MYCT1 inhibits hematopoiesis in diffuse large B-cell lymphoma by suppressing RUNX1 transcription.

BACKGROUND: The abnormality of chromosomal karyotype is one factor causing poor prognosis of lymphoma. In the analysis of abnormal karyotype of lymphoma patients, three smallest overlap regions were found, in which MYCT1 was located. MYCT1 is the first tumor suppressor gene cloned by our research team, but its studies relating to the occurrence and development of lymphoma have not been reported. METHODS: R banding analyses were employed to screen the abnormality of chromosomal karyotype in clinical specimen and MYCT1 over-expression cell lines. FISH was to monitor MYCT1 copy number aberration. RT-PCR and Western blot were to detect the mRNA and protein levels of the MYCT1 and RUNX1 genes, respectively. The MYCT1 and RUNX1 protein levels in clinical specimen were evaluated by immunohistochemical DAB staining. The interaction between MYCT1 and MAX proteins was identified via Co-IP and IF. The binding of MAX on the promoter of the RUNX1 gene was detected by ChIP and Dual-luciferase reporter assay, respectively. Flow cytometry and CCK-8 assay were to explore the effects of MYCT1 and RUNX1 on the cell cycle and proliferation, respectively. RESULTS: MYCT1 was located in one of three smallest overlap regions of diffuse large B-cell lymphoma, it altered chromosomal instability of diffuse large B-cell lymphoma cells. MYCT1 negatively correlated with RUNX1 in lymphoma tissues of the patients. MAX directly promoted the RUNX1 gene transcription by binding to its promoter region. MYCT1 may represses RUNX1 transcription by binding MAX in diffuse large B-cell lymphoma cells. MYCT1 binding to MAX probably suppressed RUNX1 transcription, leading to the inhibition of proliferation and cell cycle of the diffuse large B-cell lymphoma cells. CONCLUSION: This study finds that there is a MYCT1-MAX-RUNX1 signaling pathway in diffuse large B-cell lymphoma. And the study provides clues and basis for the in-depth studies of MYCT1 in the diagnosis, treatment and prognosis of lymphoma.

PEGA: A Privacy-Preserving Genetic Algorithm for Combinatorial Optimization.

EA, such as the genetic algorithm (GA), offer an elegant way to handle combinatorial optimization problems (COPs). However, limited by expertise and resources, most users lack the capability to implement evolutionary algorithms (EAs) for solving COPs. An intuitive and promising solution is to outsource evolutionary operations to a cloud server, however, it poses privacy concerns. To this end, this article proposes a novel computing paradigm called evolutionary computation as a service (ECaaS), where a cloud server renders evolutionary computation services for users while ensuring their privacy. Following the concept of ECaaS, this article presents privacy-preserving genetic algorithm (PEGA), a privacy-preserving GA designed specifically for COPs. PEGA enables users, regardless of their domain expertise or resource availability, to outsource COPs to the cloud server that holds a competitive GA and approximates the optimal solution while safeguarding privacy. Notably, PEGA features the following characteristics. First, PEGA empowers users without domain expertise or sufficient resources to solve COPs effectively. Second, PEGA protects the privacy of users by preventing the leakage of optimization problem details. Third, PEGA performs comparably to the conventional GA when approximating the optimal solution. To realize its functionality, we implement PEGA falling in a twin-server architecture and evaluate it on two widely known COPs: 1) the traveling Salesman problem (TSP) and 2) the 0/1 knapsack problem (KP). Particularly, we utilize encryption cryptography to protect users' privacy and carefully design a suite of secure computing protocols to support evolutionary operators of GA on encrypted chromosomes. Privacy analysis demonstrates that PEGA successfully preserves the confidentiality of COP contents. Experimental evaluation results on several TSP datasets and KP datasets reveal that PEGA performs equivalently to the conventional GA in approximating the optimal solution.

Monoterpenoid Glycosides from the Leaves of Ligustrum robustum and Their Bioactivities (II).

