High-Resolution Swin Transformer for Automatic Medical Image Segmentation.

The resolution of feature maps is a critical factor for accurate medical image segmentation. Most of the existing Transformer-based networks for medical image segmentation adopt a U-Net-like architecture, which contains an encoder that converts the high-resolution input image into low-resolution feature maps using a sequence of Transformer blocks and a decoder that gradually generates high-resolution representations from low-resolution feature maps. However, the procedure of recovering high-resolution representations from low-resolution representations may harm the spatial precision of the generated segmentation masks. Unlike previous studies, in this study, we utilized the high-resolution network (HRNet) design style by replacing the convolutional layers with Transformer blocks, continuously exchanging feature map information with different resolutions generated by the Transformer blocks. The proposed Transformer-based network is named the high-resolution Swin Transformer network (HRSTNet). Extensive experiments demonstrated that the HRSTNet can achieve performance comparable with that of the state-of-the-art Transformer-based U-Net-like architecture on the 2021 Brain Tumor Segmentation dataset, the Medical Segmentation Decathlon's liver dataset, and the BTCV multi-organ segmentation dataset.

MF-Net: Automated Muscle Fiber Segmentation From Immunofluorescence Images Using a Local-Global Feature Fusion Network.

Histological assessment of skeletal muscle slices is very important for the accurate evaluation of weightless muscle atrophy. The accurate identification and segmentation of muscle fiber boundary is an important prerequisite for the evaluation of skeletal muscle fiber atrophy. However, there are many challenges to segment muscle fiber from immunofluorescence images, including the presence of low contrast in fiber boundaries in immunofluorescence images and the influence of background noise. Due to the limitations of traditional convolutional neural network-based segmentation methods in capturing global information, they cannot achieve ideal segmentation results. In this paper, we propose a muscle fiber segmentation network (MF-Net) method for effective segmentation of macaque muscle fibers in immunofluorescence images. The network adopts a dual encoder branch composed of convolutional neural networks and transformer to effectively capture local and global feature information in the immunofluorescence image, highlight foreground features, and suppress irrelevant background noise. In addition, a low-level feature decoder module is proposed to capture more global context information by combining different image scales to supplement the missing detail pixels. In this study, a comprehensive experiment was carried out on the immunofluorescence datasets of six macaques' weightlessness models and compared with the state-of-the-art deep learning model. It is proved from five segmentation indices that the proposed automatic segmentation method can be accurately and effectively applied to muscle fiber segmentation in shank immunofluorescence images.

Ligand-Controlled NiH-Catalyzed Regiodivergent Chain-Walking Hydroalkylation of Alkenes.

A NiH-catalyzed migratory hydroalkylation of alkenyl amines with predictable and switchable regioselectivity is reported. By utilizing a ligand-controlled, directing group-assisted strategy, various alkyl units are site-selectively installed at inert sp3 C-H sites far away from the original C=C bonds. A range of structurally diverse α- and ß-branched protected amines are conveniently synthesized via stabilization of 5- and 6-membered nickelacycles respectively. This method exhibits broad scope and high functional group tolerance, and can be applied to late-stage modification of medicinally relevant molecules.

Visual experience modulates whole-brain connectivity dynamics: A resting-state fMRI study using the model of radiologists.

Visual expertise refers to proficiency in visual recognition. It is attributed to accumulated visual experience in a specific domain and manifests in widespread neural activities that extend well beyond the visual cortex to multiple high-level brain areas. An extensive body of studies has centered on the neural mechanisms underlying a distinctive domain of visual expertise, while few studies elucidated how visual experience modulates resting-state whole-brain connectivity dynamics. The current study bridged this gap by modeling the subtle alterations in interregional spontaneous connectivity patterns with a group of superior radiological interns. Functional connectivity analysis was based on functional brain segmentation, which was derived from a data-driven clustering approach to discriminate subtle changes in connectivity dynamics. Our results showed there was radiographic visual experience accompanied with integration within brain circuits supporting visual processing and decision making, integration across brain circuits supporting high-order functions, and segregation between high-order and low-order brain functions. Also, most of these alterations were significantly correlated with individual nodule identification performance. Our results implied that visual expertise is a controlled, interactive process that develops from reciprocal interactions between the visual system and multiple top-down factors, including semantic knowledge, top-down attentional control, and task relevance, which may enhance participants' local brain functional integration to promote their acquisition of specific visual information and modulate the activity of some regions for lower-order visual feature processing to filter out nonrelevant visual details. The current findings may provide new ideas for understanding the central mechanism underlying the formation of visual expertise.

