Morusin shows potent antitumor activity for melanoma through apoptosis induction and proliferation inhibition.

BACKGROUND: The discovery of new anti-melanoma drugs with low side effect is urgently required in the clinic. Recent studies showed that morusin, a flavonoid compound isolated from the root bark of Morus Alba, has the potential to treat multiple types of cancers, including breast cancer, gastric cancer, and prostate cancer. However, the anti-cancer effect of morusin on melanoma cells has not been investigated. METHODS: We analyzed the effects of morusin on the proliferation, cell cycle, apoptosis, cell migration and invasion ability of melanoma cells A375 and MV3, and further explored the effects of morusin on tumor formation of melanoma cell. Finally, the effects of morusin on the proliferation, cycle, apoptosis, migration and invasion of A375 cells after knockdown of p53 were detected. RESULTS: Morusin effectively inhibits the proliferation of melanoma cells and induces cell cycle arrest in the G2/M phase. Consistently, CyclinB1 and CDK1 that involved in the G2/M phase transition were down-regulated upon morusin treatment, which may be caused by the up-regulation of p53 and p21. In addition, morusin induces cell apoptosis and inhibits migration of melanoma cells, which correlated with the changes in the expression of the associated molecules including PARP, Caspase3, E-Cadherin and Vimentin. Moreover, morusin inhibits tumor growth in vivo with little side effect on the tumor-burden mice. Finally, p53 knockdown partially reversed morusin-mediated cell proliferation inhibition, cell cycle arrest, apoptosis, and metastasis. CONCLUSION: Collectively, our study expanded the spectrum of the anti-cancer activity of morusin and guaranteed the clinical use of the drug for melanoma treatment.

Pyroptosis, ferroptosis, and autophagy cross-talk in glioblastoma opens up new avenues for glioblastoma treatment.

Glioma is a common primary tumor of the central nervous system (CNS), with glioblastoma multiforme (GBM) being the most malignant, aggressive, and drug resistant. Most drugs are designed to induce cancer cell death, either directly or indirectly, but malignant tumor cells can always evade death and continue to proliferate, resulting in a poor prognosis for patients. This reflects our limited understanding of the complex regulatory network that cancer cells utilize to avoid death. In addition to classical apoptosis, pyroptosis, ferroptosis, and autophagy are recognized as key cell death modalities that play significant roles in tumor progression. Various inducers or inhibitors have been discovered to target the related molecules in these pathways, and some of them have already been translated into clinical treatment. In this review, we summarized recent advances in the molecular mechanisms of inducing or inhibiting pyroptosis, ferroptosis, or autophagy in GBM, which are important for treatment or drug tolerance. We also discussed their links with apoptosis to better understand the mutual regulatory network among different cell death processes. Video Abstract.

An integrated modelling framework for multiple pollution source identification in surface water.

Pollution source identification is vital in water safety management. An integrated simulation-optimization modelling framework comprising a process-based hydrodynamic water quality model, artificial neural network surrogate model and particle swarm optimization (PSO) was proposed to achieve rapid, accurate and reliable pollution source identification. In this study, the hydrodynamics and water quality processes in a straight lab-based flume were simulated to test pollution source identification under steady flow conditions. Additionally, the pollution source identification in the unsteady flow conditions was examined using a real-life estuary, specifically the Yangtze River estuary. First, we developed two process-based models to simulate hydrodynamics and water quality in the flume and estuary. Then, the data generated from the process-based models were used to develop surrogate models. Three typical artificial neural networks (ANNs) algorithms: backpropagation (BP), radial basis function (RBF) and general regression neural networks (GRNN) were selected to develop surrogates for process-based models (PBMs), and they were coupled with PSO algorithm to achieve the hybrid modelling framework for pollution source identification. Our results showed that hybrid PBM-ANNs-PSO models could be applied to identify the pollution source and quantify release intensity in spatial distribution when the discharge type was assumed as the point source with a continuous release. Multiple-performance criteria metrics, in terms of the coefficient of determination, root-mean-square error, mean absolute error, evaluated the model performance as "Excellent prediction". The BP-PSO models consistently appear to be the top-performing source identification model within the developed models, with most cases of relative error (RE) values lower than 5%. The new insights from the hybrid modelling framework would provide useful information for the local government agency to make reasonable decisions regarding pollution source identification issues.

Carpel-specific down-regulation of GhCKXs in cotton significantly enhances seed and fiber yield.

