Platelet indices and inflammatory bowel disease: a Mendelian randomization study.

Background: Platelets play a significant role in the innate and adaptive processes of immunity and inflammation. Inflammatory bowel disease (IBD) is an autoimmune disease that is widely understood to be caused by a combination of genetic predisposition, aberrant immune responses, etc. Methods: To examine the relationships between genetically determined platelet indices and IBD, we conducted a Mendelian randomization (MR) study. Data associated with platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), plateletcrit (PCT) were used from the UK Biobank. The outcome data, including IBD, Crohn's disease (CD), ulcerative colitis (UC), were from the FinnGen database. The inverse variance-weighted (IVW), MR-Egger, weighted median methods were used for MR analyses. Results: The MR estimations from the IVW approach show a significant connection between PLT and IBD. Similarly, PCT and IBD have a relationship following the IVW and MR-Egger approaches. While PLT and PCT have strong relationships with CD, according to the findings of all three approaches respectively. Nevertheless, PDW was the only relevant indicator of UC. The only significant result was IVW's. Conclusion: Our findings suggest that the fluctuation of platelet indicators is of great significance in the development of IBD. PLT and PCT have a close association with IBD and CD, respectively; PDW only has a connection with UC. Platelets play an important role in the progression of IBD (UC, CD).

Investigation of the differential susceptibility of extraocular muscles in patients diagnosed with ocular myasthenia gravis based on the computerized diplopia test and the Ocular Motor Nerve Palsy Scale.

Introduction: The pattern of extraocular muscle involvement in ocular myasthenia gravis varies across different reports, diverging from our own observations. Thus, we employed two novel tools to discern this pattern. Methods: A retrospective analysis was conducted to collect and organize clinical data from 43 patients diagnosed with ocular myasthenia gravis. Each patient underwent both the computerized diplopia test and the Ocular Motor Nerve Palsy Scale assessment to evaluate the involvement of extraocular muscles. Results: Among the patients, there were 30 male and 13 female individuals, with a total of 113 affected extraocular muscles identified. Among all the affected extraocular muscles, the involvement of the levator palpebrae superioris muscle accounted for 35.40%, medial rectus muscle 7.7%, lateral rectus muscle 16.81%, superior rectus muscle 13.27%, inferior rectus muscle 12.39%, superior oblique muscle 1.77%, and inferior oblique muscle 2.65% of the total affected extraocular muscles. The positivity rates of the Neostigmine test were 89.19%, AChR antibody detection was 59.38%, and repetitive nerve stimulation was 34.38%. The AChR antibody positive rate among patients with only diplopia was 100%; among those with only ptosis, it was 80%; and among those with both diplopia and ptosis, it was 86.67%. Conclusion: The involvement of the extraocular muscles is not uniform. The levator palpebrae superioris exhibits the highest incidence rate, followed by the four rectus muscles and two oblique muscles. The inferior oblique involvement typically occurs when four or more EOMs are affected. Moreover, the levator palpebrae superioris and medial rectus show a higher tendency for bilateral involvement compared with other extraocular muscles.

Characterization of Gut Microbiota in Rats and Rhesus Monkeys After Methamphetamine Self-administration.

Methamphetamine (MA) is one of the most abused drugs globally, but the mechanism of its addiction remains unclear. Several animal studies have shown that the gut microbiota (GM) influences addictive behaviors, but the pattern of GM changes during addiction in animals of different species remains unclear. The aim of this study was to explore the association between dynamic changes in GM and MA self-administration acquisition among two classical mammals, rhesus monkeys (Macaca mulatta) and rats, MA self-administration models. Male Sprague-Dawley rats and male rhesus monkeys were subjected to classical MA self-administration training, and fecal samples were collected before and after MA self-administration training, respectively. 16S rRNA sequencing was used for GM analyses. We found that GM changes were more pronounced in rats than in rhesus monkeys, as evidenced by more GM taxa producing significant differences before and after MA self-administration training in rats than in monkeys. We also found that the expression of the genus Clostridia_vadinBB60_group significantly decreased after MA self-administration training in both rats and rhesus monkeys. Lactobacillus changes were significantly negatively correlated with total MA uptake in rats (Pearson R = - 0.666, p = 0.035; Spearman R = - 0.721, p = 0.023), whereas its change was also highly negatively correlated with total MA uptake in rhesus monkeys (Pearson R = - 0.882, p = 0.118; Spearman R = - 1.000, p = 0.083), although this was not significant. These findings suggest that MA causes significant alterations in GM in both rhesus monkeys and rats and that the genus Lactobacillus might be a common therapeutic target for MA uptake prevention across the species.

LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data.

Neural operators, as a powerful approximation to the non-linear operators between infinite-dimensional function spaces, have proved to be promising in accelerating the solution of partial differential equations (PDE). However, it requires a large amount of simulated data, which can be costly to collect. This can be avoided by learning physics from the physics-constrained loss, which we refer to it as mean squared residual (MSR) loss constructed by the discretized PDE. We investigate the physical information in the MSR loss, which we called long-range entanglements, and identify the challenge that the neural network requires the capacity to model the long-range entanglements in the spatial domain of the PDE, whose patterns vary in different PDEs. To tackle the challenge, we propose LordNet, a tunable and efficient neural network for modeling various entanglements. Inspired by the traditional solvers, LordNet models the long-range entanglements with a series of matrix multiplications, which can be seen as the low-rank approximation to the general fully-connected layers and extracts the dominant pattern with reduced computational cost. The experiments on solving Poisson's equation and (2D and 3D) Navier-Stokes equation demonstrate that the long-range entanglements from the MSR loss can be well modeled by the LordNet, yielding better accuracy and generalization ability than other neural networks. The results show that the Lordnet can be 40× faster than traditional PDE solvers. In addition, LordNet outperforms other modern neural network architectures in accuracy and efficiency with the smallest parameter size.

Zn-Mediated Fragmentation of N-Alkoxyphthalimides Enabling the Synthesis of gem-Difluoroalkenes.

Zn-mediated generation of alkoxyl radicals from N-alkoxyphthalimides emerged as an efficient approach for forming diverse and valuable alkyl radicals through ß-scission or a hydrogen atom transfer process. The alkyl radical species can be further trapped by α-trifluoromethyl alkenes to construct a series of gem-difluoroalkenes.

Advances in genomics and genome editing for improving strawberry (Fragaria ×ananassa).

The cultivated strawberry, Fragaria ×ananassa, is a recently domesticated fruit species of economic interest worldwide. As such, there is significant interest in continuous varietal improvement. Genomics-assisted improvement, including the use of DNA markers and genomic selection have facilitated significant improvements of numerous key traits during strawberry breeding. CRISPR/Cas-mediated genome editing allows targeted mutations and precision nucleotide substitutions in the target genome, revolutionizing functional genomics and crop improvement. Genome editing is beginning to gain traction in the more challenging polyploid crops, including allo-octoploid strawberry. The release of high-quality reference genomes and comprehensive subgenome-specific genotyping and gene expression profiling data in octoploid strawberry will lead to a surge in trait discovery and modification by using CRISPR/Cas. Genome editing has already been successfully applied for modification of several strawberry genes, including anthocyanin content, fruit firmness and tolerance to post-harvest disease. However, reports on many other important breeding characteristics associated with fruit quality and production are still lacking, indicating a need for streamlined genome editing approaches and tools in Fragaria ×ananassa. In this review, we present an overview of the latest advancements in knowledge and breeding efforts involving CRISPR/Cas genome editing for the enhancement of strawberry varieties. Furthermore, we explore potential applications of this technology for improving other Rosaceous plant species.

Anti-MRSA mechanism of spirostane saponin in Rohdea pachynema F.T.Wang & tang.