Ligustrum robustum has been not only used as a heat-clearing and detoxicating functional tea (Ku-Ding-Cha) but also consumed as a hypotensive, anti-diabetic, and weight-reducing folk medicine. From the leaves of L. robustum, ten new monoterpenoid glycosides named ligurobustosides T10 (1a), T11 (1b), T12 (2a), T13 (2b), T14 (3a), T15 (3b), F1 (4b), T16 (5a), T17 (5b), and E1 (6b), together with five known ones (4a, 6a, 7, 8a, 8b), were separated and identified using the spectroscopic method and chemical method in this research. The results of biological tests exhibited that the fatty acid synthase (FAS) inhibitory action of compound 5 (IC50: 4.38 ± 0.11 µM) was as strong as orlistat (IC50: 4.46 ± 0.13 µM), a positive control; the α-glucosidase inhibitory actions of compounds 1-4 and 7-8, and the α-amylase inhibitory actions of compounds 1-8 were medium; the ABTS radical scavenging capacities of compounds 1-3 and 5-8 (IC50: 6.27 ± 0.23 ~ 8.59 ± 0.09 µM) were stronger than l-(+)-ascorbic acid (IC50: 10.06 ± 0.19 µM) served as a positive control. This research offered a theoretical foundation for the leaves of L. robustum to prevent diabetes and its complications.

Harnessing Nuclear Energy to Gold Nanoparticles for the Concurrent Chemoradiotherapy of Glioblastoma.

Nuclear fission reactions can release massive amounts of energy accompanied by neutrons and γ photons, which create a mixed radiation field and enable a series of reactions in nuclear reactors. This study demonstrates a one-pot/one-step approach to synthesizing radioactive gold nanoparticles (RGNP) without using radioactive precursors and reducing agents. Trivalent gold ions are reduced into gold nanoparticles (8.6-146 nm), and a particular portion of 197Au atoms is simultaneously converted to 198Au atoms, rendering the nanoparticles radioactive. We suggest that harnessing nuclear energy to gold nanoparticles is feasible in the interests of advancing nanotechnology for cancer therapy. A combination of RGNP applied through convection-enhanced delivery (CED) and temozolomide (TMZ) through oral administration demonstrates the synergistic effect in treating glioblastoma-bearing mice. The mean survival for RGNP/TMZ treatment was 68.9 ± 9.7 days compared to that for standalone RGNP (38.4 ± 2.2 days) or TMZ (42.8 ± 2.5 days) therapies. Based on the verification of bioluminescence images, positron emission tomography, and immunohistochemistry inspection, the combination treatment can inhibit the proliferation of glioblastoma, highlighting the niche of concurrent chemoradiotherapy (CCRT) attributed to RGNP and TMZ.

MYCT1 attenuates renal fibrosis and tubular injury in diabetic kidney disease.

Tubulointerstitial abnormalities contribute to the progression of diabetic kidney disease (DKD). However, the underlying mechanism of the pathobiology of tubulointerstitial disease is largely unknown. Here, we showed that MYCT1 expression was downregulated in in vitro and in vivo DKD models. Adeno-associated virus (AAV)-Myct1 significantly attenuated renal dysfunction and tubulointerstitial fibrosis in diabetic db/db mice and downregulated Sp1 transcription and TGF-ß1/SMAD3 pathway activation. In human proximal tubular epithelial cells, high glucose-induced high expression of SP1 and TGF-ß1/SMAD3 pathway activation as well as overaccumulation of extracellular matrix (ECM) were abrogated by MYCT1 overexpression. Mechanistically, the binding of VDR to the MYCT1 promoter was predicted and confirmed using dual-luciferase reporter and ChIP analysis. VDR transcriptionally upregulates MYCT1. Our data reveal MYCT1 as a new and potential therapeutic target in treating DKD.

The Mitochondrial Genome of the Holoparasitic Plant Thonningia sanguinea Provides Insights into the Evolution of the Multichromosomal Structure.

Multichromosomal mitochondrial genome (mitogenome) structures have repeatedly evolved in many lineages of angiosperms. However, the underlying mechanism remains unclear. The mitogenomes of three genera of Balanophoraceae, namely Lophophytum, Ombrophytum, and Rhopalocnemis, have already been sequenced and assembled, all showing a highly multichromosomal structure, albeit with different genome and chromosome sizes. It is expected that characterization of additional lineages of this family may expand the knowledge of mitogenome diversity and provide insights into the evolution of the plant mitogenome structure and size. Here, we assembled and characterized the mitogenome of Thonningia sanguinea, which, together with Balanophora, forms a clade sister to the clade comprising Lophophytum, Ombrophytum, and Rhopalocnemis. The mitogenome of T. sanguinea possesses a multichromosomal structure of 18 circular chromosomes of 8.7-19.2 kb, with a total size of 246,247 bp. There are very limited shared regions and poor chromosomal correspondence between T. sanguinea and other Balanophoraceae species, suggesting frequent rearrangements and rapid sequence turnover. Numerous medium- and small-sized repeats were identified in the T. sanguinea mitogenome; however, no repeat-mediated recombination was detected, which was verified by Illumina reads mapping and PCR experiments. Intraspecific mitogenome variations in T. sanguinea are mostly insertions and deletions, some of which can lead to degradation of perfect repeats in one or two accessions. Based on the mitogenome features of T. sanguinea, we propose a mechanism to explain the evolution of a multichromosomal mitogenome from a master circle, which involves mutation in organellar DNA replication, recombination and repair genes, decrease of recombination, and repeat degradation.

