Molecular Basis for Inhibition of Heparanases and ß-Glucuronidases by Siastatin B.

Siastatin B is a potent and effective iminosugar inhibitor of three diverse glycosidase classes, namely, sialidases, ß-d-glucuronidases, and N-acetyl-glucosaminidases. The mode of inhibition of glucuronidases, in contrast to sialidases, has long been enigmatic as siastatin B appears too bulky and incorrectly substituted to be accommodated within a ß-d-glucuronidase active site pocket. Herein, we show through crystallographic analysis of protein-inhibitor complexes that siastatin B generates both a hemiaminal and a 3-geminal diol iminosugar (3-GDI) that are, rather than the parent compound, directly responsible for enzyme inhibition. The hemiaminal product is the first observation of a natural product that belongs to the noeuromycin class of inhibitors. Additionally, the 3-GDI represents a new and potent class of the iminosugar glycosidase inhibitor. To substantiate our findings, we synthesized both the gluco- and galacto-configured 3-GDIs and characterized their binding both structurally and kinetically to exo-ß-d-glucuronidases and the anticancer target human heparanase. This revealed submicromolar inhibition of exo-ß-d-glucuronidases and an unprecedented binding mode by this new class of inhibitor. Our results reveal the mechanism by which siastatin B acts as a broad-spectrum glycosidase inhibitor, identify a new class of glycosidase inhibitor, and suggest new functionalities that can be incorporated into future generations of glycosidase inhibitors.

Metagenomics reveals the variations in functional metabolism associated with greenhouse gas emissions during legume-vegetable rotation process.

Legume-based rotation is commonly recognized for its mitigation efficiency of greenhouse gas (GHG) emissions. However, variations in GHG emission-associated metabolic functions during the legume-vegetable rotation process remain largely uncharacterized. Accordingly, a soybean-radish rotation field experiment was designed to clarify the responses of microbial communities and their GHG emission-associated functional metabolism through metagenomics. The results showed that the contents of soil organic carbon and total phosphorus significantly decreased during the soybean-radish process (P < 0.05), while soil total potassium content and bacterial richness and diversity significantly increased (P < 0.05). Moreover, the predominant bacterial phyla varied, with a decrease in the relative abundance of Proteobacteria and an increase in the relative abundance of Acidobacteria, Gemmatimonadetes, and Chloroflexi. Metagenomics clarified that bacterial carbohydrate metabolism substantially increased during the rotation process, whereas formaldehyde assimilation, methanogenesis, nitrification, and dissimilatory nitrate reduction decreased (P < 0.05). Specifically, the expression of phosphate acetyltransferase (functional methanogenesis gene, pta) and nitrate reductase gamma subunit (functional dissimilatory nitrate reduction gene, narI) was inhibited, indicating of low methane production and nitrogen metabolism. Additionally, the partial least squares path model revealed that the Shannon diversity index was negatively correlated with methane and nitrogen metabolism (P < 0.01), further demonstrating that the response of the soil bacterial microbiome responses are closely linked with GHG-associated metabolism during the soybean-radish rotation process. Collectively, our findings shed light on the responses of soil microbial communities to functional metabolism associated with GHG emissions and provide important insights to mitigate GHG emissions during the rotational cropping of legumes and vegetables.

Development of a prediction model for frailty among older Chinese individuals with type 2 diabetes residing in the community.