ETHNOPHARMACOLOGY RELEVANCE: Rohdea pachynema F.T.Wang & Tang (R. pachynema), is a traditional folk medicine used for the treatment of stomach pain, stomach ulcers, bruises, and skin infections in China. Some of the diseases may relate to microbial infections in traditional applications. However few reports on its antimicrobial properties and bioactive components. AIM OF THE STUDY: To identify its bioactive constituents against methicillin-resistant Staphylococcus aureus (MRSA) in vitro and in vivo, and its mechanism. MATERIALS AND METHODS: The anti-MRSA ingredient 6α-O-[ß-D-xylopyranosyl-(1 â†’ 3)-ß-D-quinovopyranosyl]-(25S)-5α-spirostan-3ß-ol (XQS) was obtained from R. pachynema by phytochemical isolation. Subsequently, XQS underwent screening using the broth microdilution method and growth inhibition curves to assess its antibacterial activity. The mechanism of XQS was evaluated by multigeneration induction, biofilm resistance assay, scanning electron microscopy, transmission electron microscopy, and metabolomics. Additionally, a mouse skin infection model was established in vivo. RESULTS: 26 compounds were identified from the R. pachynema, in which anti-MRSA spirostane saponin (XQS) was reported for the first time with a minimum inhibitory concentration (MIC) of 8 µg/mL. XQS might bind to peptidoglycan (PGN) of the cell wall, phosphatidylglycerol (PG), and phosphatidylethanolamine (PE) of the cell membrane, then destroying the cell wall and the cell membrane, resulting in reduced membrane fluidity and membrane depolarization. Furthermore, XQS affected MRSA lipid metabolism, amino acid metabolism, and ABC transporters by metabolomics analysis, which targeted cell walls and membranes causing less susceptibility to drug resistance. Furthermore, XQS (8 mg/kg) recovered skin wounds in mice infected by MRSA effectively, superior to vancomycin (8 mg/kg). CONCLUSIONS: XQS showed anti-MRSA bioactivity in vitro and in vivo, and its mechanism association with cell walls and membranes was reported for the first, which supported the traditional uses of R. pachynema and explained its sensitivity to MRSA.

Mesenchymal stem cell-derived exosomes as a new drug carrier for the treatment of spinal cord injury: A review.

Spinal cord injury (SCI) is a devastating traumatic disease seriously impairing the quality of life in patients. Expectations to allow the hopeless central nervous system to repair itself after injury are unfeasible. Developing new approaches to regenerate the central nervous system is still the priority. Exosomes derived from mesenchymal stem cells (MSC-Exo) have been proven to robustly quench the inflammatory response or oxidative stress and curb neuronal apoptosis and autophagy following SCI, which are the key processes to rescue damaged spinal cord neurons and restore their functions. Nonetheless, MSC-Exo in SCI received scant attention. In this review, we reviewed our previous work and other studies to summarize the roles of MSC-Exo in SCI and its underlying mechanisms. Furthermore, we also focus on the application of exosomes as drug carrier in SCI. In particular, it combs the advantages of exosomes as a drug carrier for SCI, imaging advantages, drug types, loading methods, etc., which provides the latest progress for exosomes in the treatment of SCI, especially drug carrier.

[The Role of NK Cells in Allogeneic Hematopoietic Stem Cell Micro-Transplantation for Acute Myeloid leukemia].

