MULocDeep web service for protein localization prediction and visualization at subcellular and suborganellar levels.

Predicting protein localization and understanding its mechanisms are critical in biology and pathology. In this context, we propose a new web application of MULocDeep with improved performance, result interpretation, and visualization. By transferring the original model into species-specific models, MULocDeep achieved competitive prediction performance at the subcellular level against other state-of-the-art methods. It uniquely provides a comprehensive localization prediction at the suborganellar level. Besides prediction, our web service quantifies the contribution of single amino acids to localization for individual proteins; for a group of proteins, common motifs or potential targeting-related regions can be derived. Furthermore, the visualizations of targeting mechanism analyses can be downloaded for publication-ready figures. The MULocDeep web service is available at https://www.mu-loc.org/.

High-normal serum uric acid predicts macrovascular events in patients with type 2 diabetes mellitus without hyperuricemia based on a 10-year cohort.

BACKGROUND AND AIMS: The upper limits of normal serum uric acid (SUA) or the lower limits of hyperuricemia were frequently set at 420 or 360 µmol/L (7.0 or 6.0 mg/dL). We aimed to explore the association between high-normal SUA (360 ≤ SUA≤420 µmol/L) and incidence of macrovascular and renal events based on a 10-year cohort with type 2 diabetes mellitus (T2DM) to explore which cut-off was more appropriate. METHODS AND RESULTS: A total of 2988 patients with T2DM without hyperuricemia (SUA≤420 µmol/L) were included and followed up. Cox proportional hazards models and restricted cubic spline regression were used to evaluate the relationship between baseline SUA (as continuous and categorical variable) and macrovascular and renal events. Patients were grouped as low-normal (SUA<360 µmol/L) and high-normal groups based on baseline SUA, and the latter group had higher incidence of macrovascular events. Multivariate Cox regression analysis indicated that baseline levels of SUA were significantly associated with cardiovascular (HR = 1.385, 95%CI:1.190-1.613, P < 0.001) and peripheral vascular events (HR = 1.266, 95%CI:1.018-1.574, P = 0.034), and the linear association existed. Moreover, fully adjusted multivariable Cox analyses indicated high-normal SUA increased the risks of cardiovascular (HR = 1.835, 95%CI:1.319-2.554, P < 0.001) and peripheral vascular events (HR = 1.661, 95%CI:1.000-2.760, P = 0.050) compared to low-normal SUA. CONCLUSIONS: Baseline SUA levels were positively associated with cardiovascular and peripheral vascular events, and high-normal SUA increased the risks of these events in patients with T2DM even without hyperuricemia. A threshold value for SUA of 360 µmol/L should be more appropriate in terms of predicting macrovascular events risks compared to the value of 420 µmol/L.

Exercise Changes Gut Microbiota: A New Idea to Explain that Exercise Improves Autism.

The effect of exercise interventions on autism spectrum disorder (ASD) has been demonstrated in many studies, and the discovery of a bidirectional relationship between the gut microbiome (GM) and the central nervous system (CNS) has led to the concept of the microbial gut-brain axis (MGBA) and has linked the abnormal GM to a variety of neuropsychiatric disorders, autism being one of them. Research on improving the GM through exercise is also starting to come into focus. However, there are currently few studies on exercise intervention in the GM of autism. The purpose of this review was to find evidence to explore the possible potential effects of exercise to improve the behavior of individuals with autism in the MGBA in this treatment, as well as the potential of GM as an exercise treatment for autism. We will explore (1) changes in GM components of ASD and their relationship to the pathophysiology of ASD; (2) the relationship between exercise and changes in GM components, and (3) the effect of exercise on GM in CNS disorders. Ultimately, we concluded that Streptococcus, Bifidobacterium, Clostridium, Bacteroides, and Blautia may be potential effectors through the MGBA network during exercise to ameliorate ASD targeting microbiotas. They deserve high attention in the follow-up studies.

Time-Series Representation Learning in Topology Prediction for Passive Optical Network of Telecom Operators.

The passive optical network (PON) is widely used in optical fiber communication thanks to its low cost and low resource consumption. However, the passiveness brings about a critical problem that it requires manual work to identify the topology structure, which is costly and prone to bringing noise to the topology logs. In this paper, we provide a base solution firstly introducing neural networks for such problems, and based on that solution we propose a complete methodology (PT-Predictor) for predicting PON topology through representation learning on its optical power data. Specifically, we design useful model ensembles (GCE-Scorer) to extract the features of optical power with noise-tolerant training techniques integrated. We further implement a data-based aggregation algorithm (MaxMeanVoter) and a novel Transformer-based voter (TransVoter) to predict the topology. Compared with previous model-free methods, PT-Predictor is able to improve prediction accuracy by 23.1% in scenarios where data provided by telecom operators is sufficient, and by 14.8% in scenarios where data is temporarily insufficient. Besides, we identify a class of scenarios where PON topology does not follow a strict tree structure, and thus topology prediction cannot be effectively performed by relying on optical power data alone, which will be studied in our future work.