Cytokinin is considered to be an important driver of seed yield. To increase the yield of cotton while avoiding the negative consequences caused by constitutive overproduction of cytokinin, we down-regulated specifically the carpel genes for cytokinin oxidase/dehydrogenase (CKX), a key negative regulator of cytokinin levels, in transgenic cotton. The carpel-specific down-regulation of CKXs significantly enhanced cytokinin levels in the carpels. The elevated cytokinin promoted the expression of carpel- and ovule-development-associated genes, GhSTK2, GhAG1, and GhSHP, boosting ovule formation and thus producing more seeds in the ovary. Field experiments showed that the carpel-specific increase of cytokinin significantly increased both seed yield and fiber yield of cotton, without resulting in detrimental phenotypes. Our study details the regulatory mechanism of cytokinin signaling for seed development, and provides an effective and feasible strategy for yield improvement of seed crops.

First report of green mold disease caused by Penicillium citrinum on Dictyophora rubrovalvata in China.

Dictyophora rubrovolvata is a saprophytic mushroom widely cultivated in China, including Guizhou Province for its high nutritional, medicinal, and economical values (Chen et al. 2021). In May 2021, green mold disease was observed on the fruiting bodies of D. rubrovolvata, causing its death or preventing it from forming a sporocarp, in an indoor-production facility at Asuo village, Baiyun District Guiyang city, Guizhou Province, China (26°73'51" N, 106°72'88" E). The disease incidence was 60%-70% in the affected 1.33-ha growing area, causing a serious economic loss. To identify the causal agent, a total of 15 samples with symptomatic symptoms were collected. Small pieces (5 mm × 5 mm) were cut from the diseased tissues, surface sterilized in 0.4% NaClO for 5 min, washed three times with sterilized water, placed on potato dextrose agar (PDA) medium, and incubated at 24 °C for 7 days. Twenty-one pure cultures were obtained by single-spore isolation method. The colonies were initially white but after seven days as conidia developed they turned green. Hyphae were hyaline and guttulate. Conidiophores were verrucose stipes, triverticulate, and phialides flask shaped. Conidia were smooth and pale green, with subglobose to globose shape measuring 2.0-2.5 × 1.8-2.5 µm (n=50). Based on these morphological characteristics, the isolates matched the description of the genus Penicillium (Visagie et al. 2014). To confirm the identity, DNA of five representative isolates (QS001, QS005, QS008, QS015, QS017) was extracted according to the manufacturer's instructions (Biomiga Fungal DNA Extraction Kit; CA, USA). Afterwards, PCR was performed to amplify ITS region, calmodulin and ß-tubulin genes using primer pairs ITS1/ITS4 (White et al. 1990), CMD5/CMD6 (Glass et al. 1995), and Bt2a/Bt2b (Hong et al. 2006), respectively. BLASTN analysis of these sequences showed the best matches with Penicillium citrinum CBS 139.45 (ITS region: 98.60% (493/500 bp) identity to accession MH856132.1; CMD: 99.79% (469/470 bp) identity to accession MN969245.1; ß-tubulin:100% (407/407 bp) identity to accession GU944545.1). Representative sequences of the sequenced DNA regions were deposited in GenBank (ITS region: OK446552; CMD: OK492612; ß-tubulin: OK482677). Furthermore, a phylogenetic tree was constructed with MEGA 7 based on the concatenated sequences. Koch's postulates were met to confirm the pathogenicity of the representative isolate (QS001) on D. rubrovolvata. Six discs (5mm×5mm) from actively growing P. citrinum QS001 colonies (5-day-old) were placed on six fruiting bodies of D. rubrovolvata (5-month-old). Mock inoculations were performed using PDA discs only without any fungus. The inoculation sites were wrapped with a sterilized 200-µm nylon mesh. All fruiting bodies were incubated at 23°C ± 2°C under a 0-h/24-h photoperiod and 80% relative humidity (RH) after inoculation. After 14 days, green mold was observed on all P. citrinum QS001 inoculated mushrooms. In contrast, no disease was observed in mock inoculated group. The disease assays were repeated three times. P. citrinum QS001 was isolated from all inoculated D. rubrovolvata and verified via the molecular analysis mentioned above. To the best of our knowledge, this is the first report that P. citrinum causes green mold on D. rubrovalvata in China and further studies should focus on managing this disease to prevent any disease outbreaks.

IPD-Net: Infrared Pedestrian Detection Network via Adaptive Feature Extraction and Coordinate Information Fusion.

