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• A generalized method for effective early diagnosis of pancreatic cancer based on multiple instance learning. • A spatial transformation based on anatomical structures is proposed to reduce the background interference and enhance the detection stability for the learned features. • Instance-level contrastive learning is developed to aggregate different types of tumor features, maintain the tumor feature integrity, and enhance the diagnosis stability. • The method achieves remarkable generalization performance in unseen datasets and is sensitive to tumors smaller than 2 cm in diameter. Pancreatic cancer is a highly malignant cancer type with a high mortality rate. As no obvious symptoms are associated with this cancer type, most of the diagnoses are made when the patients are already in a late stage. In this work, we propose an automated method for effective early diagnosis of pancreatic cancer based on multiple instance learning with contrast-enhanced CT images. In this method, diagnosis stability and generalizability were improved through shape normalization based on anatomical structures as well as instance-level contrastive learning. Specifically, anatomically-guided shape normalization were developed to reconstruct the pancreatic regions of interest by spatial transformations, account for larger tumor parts in these regions, and hence enhance the extraction of pancreatic features. Moreover, instance-level contrastive learning was employed to aggregate different types of tumor features within the multiple instance learning framework. This learning approach can maintain the tumor feature integrity and enhance the diagnosis stability. Finally, a balance-adjustment strategy was designed to alleviate the class imbalance problem caused by the scarcity of tumor samples. Extensive experimental results demonstrated remarkable performance of our method when conducted cross-validation on an in-house dataset with 310 patients and independent test on two unseen datasets (a private test set with 316 and a publicly-available test set with 281). The proposed strategies also led to significant improvements in generalizability. Besides, the clinical significance of the proposed method was further verified through two independent test results in which tumors smaller than 2 cm in diameter were identified at accuracies of 80.9% and 90.1%, respectively. Overall, our method provides a potentially successful tool for early diagnosis of pancreatic cancer. Our source codes will be released at https://github.com/SJTUBME-QianLab/MIL_PAdiagnosis. [Display omitted] [ABSTRACT FROM AUTHOR]

• A causal intervention based automated method for generalized pancreatic cancer diagnosis. • A continuous image generation strategy and a pancreatic feature diversification method are proposed to simulate appearance potential variations on limited dataset and enrich the feature diversity. • A causal intervention strategy is developed for alleviating spurious correlations caused by appearance changes, enhance causal feature extraction, thereby solving the challenges of generalization. • Extensive experiments conducted on a multi-center dataset with more than 1000 subjects showed that the proposed method achieves remarkable generalization performance. Pancreatic cancer (PC) is a severely malignant cancer variant with high mortality. Since PC has no obvious symptoms, most PC patients are belatedly diagnosed at advanced disease stages. Recently, artificial intelligence (AI) approaches have demonstrated promising prospects for early diagnosis of pancreatic cancer. However, certain non-causal factors (such as intensity and texture appearance variations, also called confounders) tend to induce spurious correlation with PC diagnosis. This undermines the generalization performance and the clinical applicability of the AI-based PC diagnosis approaches. Therefore, we propose a causal intervention based automated method for pancreatic cancer diagnosis with contrast-enhanced computerized tomography (CT) images, where a confounding effects reduction scheme is developed for alleviating spurious correlations to achieve unbiased learning, thereby improving the generalization performance. Specifically, a continuous image generation strategy was developed to simulate wide variations of intensity differences caused by imaging heterogeneities, where Monte Carlo sampling is added to further enhance the continuity of simulated images. Then, to enhance the pancreatic texture variability, a texture diversification method was introduced in conjunction with gradient-based data augmentation. Finally, a causal intervention strategy was proposed to alleviate the adverse confounding effects by decoupling the causal and non-causal factors and combining them randomly. Extensive experiments showed remarkable diagnosis performance on a cross-validation dataset. Also, promising generalization performance with an average accuracy of 0.87 was attained on three independent test sets of a total of 782 subjects. Therefore, the proposed method shows high clinical feasibility and applicability for pancreatic cancer diagnosis. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: To develop an apparatus for simultaneous monitoring of heart and respiratory rates using photoplethysmography (PPG) and Fast Fourier Transform algorithm (FFT), the PPG waveform was measured at the radial artery with an original based on diffuse reflectance mode photoplethysmographic device. An FFT algorithm was used to extract heart and respiratory information from the PPG waveform. The results good agree with conventional method. The correlation coefficient of heart rate and respiratory rate obtained using PPG waveform and conventional method is 0.988 and 0.976, respectively. The PPG waveform and FFT algorithm can contribute to quicker and more accurate measurement of human heart rate and respiration rate. A portable watch-like device can be made via this method and be utilized to monitor heart and respiratory rates in hospitals or daily life care. [Copyright &y& Elsevier]