SBHA: Sensitive Binary Hashing Autoencoder for Image Retrieval.

Binary hashing is an effective approach for content-based image retrieval, and learning binary codes with neural networks has attracted increasing attention in recent years. However, the training of hashing neural networks is difficult due to the binary constraint on hash codes. In addition, neural networks are easily affected by input data with small perturbations. Therefore, a sensitive binary hashing autoencoder (SBHA) is proposed to handle these challenges by introducing stochastic sensitivity for image retrieval. SBHA extracts meaningful features from original inputs and maps them onto a binary space to obtain binary hash codes directly. Different from ordinary autoencoders, SBHA is trained by minimizing the reconstruction error, the stochastic sensitive error, and the binary constraint error simultaneously. SBHA reduces output sensitivity to unseen samples with small perturbations from training samples by minimizing the stochastic sensitive error, which helps to learn more robust features. Moreover, SBHA is trained with a binary constraint and outputs binary codes directly. To tackle the difficulty of optimization with the binary constraint, we train the SBHA with alternating optimization. Experimental results on three benchmark datasets show that SBHA is competitive and significantly outperforms state-of-the-art methods for binary hashing.

An annotated plant checklist of the transboundary volcanic Mt Elgon, East Africa.

Mt Elgon is an ancient transboundary volcanic mountain found at the Kenya-Uganda boarder possessing high plant diversity. This study documents an updated checklist of the mountain's vascular plants obtained through random-walk field excursions and retrieval of herbarium specimen tracing back to 1900. We compiled 1709 species from 673 genera in 131 families. One new species of the family Cucurbitaceae was also reported. This checklist records respective habitat, habits, elevation ranges, voucher numbers and global distribution ranges of each species. Native and exotic species were also distinguished, where 8.4% of the total species in 49 families were exotic species. There were 103 endemic species, while 14 species were found to be both rare and endemic. IUCN conservation status revealed 2 Critically Endangered, 4 Endangered, 9 Vulnerable and 2 Near Threatened species. This study presents the first and most comprehensive plant inventory of Mt Elgon that will facilitate further ecological and phylogenetic studies.

Circulating tumor cells dynamics during chemotherapy predict survival and response in advanced non-small-cell lung cancer patients.

Background: Circulating tumor cells (CTCs) are prognostic biomarker in non-small-cell lung cancer (NSCLC). CTCs could also be used as predictor of efficacy of systemic treatments in advanced NSCLC. Objectives: We described the dynamic changes of CTCs during first-line platinum-based chemotherapy in advanced NSCLC and clarified the correlation between CTC counts and efficacy of chemotherapy. Design: Chemotherapy is administered and blood specimens are collected at four time points from baseline to disease progression for CTC detection. Methods: This multicenter prospective study enrolled patients with previously untreated stage III or IV NSCLC fit for standard platinum-based chemotherapy. Bloods were sampled as per standard operating procedures at baseline, cycle 1 and cycle 4 of chemotherapy, and at disease progression for CTC analysis using the CellSearch system. Results: Among 150 patients enrolled, median overall survival (OS) was 13.8, 8.4, and 7.9 months in patients with CTC-, KIT-CTC, and KIT+CTC at baseline (p = 0.002). Patients with persistent negative CTC (46.0%) had longer progression-free survival [5.7 months, 95% confidence interval (CI): 5.0-6.5 versus 3.0 months, 0.6-5.4; hazard ratio (HR): 0.34, 95% CI: 0.18-0.67) and OS (13.1 months, 10.9-15.3 versus 5.6 months, 4.1-7.1; HR: 0.17, 0.08-0.36) compared with patients with persistent positive CTC (10.7%), which was not impacted by chemotherapy. Chemotherapy decreased CTC from 36.0% (54/150) to 13.7% (13/95). Conclusions: CTC persistent presence during treatment represents poor prognosis and resistance to chemotherapy in advanced NSCLC. Chemotherapy could effectively eliminate CTCs. Molecular characterization and the functionalization of CTC will be warranted for further intensive investigation. Trial registration: NCT01740804.