The invasion depth measurement of bladder cancer using T2-weighted magnetic resonance imaging.

BACKGROUND: Invasion depth is an important index for staging and clinical treatment strategy of bladder cancer (BCa). The aim of this study was to investigate the feasibility of segmenting the BCa region from bladder wall region on MRI, and quantitatively measuring the invasion depth of the tumor mass in bladder lumen for further clinical decision-making. This retrospective study involved 20 eligible patients with postoperatively pathologically confirmed BCa. It was conducted in the following steps: (1) a total of 1159 features were extracted from each voxel of both the certain cancerous and wall tissues with the T2-weighted (T2W) MRI data; (2) the support vector machine (SVM)-based recursive feature elimination (RFE) method was implemented to first select an optimal feature subset, and then develop the classification model for the precise separation of the cancerous regions; (3) after excluding the cancerous region from the bladder wall, the three-dimensional bladder wall thickness (BWT) was calculated using Laplacian method, and the invasion depth of BCa was eventually defined by the subtraction of the mean BWT excluding the cancerous region and the minimum BWT of the cancerous region. RESULTS: The segmented results showed a promising accuracy, with the mean Dice similarity coefficient of 0.921. The "soft boundary" defined by the voxels with the probabilities between 0.1 and 0.9 could demonstrate the overlapped region of cancerous and wall tissues. The invasion depth calculated from proposed segmentation method was compared with that from manual segmentation, with a mean difference of 0.277 mm. CONCLUSION: The proposed strategy could accurately segment the BCa region, and, as the first attempt, realize the quantitative measurement of BCa invasion depth.

A photo-triggered conjugation approach for attaching RGD ligands to biodegradable mesoporous silica nanoparticles for the tumor fluorescent imaging.

Fluorescent probes conjugated to peptide or antibody directing groups, which exhibit high signal to background ratios, have been widely used to image tumors and monitor their growth. A photo-triggered cycloaddition reaction between the arginine-glycine-aspartic acid -N-ɛ-acryllysine (RGD-Acrk) peptides and the tetrazole compounds bound to the surface of biodegradable mesoporous silica nanoparticles (bMSN) has been used to construct a fluorescent nanoprobe (bMSN@T2-RGD-Acrk), which showed fluorescent emission at 550 nm and could selectively image the 4T1 cells and breast cancer. This means that the bMSN@T2-RGD-Acrk nanoprobe made by photo-triggered conjugation approach is a promising fluorescent imaging agent for visualizing tumors. Thus, the photo-triggered one-spot reaction can give a stable crosslinker in a biocompatible manner for bioconjugation with nanoparticles and produce a fluorescent group that is suitable for imaging in vivo.

In vivo near infrared fluorescence imaging and dynamic quantification of pancreatic metastatic tumors using folic acid conjugated biodegradable mesoporous silica nanoparticles.

Cancer metastasis is one of the biggest challenges in cancer treatments since it increases the likelihood that a patient will die from the disease. Therefore, the availability of techniques for the early detection and quantification of tumors is very important. We have prepared cyanine 7.5 NHS ester (Cy7.5) and folic acid (FA) conjugated biodegradable mesoporous silica nanoparticles (bMSN@Cy7.5-FA NPs) (~100 nm) for visualizing tumors in vivo. The fluorescence spectra revealed that the emission peak of bMSN@Cy7.5-FA NPs had a red-shift of 1 nm. Confocal immunofluorescent images showed that bMSN@Cy7.5-FA NPs had an excellent targeting ability for visualizing cancer cells. In vivo fluorescence imaging has been conducted using an orthotopic model for pancreatic cancer within 48 h, and the fluorescence intensity reached a maximum at a post injection time-point of 12 h, which demonstrated that the use of bMSN@Cy7.5-FA NPs provides an excellent imaging platform for tumor precision therapy in mice.

3D Fusion Framework for Infarction and Angiogenesis Analysis in a Myocardial Infarct Minipig Model.