The elaboration of nanotechnology offers valuable therapeutic options to overcome the blood-brain barrier and enable the treatment of brain diseases. However, to date, limit work has been done to reveal the fate of nanoparticles within the brain, which largely hinders their safe and effective applications. Here we demonstrated that the commonly-used organic nanoparticles reconstituted high density lipoprotein and poly(ethylene glycol)-b-poly(lactic acid) nanoparticles were cleared relatively fast from the brain (half-life <5 h). Notably, through various transgenic mice and pharmacological inhibition approaches, we revealed that the paravascular glymphatic pathway plays a key role (about 80%) in the brain clearance of the nanoparticles, and disclosed that microglia-mediated transportation is essential for facilitating nanoparticles elimination through the paravascular route. In addition, we witnessed a significant decline in the brain clearance of both of the nanoparticles in Alzheimer's model mice where the glymphatic system is impaired. These findings provide insightful data on the fate of nanoparticles in the brain, which would shed new light into the rational design and safe application of nanoparticles for brain drug delivery. The rHDL and PEG-PLA nanoparticles in the brain are majorly transported through microglia to the paravascular glymphatic pathway, the major route for their brain elimination. Unlabelled Image • rHDL and PEG-PLA nanoparticles were cleared relatively fast from the brain. • Paravascular glymphatic pathway is the major route for brain elimination of the nanoparticles. • Microglia facilitates nanoparticles transport to the paravascular route. • Brain clearance of the nanoparticles was significantly declined under Alzheimer condition. [ABSTRACT FROM AUTHOR]

Nanoparticles have been widely used in biomedical research as drug carriers or imaging agents for living animals. Blood circulation is crucial for the delivery of nanoparticles, which enter the bloodstream through injection, inhalation, or dermal exposure. However, the clearance kinetics of nanoparticles in blood circulation has been poorly studied, mainly because of the limitations of conventional detection methods, such as insufficient blood sample volumes or low spatial-temporal resolution. In addition, formation of nanoparticle aggregates is a key determinant for biocompatibility and drug delivery efficiency. Aggregation behavior of nanoparticles in blood is studied using dynamic light scattering in serum or serum protein solutions, which is still very different from in vivo condition. In this work, we monitored the dynamics of nanoparticle concentration and formation of nanoparticle aggregates in the bloodstream in live animals using in vivo flow cytometry (IVFC). The results indicated that nanoparticles in smaller size could stay longer in the bloodstream. Polyethylene glycol (PEG)-modification could prolong circulating time and reduce the formation of aggregates in the blood circulation. Our work shows that IVFC can be a powerful tool for pharmacokinetic studies of nanoparticles and other drug carriers, assessing cell-targeting efficiency, as well as potentially measuring cardiac output and hepatic function in vivo . [ABSTRACT FROM AUTHOR]

Antiangiogenesis therapy has been served as a potent cancer treatment strategy for decades, yet disrupting neovasculature would provoke tumor cells into invasive growth and result in distal metastasis. The basic cause of cancer metastasis can be traced down to the presence of circulating tumor cells (CTCs) which detach from primary tumor site and act as ‘seeds’. Epithelial cell adhesion molecule (EpCAM) is a potential biomarker for selective capture of epithelium-derived CTCs. Here, we integrated tumor neovessles-targetable ligands K237 peptide with Ep23 aptamer against EpCAM into a single drug-loaded nanoplatform using paclitaxel (PTX) as the model drug, aiming at damaging the primary tumor and neutralizing CTCs simultaneously to achieve a synergistic anti-tumor therapeutic effect. Enhanced cellular uptake, cell apoptosis-induction and cell-viability inhibition efficiency of the peptide and aptamer dual-functionalized nanoparticles (dTNP) were observed in both human umbilical vein endothelial cells (HUVEC) and 4T1 cells in vitro . Using cone-and-plate viscometer to create venous flow velocity, dTNP was also found to be able to capture CTCs under shear stress. The CTC-targeting and neutralization effect of dTNP in bloodstream and 4T1-GFP cell-derived lung metastasis mice model was confirmed via in vivo flow cytometry (IVFC), intravital imaging and confocal microscopy analysis. As a result, the orthotropic breast tumor-bearing mice administrated with PTX-loaded dTNP exhibited the optimal therapeutic effect. Taken together, the findings here provided direct evidence that the tumor neovasculature and CTCs dual-targeting drug delivery system could provide a novel modality for the treatment of highly-invasive breast cancer. [ABSTRACT FROM AUTHOR]