PriMPSO: A Privacy-Preserving Multiagent Particle Swarm Optimization Algorithm.

Centralized particle swarm optimization (PSO) does not fully exploit the potential of distributed or parallel computing and suffers from single-point-of-failure. Particularly, each particle in PSO comprises a potential solution (e.g., traveling route and neural network model parameters) which is essentially viewed as private data. Unfortunately, previously neither centralized nor distributed PSO algorithms fail to protect privacy effectively. Inspired by secure multiparty computation and multiagent system, this article proposes a privacy-preserving multiagent PSO algorithm (called PriMPSO) to protect each particle's data and enable private data sharing in a privacy-preserving manner. The goal of PriMPSO is to protect each particle's data in a distributed computing paradigm via existing PSO algorithms with competitive performance. Specifically, each particle is executed by an independent agent with its own data, and all agents jointly perform global optimization without sacrificing any particle's data. Thorough investigations show that selecting an exemplar from all particles and updating particles through the exemplar are critical operations for PSO algorithms. To this end, this article designs a privacy-preserving exemplar selection algorithm and a privacy-preserving triple computation protocol to select exemplars and update particles, respectively. Strict privacy analyses and extensive experiments on a benchmark and a realistic task confirm that PriMPSO not only protects particles' privacy but also has uniform convergence performance with the existing PSO algorithm in approximating an optimal solution.

Contributions to the Flora of Tropical East Africa.

Tropical East Africa (TEA) is one of the most important biodiversity hotspots on the planet. Its rich flora diversity and inventory have been clearly recognized after the publication of the last volume of the Flora of Tropical East Africa (FTEA) in 2012. However, many new and newly recorded taxa have been named and documented since the publication of the first volume of FTEA in 1952. In this study, we comprehensively compiled new taxa and new records by reviewing the literature on the taxonomic contributions of vascular plants in TEA from 1952 to 2022. Our list includes 444 new and newly recorded species belonging to 81 families and 218 genera. Among these taxa, 94.59% of the plants are endemic to TEA and 48.42% are herbs. Additionally, members of Rubiaceae and Aloe are the most numerous family and genus respectively. These new taxa are unevenly distributed in TEA, but are found mainly in areas of high species richness, such as coastal, central and western areas of Kenya, central and southeastern Tanzania. This study offers summative assessment of the newly recorded flora inventory in TEA and provides recommendations for future research on plant diversity survey and conservation.

Epidermal growth factor receptor inhibitors as adjuvant treatment for patients with resected non-small cell lung cancer harboring EGFR mutation: a meta-analysis of randomized controlled clinical trials.

BACKGROUND: The epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) is still under investigation as adjuvant treatment for early-stage disease. Here, we performed a meta-analysis to evaluate the efficacy of adjuvant EGFR-TKI versus non-EGFR-TKI treatment in patients with completely resected non-small cell lung cancer (NSCLC) harboring EGFR mutation. METHODS: Two investigators independently extracted data from databases. A meta-analysis was performed following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The protocol was registered in PROSPERO (ID: CRD42022316481). The primary outcome was disease-free survival (DFS) in patients with EGFR mutation, measured as the hazard ratio (HR). Other outcomes (of subgroup analyses) included overall survival (OS) and DFS. RESULTS: After the systematic screening, eight studies with a total of 3098 patients with stage IB-IIIA NSCLC were included. The results show that in patients with EGFR mutation, the DFS in the adjuvant EGFR-TKI group was significantly superior to that in the control group, with a HR of 0.47 (95% confidence interval [CI]: 0.30-0.74; P = 0.001). In subgroup analyses of DFS, the benefit was observed in the EGFR-TKI group versus the chemotherapy group (HR 0.50, 95% CI 0.30-0.84; P = 0.009), the EGFR-TKI combined with chemotherapy group versus the chemotherapy group (HR 0.37, 95% CI 0.16-0.85; P = 0.02), and in stage IIA-IIIA NSCLC (HR 0.45, 95% CI 0.27-0.74; P = 0.002). However, the benefit of DFS did not translate into improved OS in the whole population (HR 0.79, 95% CI 0.54-1.14; P = 0.20). CONCLUSION: EGFR-TKIs prolonged DFS but not OS in patients with completely resected stage II-IIIA NSCLC harboring EGFR mutation. Longer follow-ups and new clinical trials that can result in changes in clinical practice are needed.