METHODS: The study employed a retrospective survey of 458 older individuals with T2D residing in a Chinese community, conducted between June 2020 and May 2021, to develop a predictive model for frailty. Among the participants, 83 individuals (18.1%) were diagnosed with frailty using modified frailty phenotypic criteria. The predictors of frailty in this community-dwelling older population with T2D were determined using least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression. These predictors were utilized to construct a nomogram. The discrimination, calibration, and medical usefulness of the prediction model were assessed through the C-index, calibration plot, and decision curve analysis (DCA), respectively. Additionally, internal validation of the prediction model was conducted using bootstrapping validation. RESULTS: The developed nomogram for frailty prediction predominantly incorporated age, smoking status, regular exercise, depression, albumin (ALB) levels, sleep condition, HbA1c, and polypharmacy as significant predictors. Our prediction model demonstrated excellent discrimination and calibration, as evidenced by a C-index of 0.768 (95% CI, 0.714-0.822) and strong calibration. Internal validation yielded a C-index of 0.732, further confirming the reliability of the model. DCA indicated the utility of the nomogram in identifying frailty among the studied population. CONCLUSION: The development of a predictive model enables a valuable estimation of frailty among community-dwelling older individuals with type 2 diabetes. This evidence-based tool provides crucial guidance to community healthcare professionals in implementing timely preventive measures to mitigate the occurrence of frailty in high-risk patients. By identifying established predictors of frailty, interventions and resources can be appropriately targeted, promoting better overall health outcomes and improved quality of life in this vulnerable population.

Source-specific probabilistic risk evaluation of potentially toxic metal(loid)s in fine dust of college campuses based on positive matrix factorization and Monte Carlo simulation.

Contamination, hazard level and source of 10 widely concerned potentially toxic metal(loid)s (PTMs) Co, As, Pb, Cr, Cu, Zn, Ni, Mn, Ba, and V in fine dust with particle size below 63 µm (FD63) were investigated to assess the environmental quality of college campuses and influencing factors. PTMs sources were qualitatively analyzed using statistical methods and quantitatively apportioned using positive matrix factorization. Probabilistic contamination degrees of PTMs were evaluated using enrichment factor and Nemerow integrated enrichment factor. Eco-health risk levels of content-oriented and source-oriented for PTMs were evaluated using Monte Carlo simulation. Mean levels of Zn (643.8 mg kg-1), Pb (146.0 mg kg-1), Cr (145.9 mg kg-1), Cu (95.5 mg kg-1), and Ba (804.2 mg kg-1) in FD63 were significantly larger than soil background values. The possible sources of the concerned PTMs in FD63 were traffic non-exhaust emissions, natural source, mixed source (auto repair waste, paints and pigments) and traffic exhaust emissions, which accounted for 45.7%, 25.4%, 14.5% and 14.4% of total PTMs contents, respectively. Comprehensive contamination levels of PTMs were very high, mainly caused by Zn pollution and non-exhaust emissions. Combined ecological risk levels of PTMs were low and moderate, chiefly caused by Pb and traffic exhaust emissions. The non-cancer risks of the PTMs in FD63 to college students fell within safety level, while the carcinogenic PTMs in FD63 had a certain cancer risks to college students. The results of source-specific health risk assessment indicated that Cr and As were the priority PTMs, and the mixed source was the priority pollution source of PTMs in FD63 from college campuses, which should be paid attention to by the local government.

Construction of Laterally Asymmetric Heterojunctions with Sub-Micrometer Resolution by Hierarchical Self-Assembly of Polythiophene Nanofibers.

Polymeric semiconductors are crucial candidates for the construction of next-generation flexible and printable electronic devices. By virtue of the successful preparation of monodispersed colloidal solution in orthogonal solvent, poly(3-hexylthiophene) (P3HT) nanofibers are developed into versatile building blocks for nanoelectronics and their compatibilities are verified with photolithographic lift-off technology. Then, the joint efforts from both the bottom-up hierarchical self-assembly and top-down self-alignment technology have led to the realization of lateral asymmetric heterojunctions with resolution better than 1 µm. As a result, planar photovoltaic devices incorporating N,N'-dioctyl-3,4,9,10-perylenedicarboximide and P3HT supramolecular nanowires as active components are constructed with the cathode-to-anode distance being tuned from ≈0.1 to 1-2 µm. Based on such a novel device configuration, an interesting phenomenon of channel-length-dependent photovoltaic efficiency is observed for the first time, strongly suggesting the impact of near-field light intensity on the performance of nanophotonic devices.