A gradient boosting tree model for multi-department venous thromboembolism risk assessment with imbalanced data.

Venous thromboembolism (VTE) is the world's third most common cause of vascular mortality and a serious complication from multiple departments. Risk assessment of VTE guides clinical intervention in time and is of great importance to in-hospital patients. Traditional VTE risk assessment methods based on scaling tools, which always require rules carefully designed by human experts, are difficult to apply to large-population scenarios since the manually designed rules are not guaranteed to be accurate to all populations. In contrast, with the development of the electronic health record (EHR) datasets, data-driven machine-learning-based risk assessment methods have proven superior predictability in many studies in recent years. This paper uses the gradient boosting tree model to study the VTE risk assessment problem with multi-department data. There exist two distinct characteristics of VTE data collected at the level of the entire hospital: its wide distribution and heterogeneity across multiple departments. To this end, we consider the prediction task over multiple departments as a multi-task learning process, and introduce the algorithm of a task-aware tree-based method TSGB to tackle the multi-task prediction problem. Although the introduction of multi-task learning improves overall across-department performance, we reveal the problem of task-wise performance decline while dealing with imbalanced VTE data volume. According to the analysis, we finally propose two variants of TSGB to alleviate the problems and further boost the prediction performance. Compared with state-of-the-art rule-based and multi-task tree-based methods, the experimental results show the proposed methods not only improve the overall across-department AUC performance effectively, but also ensure the improvement of performance over every single department prediction.

Irisin as a predictor of bone metabolism in Han Chinese Young Men with pre-diabetic individuals.

BACKGROUND: Irisin is a novel myokine both in mice and humans, and it can also be secreted by adipose tissue and the liver in a small amounts. There are few studies on irisin and bone metabolism. The aim of this study was to assess the relationship between serum irisin levels and bone metabolism and analyze its related factors in Han young male with pre-diabetic individuals. METHODS: This cross-sectional study included 41 pre-diabetes and 45 normal glucose tolerance (NGT). Anthropometric measurements, including height, weight, waist circumference (WC), and bone mineral content (BMC), were performed. All patients underwent an oral glucose tolerance test (OGTT) after 8 h of fasting, and the levels of glucose, insulin, lipids, serum irisin and bone turnover markers were measured. RESULTS: The levels of serum irisin (4.4 ± 1.4 vs. 6.3 ± 1.5 µg/mL), P1NP and OC were significantly lower and CTX was significantly higher in the pre-diabetes group (P < 0.05). BMC did not differ in the two groups (P > 0.05). Serum irisin levels negatively correlated with BMI (r =-0.325), FPG (r =-0.329), TG (r =-0.339) (P < 0.05) in NGT individuals. Serum irisin levels positively correlated with P1NP (r = 0.398), OC (r = 0.351), HDL-C (r = 0.432) and negatively correlated with FPG (r = -0.725), 2 h-PG (r = -0.360) (P < 0.05) in pre-diabetic individuals. Multiple regression analysis revealed that Serum irisin (ß = 9.768, P = 0.025) and WC (ß = -2.355, P = 0.002) were significant independent predictors for P1NP. CONCLUSION: Bone turnover markers were changed rather than bone mineral content in young men with pre-diabetes. In pre-diabetes individuals, serum irisin levels were reduced and close relationship with P1NP. Falling irisin levels may be a predictor of decreased bone formation in Han young men with pre-diabetes individuals.

Sesamin suppresses NSCLC cell proliferation and induces apoptosis via Akt/p53 pathway.