The combination of different modality images can provide detailed and comprehensive information for the prognostic assessment and therapeutic strategy of patients with ischemic heart disease. In this study, a 3D fusion framework is designed to integrate coronary computed tomography (CT) angiography (CTA), 2-deoxy-2-[18F]fluoro-D-glucose ([18F]DG) positron emission tomography (PET)/CT, and [68Ga]-1,4,7-triazacyclononane-1,4,7-triacetic acid-(Arg-Gly-Asp)2 ([68Ga]-NOTA-PRGD2) PET/CT images of the myocardial infarction model in minipigs. First, the structural anatomy of the heart in coronary CTA and CT is segmented using a multi-atlas-based method. Then, the hearts are registered using the B-spline-based free form deformation. Finally, the [18F]DG and [68Ga]-NOTA-PRGD2 signals are mapped into the heart in coronary CTA, which produces a single fusion image to delineate both the cardiac structural anatomy and the functional information of myocardial viability and angiogenesis. Heart segmentation demonstrates high accuracy with good agreement between manual delineation and automatic segmentation. The fusion result intuitively reflects the extent of the [18F]DG uptake defect as well as the location where the [68Ga]-NOTA-PRGD2 signal appears. The fusion result verified the occurrence of angiogenesis based on the in vivo noninvasive molecular imaging approach. The presented framework is helpful in facilitating the study of the relationship between infarct territories and blocked coronary arteries as well as angiogenesis.

A cyclic HSV1-TK reporter for real-time PET imaging of apoptosis.

The coordination of cell proliferation and programmed death (apoptosis) is essential for normal physiology, and imbalance in these two opposing processes is implicated in various diseases. Objective and quantitative noninvasive imaging of apoptosis would significantly facilitate rapid screening as well as validation of therapeutic chemicals. Herein, we molecularly engineered an apoptosis switch-on PET-based cyclic herpes simplex virus type 1-thymidine kinase reporter (cTK266) containing a caspase-3 recognition domain as the switch. Translation of the reporter and protein splicing in healthy mammalian cells produce an inactive cyclic chimera. Upon apoptosis, caspase-3-specific cleavage of the circular product occurs, resulting in the restoration of the thymidine kinase activity, which can be detected in living cells and animals by noninvasive PET imaging. Our results showed the high sensitivity of this reporter in dynamic and quantitative imaging of apoptosis in living subjects. This reporter could be applied as a valuable tool for high-throughput functional screening of proapoptotic and antiapoptotic compounds in preclinical models in drug development, and monitoring the destination of therapeutic cells in clinical settings.

In Vivo Dual-Modality Fluorescence and Magnetic Resonance Imaging-Guided Lymph Node Mapping with Good Biocompatibility Manganese Oxide Nanoparticles.

Multifunctional manganese oxide nanoparticles (NPs) with impressive enhanced T1 contrast ability show great promise in biomedical diagnosis. Herein, we developed a dual-modality imaging agent system based on polyethylene glycol (PEG)-coated manganese oxide NPs conjugated with organic dye (Cy7.5), which functions as a fluorescence imaging (FI) agent as well as a magnetic resonance imaging (MRI) imaging agent. The formed Mn3O4@PEG-Cy7.5 NPs with the size of ~10 nm exhibit good colloidal stability in different physiological media. Serial FI and MRI studies that non-invasively assessed the bio-distribution pattern and the feasibility for in vivo dual-modality imaging-guided lymph node mapping have been investigated. In addition, histological and biochemical analyses exhibited low toxicity even at a dose of 20 mg/kg in vivo. Since Mn3O4@PEG-Cy7.5 NPs exhibited desirable properties as imaging agents and good biocompatibility, this work offers a robust, safe, and accurate diagnostic platform based on manganese oxide NPs for tumor metastasis diagnosis.

Intrinsically Zirconium-89 Labeled Gd2 O2 S:Eu Nanoprobes for In Vivo Positron Emission Tomography and Gamma-Ray-Induced Radioluminescence Imaging.

The engineering of a novel dual-modality imaging probe is reported here by intrinsically labeling zirconium-89 ((89) Zr, a positron emission radioisotope with a half-life of 78.4 h) to PEGylated Gd2 O2 S:Eu nanophorphors, forming [(89) Zr]Gd2 O2 S:Eu@PEG for in vivo positron emission tomography/radioluminescence lymph node mapping.

Determining scientific impact using a collaboration index.

