A role for microsomal glutathione transferase 1 in melanin biosynthesis and melanoma progression.

Recent advancements in the treatment of melanoma are encouraging, but there remains a need to identify additional therapeutic targets. We identify a role for microsomal glutathione transferase 1 (MGST1) in biosynthetic pathways for melanin and as a determinant of tumor progression. Knockdown (KD) of MGST1 depleted midline-localized, pigmented melanocytes in zebrafish embryos, while in both mouse and human melanoma cells, loss of MGST1 resulted in a catalytically dependent, quantitative, and linear depigmentation, associated with diminished conversion of L-dopa to dopachrome (eumelanin precursor). Melanin, especially eumelanin, has antioxidant properties, and MGST1 KD melanoma cells are under higher oxidative stress, with increased reactive oxygen species, decreased antioxidant capacities, reduced energy metabolism and ATP production, and lower proliferation rates in 3D culture. In mice, when compared to nontarget control, Mgst1 KD B16 cells had less melanin, more active CD8+ T cell infiltration, slower growing tumors, and enhanced animal survival. Thus, MGST1 is an integral enzyme in melanin synthesis and its inhibition adversely influences tumor growth.

Research progress on carotenoid production by Rhodosporidium toruloides.

Carotenoids are natural lipophilic pigments, which have been proven to provide significant health benefits to humans, relying on their capacity to efficiently scavenge singlet oxygen and peroxyl radicals as antioxidants. Strains belonging to the genus Rhodosporidium represent a heterogeneous group known for a number of phenotypic traits including accumulation of carotenoids and lipids and tolerance to heavy metals and oxidative stress. As a representative of these yeasts, Rhodosporidium toruloides naturally produces carotenoids with high antioxidant activity and grows on a wide variety of carbon sources. As a result, R. toruloides is a promising host for the efficient production of more value-added lipophilic compound carotenoids, e.g., torulene and torularhodin. This review provides a comprehensive summary of the research progress on carotenoid biosynthesis in R. toruloides, focusing on the understanding of biosynthetic pathways and the regulation of key enzymes and genes involved in the process. Moreover, the relationship between the accumulation of carotenoids and lipid biosynthesis, as well as the stress from diverse abiotic factors, has also been discussed for the first time. Finally, several feasible strategies have been proposed to promote carotenoid production by R. toruloides. It is possible that R. toruloides may become a critical strain in the production of carotenoids or high-value terpenoids by genetic technologies and optimal fermentation processes. KEY POINTS: • Biosynthetic pathway and its regulation of carotenoids in Rhodosporidium toruloides were concluded • Stimulation of abiotic factors for carotenoid biosynthesis in R. toruloides was summarized • Feasible strategies for increasing carotenoid production by R. toruloides were proposed.

Fostering effective and sustainable scientific collaboration and knowledge exchange: a workshop-based approach to establish a national ecological observatory network (NEON) domain-specific user group.

The decision to establish a network of researchers centers on identifying shared research goals. Ecologically specific regions, such as the USA's National Ecological Observatory Network's (NEON's) eco-climatic domains, are ideal locations by which to assemble researchers with a diverse range of expertise but focused on the same set of ecological challenges. The recently established Great Lakes User Group (GLUG) is NEON's first domain specific ensemble of researchers, whose goal is to address scientific and technical issues specific to the Great Lakes Domain 5 (D05) by using NEON data to enable advancement of ecosystem science. Here, we report on GLUG's kick off workshop, which comprised lightning talks, keynote presentations, breakout brainstorming sessions and field site visits. Together, these activities created an environment to foster and strengthen GLUG and NEON user engagement. The tangible outcomes of the workshop exceeded initial expectations and include plans for (i) two journal articles (in addition to this one), (ii) two potential funding proposals, (iii) an assignable assets request and (iv) development of classroom activities using NEON datasets. The success of this 2.5-day event was due to a combination of factors, including establishment of clear objectives, adopting engaging activities and providing opportunities for active participation and inclusive collaboration with diverse participants. Given the success of this approach we encourage others, wanting to organize similar groups of researchers, to adopt the workshop framework presented here which will strengthen existing collaborations and foster new ones, together with raising greater awareness and promotion of use of NEON datasets. Establishing domain specific user groups will help bridge the scale gap between site level data collection and addressing regional and larger ecological challenges.