OBJECTIVE: To explore the role of NK cells in allogeneic hematopoietic stem cell micro-transplantation(MST) in the treatment of patients with acute myeloid leukemia(AML). METHODS: Data from 93 AML patients treated with MST at our center from 2013-2018 were retrospectively analyzed. The induction regimen was anthracycline and cytarabine combined with peripheral blood stem cells transplantation mobilization by granulocyte colony stimulating factor (GPBSC), followed by 2-4 courses of intensive treatment with medium to high doses of cytarabine combined with GPBSC after achieving complete remission (CR). The therapeutic effects of one and two courses of MST induction therapy on 42 patients who did not reach CR before transplantation were evaluated. Cox proportional hazards regression analysis was used to analyze the impact of donor NK cell dose and KIR genotype, including KIR ligand mismatch, 2DS1, haplotype, and HLA-Cw ligands on survival prognosis of patients. RESULTS: Forty-two patients received MST induction therapy, and the CR rate was 57.1% after 1 course and 73.7% after 2 courses. Multivariate analysis showed that, medium and high doses of NK cells was significantly associated with improved disease-free survival (DFS) of patients (HR=0.27, P =0.005; HR=0.21, P =0.001), and high doses of NK cells was significantly associated with improved overall survival (OS) of patients (HR=0.15, P =0.000). Donor 2DS1 positive significantly increases OS of patients (HR=0.25, P =0.011). For high-risk patients under 60 years old, patients of the donor-recipient KIR ligand mismatch group had longer DFS compared to the nonmismatch group (P =0.036); donor 2DS1 positive significantly prolonged OS of patients (P =0.009). CONCLUSION: NK cell dose, KIR ligand mismatch and 2DS1 influence the therapeutic effect of MST, improve the survival of AML patients.

Targeted inhibition of the PI3K/AKT/mTOR pathway by (+)-anthrabenzoxocinone induces cell cycle arrest, apoptosis, and autophagy in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC), characterized by low survival rates and a high recurrence rate, is a major cause of cancer-related mortality. Aberrant activation of the PI3K/AKT/mTOR signaling pathway is a common driver of NSCLC. Within this study, the inhibitory activity of (+)-anthrabenzoxocinone ((+)-ABX), an oxygenated anthrabenzoxocinone compound derived from Streptomyces, against NSCLC is demonstrated for the first time both in vitro and in vivo. Mechanistically, it is confirmed that the PI3K/AKT/mTOR signaling pathway is targeted and suppressed by (+)-ABX, resulting in the induction of S and G2/M phase arrest, apoptosis, and autophagy in NSCLC cells. Additionally, the augmentation of intracellular ROS levels by (+)-ABX is revealed, further contributing to the inhibition of the signaling pathway and exerting inhibitory effects on tumor growth. The findings presented in this study suggest that (+)-ABX possesses the potential to serve as a lead compound for the treatment of NSCLC.

Tryptophan catabolism via the kynurenine pathway regulates infection and inflammation: from mechanisms to biomarkers and therapies.

BACKGROUND: L-Tryptophan (L-Trp), an essential amino acid, is the only amino acid whose level is regulated specifically by immune signals. Most proportions of Trp are catabolized via the kynurenine (Kyn) pathway (KP) which has evolved to align the food availability and environmental stimulation with the host pathophysiology and behavior. Especially, the KP plays an indispensable role in balancing the immune activation and tolerance in response to pathogens. SCOPE OF REVIEW: In this review, we elucidate the underlying immunological regulatory network of Trp and its KP-dependent catabolites in the pathophysiological conditions by participating in multiple signaling pathways. Furthermore, the KP-based regulatory roles, biomarkers, and therapeutic strategies in pathologically immune disorders are summarized covering from acute to chronic infection and inflammation. MAJOR CONCLUSIONS: The immunosuppressive effects dominate the functions of KP induced-Trp depletion and KP-produced metabolites during infection and inflammation. However, the extending minor branches from the KP are not confined to the immune tolerance, instead they go forward to various functions according to the specific condition. Nevertheless, persistent efforts should be made before the clinical use of KP-based strategies to monitor and cure infectious and inflammatory diseases.

Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling study.