Heterogeneous Nuclear Ribonucleoprotein H1 Coordinates with Phytochrome and the U1 snRNP Complex to Regulate Alternative Splicing in Physcomitrella patens.

Plant photoreceptors tightly regulate gene expression to control photomorphogenic responses. Although gene expression is modulated by photoreceptors at various levels, the regulatory mechanism at the pre-mRNA splicing step remains unclear. Alternative splicing, a widespread mechanism in eukaryotes that generates two or more mRNAs from the same pre-mRNA, is largely controlled by splicing regulators, which recruit spliceosomal components to initiate pre-mRNA splicing. The red/far-red light photoreceptor phytochrome participates in light-mediated splicing regulation, but the detailed mechanism remains unclear. Here, using protein-protein interaction analysis, we demonstrate that in the moss Physcomitrella patens, phytochrome4 physically interacts with the splicing regulator heterogeneous nuclear ribonucleoprotein H1 (PphnRNP-H1) in the nucleus, a process dependent on red light. We show that PphnRNP-H1 is involved in red light-mediated phototropic responses in P. patens and that it binds with higher affinity to the splicing factor pre-mRNA-processing factor39-1 (PpPRP39-1) in the presence of red light-activated phytochromes. Furthermore, PpPRP39-1 associates with the core component of U1 small nuclear RNP in P. patens Genome-wide analyses demonstrated the involvement of both PphnRNP-H1 and PpPRP39-1 in light-mediated splicing regulation. Our results suggest that phytochromes target the early step of spliceosome assembly via a cascade of protein-protein interactions to control pre-mRNA splicing and photomorphogenic responses.

Two novel prognostic models for ovarian cancer respectively based on ferroptosis and necroptosis.

BACKGROUND: Platinum-resistant cases account for 25% of ovarian cancer patients. Our aim was to construct two novel prognostic models based on gene expression data respectively from ferroptosis and necroptosis, for predicting the prognosis of advanced ovarian cancer patients with platinum treatment. METHODS: According to the different overall survivals, we screened differentially expressed genes (DEGs) from 85 ferroptosis-related and 159 necroptosis-related gene expression data in the GSE32062 cohort, to establish two ovarian cancer prognostic models based on calculating risk factors of DEGs, and log-rank test was used for statistical significance test of survival data. Subsequently, we validated the two models in the GSE26712 cohort and the GSE17260 cohort. In addition, we took gene enrichment and microenvironment analyses respectively using limma package and GSVA software to compare the differences between high- and low-risk ovarian cancer patients. RESULTS: We constructed two ovarian cancer prognostic models: a ferroptosis-related model based on eight-gene expression signature and a necroptosis-related model based on ten-gene expression signature. The two models performed well in the GSE26712 cohort, but the performance of necroptosis-related model was not well in the GSE17260 cohort. Gene enrichment and microenvironment analyses indicated that the main differences between high- and low- risk ovarian cancer patients occurred in the immune-related indexes, including the specific immune cells abundance and overall immune indexes. CONCLUSION: In this study, ovarian cancer prognostic models based on ferroptosis and necroptosis have been preliminarily validated in predicting prognosis of advanced patients treated with platinum drugs. And the risk score calculated by these two models reflected immune microenvironment. Future work is needed to find out other gene signatures and clinical characteristics to affect the accuracy and applicability of the two ovarian cancer prognostic models.

Review on the COVID-19 pandemic prevention and control system based on AI.

As a new technology, artificial intelligence (AI) has recently received increasing attention from researchers and has been successfully applied to many domains. Currently, the outbreak of the COVID-19 pandemic has not only put people's lives in jeopardy but has also interrupted social activities and stifled economic growth. Artificial intelligence, as the most cutting-edge science field, is critical in the fight against the pandemic. To respond scientifically to major emergencies like COVID-19, this article reviews the use of artificial intelligence in the combat against the pandemic from COVID-19 large data, intelligent devices and systems, and intelligent robots. This article's primary contributions are in two aspects: (1) we summarized the applications of AI in the pandemic, including virus spreading prediction, patient diagnosis, vaccine development, excluding potential virus carriers, telemedicine service, economic recovery, material distribution, disinfection, and health care. (2) We concluded the faced challenges during the AI-based pandemic prevention process, including multidimensional data, sub-intelligent algorithms, and unsystematic, and discussed corresponding solutions, such as 5G, cloud computing, and unsupervised learning algorithms. This article systematically surveyed the applications and challenges of AI technology during the pandemic, which is of great significance to promote the development of AI technology and can serve as a new reference for future emergencies.