Intake of tobacco nitrosamines of smokers in various provinces of China and their cancer risk: A meta-analysis.

Nitrosamines are a class of carcinogens which have been detected widely in food, water, some pharmaceuticals as well as tobacco. The objectives of this paper include reviewing the basic information on tobacco consumption and nitrosamine contents, and assessing the health risks of tobacco nitrosamines exposure to Chinese smokers. We searched the publications in English from "Web of Science" and those in Chinese from the "China National Knowledge Infrastructure" in 2022 and collected 151 literatures with valid information. The content of main nitrosamines in tobacco, including 4-(methylnitrosoamino)-1-(3-pyridyl)-1-butanone (NNK), N-nitrosonornicotine (NNN), N-nitrosoanatabine (NAT), N-nitrosoanabasine (NAB), total tobacco-specific nitrosamines (TSNA), and N-nitrosodimethylamine (NDMA) were summarized. The information of daily tobacco consumption of smokers in 30 provinces of China was also collected. Then, the intakes of NNN, NNK, NAT, NAB, TSNAs, and NDMA via tobacco smoke were estimated as 1534 ng/day, 591 ng/day, 685 ng/day, 81 ng/day, 2543 ng/day, and 484 ng/day by adult smokers in 30 provinces, respectively. The cancer risk (CR) values for NNN and NNK inhalation intake were further calculated as 1.44 × 10-5 and 1.95 × 10-4. The CR value for NDMA intake via tobacco smoke (inhalation: 1.66 × 10-4) indicates that NDMA is similarly dangerous in tobacco smoke when compared with the TSNAs. In China, the CR values caused by average nitrosamines intake via various exposures and their order can be estimated as the following: smoke (3.75 × 10-4) > food (1.74 × 10-4) > drinking water (1.38 × 10-5). Smokers in China averagely suffer 200% of extra cancer risk caused by nitrosamines in tobacco when compared with non-smokers.

CPPVec: an accurate coding potential predictor based on a distributed representation of protein sequence.

Long non-coding RNAs (lncRNAs) play a crucial role in numbers of biological processes and have received wide attention during the past years. Since the rapid development of high-throughput transcriptome sequencing technologies (RNA-seq) lead to a large amount of RNA data, it is urgent to develop a fast and accurate coding potential predictor. Many computational methods have been proposed to address this issue, they usually exploit information on open reading frame (ORF), protein sequence, k-mer, evolutionary signatures, or homology. Despite the effectiveness of these approaches, there is still much room to improve. Indeed, none of these methods exploit the contextual information of RNA sequence, for example, k-mer features that counts the occurrence frequencies of continuous nucleotides (k-mer) in the whole RNA sequence cannot reflect local contextual information of each k-mer. In view of this shortcoming, here, we present a novel alignment-free method, CPPVec, which exploits the contextual information of RNA sequence for coding potential prediction for the first time, it can be easily implemented by distributed representation (e.g., doc2vec) of protein sequence translated from the longest ORF. The experimental findings demonstrate that CPPVec is an accurate coding potential predictor and significantly outperforms existing state-of-the-art methods.

Recruiting Rate Determines the Blinking Propensity of Rhodamine Fluorophores for Super-Resolution Imaging.

Live-cell single-molecule localization microscopy has advanced with the development of self-blinking rhodamines. A pKcycling of <6 is recognized as the criterion for self-blinking, yet a few rhodamines matching the standard fail for super-resolution reconstruction. To resolve this controversy, we constructed two classic rhodamines (pKcycling < 6) and four sulfonamide rhodamines with three exhibited exceptional larger pKcycling characteristics (6.91-7.34). A kinetic study uncovered slow equilibrium rates, and limited switch numbers resulted in the reconstruction failure of some rhodamines. From the kinetic disparity, a recruiting rate was first abstracted to reveal the natural switching frequency of spirocycling equilibrium. The new parameter independent from applying a laser satisfactorily explained the imaging failure, efficacious for determining the propensity of self-blinking from a kinetic perspective. Following the prediction from this parameter, the sulfonamide rhodamines enabled live-cell super-resolution imaging of various organelles through Halo-tag technology. It is determined that the recruiting rate would be a practical indicator of self-blinking and imaging performance.

