or facing high-reflective surfaces, have low bright and signal-to-noise rates (SNR), and restrict OCT technique and clinical applications. While low input power, low quantum efficiency, and low exposure time can help reduce the hardware requirements and accelerate imaging speed; high-reflective surfaces are unavoidable sometimes. Here we propose a deep-learning-based technique to brighten and denoise low-light OCT images, termed SNR-Net OCT. The proposed SNR-Net OCT deeply integrated a conventional OCT setup and a residual-dense-block U-Net generative adversarial network with channel-wise attention connections trained using a customized large speckle-free SNR-enhanced brighter OCT dataset. Results demonstrated that the proposed SNR-Net OCT can brighten low-light OCT images and remove the speckle noise effectively, with enhancing SNR and maintaining the tissue microstructures well. Moreover, compared to the hardware-based techniques, the proposed SNR-Net OCT can be of lower cost and better performance.

MAS-Net OCT: a deep-learning-based speckle-free multiple aperture synthetic optical coherence tomography.

High-resolution spectral domain optical coherence tomography (SD-OCT) is a vital clinical technique that suffers from the inherent compromise between transverse resolution and depth of focus (DOF). Meanwhile, speckle noise worsens OCT imaging resolving power and restricts potential resolution-enhancement techniques. Multiple aperture synthetic (MAS) OCT transmits light signals and records sample echoes along a synthetic aperture to extend DOF, acquired by time-encoding or optical path length encoding. In this work, a deep-learning-based multiple aperture synthetic OCT termed MAS-Net OCT, which integrated a speckle-free model based on self-supervised learning, was proposed. MAS-Net was trained on datasets generated by the MAS OCT system. Here we performed experiments on homemade microparticle samples and various biological tissues. Results demonstrated that the proposed MAS-Net OCT could effectively improve the transverse resolution in a large imaging depth as well as reduced most speckle noise.

TiO2-Coated Silicon Nanoparticle Core-Shell Structure for High-Capacity Lithium-Ion Battery Anode Materials.

Silicon-based anode materials are considered one of the highly promising anode materials due to their high theoretical energy density; however, problems such as volume effects and solid electrolyte interface film (SEI) instability limit the practical applications. Herein, silicon nanoparticles (SiNPs) are used as the nucleus and anatase titanium dioxide (TiO2) is used as the buffer layer to form a core-shell structure to adapt to the volume change of the silicon-based material and improve the overall interfacial stability of the electrode. In addition, silver nanowires (AgNWs) doping makes it possible to form a conductive network structure to improve the conductivity of the material. We used the core-shell structure SiNPs@TiO2/AgNWs composite as an anode material for high-efficiency Li-ion batteries. Compared with the pure SiNPs electrode, the SiNPs@TiO2/AgNWs electrode exhibits excellent electrochemical performance with a first discharge specific capacity of 3524.2 mAh·g-1 at a current density of 400 mA·g-1, which provides a new idea for the preparation of silicon-based anode materials for high-performance lithium-ion batteries.

SMAGP regulates doxorubicin sensitivity in triple-negative breast cancer cells via modulating mitochondrial respiration.

Doxorubicin-based chemotherapy remains as a major therapeutic approach for patients with triple-negative breast cancer (TNBC). However, insensitivity or resistance to doxorubicin treatment limits the therapeutic efficacy. Mitochondrial respiration plays a critical role in regulating the sensitivity of cancer cells to chemotherapy drugs. Here, we found that small trans-membrane and glycosylated protein (SMAGP) is upregulated in TNBC cells in comparison to normal breast and other subtypes of breast cancer cells. High SMAGP expression is associated with poorer overall survival of TNBC patients. Importantly, loss of SMAGP enhanced the sensitivity of TNBC cells to doxorubicin treatment. Mechanistically, we detected a functional pool of SMAGP in the mitochondria of TNBC cells controlling doxorubicin sensitivity via regulating mitochondrial respiration. Thus, our data suggest that SMAGP acts as a novel regulator of doxorubicin sensitivity in TNBC, identifying SMAGP as a promising therapeutic target for improving the efficacy of doxorubicin-based chemotherapy in TNBC patients.

RGBD Salient Object Detection, Based on Specific Object Imaging.