Infrared pedestrian detection has important theoretical research value and a wide range of application scenarios. Because of its special imaging method, infrared images can be used for pedestrian detection at night and in severe weather conditions. However, the lack of pedestrian feature information in infrared images and the small scale of pedestrian objects makes it difficult for detection networks to extract feature information and accurately detect small-scale pedestrians. To address these issues, this paper proposes an infrared pedestrian detection network based on YOLOv5, named IPD-Net. Firstly, an adaptive feature extraction module (AFEM) is designed in the backbone network section, in which a residual structure with stepwise selective kernel was included to enable the model to better extract feature information under different sizes of the receptive field. Secondly, a coordinate attention feature pyramid network (CA-FPN) is designed to enhance the deep feature map with location information through the coordinate attention module, so that the network gains better capability of object localization. Finally, shallow information is introduced into the feature fusion network to improve the detection accuracy of weak and small objects. Experimental results on the large infrared image dataset ZUT show that the mean Average Precision (mAP50) of our model is improved by 3.6% compared to that of YOLOv5s. In addition, IPD-Net shows various degrees of accuracy improvement compared to other excellent methods.

Antheraea pernyi Suppressor of Cytokine Signaling 2 Negatively Modulates the JAK/STAT Pathway to Attenuate Microbial Infection.

The Janus kinase (JAK) signal transducer and activator of transcription (STAT) pathway has been shown to govern various physiological processes, including immune responses, hematopoiesis, cell growth, and differentiation. Recent studies show that suppressors of cytokine signaling (SOCS) proteins attenuate JAK-STAT signaling in mammals; however, their functions are less clear in lepidopteran insects. Here, we report a full-length sequence of SOCS-2 from the Chinese oak silkworm Antheraea pernyi (designated as ApSOCS-2) and study its biological role in immune responses via the JAK-STAT pathway. ApSOCS-2 expression was high in the fat bodies and hemocytes of A. pernyi fifth instar larvae. After pathogen infection with nucleopolyhedrovirus, Beauveria bassiana, Escherichia coli, and Microccus luteus, ApSOCS-2 mRNA was strongly increased compared to the control group. To elucidate the possible involvement in innate immunity, we measured antimicrobial peptide genes expression profiles in the fat body of A. pernyi. In contrast, recombinant ApSOCS-2 protein administration significantly reduced the AMPs transcription, while the depletion of ApSOCS-2 by RNAi increased their expression. Furthermore, we observed higher antibacterial activity and lower bacterial replication in dsApSOCS-2-treated larvae. The ApSOCS-2 transcription level was reduced in STAT depleted A. pernyi larvae challenged by M. luteus. The ApSOCS-2 RNAi data sets were also subjected to transcriptomic analysis, which suggests that ApSOCS-2 is a key regulator of immune function. Taken together, our data suggest that ApSOCS-2 is required for the negative regulation of AMPs transcripts via the JAK-STAT pathway in the insect.

DNA methylation occurring in Cre-expressing cells inhibits loxP recombination and silences loxP-sandwiched genes.

The low DNA recombination efficiency of site-specific recombinase systems in plants limits their application; however, the underlying mechanism is unknown. We evaluate the gene deletion performance of four recombinase systems (Cre/loxP, Flp/FRT, KD/KDRT and B3/B3RT) in tobacco where the recombinases are under the control of germline-specific promoters. We find that the expression of these recombinases results mostly in gene silencing rather than gene deletion. Using the Cre/loxP system as a model, we reveal that the region flanked by loxP sites (floxed) is hypermethylated, which prevents floxed genes from deletion while silencing the expression of the genes. We further show CG methylation alone in the recombinase binding element of the loxP site is unable to impede gene deletion; instead, CHH methylation in the crossover region is required to inhibit loxP recombination. Our study illustrates the important role of recombinase-induced DNA methylation in the inhibition of site-specific DNA recombination and uncovers the mechanism underlying recombinase-associated gene silence in plants.

A Self-Adaptive Response Strategy for Dynamic Multiobjective Evolutionary Optimization Based on Objective Space Decomposition.

Dynamic multiobjective optimization deals with simultaneous optimization of multiple conflicting objectives that change over time. Several response strategies for dynamic optimization have been proposed, which do not work well for all types of environmental changes. In this article, we propose a new dynamic multiobjective evolutionary algorithm based on objective space decomposition, in which the maxi-min fitness function is adopted for selection and a self-adaptive response strategy integrating a number of different response strategies is designed to handle unknown environmental changes. The self-adaptive response strategy can adaptively select one of the strategies according to their contributions to the tracking performance in the previous environments. Experimental results indicate that the proposed algorithm is competitive and promising for solving different DMOPs in the presence of unknown environmental changes. Meanwhile, the proposed algorithm is applied to solve the parameter tuning problem of a proportional integral derivative (PID) controller of a dynamic system, obtaining better control effect.