Chemical Constituents from the Leaves of Ligustrum robustum and Their Bioactivities.

The leaves of Ligustrum robustum have been consumed as Ku-Ding-Cha for clearing heat and removing toxins, and they have been used as a folk medicine for curing hypertension, diabetes, and obesity in China. The phytochemical research on the leaves of L. robustum led to the isolation and identification of two new hexenol glycosides, two new butenol glycosides, and five new sugar esters, named ligurobustosides X (1a), X1 (1b), Y (2a), and Y1 (2b) and ligurobustates A (3a), B (3b), C (4b), D (5a), and E (5b), along with seven known compounds (4a and 6-10). Compounds 1-10 were tested for their inhibitory effects on fatty acid synthase (FAS), α-glucosidase, and α-amylase, as well as their antioxidant activities. Compound 2 showed strong FAS inhibitory activity (IC50 4.10 ± 0.12 µM) close to that of the positive control orlistat (IC50 4.46 ± 0.13 µM); compounds 7 and 9 revealed moderate α-glucosidase inhibitory activities; compounds 1-10 showed moderate α-amylase inhibitory activities; and compounds 1 and 10 displayed stronger 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid) ammonium salt (ABTS) radical scavenging effects (IC50 3.41 ± 0.08~5.65 ± 0.19 µM) than the positive control l-(+)-ascorbic acid (IC50 10.06 ± 0.19 µM). This study provides a theoretical foundation for the leaves of L. robustum as a functional tea to prevent diabetes and its complications.

Micro-CT analysis reveals the changes in bone mineral density in zebrafish craniofacial skeleton with age.

Bone has multiple functions in animals, such as supporting the body for mobility. The zebrafish skeleton is composed of craniofacial and axial skeletons. It shares a physiological curvature and consists of a similar number of vertebrae as humans. Bone degeneration and malformations have been widely studied in zebrafish as human disease models. High-resolution imaging and different bone properties such as density and volume can be obtained using micro-computed tomography (micro-CT). This study aimed to understand the possible changes in the structure and bone mineral density (BMD) of the vertebrae and craniofacial skeleton with age (4, 12 and 24 months post fertilisation [mpf]) in zebrafish. Our data showed that the BMD in the vertebrae and specific craniofacial skeleton (mandibular arch, ceratohyal and ethmoid plate) of 12 and 24 mpf fish were higher than that of the 4 mpf fish. In addition, we found the age-dependent increase in BMD was not ubiquitously observed in facial bones, and such differences were not correlated with bone type. In summary, such additional information on the craniofacial skeleton could help in understanding bone development throughout the lifespan of zebrafish.

A swarm-optimizer-assisted simulation and prediction model for emerging infectious diseases based on SEIR.

Mechanism-driven models based on transmission dynamics and statistic models driven by public health data are two main methods for simulating and predicting emerging infectious diseases. In this paper, we intend to combine these two methods to develop a more comprehensive model for the simulation and prediction of emerging infectious diseases. First, we combine a standard epidemic dynamic, the susceptible-exposed-infected-recovered (SEIR) model with population migration. This model can provide a biological spread process for emerging infectious diseases. Second, to determine suitable parameters for the model, we propose a data-driven approach, in which the public health data and population migration data are assembled. Moreover, an objective function is defined to minimize the error based on these data. Third, based on the proposed model, we further develop a swarm-optimizer-assisted simulation and prediction method, which contains two modules. In the first module, we use a level-based learning swarm optimizer to optimize the parameters required in the epidemic mechanism. In the second module, the optimized parameters are used to predicate the spread of emerging infectious diseases. Finally, various experiments are conducted to validate the effectiveness of the proposed model and method.

Recycling of valuable metals from spent lithium-ion batteries by self-supplied reductant roasting.

The massive spent lithium-ion batteries (LIBs) need to be recycled due to their increasing decommission in recent years. This paper aims to propose an effective process that uses self-supplied reductant roasting and acid leaching to recover Lithium, Nickle, Cobalt and Manganese from spent LIBs. In the absence of external carbon resources, the waste membrane from spent LIBs was used as the reductant in the self-supplied reductant roasting. A thermodynamic analysis was conducted to judge the possible reduction reaction between the cathode material and waste membrane. Then, the effects of roasting temperature, roasting time and membrane dosage on the crystal structure and phase transformation of roasting products were investigated and optimized. After the roasting process, the valence state of metals in the cathode material decreased and the structure became loose and porous. Moreover, the layer structure of the cathode material was transformed into groups of Li2CO3, Ni, Co, NiO, CoO and MnO. Further, the reduction effect of cathode powders under each roasting condition was verified under the same leaching conditions. After leaching for 30 min, the leaching efficiencies of Li, Ni, Co and Mn were over 99% under the optimum roasting conditions. Finally, economic assessments proved that the proposed process is profitable. The whole process demonstrates an effective and positive way for recycling spent LIBs and making full use of their waste membrane, which promotes resource recovery and environmental protection.

