USP39 Promotes the Viability and Migration of Head and Neck Squamous Cell Carcinoma Cell by Regulating STAT1.

Objective: Ubiquitin-specific peptidase 39 (USP39) plays a carcinogenic role in many cancers, but little research has been conducted examining whether it is involved in head and neck squamous cell carcinoma (HNSCC). Therefore, this study explored the functional role of USP39 in HNSCC. Method: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify differentially expressed proteins (DEPs) between the HNSCC tumor and adjacent healthy tissues. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to assess the functional enrichment of DEPs. Immunohistochemistry was used to detect protein expression. The viability and migration of two HNSCC cell lines, namely CAL27 and SCC25, were detected using the cell counting kit-8 assay and a wound healing assay, respectively. Quantitative real-time PCR was used to detect the expression level of signal transducer and activator of transcription 1 (STAT1) mRNA. Results: LC-MS/MS results identified 590 DEPs between HNSCC and adjacent tissues collected from 4 patients. Through GO and KEGG pathway analyses, 34 different proteins were found to be enriched in the spliceosome pathway. The expression levels of USP39 and STAT1 were significantly higher in HNSCC tumor tissue than in adjacent healthy tissue as assessed by LC-MS/MS analysis, and the increased expression of USP39 and STAT1 protein was confirmed by immunohistochemistry in clinical samples collected from 7 additional patients with HNSCC. Knockdown of USP39 or STAT1 inhibited the viability and migration of CAL27 and SCC25 cells. In addition, USP39 knockdown inhibited the expression of STAT1 mRNA in these cells. Conclusion: Our findings indicated that USP39 knockdown may inhibit HNSCC viability and migration by suppressing STAT1 expression. The results of this study suggest that USP39 may be a potential new target for HNSCC clinical therapy or a new biomarker for HNSCC.

A review of deep learning-based multiple-lesion recognition from medical images: classification, detection and segmentation.

Deep learning-based methods have become the dominant methodology in medical image processing with the advancement of deep learning in natural image classification, detection, and segmentation. Deep learning-based approaches have proven to be quite effective in single lesion recognition and segmentation. Multiple-lesion recognition is more difficult than single-lesion recognition due to the little variation between lesions or the too wide range of lesions involved. Several studies have recently explored deep learning-based algorithms to solve the multiple-lesion recognition challenge. This paper includes an in-depth overview and analysis of deep learning-based methods for multiple-lesion recognition developed in recent years, including multiple-lesion recognition in diverse body areas and recognition of whole-body multiple diseases. We discuss the challenges that still persist in the multiple-lesion recognition tasks by critically assessing these efforts. Finally, we outline existing problems and potential future research areas, with the hope that this review will help researchers in developing future approaches that will drive additional advances.

Transition to chaos of thermocapillary convection.

Thermocapillary convection is a common flow in space. Experiments regarding thermocapillary convection were previously carried out in a large-scale liquid bridge with a diameter of 20 mm on the Tiangong-2 space station, and the transition process to chaos was systematically studied. Under microgravity conditions, gravity is greatly weakened, and the transition process of the flow is very slow. This allows for the opportunity to study the bifurcation process in detail. It has been found that there are abundant nonlinear physical phenomena associated with the changing geometric parameters in thermocapillary convection systems. The transition mechanisms interact with each other, leading to various transition routes. The phase space trajectories, the Lyapunov exponents, and correlation dimensions are calculated to distinguish the chaotic state under a variety of conditions. Through the chaotic dynamics analysis, the chaotic characteristics of the entire transition process are quantitatively discussed.

Flexible needle puncture path planning for liver tumors based on deep reinforcement learning.