Researchers collaborate on scientific projects that are often measured by both the quantity and the quality of the resultant peer-reviewed publications. However, not all collaborators contribute to these publications equally, making metrics such as the total number of publications and the H-index insufficient measurements of individual scientific impact. To remedy this, we use an axiomatic approach to assign relative credits to the coauthors of a given paper, referred to as the A-index for its axiomatic foundation. In this paper, we use the A-index to compute the weighted sums of peer-reviewed publications and journal impact factors, denoted as the C- and P-indexes for collaboration and productivity, respectively. We perform an in-depth analysis of bibliometric data for 186 biomedical engineering faculty members and from extensive simulation. It is found that these axiomatically weighted indexes better capture a researcher's scientific caliber than do the total number of publications and the H-index, allowing for fairer and sharper evaluation of researchers with diverse collaborative behaviors.

Feasibility study of novel endoscopic Cerenkov luminescence imaging system in detecting and quantifying gastrointestinal disease: first human results.

OBJECTIVES: Cerenkov luminescence imaging (CLI) provides potential to use clinical radiotracers for optical imaging. The goal of this study was to present a newly developed endoscopic CLI (ECLI) system and illustrate its feasibility and potential in distinguishing and quantifying cancerous lesions of the GI tract. METHODS: The ECLI system was established by integrating an electron-multiplying charge-coupled device camera with a flexible fibre endoscope. Phantom experiments and animal studies were conducted to test and illustrate the system in detecting and quantifying the presence of radionuclide in vitro and in vivo. A pilot clinical study was performed to evaluate our system in clinical settings. RESULTS: Phantom and mice experiments demonstrated its ability to acquire both the luminescent and photographic images with high accuracy. Linear quantitative relationships were also obtained when comparing the ECLI radiance with the radiotracer activity (r (2) = 0.9779) and traditional CLI values (r (2) = 0.9025). Imaging of patients revealed the potential of ECLI in the identification and quantification of cancerous tissue from normal, which showed good consistence with the clinical PET examination. CONCLUSIONS: The new ECLI system shows good consistence with the clinical PET examination and has great potential for clinical translation and in aiding detection of the GI tract disease. KEY POINTS: • CLI preserves the characteristics of both optical and radionuclide imaging. • CLI provides great potential for clinical translation of optical imaging. • The newly developed endoscopic CLI (ECLI) has quantification and imaging capacities. • GI tract has accessible open surfaces, making ECLI a potentially suitable technique. • Cerenkov endoscopy has great clinical potential in detecting GI disease.

Relationship Between the Parietal Cortex and Task Switching: Transcranial Direct Current Stimulation Combined with an Event-related Potential Study.

Task switching refers to a set of cognitive processes involved in shifting attention from one task to another. In recent years, researchers have applied transcranial direct current stimulation (tDCS) to investigate the causal relationship between the parietal cortex and task switching. However, results from available studies are highly inconsistent. This may be due to the unclear understanding of the underlying mechanisms. Therefore, the current study utilized event-related potential (ERP) analysis to investigate the modulatory effects of tDCS on task-switching processes. Twenty-four subjects were recruited to perform both predictable and unpredictable parity/magnitude tasks under anodal (RA) and sham conditions. The results showed no significant changes in behavioral performance. However, marked tDCS-induced ERP changes were observed. Specifically, for the predictable task switching, compared with the sham condition, the target-N2 component occurred significantly earlier for switch trials than repeat trials under the RA condition in males, while no difference was found in females. For unpredictable task switching, under the sham condition, the P2 peak was significantly larger for switch trials compared with repeat trials, whereas this difference was not observed under the RA condition. These results indicated the causal relationship between the right parietal cortex and exogenous adjustment processes involved in task switching. Moreover, anodal tDCS over the right parietal cortex may lead to the manifestation of gender differences.

Ensembled-SAMs for Enhanced Small Coronary Artery Segmentation in CCTA Images.