Activity-Based Protein Profiling of Retaining α-Amylases in Complex Biological Samples.

Amylases are key enzymes in the processing of starch in many kingdoms of life. They are important catalysts in industrial biotechnology where they are applied in, among others, food processing and the production of detergents. In man amylases are the first enzymes in the digestion of starch to glucose and arguably also the preferred target in therapeutic strategies aimed at the treatment of type 2 diabetes patients through down-tuning glucose assimilation. Efficient and sensitive assays that report selectively on retaining amylase activities irrespective of the nature and complexity of the biomaterial studied are of great value both in finding new and effective human amylase inhibitors and in the discovery of new microbial amylases with potentially advantageous features for biotechnological application. Activity-based protein profiling (ABPP) of retaining glycosidases is inherently suited for the development of such an assay format. We here report on the design and synthesis of 1,6-epi-cyclophellitol-based pseudodisaccharides equipped with a suite of reporter entities and their use in ABPP of retaining amylases from human saliva, murine tissue as well as secretomes from fungi grown on starch. The activity and efficiency of the inhibitors and probes are substantiated by extensive biochemical analysis, and the selectivity for amylases over related retaining endoglycosidases is validated by structural studies.

Design, Synthesis and Structural Analysis of Glucocerebrosidase Imaging Agents.

Gaucher disease (GD) is a lysosomal storage disorder caused by inherited deficiencies in ß-glucocerebrosidase (GBA). Current treatments require rapid disease diagnosis and a means of monitoring therapeutic efficacy, both of which may be supported by the use of GBA-targeting activity-based probes (ABPs). Here, we report the synthesis and structural analysis of a range of cyclophellitol epoxide and aziridine inhibitors and ABPs for GBA. We demonstrate their covalent mechanism-based mode of action and uncover binding of the new N-functionalised aziridines to the ligand binding cleft. These inhibitors became scaffolds for the development of ABPs; the O6-fluorescent tags of which bind in an allosteric site at the dimer interface. Considering GBA's preference for O6- and N-functionalised reagents, a bi-functional aziridine ABP was synthesized as a potentially more powerful imaging agent. Whilst this ABP binds to two unique active site clefts of GBA, no further benefit in potency was achieved over our first generation ABPs. Nevertheless, such ABPs should serve useful in the study of GBA in relation to GD and inform the design of future probes.

Discovery of a Dual Function Cytochrome†P450 that Catalyzes Enyne Formation in Cyclohexanoid Terpenoid Biosynthesis.

The 1,3-enyne moiety is commonly found in cyclohexanoid natural products produced by endophytic and plant pathogenic fungi. Asperpentyn (1) is a 1,3-enyne-containing cyclohexanoid terpenoid isolated from Aspergillus and Pestalotiopsis. The genetic basis and biochemical mechanism of 1,3-enyne biosynthesis in 1, and other natural products containing this motif, has remained enigmatic despite their potential ecological roles. Identified here is the biosynthetic gene cluster and characterization of two crucial enzymes in the biosynthesis of 1. A P450 monooxygenase that has a dual function, to first catalyze dehydrogenation of the prenyl chain to generate a cis-diene intermediate and then serve as an acetylenase to yield an alkyne moiety, and thus the 1,3-enyne, was discovered. A UbiA prenyltransferase was also characterized and it is unusual in that it favors transferring a five-carbon prenyl chain, rather than a polyprenyl chain, to a p-hydroxybenzoic acid acceptor.