Subtle Structural Translation Magically Modulates the Super-Resolution Imaging of Self-Blinking Rhodamines.

The evolution of super-resolution imaging techniques is benefited from the ongoing competition for optimal rhodamine fluorophores. Yet, it seems blind to construct the desired rhodamine molecule matching the imaging need without the knowledge on imaging impact of even the minimum structural translation. Herein, we have designed a pair of self-blinking sulforhodamines (STMR and SRhB) with the bare distinction of methyl or ethyl substituents and engineered them with Halo protein ligands. Although the two possess similar spectral properties (λab, λfl, ϕ, etc.), they demonstrated unique single-molecule characteristics preferring to individual imaging applications. Experimentally, STMR with high emissive rates was qualified for imaging structures with rapid dynamics (endoplasmic reticulum, and mitochondria), and SRhB with prolonged on-times and photostability was suited for relatively "static" nuclei and microtubules. Using this new knowledge, the mitochondrial morphology during apoptosis and ferroptosis was first super-resolved by STMR. Our study highlights the significance of even the smallest structural modification to the modulation of super-resolution imaging performance and would provide insights for future fluorophore design.

Characterization of differential modal group delay in few-mode fiber using a digital re-sampling technique.

We characterize the differential modal group delay (DMGD) arising in few-mode fibers (FMFs) based on the digital re-sampling technique, which is commonly used in current digital signal processing flow at the receiver-side. When the DMGD of a 291-m two-mode fiber is characterized over the C-band by using a 500-Mb/s non-return-to-zero (NRZ) signal and 1-GSa/s real-time oscilloscope, the experimental results are consistent with the DMGD obtained from the traditional time-of-flight (TOF) method. However, the wide-bandwidth instruments of the traditional TOF method can be replaced by cheap ones with a bandwidth of only a few hundred MHz, but the same temporal precision is achieved. Moreover, our proposed DMGD characterization method is not limited by the number of guided modes arising in the FMF, together with the capability to obtain both the DMGD value and its sign between two arbitrary guided modes.

Microsomal glutathione transferase 1 controls metastasis and therapeutic response in melanoma.

While recent targeted and immunotherapies in malignant melanoma are encouraging, most patients acquire resistance, implicating a need to identify additional drug targets to improve outcomes. Recently, attention has been given to pathways that regulate redox homeostasis, especially the lipid peroxidase pathway that protects cells against ferroptosis. Here we identify microsomal glutathione S-transferase 1 (MGST1), a non-selenium-dependent glutathione peroxidase, as highly expressed in malignant and drug resistant melanomas and as a specific determinant of metastatic spread and therapeutic sensitivity. Loss of MGST1 in mouse and human melanoma enhanced cellular oxidative stress, and diminished glycolysis, oxidative phosphorylation, and pentose phosphate pathway. Gp100 activated pmel-1 T cells killed more Mgst1 KD than control melanoma cells and KD cells were more sensitive to cytotoxic anticancer drugs and ferroptotic cell death. When compared to control, mice bearing Mgst1 KD B16 tumors had more CD8+ T cell infiltration with reduced expression of inhibitory receptors and increased cytokine response, large reduction of lung metastases and enhanced survival. Targeting MGST1 alters the redox balance and limits metastases in melanoma, enhancing the therapeutic index for chemo- and immunotherapies.

Progress in biological activities and biosynthesis of edible fungi terpenoids.

The edible fungi have both edible and medicinal functions, in which terpenoids are one of the most important active ingredients. Terpenoids possess a wide range of biological activities and show great potential in the pharmaceutical and healthcare industries. In this review, the diverse biological activities of edible fungi terpenoids were summarized with emphasis on the mechanism of anti-cancer and anti-inflammation. Subsequently, this review focuses on advances in knowledge and understanding of the biosynthesis of terpenoids in edible fungi, especially in the generation of sesquiterpenes, diterpenes, and triterpenes. This paper is aim to provide an overview of biological functions and biosynthesis developed for utilizing the terpenoids in edible fungi.