Background: Influenza A virus have a distinctive ability to exacerbate SARS-CoV-2 infection proven by in vitro studies. Furthermore, clinical evidence suggests that co-infection with COVID-19 and influenza not only increases mortality but also prolongs the hospitalization of patients. COVID-19 is in a small-scale recurrent epidemic, increasing the likelihood of co-epidemic with seasonal influenza. The impact of co-infection with influenza virus and SARS-CoV-2 on the population remains unstudied. Method: Here, we developed an age-specific compartmental model to simulate the co-circulation of COVID-19 and influenza and estimate the number of co-infected patients under different scenarios of prevalent virus type and vaccine coverage. To decrease the risk of the population developing severity, we investigated the minimum coverage required for the COVID-19 vaccine in conjunction with the influenza vaccine, particularly during co-epidemic seasons. Result: Compared to the single epidemic, the transmission of the SARS-CoV-2 exhibits a lower trend and a delayed peak when co-epidemic with influenza. Number of co-infection cases is higher when SARS-CoV-2 co-epidemic with Influenza A virus than that with Influenza B virus. The number of co-infected cases increases as SARS-CoV-2 becomes more transmissible. As the proportion of individuals vaccinated with the COVID-19 vaccine and influenza vaccines increases, the peak number of co-infected severe illnesses and the number of severe illness cases decreases and the peak time is delayed, especially for those >60 years old. Conclusion: To minimize the number of severe illnesses arising from co-infection of influenza and COVID-19, in conjunction vaccinations in the population are important, especially priority for the elderly.

Examining preharvest genetic and morphological factors contributing to lettuce (Lactuca sativa L.) shelf-life.

Lettuce is a highly perishable horticultural crop with a relatively short shelf-life that limits its commercial value and contributes to food waste. Postharvest senescence varies with influences of both environmental and genetic factors. From a larger pool of romaine lettuce genotypes, we identified three genotypes with variable shelf lives and evaluated their leaf morphology characteristics and transcriptomic profiles at preharvest to predict postharvest quality. Breeding line 60184 had the shortest shelf-life (SSL), cultivar 'Manatee' had an intermediate shelf-life (ISL), and 'Okeechobee' had the longest shelf-life (LSL). We observed significantly larger leaf lamina thickness and higher stomatal index in the SSL genotypes relative to the LSL cultivar. To identify molecular indicators of shelf-life, we used a transcriptional approach between two of the contrasting genotypes, breeding line 60184 and cultivar 'Okeechobee' at preharvest. We identified 552 upregulated and 315 downregulated differentially expressed genes between the genotypes, from which 27% of them had an Arabidopsis thaliana ortholog previously characterized as senescence associated genes (SAGs). Notably, we identified several SAGs including several related to jasmonate ZIM-domain jasmonic acid signaling, chlorophyll a-b binding, and cell wall modification including pectate lyases and expansins. This study presented an innovative approach for identifying preharvest molecular factors linked to postharvest traits for prolonged shelf.

Randomness Regularization With Simple Consistency Training for Neural Networks.

Randomness is widely introduced in neural network training to simplify model optimization or avoid the over-fitting problem. Among them, dropout and its variations in different aspects (e.g., data, model structure) are prevalent in regularizing the training of deep neural networks. Though effective and performing well, the randomness introduced by these dropout-based methods causes nonnegligible inconsistency between training and inference. In this paper, we introduce a simple consistency training strategy to regularize such randomness, namely R-Drop, which forces two output distributions sampled by each type of randomness to be consistent. Specifically, R-Drop minimizes the bidirectional KL-divergence between two output distributions produced by dropout-based randomness for each training sample. Theoretical analysis reveals that R-Drop can reduce the above inconsistency by reducing the inconsistency among the sampled sub structures and bridging the gap between the loss calculated by the full model and sub structures. Experiments on 7 widely-used deep learning tasks ( 23 datasets in total) demonstrate that R-Drop is universally effective for different types of neural networks (i.e., feed-forward, recurrent, and graph neural networks) and different learning paradigms (supervised, parameter-efficient, and semi-supervised). In particular, it achieves state-of-the-art performances with the vanilla Transformer model on WMT14 English → German translation ( 30.91 BLEU) and WMT14 English → French translation ( 43.95 BLEU), even surpassing models trained with extra large-scale data and expert-designed advanced variants of Transformer models.

Tissue-specific proteome profile analysis reveals regulatory and stress responsive networks in passion fruit during storage.