Direct Stereoselective Aziridination of Cyclohexenols with 3-Amino-2-(trifluoromethyl)quinazolin-4(3H)-one in the Synthesis of Cyclitol Aziridine Glycosidase Inhibitors.

Cyclophellitol aziridine and its configurational and functional isomers are powerful covalent inhibitors of retaining glycosidases, and find application in fundamental studies on glycosidases, amongst others in relation to inherited lysosomal storage disorders caused by glycosidase malfunctioning. Few direct and stereoselective aziridination methodologies are known for the synthesis of cyclophellitol aziridines. Herein, we present our studies on the scope of direct 3-amino-2-(trifluoromethyl)quinazolin-4(3H)-one-mediated aziridination on a variety of configurational and functional cyclohexenol isosters. We demonstrate that the aziridination can be directed by an allylic or homoallylic hydroxyl through H-bonding and that steric hindrance plays a key role in the diastereoselectivity of the reaction.

Regression analysis of current status data with auxiliary covariates and informative observation times.

This paper discusses regression analysis of current status failure time data with information observations and continuous auxiliary covariates. Under the additive hazards model, we employ a frailty model to describe the relationship between the failure time of interest and censoring time through some latent variables and propose an estimated partial likelihood estimator of regression parameters that makes use of the available auxiliary information. Asymptotic properties of the resulting estimators are established. To assess the finite sample performance of the proposed method, an extensive simulation study is conducted, and the results indicate that the proposed method works well. An illustrative example is also provided.

Constitutive expression of the tzs gene from Agrobacterium tumefaciens virG mutant strains is responsible for improved transgenic plant regeneration in cotton meristem transformation.

KEY MESSAGE : virG mutant strains of a nopaline type of Agrobacterium tumefaciens increase the transformation frequency in cotton meristem transformation. Constitutive cytokinin expression from the tzs gene in the virG mutant strains is responsible for the improvement. Strains of Agrobacterium tumefaciens were tested for their ability to improve cotton meristem transformation frequency. Two disarmed A. tumefaciens nopaline strains with either a virGN54D constitutively active mutation or virGI77V hypersensitive induction mutation significantly increased the transformation frequency in a cotton meristem transformation system. The virG mutant strains resulted in greener explants after three days of co-culture in the presence of light, which could be attributed to a cytokinin effect of the mutants. A tzs knockout strain of virGI77V mutant showed more elongated, less green explants and decreased cotton transformation frequency, as compared to a wild type parental strain, suggesting that expression of the tzs gene is required for transformation frequency improvement in cotton meristem transformation. In vitro cytokinin levels in culture media were tenfold higher in the virGN54D strain, and approximately 30-fold higher in the virGI77V strain, in the absence of acetosyringone induction, compared to the wild type strain. The cytokinin level in the virGN54D strain is further increased upon acetosyringone induction, while the cytokinin level in the virGI77V mutant is decreased by induction, suggesting that different tzs gene expression regulation mechanisms are present in the two virG mutant strains. Based on these data, we suggest that the increased cytokinin levels play a major role in increasing Agrobacterium attachment and stimulating localized division of the attached plant cells.

Effects of PTEN inhibition on the regulation of Tau phosphorylation in rat cortical neuronal injury after oxygen and glucose deprivation.

OBJECTIVE: This report investigated the involvement of the PTEN pathway in the regulation of Tau phosphorylation using an oxygen and glucose deprivation (OGD) model with rat cortical neurons. METHODS: Primary cortical neurons were used to establish the oxygen and glucose deprivation (OGD) model in vitro. These were randomly divided into control, OGD, bpV+OGD, As+OGD, Se+OGD and Mock treatment groups. The neuron viability was assessed by MTT, the cell apoptosis was detected using TUNEL staining. The expression of Phospho-PTEN/PTEN, Phospho-Tau/Tau, Phospho-Akt/Akt and Phospho-GSK-3ß/GSK-3ß were detected by Western blotting. RESULTS: OGD induced Tau phosphorylation through PTEN and glycogen synthase kinase-3ß (GSK-3ß) activation, together with a decrease in AKT activity. Pre-treatment with bpv, a potent PTEN inhibitor, and PTEN antisense nucleotides decreased PTEN and GSK-3ß activity and caused alterations in Tau phosphorylation. Neuronal apoptosis was also reduced. CONCLUSIONS: The PTEN/Akt/GSK-3ß/Tau pathway is involved in the regulation of neuronal injury, providing a novel route for protecting neurons following neonatal HI.