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer with a disappointing prognosis. The aim of this study was to investigate the anticancer effect of sesamin and the underlying mechanism. The MTT assay was used to detect the proliferation of NSCLC cells. The cell cycle and apoptosis were analyzed by flow cytometry. The protein levels of Akt, p-Akt (Ser473), p53, cyclin D1, CDK2, MDM2, p-MDM2 (Ser166) were detected by western blotting. The expression of p-Akt (Ser473), p53 and Ki67 in vivo was analyzed by IHC. Histopathologic analyses of major organs (heart, liver, spleen, lung and kidney) were performed by H&E staining. The results show that sesamin suppressed cell proliferation and induced apoptosis of NSCLC cells (A549 and H1792) in a dose-dependent manner. Treatment with sesamin caused cell cycle arrest at G1 phase and inhibited cyclin D1 and CDK2 expression. In addition, sesamin inhibited Akt activity and upregulated p53 expression both in vivo and in vitro. When Akt and p53 were suppressed by LY294002 and PFTα, respectively, sesamin exerted no additional effects. The in vivo results mostly matched the in vitro findings. Specifically, sesamin exerted little damage to major organs. Taken together, this study demonstrates that sesamin suppresses NSCLC cell proliferation by induction of G1 phase cell cycle arrest and apoptosis via Akt/p53 pathway. Therefore, sesamin may be a promising adjuvant treatment for NSCLC therapy.

Alpha lipoic acid antagonizes cytotoxicity of cobalt nanoparticles by inhibiting ferroptosis-like cell death.

As a main element in the hard metal industry, cobalt is one of the major components of human metal implants. Cobalt-containing implants, especially joint prostheses used for artificial joint replacement, can be corroded due to the complex physiological environment in vivo, producing a large number of nanoscale cobalt particles (Cobalt Nanoparticles, CoNPs). These CoNPs can be first accumulated around the implant to cause adverse local reactions and then enter into the blood vessels followed by reaching the liver, heart, brain, kidney, and other organs through systematic circulation, which leads to multi-system toxicity symptoms. To ensure the long-term existence of cobalt-containing implants in the body, it is urgently required to find out a safe and effective detoxification drug. Herein, we have demonstrated that CoNPs could induce the ferroptosis-like cell death through the enhancement of intracellular reactive oxygen species (ROS) level, cytoplasmic Fe2+ level, lipid peroxidation, and consumption of reduced glutathione (GSH) as well as inhibition of glutathione peroxidase 4 (GPX4) activity. Importantly, α-lipoic acid (ALA), a natural antioxidant with the capability to scavenge free radicals and chelate toxic metals, was found to efficiently alleviate the adverse effects of CoNPs. The present study illustrates a new mechanism of CoNPs mediated by ferroptosis-like cytotoxicity and discloses an effective method for the detoxification of CoNPs by employing the natural antioxidant of ALA, providing a basis for further in vivo detoxification study.

Correction: Qi, W., et al. (+)-Usnic Acid Induces ROS-dependent Apoptosis via Inhibition of Mitochondria Respiratory Chain Complexes and Nrf2 Expression in Lung Squamous Cell Carcinoma. Int. J. Mol. Sci. 2020, 21, 876.

The authors wish to make the following corrections to this paper [1]:[...].

(+)-Usnic Acid Induces ROS-dependent Apoptosis via Inhibition of Mitochondria Respiratory Chain Complexes and Nrf2 Expression in Lung Squamous Cell Carcinoma.

Lung squamous cell carcinoma (LUSC) has a poor prognosis, in part due to poor therapeutic response and limited therapeutic alternatives. Lichens are symbiotic organisms, producing a variety of substances with multiple biological activities. (+)-Usnic acid, an important biologically active metabolite of lichens, has been shown to have high anti-cancer activity at low doses. However, there have been no reports regarding the effect of (+)-usnic acid on LUSC cells. This study found that (+)-usnic acid reduced viability and induced apoptosis in LUSC cells by reactive oxygen species (ROS) accumulation. (+)-Usnic acid induced mitochondria-derived ROS production via inhibition of complex I and complex III of the mitochondrial respiratory chain (MRC). Interestingly, the elimination of mitochondrial ROS by Mito-TEMPOL only partially reversed the effect of (+)-usnic acid on cellular ROS production. Further study showed that (+)-usnic acid also induced ROS production via reducing Nrf2 stability through disruption of the PI3K/Akt pathway. The in vitro and in vivo xenograft studies showed that combined treatment of (+)-usnic acid and paclitaxel synergistically suppressed LUSC cells. In conclusion, this study indicates that (+)-usnic acid induces apoptosis of LUSC cells through ROS accumulation, probably via disrupting the mitochondrial respiratory chain (MRC) and the PI3K/Akt/Nrf2 pathway. Therefore, although clinical use of (+)-usnic acid will be limited due to toxicity issues, derivatives thereof may turn out as promising anticancer candidates for adjuvant treatment of LUSC.

Delving Deep into Multiscale Pedestrian Detection via Single Scale Feature Maps.