Passiflora edulis, commonly known as passion fruit, is a crop with a fragrant aroma and refreshingly tropical flavor that is a valuable source of antioxidants. It offers a unique opportunity for growers because of its adaptability to tropical and subtropical climates. Passion fruit can be sold in the fresh market or used in value-added products, but its postharvest shelf life has not been well-researched, nor have superior cultivars been well-developed. Understanding the proteins expressed at the tissue level during the postharvest stage can help improve fruit quality and extend shelf life. In this study, we carried out comparative proteomics analysis on four passion fruit tissues, the epicarp, mesocarp, endocarp, and pulp, using multiplexed isobaric tandem mass tag (TMT) labeling quantitation. A total of 3352 proteins were identified, including 295 differentially expressed proteins (DEPs). Of these DEPs, 213 showed a fold increase greater than 1.45 (50 proteins) or a fold decrease less than 0.45 (163 proteins) with different patterns among tissue types. Among the DEPs, there were proteins expressed with functions in oxygen scavenging, lipid peroxidation, response to heat stress, and pathogen resistance. Thirty-six proteins were designated as hypothetical proteins were characterized for potential functions in immunity, cell structure, homeostasis, stress response, protein metabolism and miraculin biosynthesis. This research provides insight into tissue-specific pathways that can be further studied within fruit physiology and postharvest shelf life to aid in implementing effective plant breeding programs. Knowing the tissue-specific function of fruit is essential for improving fruit quality, developing new varieties, identifying health benefits, and optimizing processing techniques.

Shrinkage Reduction in Nanopore-Rich Cement Paste Based on Facile Organic Modification of Montmorillonite.

The organic modification of montmorillonite was successfully achieved using cetyltrimethyl ammonium bromide under facile conditions. The modified montmorillonite was subsequently used for the fabrication of montmorillonite-induced nanopore-rich cement paste (MNCP), and the shrinkage behavior and fundamental performance of MNCP were also investigated. The results indicate that alkali cations on a montmorillonite layer surface were exchanged by using CTAB under 80 °C, successfully achieving the organic modification of montmorillonite. As a pore-forming agent, the modified montmorillonite caused a reduction in shrinkage: the 28-day autogenous shrinkage at a design density of 400 kg/m3 and 800 kg/m3 was reduced to 2.05 mm/m and 0.24 mm/m, and the highest reduction percentages during the 28-day drying shrinkage were 68.1% and 62.2%, respectively. The enlarged interlamellar pores and hydrophobic effects caused by the organic modification of montmorillonite aided this process. Organic-modified montmorillonite had a minor influence on dry density and thermal conductivity and could contribute to an enhancement of strength in MNCP.

Functional Composite Dual-Phase In Situ Self-Reconstruction Design for High-Energy-Density Li-Rich Cathodes.

The unique anionic redox mechanism provides, high-capacity, irreversible oxygen release and voltage/capacity degradation to Li-rich cathode materials (LRO, Li1.2Mn0.54Co0.13Ni0.13O2). In this study, an integrated stabilized carbon-rock salt/spinel composite heterostructured layers (C@spinel/MO) is constructed by in situ self-reconstruction, and the generation mechanism of the in situ reconstructed surface is elucidated. The formation of atomic-level connections between the surface-protected phase and bulk-layered phase contributes to electrochemical performance. The best-performing sample shows a high increase (63%) of capacity retention compared to that of the pristine sample after 100 cycles at 1C, with an 86.7% reduction in surface oxygen release shown by differential electrochemical mass spectrometry. Soft X-ray results show that Co3+ and Mn4+ are mainly reduce in the carbothermal reduction reaction and participate in the formation of the spinel/MO rock-salt phase. The results of oxygen release characterized by Differential electrochemical mass spectrometry (DEMS) strongly prove the effectiveness of surface reconstruction.

Assessing Face Image Quality: A Large-Scale Database and a Transformer Method.