A Decomposition-Based Evolutionary Algorithm with Correlative Selection Mechanism for Many-Objective Optimization.

Decomposition-based evolutionary algorithms have been quite successful in dealing with multiobjective optimization problems. Recently, more and more researchers attempt to apply the decomposition approach to solve many-objective optimization problems. A many-objective evolutionary algorithm based on decomposition with correlative selection mechanism (MOEA/D-CSM) is also proposed to solve many-objective optimization problems in this article. Since MOEA/D-SCM is based on a decomposition approach which adopts penalty boundary intersection (PBI), a set of reference points must be generated in advance. Thus, a new concept related to the set of reference points is introduced first, namely, the correlation between an individual and a reference point. Thereafter, a new selection mechanism based on the correlation is designed and called correlative selection mechanism. The correlative selection mechanism finds its correlative individuals for each reference point as soon as possible so that the diversity among population members is maintained. However, when a reference point has two or more correlative individuals, the worse correlative individuals may be removed from a population so that the solutions can be ensured to move toward the Pareto-optimal front. In a comprehensive experimental study, we apply MOEA/D-CSM to a number of many-objective test problems with 3 to 15 objectives and make a comparison with three state-of-the-art many-objective evolutionary algorithms, namely, NSGA-III, MOEA/D, and RVEA. Experimental results show that the proposed MOEA/D-CSM can produce competitive results on most of the problems considered in this study.

Microwell Array Method for Rapid Generation of Uniform Agarose Droplets and Beads for Single Molecule Analysis.

Compartmentalization of aqueous samples in uniform emulsion droplets has proven to be a useful tool for many chemical, biological, and biomedical applications. Herein, we introduce an array-based emulsification method for rapid and easy generation of monodisperse agarose-in-oil droplets in a PDMS microwell array. The microwells are filled with agarose solution, and subsequent addition of hot oil results in immediate formation of agarose droplets due to the surface-tension of the liquid solution. Because droplet size is determined solely by the array unit dimensions, uniform droplets with preselectable diameters ranging from 20 to 100 µm can be produced with relative standard deviations less than 3.5%. The array-based droplet generation method was used to perform digital PCR for absolute DNA quantitation. The array-based droplet isolation and sol-gel switching property of agarose enable formation of stable beads by chilling the droplet array at -20 °C, thus, maintaining the monoclonality of each droplet and facilitating the selective retrieval of desired droplets. The monoclonality of droplets was demonstrated by DNA sequencing and FACS analysis, suggesting the robustness and flexibility of the approach for single molecule amplification and analysis. We believe our approach will lead to new possibilities for a great variety of applications, such as single-cell gene expression studies, aptamer selection, and oligonucleotide analysis.

The phosphatidylinositol synthase gene (GhPIS) contributes to longer, stronger, and finer fibers in cotton.

Cotton fibers are the most important natural raw material used in textile industries world-wide. Fiber length, strength, and fineness are the three major traits which determine the quality and economic value of cotton. It is known that exogenous application of phosphatidylinositols (PtdIns), important structural phospholipids, can promote cotton fiber elongation. Here, we sought to increase the in planta production of PtdIns to improve fiber traits. Transgenic cotton plants were generated in which the expression of a cotton phosphatidylinositol synthase gene (i.e., GhPIS) was controlled by the fiber-specific SCFP promoter element, resulting in the specific up-regulation of GhPIS during cotton fiber development. We demonstrate that PtdIns content was significantly enhanced in transgenic cotton fibers and the elevated level of PtdIns stimulated the expression of genes involved in PtdIns phosphorylation as well as promoting lignin/lignin-like phenolic biosynthesis. Fiber length, strength and fineness were also improved in the transgenic plants as compared to the wild-type cotton, with no loss in overall fiber yield. Our data indicate that fiber-specific up-regulation of PtdIns synthesis is a promising strategy for cotton fiber quality improvement.

Dopamine Surface Modification of Trititanate Nanotubes: Proposed In-Situ Structure Models.