A review on recent advances in LED-based non-thermal technique for food safety: current applications and future trends.

Light-emitting diodes (LEDs) is an eco-friendly light source with broad-spectrum antimicrobial activity. Recent studies have extensively been conducted to evaluate its efficacy in microbiological safety and the potential as a preservation method to extend the shelf-life of foods. This review aims to present the latest update of recent studies on the basics (physical, biochemical and mechanical basics) and antimicrobial activity of LEDs, as well as its application in the food industry. The highlight will be focused on the effects of LEDs on different types (bacteria, yeast/molds, viruses) and forms (planktonic cells, biofilms, endospores, fungal toxin) of microorganisms. The antimicrobial activity of LEDs on various food matrices was also evaluated, together with further analysis on the food-related factors that lead to the differences in LEDs efficiency. Besides, the applications of LEDs on the food-related conditions, packaged food, and equipment that could enhance LEDs efficiency were discussed to explore the future trends of LEDs technology in the food industry. Overall, the present review provides important insights for future research and the application of LEDs in the food industry.

The beneficial potential of protein hydrolysates as prebiotic for probiotics and its biological activity: a review.

Probiotics are not only a food supplement, but they have shown great potential in their nutritional, health and therapeutic effects. To maximize the beneficial effects of probiotics, it is commonly achieved by adding prebiotics. Prebiotics primarily comprise indigestible carbohydrates, specific peptides, proteins, and lipids, with oligosaccharides being the most extensively studied prebiotics. However, these rapidly fermenting oligosaccharides have many drawbacks and can cause diarrhea and flatulence in the body. Hence, the exploration of new prebiotic is of great interest. Besides oligosaccharides, protein hydrolysates have been demonstrated to enhance the expression of beneficial properties of probiotics. Consequently, this paper outlines the mechanism underlying the action of protein hydrolysates on probiotics, as well as the advantageous impacts of proteins hydrolysates derived from various food sources on probiotics. In addition, this paper also reviews the currently reported biological activities of protein hydrolysates. The aim is a theoretical basis for the development and implementation of novel prebiotics.

Object Detection Based on Lightweight YOLOX for Autonomous Driving.

Accurate and rapid response in complex driving scenarios is a challenging problem in autonomous driving. If a target is detected, the vehicle will not be able to react in time, resulting in fatal safety accidents. Therefore, the application of driver assistance systems requires a model that can accurately detect targets in complex scenes and respond quickly. In this paper, a lightweight feature extraction model, ShuffDet, is proposed to replace the CSPDark53 model used by YOLOX by improving the YOLOX algorithm. At the same time, an attention mechanism is introduced into the path aggregation feature pyramid network (PAFPN) to make the network focus more on important information in the network, thereby improving the accuracy of the model. This model, which combines two methods, is called ShuffYOLOX, and it can improve the accuracy of the model while keeping it lightweight. The performance of the ShuffYOLOX model on the KITTI dataset is tested in this paper, and the experimental results show that compared to the original network, the mean average precision (mAP) of the ShuffYOLOX model on the KITTI dataset reaches 92.20%. In addition, the number of parameters of the ShuffYOLOX model is reduced by 34.57%, the Gflops are reduced by 42.19%, and the FPS is increased by 65%. Therefore, the ShuffYOLOX model is very suitable for autonomous driving applications.

Cordyceps militaris polysaccharides modulate gut microbiota and improve metabolic disorders in mice with diet-induced obesity.

BACKGROUND: Cordyceps militaris is an edible and medicinal fungus, and its polysaccharides are among its main pharmacological components. They can display immunomodulation, anti-oxidation, anti-inflammation, anti-hypolipidemic, and other functions. The anti-obesity effect of C. militaris polysaccharides (CMP) is not yet fully understood, however. RESULTS: In this study, a CMP diet intervention was applied over a 4 week period to mice with obesity induced by a high-fat diet (HFD), followed by profiling of obesity-induced dyslipidemia, low-grade inflammation, and gut dysbiosis. The results suggested that CMP could significantly reduce HFD-induced obesity, alleviate obesity-induced hyperlipidemia and insulin resistance, and ameliorate systemic inflammation, showing a promising ability to protect mice from obesity. Further analyses revealed that CMP could regulate obesity-induced gut dysbiosis by restoring the phylogenetic diversity of gut microbiota. It could also increase the relative abundance of short-chain fatty acid (SCFA)-producing bacteria, while down-regulating the level of bacteria that were positively related to the development of obesity. A correlation analysis showed that Helicobacter, Allobaculum, Clostridium XVIII, Parabacteroides, Ligilactobacillus, Faecalibaculum, Adlercreutzia, and Mediterraneibacter were positively related to obese phenotypes. CONCLUSION: This study highlights the potential of CMP as a prebiotic agent to protect obese individuals from metabolic disorders and gut dysbiosis. © 2022 Society of Chemical Industry.