RGBD salient object detection, based on the convolutional neural network, has achieved rapid development in recent years. However, existing models often focus on detecting salient object edges, instead of objects. Importantly, detecting objects can more intuitively display the complete information of the detection target. To take care of this issue, we propose a RGBD salient object detection method, based on specific object imaging, which can quickly capture and process important information on object features, and effectively screen out the salient objects in the scene. The screened target objects include not only the edge of the object, but also the complete feature information of the object, which realizes the detection and imaging of the salient objects. We conduct experiments on benchmark datasets and validate with two common metrics, and the results show that our method reduces the error by 0.003 and 0.201 (MAE) on D3Net and JLDCF, respectively. In addition, our method can still achieve a very good detection and imaging performance in the case of the greatly reduced training data.

Remifentanil Anesthesia on the Expression of Apoptosis-Related Proteins Bcl-2 and Bax in Rat Myocardial Cells with Ischemia-Reperfusion Injury.

Ischemia-reperfusion damage to the myocardium is inevitable. This study mainly explored the effect of remifentanil anesthesia on the expression of apoptosis-related proteins Bcl-2 and Bax in rat myocardial ischemia-reperfusion injury. Select 48 mice (n=6). First, prepare solutions of different concentrations of remifentanil. A model of ischemia-reperfusion cardiomyocytes was established, and 6 slices of tissue were taken from each specimen, and the positive cells were observed with an optical microscope and magnified 100 times. Bcl-2 and Bax were positive in the cytoplasm and yellowish-brown particles in the inner membrane. According to the distribution of positive cells, randomly select 3 clear fields of view from each part, count the number of positive cells in each field, and then take the average of the proportion of positive cells to get Bcl-2 or Bax protein-positive Index (PEI). Comparison of mRNA levels in each group: Compared with the R3 group, the ratio of the M, R1, and R2 groups increased, and the mRNA expression level of the M group increased almost 3 times, P<0.05. The results of the study show that remifentanil reduces the mortality of myocardial cells by regulating the appearance of Bcl-2 and Bax proteins, and has a certain protective effect on the rat heart during myocardial ischemia and reperfusion. There is no statistically significant difference in the protective effect of remifentanil on myocardial ischemia-reperfusion.

Voluven treatment could induce NLRP3 inflammasome-mediated pyroptosis of bone marrow-derived macrophages.

The aim of this study was to investigate the influence of Voluven on the NLRP3 inflammasome-mediated pyroptosis in bone marrow-derived macrophage (BMDM). Separated BMDMs were cultured and treated with different concentration of Voluven (0, 0.1, and 0.5 µg) dissolved in 10 µL 0.9% NaCl solution for 24 h. Both wild-type and nucleotide-binding domain and leucine-rich repeat protein 3 (NLRP3)-/- C57BL/6J mice (n = 18) were intravenously injected with 0.2 mL of 0%, 5%, and 10% Voluven through femoral vein, respectively. Pyroptosis was inspected with flow cytometry. The mRNA levels of NLRP3 and caspase-1 were detected with quantitative real-time polymerase chain reaction (qRT-PCR). The levels of NLRP3, pro-caspase-1, and cleaved caspase-1 (p10) in serum were determined with Western blot. The expression of IL-17A in peripheral blood CD4+ T cells was analyzed with flow cytometry. The expression of cleaved caspase-1 (p10) in mice spleens was inspected with immunofluorescence. Compared with control group, the ratio of pyroptosis in all Voluven-treated groups rose significantly. The levels of NLRP3 and caspase-1 were increased after Voluven treatment. The expression of interleukin (IL)-17A in Voluven-treated CD4+ T cells was also increased, exhibiting a dose-dependent pattern. In wild-type mice, Voluven-treated mice had higher levels of IL-17A, NLRP3, and cleaved caspase-1 (p10) in a dose-dependent manner. The effects of Voluven were diminished in NLRP3-/- mice.

Association Between MTHFR Polymorphisms and the Risk of Essential Hypertension: An Updated Meta-analysis.