Two models for self-assembled dopamine on the surface of trititanate nanotubes are proposed: individual monomer units linked by π-π stacking of the aromatic regions and mono-attached units interacting through hydrogen bonds. This was investigated with solid state NMR spectroscopy studies and powder X-ray diffraction.

OTUD4 promotes the progression of glioblastoma by deubiquitinating CDK1 and activating MAPK signaling pathway.

Glioblastoma, IDH-Wild type (GBM, CNS WHO Grade 4) is a highly heterogeneous and aggressive primary malignant brain tumor with high morbidity, high mortality, and poor patient prognosis. The global burden of GBM is increasing notably due to limited treatment options, drug delivery problems, and the lack of characteristic molecular targets. OTU deubiquitinase 4 (OTUD4) is a potential predictive factor for several cancers such as breast cancer, liver cancer, and lung cancer. However, its function in GBM remains unknown. In this study, we found that high expression of OTUD4 is positively associated with poor prognosis in GBM patients. Moreover, we provided in vitro and in vivo evidence that OTUD4 promotes the proliferation and invasion of GBM cells. Mechanism studies showed that, on the one hand, OTUD4 directly interacts with cyclin-dependent kinase 1 (CDK1) and stabilizes CDK1 by removing its K11, K29, and K33-linked polyubiquitination. On the other hand, OTUD4 binds to fibroblast growth factor receptor 1 (FGFR1) and reduces FGFR1's K6 and K27-linked polyubiquitination, thereby indirectly stabilizing CDK1, ultimately influencing the activation of the downstream MAPK signaling pathway. Collectively, our results revealed that OTUD4 promotes GBM progression via OTUD4-CDK1-MAPK axis, and may be a prospective therapeutic target for GBM treatment.

Noncontact Perception of Thin-Film Transistors by the Synergy of Both Capacitive and Electrostatic Induction Mechanisms.

In recent years, the rapid expansion of research and application of the Internet of Things and wearable electronics has prompted the development of a variety of sensors to perceive physical or chemical information from both the human body and the environment, among which the proximity sensor is a kind of noncontact sensor used to detect the approach of a target and thus exhibits promising applications in human-machine interactions. Thin-film transistors are one type of key components in modern electronics and have been further developed as electrostatic-induction-type proximity sensors to perceive the approach of electrically charged objects. However, they are immune to the approach of a zero-potential object. Capacitive-induction-type proximity sensors are capable of detecting the approach of conductive targets while being less sensitive to insulated ones. Integration of both electrostatic and capacitive induction mechanisms into one proximity sensor is highly expected to broaden its perception to a variety of targets. Here, an interdigital electrode was introduced as an extended gate into an amorphous metal oxide thin-film transistor to construct proximity sensors that combine both electrostatic and capacitive induction mechanisms and therefore can sensitively perceive the approach of a variety of objects that were electrically charged, grounded, or floated. Besides proximity sensing, remote velocity measurement and positioning of an invasive object were also realized, which further extended its functions as a kind of interdigital-electrode gate transistor.

Controllable Iodoplumbate-Coordination of Hybrid Lead Iodide Perovskites via Additive Engineering for High-Performance Solar Cells.

The crystallization and growth of perovskite crystals are two crucial factors influencing the performance of perovskite solar cells (PSCs). Moreover, iodoplumbate complexes such as PbI2, PbI3-, and PbI42- in perovskite precursor solution dictate both the quality of perovskite crystals and the optoelectrical performance of PSCs. Here, we propose an iodoplumbate-coordination strategy that employs pentafluorophenylsulfonyl chloride (PTFC) as an additive to tailor the crystal quality. This strategy directly affects the thermodynamics and kinetics of perovskite crystal formation by regulating hydrogen bonds or coordination bonds with Pb2+ or I- ions. Subsequently, the synergistic effect of the PTFC and FA+ complex was beneficial for intermediate-to-perovskite phase transition, improving the crystalline quality and reducing the defect density in the perovskite film to suppress nonradiative recombination loss. Consequently, the treated PSCs achieved a power conversion efficiency (PCE) of 24.61%, demonstrating enhanced long-term stability under both light and thermal stress. The developed device retained 92.53% of its initial PCE after 1200 h of continuous illumination and 88.6% of its initial PCE after 600 h of 85 °C thermal stability tests, respectively, both conducted in N2 atmospheres.

A multipopulation PSO based memetic algorithm for permutation flow shop scheduling.

The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS) and individual improvement scheme (IIS). Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA) and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA) and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA), on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP.

[Effects of electroacupuncture on neurological function and expressions of p-JNK and Beclin-1 in traumatic brain injury rats].