Objective.Minimally invasive surgery has been widely adopted in the treatment of patients with liver tumors. In liver tumor puncture surgery, an image-guided ablation needle for puncture surgery, which first reaches a target tumor along a predetermined path, and then ablates the tumor or injects drugs near the tumor, is often used to reduce patient trauma, improving the safety of surgery operations and avoiding possible damage to large blood vessels and key organs. In this paper, a path planning method for computer tomography (CT) guided ablation needle in liver tumor puncture surgery is proposed.Approach.Given a CT volume containing abdominal organs, we first classify voxels and optimize the number of voxels to reduce volume rendering pressure, then we reconstruct a multi-scale 3D model of the liver and hepatic vessels. Secondly, multiple entry points of the surgical path are selected based on the strong and weak constraints of clinical puncture surgery through multi-agent reinforcement learning. We select the optimal needle entry point based on the length measurement. Then, through the incremental training of the double deep Q-learning network (DDQN), the transmission of network parameters from the small-scale environment to the larger-scale environment is accomplished, and the optimal surgical path with more optimized details is obtained.Main results.To avoid falling into local optimum in network training, improve both the convergence speed and performance of the network, and maximize the cumulative reward, we train the path planning network on different scales 3D reconstructed organ models, and validate our method on tumor samples from public datasets. The scores of human surgeons verified the clinical relevance of the proposed method.Significance.Our method can robustly provide the optimal puncture path of flexible needle for liver tumors, which is expected to provide a reference for surgeons' preoperative planning.

Strong-Induced CPL Emission Promoted from Achiral Conjugated Polymer-Containing Emissive Nematic Liquid Crystals (P-N*-LCs).

With the rapid development on 3D printing technology, more and more works have been devoted to 3D display. 3D display will really come true by using circularly polarized luminescence (CPL)-active materials with both high quantum yield and dissymmetry factor (gem ) in organic light-emitting diode or liquid crystals (LCs). But so far most of these CPL materials cannot meet the real application requirement because of the low gem values in the range of 10-5 -10-2 . In this paper, ternary chiral emissive LCs (P-N*-LCs) is designed by doping chiral binaphthyl-based enantiomers as chiral dopant (Guest 1) and achiral conjugated polymer as induced CPL emitter (Guest 2) into nematic liquid crystal (N-LCs) Host 5CB. Both Guest 1 and Guest 2 show excellent compatibility with Host 5CB. The obtained ternary P-N*-LCs can emit strong-induced CPL signal with gem up to 1.12 and ФFL up to 66.1%. This work first develops a new strategy for the smart design of excellent CPL materials from versatile achiral conjugation fluorescence polymers.

Prognosis of Diabetic Peripheral Neuropathy via Decomposed Digital Volume Pulse from the Fingertip.

Diabetic peripheral neuropathy (DPN) is a very common neurological disorder in diabetic patients. This study presents a new percussion-based index for predicting DPN by decomposing digital volume pulse (DVP) signals from the fingertip. In this study, 130 subjects (50 individuals 44 to 89 years of age without diabetes and 80 patients 37 to 86 years of age with type 2 diabetes) were enrolled. After baseline measurement and blood tests, 25 diabetic patients developed DPN within the following five years. After removing high-frequency noise in the original DVP signals, the decomposed DVP signals were used for percussion entropy index (PEIDVP) computation. Effects of risk factors on the incidence of DPN in diabetic patients within five years of follow-up were tested using binary logistic regression analysis, controlling for age, waist circumference, low-density lipoprotein cholesterol, and the new index. Multivariate analysis showed that patients who did not develop DPN in the five-year period had higher PEIDVP values than those with DPN, as determined by logistic regression model (PEIDVP: odds ratio 0.913, 95% CI 0.850 to 0.980). This study shows that PEIDVP can be a major protective factor in relation to the studied binary outcome (i.e., DPN or not in diabetic patients five years after baseline measurement).

Percussion Entropy Analysis of Synchronized ECG and PPG Signals as a Prognostic Indicator for Future Peripheral Neuropathy in Type 2 Diabetic Subjects.