Development of high oleic oil crop platform in flax through RNAi-mediated multiple FAD2 gene silencing.

KEY MESSAGE: Simultaneous gene silencing of both FAD2 genes in high linoleic acid flax leads to high level of oleic acid, which is stable across multiple generations. High oleic oil is one of the preferred traits in oil crop engineering due to its stability and multiple applications as an industrial feedstock. Flax possesses two isoforms of FAD2 enzymes that desaturate monounsaturated oleic acid to polyunsaturated linoleic acid. These two enzymes are encoded by two FAD2 genes. By simultaneous gene silencing both FAD2 genes in high linoleic acid flax, Linola, high level of oleic acid up to 80% was achieved in 69 silencing lines. The high oleic trait was stable across multiple generations with oleic acid reaching up to 77% in homozygote T3 progeny. The RNAi-mediated gene-silencing approach generated high oleic linseed oil, as well as a high oleic platform that can be exploited for further fatty acid engineering.

Distinct phytochrome actions in nonvascular plants revealed by targeted inactivation of phytobilin biosynthesis.

The red/far-red light photoreceptor phytochrome mediates photomorphological responses in plants. For light sensing and signaling, phytochromes need to associate with open-chain tetrapyrrole molecules as the chromophore. Biosynthesis of tetrapyrrole chromophores requires members of ferredoxin-dependent bilin reductases (FDBRs). It was shown that LONG HYPOCOTYL 2 (HY2) is the only FDBR in flowering plants producing the phytochromobilin (PΦB) for phytochromes. However, in the moss Physcomitrella patens, we found a second FDBR that catalyzes the formation of phycourobilin (PUB), a tetrapyrrole pigment usually found as the protein-bound form in cyanobacteria and red algae. Thus, we named the enzyme PUB synthase (PUBS). Severe photomorphogenic phenotypes, including the defect of phytochrome-mediated phototropism, were observed in Physcomitrella patens when both HY2 and PUBS were disrupted by gene targeting. This indicates HY2 and PUBS function redundantly in phytochrome-mediated responses of nonvascular plants. Our studies also show that functional PUBS orthologs are found in selected lycopod and chlorophyte genomes. Using mRNA sequencing for transcriptome profiling, we demonstrate that expression of the majority of red-light-responsive genes are misregulated in the pubs hy2 double mutant. These studies showed that moss phytochromes rapidly repress expression of genes involved in cell wall organization, transcription, hormone responses, and protein phosphorylation but activate genes involved in photosynthesis and stress signaling during deetiolation. We propose that, in nonvascular plants, HY2 and PUBS produce structurally different but functionally similar chromophore precursors for phytochromes. Holophytochromes regulate biological processes through light signaling to efficiently reprogram gene expression for vegetative growth in the light.

High throughput Agrobacterium tumefaciens-mediated germline transformation of mechanically isolated meristem explants of cotton (Gossypium hirsutum L.).