NADH shuttles, including malate-aspartate shuttle (MAS) and glycerol-3-phosphate shuttle, can shuttle the reducing equivalents of cytosolic NADH into mitochondria. It is widely accepted that the major function of NADH shuttles is to increase mitochondrial energy production. Our study tested the hypothesis that the novel major function of NADH shuttles in cancer cells is to maintain glycolysis by decreasing cytosolic NADH/NAD(+) ratios. We found that AOAA, a widely used MAS inhibitor, led to decreased intracellular ATP levels, altered cell cycle and increased apoptosis and necrosis of C6 glioma cells, without affecting the survival of primary astrocyte cultures. AOAA also decreased the glycolytic rate and the levels of extracellular lactate and pyruvate, without affecting the mitochondrial membrane potential of C6 cells. Moreover, the toxic effects of AOAA were completely prevented by pyruvate treatment. Collectively, our study has suggested that AOAA may be used to selectively decrease glioma cell survival, and the major function of MAS in cancer cells may be profoundly different from its major function in normal cells: The major function of MAS in cancer cells is to maintain glycolysis, instead of increasing mitochondrial energy metabolism. [ABSTRACT FROM AUTHOR]

Highlights: [•] NAD+ treatment can decrease rotenone-induced early-stage and late-stage apoptosis of PC12 cells. [•] NAD+ treatment can decrease rotenone-induced necrosis of PC12 cells. [•] NAD+ treatment can restore the intracellular NAD+ levels of rotenone-treated PC12 cells. [•] NAD+ treatment can prevent rotenone-induced mitochondrial depolarization of PC12 cells. [Copyright &y& Elsevier]

Highlights: [•] The SIRT2 inhibitor AGK2 can induce both late-stage apoptosis and necrosis of microglial BV2 cells. [•] The SIRT2 inhibitor AGK2 can induce a decrease in the intracellular ATP levels of microglial BV2 cells. [•] Poly(ADP-ribose) polymerase activation mediates both the cell death and the ATP decline of AGK2-treated microglial BV2 cells. [ABSTRACT FROM AUTHOR]

Abstract: We report, for the first time to our knowledge, on the application of a micro-optical lens fabricated by three-dimensional (3D) femtosecond laser direct writing for two-photon fluorescence imaging of biological tissues. We show that the two-photon fluorescence images of a plant leaf tissue acquired with the micro-optical lens are comparable to that of a 5× objective lens. Our result represents an important step towards the application of micro-optical components fabricated by femtosecond laser micromachining in miniaturized nonlinear fluorescence microscopy applications, such as two-photon endoscopy. [Copyright &y& Elsevier]

Abstract: Confocal fluorescence imaging and fluorescence resonance energy transfer (FRET) technology have been widely used to study protein–protein interactions in living cells. However, it is very difficult to quantitatively analyze FRET efficiency due to the excitation spectral crosstalk and emission spectral crosstalk between donor and acceptor. In this study, we developed a novel method to quantitatively obtain the FRET efficiency by fitting the emission spectra (FES) of donor–acceptor pair, and this method is free from both excitation and emission spectral crosstalk. We used the FES method to quantitatively monitor the FRET efficiency of SCAT3, a caspase-3 indicator based on FRET, inside living cells stably expressing SCAT3 during STS-induced apoptosis. At 0, 6 and 12h after STS treatment, the FRET efficiency of SCAT3 obtained by FES are consistent with that by two-photon excitation (TPE) fluorescence lifetime imaging microscopy (FLIM) in living cells stably expressing SCAT3. In this study, the FES was also used to analyze the caspase-3 activation in living cells during anti-cancer drug such as taxol, Artesunate (ART) or Dihydroartemisinin (DHA) treatment. Our results showed that ART or DHA induced apoptosis by a caspase-3-dependent manner, while caspase-3 was not involved in taxol-induced cell death. [Copyright &y& Elsevier]

Cancer severely threatens human health currently, promoting the rapid development of cancer treatment strategies. In addition to cancer therapy, assessment of cancer prognosis, which can evaluate the success with treatment and chances of recovery as well as assist to make subsequent therapeutic schedule, is also remarkably indispensable and important. Conventional technologies can't provide rapid and highly-sensitive assessment of cancer prognosis at cytological level. Herein, an effective nitrogen doped carbon dots with intrinsic nucleolus-targeting capability and high fluorescence quantum yield are synthesized, characterized and employed for fluorescence imaging of nucleolus, which is closely related to the biological alteration of cancer cell. The cancer prognosis thus can be accurately (limit of detection: 50 nM) and rapidly (5 min) assessed at subcellular organelle level from nucleolar characteristics, which are visualized and analyzed by the captured fluorescence images. Outstanding assessment performance endows the proposed technology with great potential for future clinical research. [Display omitted] • Nitrogen doped carbon dots are synthesized for fluorescence imaging of nucleolus related to the biological alteration of cancer cell. • The cancer prognosis can be assessed at subcellular organelle level, which is not achievable using conventional technologies. • The proposed assessment method for cancer prognosis shows faster and more sensitive features as compared with AgNOR method. [ABSTRACT FROM AUTHOR]