Surpassing the Background Barrier for Multidimensional Single-Molecule Localization Super-Resolution Imaging: A Case of Lysosome-Exclusively Turn-on Probe.

The background barrier restricts the dimensionality of live-cell single-molecule localization super-resolution imaging. Ideally, a probe exclusively turned on by its target, without any nonspecific fluorescence signals from off-target molecules, constitutes a practical solution to surpass this barrier. Yet, few such fluorophores have been developed. A lysosome with a unique acidic lumen was chosen as the target for demonstrating the concept advantage. A representative lyso-tracker Lyso-R (piperazine rhodamine) with high brightness has been spirocyclized with o-phenylenediamine to form Lyso-Ropa. This probe shifted its bright-dark spirocyclization balance to a strong acidity domain (pKa = -0.18). Consequently, under no-wash conditions, Lyso-Ropa showed almost undetectable background photons (only one-sixtieth of that of Lyso-R) in a neutral cellular environment, and it formed sparsely brightened molecules at a low ratio (∼1 × 10-3%) in lysosomes. This background-free probe enabled super-resolution imaging and modeling of live-cell lysosomes in four dimensions at 2 s resolution, with quantitative determination of lysosomal volume expansion and deformation at starvation. Our molecular approach sheds new light on surpassing the background barrier for multidimensional super-resolution imaging.

Super-Resolution Imaging of Autophagy by a Preferred Pair of Self-Labeling Protein Tags and Fluorescent Ligands.

Autophagy is a core recycling process for homeostasis, with its dysfunction associated with tumorigenesis and various diseases. Yet, its subtle intracellular details are covered due to the limited resolution of conventional microscopies. The major challenge for modern super-resolution microscopy deployment is the lack of a practical labeling system, which could provide robust fluorescence with fidelity in the context of the dynamic autophagy microenvironment. Herein, a representative autophagy marker LC3 protein is selected to develop two hybrid self-labeling systems with tetramethylrhodamine (TMR) fluorophores through SNAP/Halo-tag technologies. A systematic investigation indicated that the match of the LC3-Halo and TMR ligand remarkably outperforms that of LC3-SNAP, as the former Halo system exhibited more robust single-molecule brightness (440 vs 247), total photon numbers (45600 vs 13500), and dwell time of the initial bright state (0.82 vs 0.40 s) than the latter. With the aid of this desirable Halo system, for the first time, live-cell ferritinophagy is monitored with a spatial resolution of ∼50 nm, which disclosed reduced sizes of autophagosomes (∼650 nm, ferritinophagy) than those in nonselective (∼840 nm, mammalian target of rapamycin (mTOR)) and selective autophagy (∼900 nm, mitophagy).

Enhancement of ergothioneine production by discovering and regulating its metabolic pathway in Cordyceps militaris.

BACKGROUND: Cordyceps militaris is a traditional medicinal fungus contains a variety of functional ingredients and has been developed as an important mushroom food recently. Ergothioneine, one of the antioxidative compounds in C. militaris, is benefits on aging-related diseases and therefore became a novel functional food nutritive fortifier. Currently, the main diet source of ergothioneine is mushroom food. However, the mushroom farming faces the problems such as rather low ingredient yield and spontaneous degeneration associated fruiting body that restricts large scale production of ergothioneine. RESULTS: In this study, we excavated the ergothioneine synthetases in mushroom and modified the genes in C. militaris to construct a new ergothioneine synthesis pathway. By further introducing this pathway into C. militaris genome, we succeeded to increase the ingredients' production of engineering strain, the highest amount of ergothioneine and cordycepin were up to 2.5 g/kg dry weight and 2 g/L, respectively. Additionally, the expression of ergothioneine synthetase genes in the shape-mutated degenerative C. militaris could recover the ability of degenerative strain to produce high amount of ingredients, suggesting the metabolic regulation of ergothioneine might release the symptom of mushroom degeneration. CONCLUSION: This study reveals a new pathway to fulfill the market needs of functional mushroom food and food fortifier ergothioneine. It implied the mycelium of C. militaris could be engineered as a novel medicinal mushroom food which could produce higher amount of valuable ingredients.