The standard pipeline in pedestrian detection is sliding a pedestrian model on an image feature pyramid to detect pedestrians of different scales. In this pipeline, feature pyramid construction is time consuming and becomes the bottleneck for fast detection. Recently, a method called multiresolution filtered channels (MRFC) was proposed which only used single scale feature maps to achieve fast detection. However, there are two shortcomings in MRFC which limit its accuracy. One is that the receptive field correspondence in different scales is weak. Another is that the features used are not scale invariance. In this paper, two solutions are proposed to tackle with the two shortcomings respectively. Specifically, scale-aware pooling is proposed to make a better receptive field correspondence, and soft decision tree is proposed to relive scale variance problem. When coupled with efficient sliding window classification strategy, our detector achieves fast detecting speed at the same time with state-of-the-art accuracy.

600-Hz linewidth short-linear-cavity fiber laser.

We proposed a short-linear-cavity (SLC) fiber laser based on a virtual-folded-ring (VFR) resonator and a fiber Bragg grating Fabry-Perot filter. Spatial hole burning effect was reduced by retarding the polarization state of the counter-propagating light waves utilizing the VFR structure. The photon lifetime of the resonator was extended due to the multi-reflection inside the FBG FP, which increased the intra-cavity power and relatively suppressed the contribution of phase diffusion from spontaneous emission. The relaxation oscillation frequency is around 160 kHz due to the slow light effect. The linewidth of the SLC fiber laser was measured to be less than 600 Hz.

Subtle magnesium liberation of self-fabricated functional filler actuates highly efficient phosphorus removal from source-separated urine by SBBR.

Domestic wastewater source-separated treatment has attracted wide attention due to the efficiency improvement of sewage treatment systems, energy saving, resource reuse, and the construction and operation cost saving of pipeline networks. Nonetheless, the excess source-separated urine still demands further harmless treatment. Sequencing batch biofilm reactor (SBBR), a new type of composite biofilm reactor developed by filling different fillers into the sequential batch reactor (SBR) reactor, has higher pollutant removal performance and simpler operation and maintenance. However, the phosphorus removal ability of the SBBR filling with conventional fillers is still limited and needs further improvement. In this study, we developed two new fillers, the self-fabricated filler A and B (SFA/SFB), and compared their source-separated urine treatment performance. Long-term treatment experimental results demonstrated that the SBBR systems with different fillers had good removal performance on the COD and TN in the influent, and the removal rate increased with the increasing HRT. However, only the SBBR system with the SFA showed excellent PO43--P and TP removal performance, with the removal rates being 83.7 ± 11.9% and 77.3 ± 13.7% when the HRT was 1 d. Microbial community analysis results indicated that no special bacteria with strong phosphorus removal ability were present on the surface of the SFA. Adsorption experimental results suggested that the SFA had better adsorption performance for phosphorus than the SFB, but it could not always have stronger phosphorus adsorption and removal performance during long-term operation due to the adsorption saturation. Through a series of characterizations such as SEM, XRD, and BET, it was found that the SFA had a looser structure due to the use of different binder and production processes, and the magnesium in the SFA gradually released and reacted with PO43- and NH4+ in the source-separated urine to form dittmarite and struvite, thus achieving efficient phosphorus removal. This study provides a feasible manner for the efficient treatment of source-separated urine using the SBBR system with self-fabricated fillers.

Printed smart devices for anti-counterfeiting allowing precise identification with household equipment.

Counterfeiting has become a serious global problem, causing worldwide losses and disrupting the normal order of society. Physical unclonable functions are promising hardware-based cryptographic primitives, especially those generated by chemical processes showing a massive challenge-response pair space. However, current chemical-based physical unclonable function devices typically require complex fabrication processes or sophisticated characterization methods with only binary (bit) keys, limiting their practical applications and security properties. Here, we report a flexible laser printing method to synthesize unclonable electronics with high randomness, uniqueness, and repeatability. Hexadecimal resistive keys and binary optical keys can be obtained by the challenge with an ohmmeter and an optical microscope. These readout methods not only make the identification process available to general end users without professional expertise, but also guarantee device complexity and data capacity. An adopted open-source deep learning model guarantees precise identification with high reliability. The electrodes and connection wires are directly printed during laser writing, which allows electronics with different structures to be realized through free design. Meanwhile, the electronics exhibit excellent mechanical and thermal stability. The high physical unclonable function performance and the widely accessible readout methods, together with the flexibility and stability, make this synthesis strategy extremely attractive for practical applications.

Engineering Hyaluronic Acid Microneedles Loaded with Mn2+ and Temozolomide for Topical Precision Therapy of Melanoma.