Diabetic peripheral neuropathy (DPN) is one of the most common chronic complications of diabetes. It has become an essential public health crisis, especially for care in the home. Synchronized electrocardiogram (ECG) and photoplethysmography (PPG) signals were obtained from healthy non-diabetic (n = 37) and diabetic (n = 85) subjects without peripheral neuropathy, recruited from the diabetic outpatient clinic. The conventional parameters, including low-/high-frequency power ratio (LHR), small-scale multiscale entropy index (MEISS), large-scale multiscale entropy index (MEILS), electrocardiogram-based pulse wave velocity (PWVmean), and percussion entropy index (PEI), were computed as baseline and were then followed for six years after the initial PEI measurement. Three new diabetic subgroups with different PEI values were identified for the goodness-of-fit test and Cox proportional Hazards model for relative risks analysis. Finally, Cox regression analysis showed that the PEI value was significantly and independently associated with the risk of developing DPN after adjustment for some traditional risk factors for diabetes (relative risks = 4.77, 95% confidence interval = 1.87 to 6.31, p = 0.015). These findings suggest that the PEI is an important risk parameter for new-onset DPN as a result of a chronic complication of diabetes and, thus, a smaller PEI value can provide valid information that may help identify type 2 diabetic patients at a greater risk of future DPN.

Circularly Polarized Electroluminescence of Thermally Activated Delayed Fluorescence-Active Chiral Binaphthyl-Based Luminogens.

Two pairs of thermally activated delayed fluorescence (TADF)-active chiral luminogens (R/S-1 and R/S-2) can be achieved by introducing D-A-type groups to chiral BINOL skeletons. The resulting chiral luminogens can exhibit aggregation-induced emission properties in THF-water mixtures and TADF emission in a doped-film state. The absolute photoluminescence quantum yield (ΦPL) and delayed fluorescence lifetimes (τdelayed) were measured to be 18.5% and 1.03 µs for R-1 and 15.7% and 0.97 µs for R-2. However, only R/S-1 with the fixed conjugation structure can emit circularly polarized luminescence signals, and glum can reach 1.6 × 10-3 in toluene solution and 9.2 × 10-4 in the neat film. Most importantly, R/S-1 was chosen as the emitting layers for orange-red circularly polarized organic light-emitting diodes, which can display low turn-on voltage (Von) of 3.4 V, high maximum brightness (Lmax) up to 40 470 cd m-2, moderate external quantum efficiency of 4.1%, as well as circularly polarized electroluminescence signal with gEL = -0.9 × 10-3/+1.0 × 10-3.

Strong CPL of achiral AIE-active dyes induced by supramolecular self-assembly in chiral nematic liquid crystals (AIE-N*-LCs).

Chiral binaphthyl enantiomers (Guest 1) were doped into commercial nematic liquid crystals (N-LCs, Host E7) to form chiral nematic liquid crystals (N*-LCs). The new ternary AIE-N*-LCs prepared by introducing four achiral AIE dyes (Guest 2) into N*-LCs can give rise to strong CPL responses with high luminescence dissymmetry factor (gem) values of up to1.42.

Temporal Restricted Visual Tracking Via Reverse-Low-Rank Sparse Learning.

An effective representation model, which aims to mine the most meaningful information in the data, plays an important role in visual tracking. Some recent particle-filter-based trackers achieve promising results by introducing the low-rank assumption into the representation model. However, their assumed low-rank structure of candidates limits the robustness when facing severe challenges such as abrupt motion. To avoid the above limitation, we propose a temporal restricted reverse-low-rank learning algorithm for visual tracking with the following advantages: 1) the reverse-low-rank model jointly represents target and background templates via candidates, which exploits the low-rank structure among consecutive target observations and enforces the temporal consistency of target in a global level; 2) the appearance consistency may be broken when target suffers from sudden changes. To overcome this issue, we propose a local constraint via l1,2 mixed-norm, which can not only ensures the local consistency of target appearance, but also tolerates the sudden changes between two adjacent frames; and 3) to alleviate the inference of unreasonable representation values due to outlier candidates, an adaptive weighted scheme is designed to improve the robustness of the tracker. By evaluating on 26 challenge video sequences, the experiments show the effectiveness and favorable performance of the proposed algorithm against 12 state-of-the-art visual trackers.