The amount of face images has been witnessing an explosive increase in the last decade, where various distortions inevitably exist on transmitted or stored face images. The distortions lead to visible and undesirable degradation on face images, affecting their quality of experience (QoE). To address this issue, this paper proposes a novel Transformer-based method for quality assessment on face images (named as TransFQA). Specifically, we first establish a large-scale face image quality assessment (FIQA) database, which includes 42,125 face images with diversifying content at different distortion types. Through an extensive crowdsource study, we obtain 712,808 subjective scores, which to the best of our knowledge contribute to the largest database for assessing the quality of face images. Furthermore, by investigating the established database, we comprehensively analyze the impacts of distortion types and facial components (FCs) on the overall image quality. Accordingly, we propose the TransFQA method, in which the FC-guided Transformer network (FT-Net) is developed to integrate the global context, face region and FC detailed features via a new progressive attention mechanism. Then, a distortion-specific prediction network (DP-Net) is designed to weight different distortions and accurately predict final quality scores. Finally, the experiments comprehensively verify that our TransFQA method significantly outperforms other state-of-the-art methods for quality assessment on face images.

Dynamics of algal blooms in typical low-latitude plateau lakes: Spatiotemporal patterns and driving factors.

The alpine lakes distributed on the plateau are crucial for the hydrological, and biogeochemical cycle, and also serve as a guarantee for regional economic development and human survival. However, under the influence of human interference and climate fluctuations, lakes are facing problems of eutrophication and subsequent algal blooms (ABs) with acceleration, and the development and driving factors of this phenomenon need to be considered as a whole. In this study, ten lakes located on the Yunnan-Guizhou Plateau were selected as the study area to analyze the spatiotemporal distribution of ABs and possible controlling forces. The FAI (Floating Algae Index) derived from multiple MODIS products and water quality data under high-frequency monitoring were selected as the data sources for characterizing ABs. Three nutrient parameters and five meteorological variables were used to explore the driving factors affecting ABs. Various methods of trend detection and correlation analysis have been applied. The main results are as follows: (1) Dianchi Lake (in lake area) and Xingyun Lake (in area proportion) are the two lakes with the most serious ABs in the historical period; (2) ABs are mainly distributed on the shoreline and northern edge of lakes, and tend to stay away from the lake center during high-temperature periods of the day; (3) Six lakes show a decreasing trend in ABs, especially after 2018, while other lakes (including Fuxian, Chenghai, Yangzong, and Erhai) are increasing, not only in peak value but also in duration; (4) Lakes with severe ABs are all P-restricted lakes, the minimum temperature is the most sensitive meteorological factor, while the impact of precipitation against ABs has a time lag; (5) Establishing a warning system of temperature and nutrient concentration is critical in ABs adaptive strategy. This study is expected to provide scientific references for regional water management and the restoration of the eutrophic aquatic ecosystem.

NaturalSpeech: End-to-End Text-to-Speech Synthesis With Human-Level Quality.

Text-to-speech (TTS) has made rapid progress in both academia and industry in recent years. Some questions naturally arise that whether a TTS system can achieve human-level quality, how to define/judge that quality, and how to achieve it. In this paper, we answer these questions by first defining the human-level quality based on the statistical significance of subjective measure and introducing appropriate guidelines to judge it, and then developing a TTS system called NaturalSpeech that achieves human-level quality on benchmark datasets. Specifically, we leverage a variational auto-encoder (VAE) for end-to-end text-to-waveform generation, with several key modules to enhance the capacity of the prior from text and reduce the complexity of the posterior from speech, including phoneme pre-training, differentiable duration modeling, bidirectional prior/posterior modeling, and a memory mechanism in VAE. Experimental evaluations on the popular LJSpeech dataset show that our proposed NaturalSpeech achieves -0.01 CMOS (comparative mean opinion score) to human recordings at the sentence level, with Wilcoxon signed rank test at p-level p >> 0.05, which demonstrates no statistically significant difference from human recordings for the first time.