Activation of Wnt/ß-catenin signalling and HIF1α stabilisation alters pluripotency and differentiation/proliferation properties of human-induced pluripotent stem cells.

BACKGROUND INFORMATION: Wnt/ß-catenin signalling, in the microenvironment of pluripotent stem cells (PSCs), plays a critical role in their differentiation and proliferation. Contradictory reports on the role of Wnt/ß-catenin signalling in PSCs self-renewal and differentiation, however, render these mechanisms largely unclear. RESULTS: Wnt/ß-catenin signalling pathway in human-induced pluripotent stem cells (hiPSCs) was activated by inhibiting glycogen synthase kinase 3 (GSK3), driving the cells into a mesodermal/mesenchymal state, exhibiting proliferative, invasive and anchorage-independent growth properties, where over 70% of cell population became CD 44 (+)/CD133 (+). Wnt/ß-catenin signalling activation also altered the metabolic state of hiPSCs from aerobic glycolysis to oxidative metabolism and changed their drug and oxidative stress sensitivities. These effects of GSK3 inhibition were suppressed in HIF1α-stabilised cells. CONCLUSIONS: Persistent activation of Wnt/ß-catenin signalling endows hiPSCs with proliferative/invasive 'teratoma-like' states, shifting their metabolic dependence and allowing HIF1α-stabilisation to inhibit their proliferative/invasive properties. SIGNIFICANCE: The hiPSC potential to differentiate into 'teratoma-like' cells suggest that stem cells may exist in two states with differential metabolic and drug dependency.

Discrete Missing Data Imputation Using Multilayer Perceptron and Momentum Gradient Descent.

Data are a strategic resource for industrial production, and an efficient data-mining process will increase productivity. However, there exist many missing values in data collected in real life due to various problems. Because the missing data may reduce productivity, missing value imputation is an important research topic in data mining. At present, most studies mainly focus on imputation methods for continuous missing data, while a few concentrate on discrete missing data. In this paper, a discrete missing value imputation method based on a multilayer perceptron (MLP) is proposed, which employs a momentum gradient descent algorithm, and some prefilling strategies are utilized to improve the convergence speed of the MLP. To verify the effectiveness of the method, experiments are conducted to compare the classification accuracy with eight common imputation methods, such as the mode, random, hot-deck, KNN, autoencoder, and MLP, under different missing mechanisms and missing proportions. Experimental results verify that the improved MLP model (IMLP) can effectively impute discrete missing values in most situations under three missing patterns.

Social-path embedding-based transformer for graduation development prediction.

As the education of students attracts more and more attention, the task of graduation development prediction has gradually become a hot topic in academia and industry. The task of graduation development prediction aims to predict the employment category of students in advance via academic achievement data, which can help administrators understand students' learning status and set up a reasonable learning plan. However, existing research ignores the potential impact of social relationships on students' graduation development choices. To fully explore social relationships among students, we propose a Social-path Embedding-based Transformer Neural Network (SPE-TNN) for the task of graduation development prediction in this paper. Specifically, SPE-TNN is divided into the Social-path selection layer, the Social-path embedding layer, the Transformer layer, and the Multi-layer projection layer. Firstly, the Social-path selection layer is designed to find social relationships that impact graduation development and embed them into the student's performance features through the Social-path embedding layer. Secondly, the Transformer layer is adopted to balance the weights of the students' features. Finally, the Multi-layer projection layer is used to achieve the student graduation development prediction. Experimental results on the real-world datasets show that SPE-TNN outperforms the existing popular approaches.