The Twist Tensor Nuclear Norm for Video Completion.

In this paper, we propose a new low-rank tensor model based on the circulant algebra, namely, twist tensor nuclear norm (t-TNN). The twist tensor denotes a three-way tensor representation to laterally store 2-D data slices in order. On one hand, t-TNN convexly relaxes the tensor multirank of the twist tensor in the Fourier domain, which allows an efficient computation using fast Fourier transform. On the other, t-TNN is equal to the nuclear norm of block circulant matricization of the twist tensor in the original domain, which extends the traditional matrix nuclear norm in a block circulant way. We test the t-TNN model on a video completion application that aims to fill missing values and the experiment results validate its effectiveness, especially when dealing with video recorded by a nonstationary panning camera. The block circulant matricization of the twist tensor can be transformed into a circulant block representation with nuclear norm invariance. This representation, after transformation, exploits the horizontal translation relationship between the frames in a video, and endows the t-TNN model with a more powerful ability to reconstruct panning videos than the existing state-of-the-art low-rank models.

Effect of volume ratio on thermocapillary flow in liquid bridges of high-Prandtl-number fluids.

In present study, the transition of thermocapillary convection from the axisymmetric stationary flow to oscillatory flow in liquid bridges of 5cst silicon oil (aspect ratio 1.0 and 1.6) is investigated in microgravity conditions by the linear instability analysis. The corresponding marginal instability boundary is closely related to the gas/liquid configuration of the liquid bridge noted as volume ratio. With the increasing volume ratio, the marginal instability boundary consists of the increasing branch and the decreasing branch. A gap region exists between the branches where the critical Marangoni number of the corresponding axisymmetric stationary flow increases drastically. Particularly, a unique axisymmetric oscillatory flow (the critical azimuthal wave number is m=0 ) in the gap region is reported for the liquid bridge of aspect ratio 1.6. Moreover, the energy transfer between the basic state and the disturbance fields of the thermocapillary convection is analyzed at the corresponding critical Marangoni number, which reveals different major sources of the energy transfer for the development of the disturbances in regimes of the increasing branch, the gap region and the decreasing branch, respectively.

Experimental investigation on thermocapillary drop migration at large Marangoni number in reduced gravity.

Results from a space experiment on thermocapillary drop migration conducted on board the Chinese spacecraft ShenZhou-4 are presented in this paper. In the experiment, isolated drops of Fluorinert liquid moved in a matrix liquid of 5cst silicone oil at values of the Marangoni numbers (Ma) ranging up to 5500 and the interferometry images showed the temperature distribution inside the test cell. The drop migration velocity was measured. The experimental results show that the scaled drop migration velocity V/V(YGB) obviously decreases with Ma increasing the values up to 5500. The space experimental results are also compared with those from our early experiments, other space experiments, and some theoretical predictions.

The thermocapillary migrations of two bubbles in microgravity environment.

The thermocapillary motion of two bubbles along their line of centers in a uniform temperature gradient is investigated theoretically. The bubbles are moving in the direction of the temperature gradient. And the interaction between the leading bubble and the trailing one becomes significant as the separation distance between them is decreased greatly so that the bubble interaction is considered in this case. The appropriate equations of momentum and energy are solved using the method of reflections. In order to proceed analytically, sets of transformations between two coordinates are obtained. By using these transformations and the reflection process, accurate migration velocities of these two bubbles in the microgravity environment are derived for the limit of small Marangoni and Reynolds numbers. These results are employed to describe the thermocapillary motion of two bubbles and to estimate the effects of bubble size and the thermal gradient on the interaction between two bubbles. All of our results for the migration of the two bubbles demonstrate that the approach of the second bubble to the first one intensifies the mutual interaction between these two bubbles and yields some interesting thermocapillary motions.