BACKGROUND: Since the 1990s, there have been a lot of research on single-nucleotide polymorphism (SNP) and different diseases, including many studies on 5,10-methylenetetrahydrofolate reductase (MTHFR) polymorphism and essential hypertension (EH). Nevertheless, their conclusions were controversial. So far, six previous meta-analyses discussed the internal relationship between the MTHFR polymorphism and EH, respectively. However, they did not evaluate the credibility of the positive associations. To build on previous meta-analyses, we updated the literature by including previously included papers as well as nine new articles, improved the inclusion criteria by also considering the quality of the papers, and applied new statistical techniques to assess the observed associations. OBJECTIVES: This study aims to explore the degree of risk correlation between two MTHFR polymorphisms and EH. METHODS: PubMed, EMBASE, the Cochrane Library, CNKI, and Wan Fang electronic databases were searched to identify relevant studies. We evaluated the relation between the MTHFR C677T (rs1801133) and A1298C (rs1801131) polymorphisms and EH by calculating the odds ratios (OR) as well as 95% confidence intervals (CI). Here we used subgroup analysis, sensitivity analysis, cumulative meta-analysis, assessment of publication bias, meta-regression meta, False-positive report probability (FPRP), Bayesian false discovery probability (BFDP), and Venice criterion. RESULTS: Overall, harboring the variant of MTHFR C677T was associated with an increased risk of EH in the overall populations, East Asians, Southeast Asians, South Asians, Caucasians/Europeans, and Africans. After the sensitivity analysis, positive results were found only in the overall population (TT vs. CC: OR = 1.14, 95% CI: 1.00-1.30, P h = 0.032, I 2 = 39.8%; TT + TC vs. CC: OR = 1.15, 95% CI: 1.01-1.29, P h = 0.040, I 2 = 38.1%; T vs. C: OR = 1.14, 95% CI: 1.04-1.25, P h = 0.005, I 2 = 50.2%) and Asian population (TC vs. CC: OR = 1.14, 95% CI: 1.01-1.28, P h = 0.265, I 2 = 16.8%; TT + TC vs. CC: OR = 1.17, 95% CI: 1.04-1.30, P h = 0.105, I 2 = 32.9%; T vs. C: OR = 1.10, 95% CI: 1.02-1.19, P h = 0.018, I 2 = 48.6%). However, after further statistical assessment by FPRP, BFDP, and Venice criteria, the positive associations reported here could be deemed to be false-positives and present only weak evidence for a causal relationship. In addition, when we performed pooled analysis and sensitivity analysis on MTHFR A1298C; all the results were negative. CONCLUSION: The positive relationships between MTHFR C677T and A1298C polymorphisms with the susceptibility to present with hypertension were not robust enough to withstand statistical interrogation by FPRP, BFDP, and Venice criteria. Therefore, these SNPs are probably not important in EH etiology.

Evaluation of association studies and a systematic review and meta-analysis of VDR polymorphisms in type 2 diabetes mellitus risk.

ABSTRACT: Numerous original studies and 4 published meta-analyses have reported the association between the Vitamin D receptor (VDR) BsmI, FokI, ApaI, and TaqI polymorphisms and type 2 diabetes mellitus (T2DM) risk. However, the results were inconsistent. Therefore, an updated meta-analysis was performed to further explore these issues.To further explore the association between the VDR BsmI, FokI, ApaI, and TaqI polymorphisms and T2DM risk.PubMed, EMBASE, Scopus, and Wanfang databases were searched. The following search strategy were used: (VDR OR vitamin D receptor) AND (polymorphism OR variant OR mutation) AND (diabetes OR mellitus OR diabetes mellitus). Pooled crude odds ratios with 95% confidence intervals were applied to evaluate the strength of association in 5 genetic models. Statistical heterogeneity, the test of publication bias, and sensitivity analysis were carried out using the STATA software (Version 12.0). To evaluate the credibility of statistically significant associations, we applied the false-positive report probabilities (FPRP) and Bayesian false discovery probability (BFDP) test.Overall, the VDR BsmI polymorphism was associated with a significantly decreased T2DM risk in Asians; the VDR FokI polymorphism was associated with a significantly decreased T2DM risk in Asians, African countries, and Asian countries; the VDR ApaI polymorphism was associated with a significantly decreased T2DM risk in Caucasians and North American countries.On the VDR ApaI polymorphism, a significantly increased T2DM risk was found in a mixed population. However, when we further performed a sensitivity analysis, FPRP, and BFDP test, less-credible positive results were identified (all FPRP > 0.2 and BFDP > 0.8) in any significant association.In summary, this study strongly indicates that all significant associations were less credible positive results, rather than from true associations.

Assessing spatial variability of soil organic carbon and total nitrogen in eroded hilly region of subtropical China.