Accurate coronary artery segmentation is crucial for quantitative analysis of coronary arteries in noninvasive coronary computed tomography angiography (CCTA) images. However, current segmentation algorithms often have unsatisfactory recall due to the small size and complex morphology of coronary arteries, particularly in the distal segments. To address this issue, we introduce a new fully automated method named Ensembled-SAMs, which harnesses the strengths of the Segment Anything Model (SAM) and the no-new-U-Net (nnU-Net). First, noisy bounding box prompts are automatically generated by a vesselness algorithm that highlights the tubular structures in the CCTA images. These noisy prompts are then used to fine-tune the SAM and its two variants separately. The SAM variants introduce a classification head in their mask decoder to alleviate the false positives. In addition, an nnU-Net segmentation network is trained from scratch. Finally, the outputs of the SAMs and the nnU-Net are strategically aggregated to obtain the final segmentation result. Experiments on both a self-built dataset and the public Automated Segmentation of Coronary Arteries (ASOCA) challenge dataset demonstrate that the proposed Ensembled-SAMs outperforms the state-of-the-arts, achieving precise segmentation of coronary arteries, with particular enhancement in delineating small coronary artery segments.

Contrastive Disentanglement for Quantitative Ultrasound Muscle Atrophy Evaluation.

OBJECTIVE: Muscleatrophy reduces the quality of life and increases morbidity and mortality from other diseases. The development of non-invasive muscle atrophy evaluation method is of great practical value. The lack of gold standard for pathological grading usually allows only the duration of weightlessness as a criterion for the degree of atrophy. However, the adaptive reductive remodeling of muscle physiology and structure shows a trend of nonlinear changes in time. Consequently, using weightlessness time as a benchmark for the degree of atrophy is inaccurate. METHODS: This paper proposes a new ultrasound imaging-based method for quantifying muscle atrophy that utilizes weakly supervised information between multiple data partitions with controlled variance components, overcoming the limitations of using the weightlessness time as a criterion. We introduce a group-supervised contrastive disentanglement network (GCDNet) to disentangle the individual variances, muscle growth and atrophy components of ultrasound images, and quantify the degree of atrophy using the disentangled atrophy component. RESULTS: The feasibility of GCDNet is validated by the separability, independence, and representativeness of the disentangled components. To simplify the application of GCDNet, a muscle atrophy scoring network requiring no reference images is developed by distilling the GCDNet's knowledge of muscle atrophy quantization. The strength of the proposed methodology allows us, for the first time to our knowledge, to study the muscle growth attribute during hind-limb unloading and the spatial distribution of muscle atrophy.

Feasibility study of functional near-infrared spectroscopy in the ventral visual pathway for real-life applications.

Significance: fNIRS-based neuroenhancement depends on the feasible detection of hemodynamic responses in target brain regions. Using the lateral occipital complex (LOC) and the fusiform face area (FFA) in the ventral visual pathway as neurofeedback targets boosts performance in visual recognition. However, the feasibility of utilizing fNIRS to detect LOC and FFA activity in adults remains to be validated as the depth of these regions may exceed the detection limit of fNIRS. Aim: This study aims to investigate the feasibility of using fNIRS to measure hemodynamic responses in the ventral visual pathway, specifically in the LOC and FFA, in adults. Approach: We recorded the hemodynamic activities of the LOC and FFA regions in 35 subjects using a portable eight-channel fNIRS instrument. A standard one-back object and face recognition task was employed to elicit selective brain responses in the LOC and FFA regions. The placement of fNIRS optodes for LOC and FFA detection was guided by our group's transcranial brain atlas (TBA). Results: Our findings revealed selective activation of the LOC target channel (CH2) in response to objects, whereas the FFA target channel (CH7) did not exhibit selective activation in response to faces. Conclusions: Our findings indicate that, although fNIRS detection has limitations in capturing FFA activity, the LOC region emerges as a viable target for fNIRS-based detection. Furthermore, our results advocate for the adoption of the TBA-based method for setting the LOC target channel, offering a promising solution for optrode placement. This feasibility study stands as the inaugural validation of fNIRS for detecting cortical activity in the ventral visual pathway, underscoring its ecological validity. We suggest that our findings establish a pivotal technical groundwork for prospective real-life applications of fNIRS-based research.

Exploring Radiomics Features Based on H&E Images as Potential Biomarkers for Evaluating Muscle Atrophy: A Preliminary Study.