OBJECTIVE: To observe the effect of electroacupuncture (EA) on neurological function, the expressions of phosphorylated c-Jun amino terminal kinase (p-JNK) and Beclin-1 in rats with traumatic brain injury (TBI), so as to explore the underlying mechanism of EA in the treatment of TBI. METHODS: A total of 64 SD rats were randomly divided into blank, sham, modeling groups, with 8 rats in the blank group and the sham group and 48 rats in the modeling group. The modified Feeney free-fall impact method was used to establish the TBI rat model. After modeling, rats of the modeling group were randomly divided into model and EA groups, which were further divided into 3 d, 7 d and 14 d subgroups with 8 rats in each group. Rats in the EA group were treated with acupuncture at "Baihui" (GV20, retained for 15 min), "Shuigou" (GV26, stabbed for 20 s), "Neiguan" (PC6) and "Zusanli" (ST36) of the right side. EA (2 Hz, 1 mA) was applied to PC6 and ST36 for 15 min. The above treatments were performed once a day, and different subgroups were continuously stimulated for 3, 7 and 14 days, respectively. The neurological impairment was evaluated by modified neurological severity score(mNSS). The pathological morphological changes and the protein expressions of p-JNK and Beclin-1 in the injured area of the brain were detected by Nissl staining and immunohistochemistry, separately. RESULTS: After modeling, the mNSS and the protein expressions of p-JNK and Beclin-1 were increased (P< 0.05) on day 3, 7 and 14 in the model group relative to the sham group. The Nissl bodies were reduced or even dissolved and neurons were seriously damaged in the model group on the 3rd day, which were mildly repaired on day 7 and 14. Following acupuncture interventions, compared with the model group, the mNSS on day 7 and 14 and the protein expressions of p-JNK and Beclin-1 on day 3, 7 and 14 were decreased (P< 0.05)in the EA group. The status of Nissl bodies and neurons in the EA group was better at all time points than that in the model group. There were no significant differences in the above indicators between the blank group and the sham group. CONCLUSION: EA can significantly improve the neurological function of TBI model rats, which may be related to its effects in down-regulating the protein expressions of p-JNK and Beclin-1 in the injured area of the brain.

Methylation across the central dogma in health and diseases: new therapeutic strategies.

The proper transfer of genetic information from DNA to RNA to protein is essential for cell-fate control, development, and health. Methylation of DNA, RNAs, histones, and non-histone proteins is a reversible post-synthesis modification that finetunes gene expression and function in diverse physiological processes. Aberrant methylation caused by genetic mutations or environmental stimuli promotes various diseases and accelerates aging, necessitating the development of therapies to correct the disease-driver methylation imbalance. In this Review, we summarize the operating system of methylation across the central dogma, which includes writers, erasers, readers, and reader-independent outputs. We then discuss how dysregulation of the system contributes to neurological disorders, cancer, and aging. Current small-molecule compounds that target the modifiers show modest success in certain cancers. The methylome-wide action and lack of specificity lead to undesirable biological effects and cytotoxicity, limiting their therapeutic application, especially for diseases with a monogenic cause or different directions of methylation changes. Emerging tools capable of site-specific methylation manipulation hold great promise to solve this dilemma. With the refinement of delivery vehicles, these new tools are well positioned to advance the basic research and clinical translation of the methylation field.

Targeting serine-glycine-one-carbon metabolism as a vulnerability in cancers.

The serine-glycine-one-carbon (SGOC) metabolic pathway is critical for DNA methylation, histone methylation, and redox homeostasis, in addition to protein, lipid, and nucleotide biosynthesis. The SGOC pathway is a crucial metabolic network in tumorigenesis, wherein the outputs are required for cell survival and proliferation and are particularly likely to be co-opted by aggressive cancers. SGOC metabolism provides an integration point in cell metabolism and is of crucial clinical significance. The mechanism of how this network is regulated is the key to understanding tumor heterogeneity and overcoming the potential mechanism of tumor recurrence. Herein, we review the role of SGOC metabolism in cancer by focusing on key enzymes with tumor-promoting functions and important products with physiological significance in tumorigenesis. In addition, we introduce the ways in which cancer cells acquire and use one-carbon unit, and discuss the recently clarified role of SGOC metabolic enzymes in tumorigenesis and development, as well as their relationship with cancer immunotherapy and ferroptosis. The targeting of SGOC metabolism may be a potential therapeutic strategy to improve clinical outcomes in cancers.