The hilly red soil region of southern China suffers from severe soil erosion that has led to soil degradation and loss of soil nutrients. Estimating the content and spatial variability of soil organic carbon (SOC) and soil total nitrogen (STN) and assessing the influence of topography and land-use type on SOC and STN after years of soil erosion control are important for vegetation restoration and ecological reconstruction. A total of 375 topsoil samples were collected from Changting County, and their SOC and STN distributions were studied by using descriptive statistics and geostatistical methods. Elevation, slope, aspect and land-use type were selected to investigate the impacts of natural and human factors on the spatial heterogeneity of SOC and STN. The mean SOC and STN concentrations were 15.85 and 0.98 g kg-1 with moderate spatial variations, respectively. SOC and STN exhibited relatively uniform distributions that decreased gradually from the outside parts to the center of the study area. The SOC and STN contents in the study area were still at moderate and low levels after years of erosion control, which suggests that soil nutrient improvement is a slow process. The lowest SOC and STN values were at lower elevations in the center of Changting County. The results indicated that the SOC and STN contents increased most significantly with elevation and slope due to the influence of topography on the regional natural environment and soil erosion in the eroded hilly region. No significant variations were observed among different slope directions and land-use types.

Semaphorin-4C is upregulated in epithelial ovarian cancer.

The present retrospective study aimed to investigate the expression of semaphorin-4C (Sema4C) in epithelial ovarian cancer (EOC), and to determine the association between Sema4C expression and patient clinicopathological characteristics. Sema4C mRNA expression was detected by reverse transcription-quantitative polymerase chain reaction in the tissues of 74 cases of EOC, 20 cases of ovarian epithelial benign tumor, 20 cases of ovarian borderline epithelial tumor and 15 cases of normal ovarian tissue. Immunohistochemistry was used to detect the expression and localization of Sema4C. The association between Sema4C expression level and patients clinicopathological characteristics was determined by χ2 test. The results demonstrated that Sema4C expression level in ovarian epithelial carcinoma tissues was significantly higher compared with that in benign tumors, borderline epithelial tumors and normal ovarian tissues (P<0.05). In addition, Sema4C expression in ovarian cancer tissues was significantly associated with the clinical and pathological stages of tumors (P<0.05). In conclusion, the present study demonstrated that Sema4C expression was upregulated in EOC.

MDSCs drive the process of endometriosis by enhancing angiogenesis and are a new potential therapeutic target.

Endometriosis affects women of reproductive age via unclear immunological mechanism(s). Myeloid-derived suppressor cells (MDSCs) are a heterogeneous group of myeloid cells with potent immunosuppressive and angiogenic properties. Here, we found MDSCs significantly increased in the peripheral blood of patients with endometriosis and in the peritoneal cavity of a mouse model of surgically induced endometriosis. Majority of MDSCs were granulocytic, produced ROS, and arginase, and suppressed T-cell proliferation. Depletion of MDSCs by antiGr-1 antibody dramatically suppressed development of endometrial lesions in mice. The chemokines CXCL1, 2, and 5 were expressed at sites of lesion while MDSCs expressed CXCR-2. These CXC-chemokines promoted MDSC migration toward endometriotic implants both in vitro and in vivo. Also, CXCR2-deficient mice show significantly decreased MDSC induction, endometrial lesions, and angiogenesis. Importantly, adoptive transfer of MDSCs into CXCR2-KO mice restored endometriotic growth and angiogenesis. Together, this study demonstrates that MDSCs play a role in the pathogenesis of endometriosis and identifies a novel CXC-chemokine and receptor for the recruitment of MDSCs, thereby providing a potential target for endometriosis treatment.

Investigation on the Interaction of Hydroxyethyl Starch 130/0.4 (Voluven) and Serum Albumin for Pharmacokinetic and Toxicological Implications.

The interaction of hydroxyethyl starch 130/0.4 (Voluven) with human serum albumin (HSA) has been investigated by fluorescence (steady state and synchronous), Fourier transforms infrared (FT-IR), and circular dichroism (CD) spectroscopies. Analysis of the fluorescence quenching data of HSA by Voluven using the Stern-Volmer method revealed the formation of 1:1 ground-state complex. Evaluation of binding parameters and binding energy indicated that the binding reaction was exothermic. On the basis of fluorescence measurements, it was concluded that electrostatic forces play a crucial role in stabilizing the complex. The binding distance was calculated by using Förster resonance energy transfer (FRET) theory. The conformational changes of HSA were obtained qualitatively as well as quantitatively using synchronous fluorescence, FT-IR, and CD. The HSA underwent partial unfolding in the presence of Voluven.