Radiomics features have been widely used as novel biomarkers in the diagnosis of various diseases, but whether radiomics features derived from hematoxylin and eosin (H&E) images can evaluate muscle atrophy has not been studied. Therefore, this study aims to establish a new biomarker based on H&E images using radiomics methods to quantitatively analyze H&E images, which is crucial for improving the accuracy of muscle atrophy assessment. Firstly, a weightless muscle atrophy model was established by laying macaques in bed, and H&E images of the shank muscle fibers of the control and bed rest (BR) macaques were collected. Muscle fibers were accurately segmented by designing a semi-supervised segmentation framework based on contrastive learning. Then, 77 radiomics features were extracted from the segmented muscle fibers, and a stable subset of features was selected through the LASSO method. Finally, the correlation between radiomics features and muscle atrophy was analyzed using a support vector machine (SVM) classifier. The semi-supervised segmentation results show that the proposed method had an average Spearman's and intra-class correlation coefficient (ICC) of 88% and 86% compared to manually extracted features, respectively. Radiomics analysis showed that the AUC of the muscle atrophy evaluation model based on H&E images was 96.87%. For individual features, GLSZM_SZE outperformed other features in terms of AUC (91.5%) and ACC (84.4%). In summary, the feature extraction based on the semi-supervised segmentation method is feasible and reliable for subsequent radiomics research. Texture features have greater advantages in evaluating muscle atrophy compared to other features. This study provides important biomarkers for accurate diagnosis of muscle atrophy.

Cerenkov luminescence tomography of aminopeptidase N (APN/CD13) expression in mice bearing HT1080 tumors.

In vivo imaging of aminopeptidase N (APN/CD13) expression is crucial for the early detection of cancer. This study attempted to show that APN/CD13 expression can be imaged and quantified with novel Cerenkov luminescence tomography (CLT). Na131I with various activities was placed at different depths in a tissue-mimicking phantom, and various porcine tissues and luminescent images were acquired. The binding of 131I-NGR with human fibrosarcoma HT1080 and human colon cancer HT-29 cells was detected with Cerenkov luminescence imaging (CLI). Nude mice bearing HT-1080 tumors were imaged after injection with 131I-NGR using both planar and tomographic CLI methods. The penetration depth increased with ascending activity of Na131I. There was a robust linear correlation between the optical signal intensity and the HT1080 cell numbers (r2 = .9691), as well as the activity (r2 = .9860). The three-dimensional visualization CLT results clearly showed that 131I-NGR uptake in tumor tissues represented a high expression of the APN/CD13 receptor. CLT also allowed quantifying 131I-NGR uptake in tumor tissues showing an average activity of 0.1388 ± 4.6788E-6 MBq in tumor tissues. Our study indicated that 131I-NGR combined with CLT allowed us to image and quantify tumor-associated APN/CD13 expression noninvasively. The promising CLT technique could be potentially used for sensitively evaluating tumor angiogenesis in vivo.

Molecular imaging of p53 signal pathway in lung cancer cell cycle arrest induced by cisplatin.

Cisplatin is a commonly employed chemotherapy drug for lung malignancy. However its efficacy is limited by acquired drug resistance and lacking of an in vivo real-time monitoring approach. The aim of this study is to investigate the effect of cisplatin on lung adenocarcinoma cell line p53-RE-Fluc/A549 in vivo via non-invasive reporter gene by molecular imaging. For this study, we employed p53-RE-Fluc/A549 cells that overexpressed a vector with three tandem repeats of p53 response element followed by the luciferase reporter gene. P53 activity was evaluated by optical imaging and verified by Western blot after cells were exposed to 10 µM cisplatin for 72 h. The cell cycle was mainly blocked at the S- and G2/M-phases after cisplatin treatment, whereas no significant change was observed in cell apoptotic index. Increased expression of p21 and Bcl-2 as well as decreased expression of Bax were observed after cisplatin treatment by Western blotting. Longitudinal in vivo bioluminescent imaging (BLI) revealed that the p53 activity was increased from 24 to 48 h after transient cisplatin treatment in p53-RE-Fluc/A549-bearing nude mice. RNA sequencing further revealed that cell cycle and p53 signaling pathway genes, such as E2F1, CCNA2, CDK1, and CCNE2 were significantly downregulated after long-term cisplatin treatment. Thus, our study showed that cisplatin exerts its cytotoxic effect through blockage of the cell cycle and may be partly regulated by the p53 signaling pathway. Furthermore, molecular imaging is a useful tool to investigate the mechanism and evaluate the effect of chemotherapy drugs both in vivo and in vitro.