Edge-Cloud Co-Evolutionary Algorithms for Distributed Data-Driven Optimization Problems.

Surrogate-assisted evolutionary algorithms (EAs) have been proposed in recent years to solve data-driven optimization problems. Most existing surrogate-assisted EAs are for centralized optimization and do not take into account the challenges brought by the distribution of data at the edge of networks in the era of the Internet of Things. To this end, we propose edge-cloud co-EAs (ECCoEAs) to solve distributed data-driven optimization problems, where data are collected by edge servers. Specifically, we first propose a distributed framework of ECCoEAs, which consists of a communication mechanism, edge model management, and cloud model management. This communication mechanism is to avoid deadlock during the collaboration of edge servers and the cloud server. In edge model management, the edge models are trained based on local historical data and data composed of new solutions generated by co-evolutionary and their real evaluation values. In cloud model management, the black-box prediction functions received from edge models are used to find promising solutions to guide the edge model management. Moreover, two ECCoEAs are implemented, which proves the generality of the framework. To verify the performance of algorithms for distributed data-driven optimization problems, we design a novel benchmark test suite. The performance on the benchmarks and practical distributed clustering problems shows the effectiveness of ECCoEAs.

An estimation of distribution algorithm with clustering for scenario-based robust financial optimization.

One important problem in financial optimization is to search for robust investment plans that can maximize return while minimizing risk. The market environment, namely the scenario of the problem in optimization, always affects the return and risk of an investment plan. Those financial optimization problems that the performance of the investment plans largely depends on the scenarios are defined as scenario-based optimization problems. This kind of uncertainty is called scenario-based uncertainty. The consideration of scenario-based uncertainty in multi-objective optimization problem is a largely under explored domain. In this paper, a nondominated sorting estimation of distribution algorithm with clustering (NSEDA-C) is proposed to deal with scenario-based robust financial problems. A robust group insurance portfolio problem is taken as an instance to study the features of scenario-based robust financial problems. A simplified simulation method is applied to measure the return while an estimation model is devised to measure the risk. Applications of the NSEDA-C on the group insurance portfolio problem for real-world insurance products have validated the effectiveness of the proposed algorithm.

MYCT1 alters the glycogen shunt by regulating selective translation of RACK1-mediated enzymes.

MYCT1 has been shown to function as a tumor suppressor in various tumors, but its role in metabolism has never been reported. Here, we showed that global inactivation of Myct1 in mice led to progressive accumulation of glycogen in the liver, which was accompanied by aberrant changes in intermediates of the glycogen metabolic pathway. Mechanistically, MYCT1 appeared to promote translation efficiency of PGM1, UGP2 and GSK3A in hepatic cells in a RACK1-dependent manner. Consequently, upregulation of the three enzymes enhanced the glycogen shunt. Our data reveal a critical role of MYCT1 as a switch for the glycogen shunt in tumor cells.

Using Exciton/Trion Dynamics to Spatially Monitor the Catalytic Activities of MoS2 during the Hydrogen Evolution Reaction.

The adsorption and desorption of electrolyte ions strongly modulates the carrier density or carrier type on the surface of monolayer-MoS2 catalyst during the hydrogen evolution reaction (HER). The buildup of electrolyte ions onto the surface of monolayer MoS2 during the HER may also result in the formation of excitons and trions, similar to those observed in gate-controlled field-effect transistor devices. Using the distinct carrier relaxation dynamics of excitons and trions of monolayer MoS2 as sensitive descriptors, an in situ microcell-based scanning time-resolved liquid cell microscope is set up to simultaneously measure the bias-dependent exciton/trion dynamics and spatially map the catalytic activity of monolayer MoS2 during the HER. This operando probing technique used to monitor the interplay between exciton/trion dynamics and electrocatalytic activity for two-dimensional transition metal dichalcogenides provides an excellent platform to investigate the local carrier behaviors at the atomic layer/liquid electrolyte interfaces during electrocatalytic reaction.