KEY MESSAGE: Agrobacterium tumefaciens mediates high frequency of germline transformation of cotton meristem explants. The meristem transformation system we developed is rapid, high throughput and genotype-flexible. We have developed a high throughput cotton transformation system based on direct Agrobacterium inoculation of mechanically isolated meristem explants of cotton (Gossypium hirsutum L.). The explants were inoculated with a disarmed A. tumefaciens strain, AB33 harboring a 2 T-DNA binary vector pMON114908. This vector contained a gene of interest, an intron-disrupted ß-glucuronidase gene in one T-DNA, and a selectable marker gene, aadA in the other T-DNA. Critical factors, such as method of co-culture, culture temperature during selection, composition of selection medium, and selection scheme were found to influence transformation frequency. The cycle time from initial inoculation to the transplanting of transgenic plants to soil was 7-8 weeks. Stable integration of transgenes and their transmission to progeny were confirmed by molecular and genetic analyses. Transgenes segregated in the expected Mendelian fashion in the T1 generation for most of the transgenic events. It was possible to recover marker-free events in the T1 generation when utilizing a binary vector that contained the selectable marker and gene of interest expression cassettes on independent T-DNAs. The procedure presented here has been used to regenerate thousands of independent transgenic events from multiple varieties with numerous constructs, and we believe it represents a major step forward in cotton transformation technology.

Nicotinamide Mononucleotide improves oocyte maturation of mice with type 1 diabetes.

BACKGROUND: The number of patients with type 1 diabetes rises rapidly around the world in recent years. Maternal diabetes has a detrimental effect on reproductive outcomes due to decreased oocyte quality. However, the strategies to improve the oocyte quality and artificial reproductive technology (ART) efficiency of infertile females suffering from diabetes have not been fully studied. In this study, we aimed to examine the effects of nicotinamide mononucleotide (NMN) on oocyte maturation of mouse with type 1 diabetes mouse and explore the underlying mechanisms of NMN's effect. METHODS: Streptozotocin (STZ) was used to establish the mouse models with type 1 diabetes. The successful establishment of the models was confirmed by the results of body weight test, fasting blood glucose test and haematoxylin and eosin (H&E) staining. The in vitro maturation (IVM) rate of oocytes from diabetic mice was examined. Immunofluorescence staining (IF) was performed to examine the reactive oxygen species (ROS) level, spindle/chromosome structure, mitochondrial function, actin dynamics, DNA damage and histone modification of oocytes, which are potential factors affecting the oocyte quality. The quantitative reverse transcription PCR (RT-qPCR) was used to detect the mRNA levels of Sod1, Opa1, Mfn2, Drp1, Sirt1 and Sirt3 in oocytes. RESULTS: The NMN supplementation increased the oocyte maturation rate of the mice with diabetes. Furthermore, NMN supplementation improved the oocyte quality by rescuing the actin dynamics, reversing meiotic defects, improving the mitochondrial function, reducing ROS level, suppressing DNA damage and restoring changes in histone modifications of oocytes collected from the mice with diabetes. CONCLUSION: NMN could improve the maturation rate and quality of oocytes in STZ-induced diabetic mice, which provides a significant clue for the treatment of infertility of the patients with diabetes.

Flex-DLD: Deep Low-Rank Decomposition Model With Flexible Priors for Hyperspectral Image Denoising and Restoration.

Hyperspectral images (HSIs) are composed of hundreds of contiguous waveband images, offering a wealth of spatial and spectral information. However, the practical use of HSIs is often hindered by the presence of complicated noise caused by various factors such as non-uniform sensor response and dark current. Traditional methods for denoising HSIs rely on constrained optimization approaches, where selecting appropriate prior knowledge is critical for achieving satisfactory results. Nevertheless, these traditional algorithms are limited by hand-crafted priors, leaving room for improvement in their denoising performance. Recently, the supervised deep learning technique has emerged as a promising approach for HSI denoising. However, their requirement for paired training data and poor generalization ability on untrained noise distributions pose challenges in practical applications. In this paper, we design a novel algorithm by the synergism of optimization-based methods and deep learning techniques. Specifically, we introduce a plug-and-play Deep Low-rank Decomposition (DLD) model into the optimization framework. Furthermore, we propose an effective mechanism to incorporate traditional prior knowledge into the DLD model. Finally, we provide a detailed analysis of the optimization process and convergence of the proposed method. Empirical evaluations on various tasks, including hyperspectral image denoising and spectral compressive imaging, demonstrate the superiority of our approach over state-of-the-art methods.