Topical therapy has received worldwide attention for in situ tumors owing to its higher efficacy of drug delivery. Herein, this work reports a dissolvable multifunctional hyaluronic acid microneedles (HMNs) patch coloaded with temozolomide (TMZ) and MnCl2 (TMZ/MnCl2@HMN) for chemoimmunotherapy of melanoma. HMNs can ensure the stability of TMZ over time, and exhibit fewer side effects with a localized release way. In particular, TMZ not only promotes dendritic cell maturation by triggering immunogenic cell death in tumor cells, but also induces DNA damage that can further enhance the Mn2+-activated cGAS-STING (stimulator of interferon genes pathway). As a result, the TMZ/MnCl2@HMN multifunctional platform significantly inhibits lung metastases for melanoma, providing a practical strategy for precision therapy of melanoma.

A 1014 nm linearly polarized low noise narrow-linewidth single-frequency fiber laser.

We present the demonstration of a compact linearly polarized low noise narrow-linewidth single-frequency fiber laser at 1014 nm. The compact fiber laser is based on a 5-mm-long homemade Yb(3+)-doped phosphate fiber. Over 164 mW stable continuous-wave single transverse and longitudinal mode lasing at 1014 nm has been achieved. The measured relative intensity noise is less than -135 dB/Hz at frequencies of over 2.5 MHz. The signal-to-noise ratio of the laser is larger than 70 dB, and the linewidth is less than 7 kHz, while the obtained linear polarization extinction ratio is higher than 30 dB.

Low noise single-frequency single-polarization ytterbium-doped phosphate fiber laser at 1083 nm.

We present a low noise single-frequency and single-polarization distributed Bragg reflector fiber laser at 1083 nm by using a 1.8 cm long newly developed ytterbium-doped phosphate single mode glass fiber. The maximum output power is more than 100 mW with a slope efficiency of >29.6%. The signal to noise ratio is higher than 61 dB and the laser linewidth of less than 2 kHz is estimated. The obtained relative intensity noise for frequencies of over 4.0 MHz is less than -150 dB/Hz, which approaches the shot noise limit. The achieved linear polarization extinction ratio is more than 30 dB.

Improving Robustness of Intent Detection Under Adversarial Attacks: A Geometric Constraint Perspective.

Deep neural networks (DNNs)-based natural language processing (NLP) systems are vulnerable to being fooled by adversarial examples presented in recent studies. Intent detection tasks in dialog systems are no exception, however, relatively few works have been attempted on the defense side. The combination of linear classifier and softmax is widely used in most defense methods for other NLP tasks. Unfortunately, it does not encourage the model to learn well-separated feature representations. Thus, it is easy to induce adversarial examples. In this article, we propose a simple, yet efficient defense method from the geometric constraint perspective. Specifically, we first propose an M-similarity metric to shrink variances of intraclass features. Intuitively, better geometric conditions of feature space can bring lower misclassification probability (MP). Therefore, we derive the optimal geometric constraints of anchors within each category from the overall MP (OMP) with theoretical guarantees. Due to the nonconvex characteristic of the optimal geometric condition, it is hard to satisfy the traditional optimization process. To this end, we regard such geometric constraints as manifold optimization processes in the Stiefel manifold, thus naturally avoiding the above challenges. Experimental results demonstrate that our method can significantly improve robustness compared with baselines, while retaining the excellent performance on normal examples.

The role of CD4+ T cells in tumor and chronic viral immune responses.

Immunotherapies are mainly aimed to promote a CD8+ T cell response rather than a CD4+ T cell response as cytotoxic T lymphocytes (CTLs) can directly kill target cells. Recently, CD4+ T cells have received more attention due to their diverse roles in tumors and chronic viral infections. In antitumor and antichronic viral responses, CD4+ T cells relay help signals through dendritic cells to indirectly regulate CD8+ T cell response, interact with B cells or macrophages to indirectly modulate humoral immunity or macrophage polarization, and inhibit tumor blood vessel formation. Additionally, CD4+ T cells can also exhibit direct cytotoxicity toward target cells. However, regulatory T cells exhibit immunosuppression and CD4+ T cells become exhausted, which promote tumor progression and chronic viral persistence. Finally, we also outline immunotherapies based on CD4+ T cells, including adoptive cell transfer, vaccines, and immune checkpoint blockade. Overall, this review summarizes diverse roles of CD4+ T cells in the antitumor or protumor and chronic viral responses, and also highlights the immunotherapies based on CD4+ T cells, giving a better understanding of their roles in tumors and chronic viral infections.