Enhanced classification and severity prediction of major depressive disorder using acoustic features and machine learning.

Background: Previous studies have classified major depression and healthy control groups based on vocal acoustic features, but the classification accuracy needs to be improved. Therefore, this study utilized deep learning methods to construct classification and prediction models for major depression and healthy control groups. Methods: 120 participants aged 16-25 participated in this study, included 64 MDD group and 56 HC group. We used the Covarep open-source algorithm to extract a total of 1200 high-level statistical functions for each sample. In addition, we used Python for correlation analysis, and neural network to establish the model to distinguish whether participants experienced depression, predict the total depression score, and evaluate the effectiveness of the classification and prediction model. Results: The classification modelling of the major depression and the healthy control groups by relevant and significant vocal acoustic features was 0.90, and the Receiver Operating Characteristic (ROC) curves analysis results showed that the classification accuracy was 84.16%, the sensitivity was 95.38%, and the specificity was 70.9%. The depression prediction model of speech characteristics showed that the predicted score was closely related to the total score of 17 items of the Hamilton Depression Scale(HAMD-17) (r=0.687, P<0.01); and the Mean Absolute Error(MAE) between the model's predicted score and total HAMD-17 score was 4.51. Limitation: This study's results may have been influenced by anxiety comorbidities. Conclusion: The vocal acoustic features can not only effectively classify the major depression and the healthy control groups, but also accurately predict the severity of depressive symptoms.

Effects of lactic acid etching on immediate and aged bond strength of resin-dentin bonding interface.

To investigate the effects of lactic acid etching on the immediate and aged bond strength of the resin-dentin bonding interface, the resin-dentin bonding interface was evaluated 24 hours and 6 months later. A total of 42 isolated third molars were randomly divided into 6 experimental groups according to different lactate concentration (35%, 40%, 45%) and acid etching time (30 s, 45 s), with 37% phosphoric acid etching 15 s as a control. In each group, dentin samples were etched under different acidic conditions and bonded with Adper Single Bond 2 (3M ESPE) as directed. The immediate group was immediately stored in deionized water at 37 °C for 24 h, and the aging group was stored in artificial saliva at 37 °C for 6 months. Immediate and aged bond strengths were measured by a micro-tensile tester, and the specimen fracture surface was observed under a microscope. 14 isolated third molars were randomly divided into 7 groups, and each group was etched with acid. Collagen fibers morphology in dentin was examined after gradient dehydration with ethanol by scanning electron microscopy (SEM). Statistically, there was no difference between the resin-dentin immediate bonding strength of 35% lactic acid for 30 s and 37% phosphoric acid for 15 s, but the aged bond strength was greater than that of the phosphoric acid group. According to scanning electron microscope observations, the collagen fiber morphology in 35% and 40% lactate etching dentin 30 s groups was relatively intact compared with other groups. In conclusion, 35% lactic acid etching of dentin 30 s ensures both immediate and aged resin-dentin bond strength.

Proteomic landscape of epithelial ovarian cancer.

Epithelial ovarian cancer (EOC) is a deadly disease with limited diagnostic biomarkers and therapeutic targets. Here we conduct a comprehensive proteomic profiling of ovarian tissue and plasma samples from 813 patients with different histotypes and therapeutic regimens, covering the expression of 10,715 proteins. We identify eight proteins associated with tumor malignancy in the tissue specimens, which are further validated as potential circulating biomarkers in plasma. Targeted proteomics assays are developed for 12 tissue proteins and 7 blood proteins, and machine learning models are constructed to predict one-year recurrence, which are validated in an independent cohort. These findings contribute to the understanding of EOC pathogenesis and provide potential biomarkers for early detection and monitoring of the disease. Additionally, by integrating mutation analysis with proteomic data, we identify multiple proteins related to DNA damage in recurrent resistant tumors, shedding light on the molecular mechanisms underlying treatment resistance. This study provides a multi-histotype proteomic landscape of EOC, advancing our knowledge for improved diagnosis and treatment strategies.

POLM variant G312R promotes ovarian tumorigenesis through genomic instability and COL11A1-NF-κB axis.

In ovarian cancer (OC), identifying key molecular players in disease escalation and chemoresistance remains critical. Our investigation elucidates the role of the DNA polymerase mu (POLM), especially G312R mutation, in propelling oncogenesis through dual pathways. POLMG312R markedly augments the ribonucleotide insertion capability of POLM, precipitating genomic instability. In addition, our research reveals that POLMG312R perturbs collagen alpha-1 (XI) chain (COL11A1) expression-a gene that plays a key role in oncogenesis-and modulates the NF-κB signaling pathway, alters the secretion of downstream inflammatory cytokines, and promotes tumor-macrophage interactions. We illustrate a bidirectional regulatory interaction between POLM, particularly its G312R variant, and COL11A1. This interaction regulates NF-κB signaling, culminating in heightened malignancy and resistance to chemotherapy in OC cells. These insights position the POLM as a potential molecular target for OC therapy, shedding light on the intricate pathways underpinning POLM variant disease progression.NEW & NOTEWORTHY Our research reveals that POLM plays an important role in ovarian cancer development, especially the mutation G312R. We uncover the POLMG312R mutation as a driver of genomic instability in ovarian cancer via aberrant ribonucleotide incorporation. We reveal that POLMG312R upregulates COL11A1 and activates NF-κB signaling, contributing to tumor progression and chemoresistance. This study identifies the POLM-COL11A1-NF-κB axis as a novel oncogenic pathway.

Candidate prognostic biomarkers and prediction models for high-grade serous ovarian cancer from urinary proteomics.

High-grade serous ovarian cancer (HGSOC) is one of the most common histologic types of ovarian cancer. The purpose of this study was to identify potential prognostic biomarkers in urine specimens from patients with HGSOC. First, 56 urine samples with information on relapse-free survival (RFS) months were collected and classified into good prognosis (RFS ≥ 12 months) and poor prognosis (RFS < 12 months) groups. Next, data-independent acquisition (DIA)-based mass spectrometry (MS) analysis was combined with MSFragger-DIA workflow to identify potential prognostic biomarkers in a discovery set (n = 31). With the aid of parallel reaction monitoring (PRM) analysis, four candidate biomarkers (ANXA1, G6PI, SPB3, and SPRR3) were finally validated in both the discovery set and an independent validation set (n = 25). Subsequent RFS and Cox regression analyses confirmed the utility of these candidate biomarkers as independent prognostic factors affecting RFS in patients with HGSOC. Regression models were constructed to predict the 12-month RFS rate, with area under the receiver operating characteristic curve (AUC) values ranging from 0.847 to 0.905. Overall, candidate prognostic biomarkers were identified in urine specimens from patients with HGSOC and prediction models for the 12-month RFS rate constructed. SIGNIFICANCE: OC is one of the leading causes of death due to gynecological malignancies. HGSOC constitutes one of the most common histologic types of OC with aggressive characteristics, accounting for the majority of advanced cases. In cases where patients with advanced HGSOC potentially face high risk of unfavorable prognosis or disease advancement within a 12-month period, intensive medical monitoring is necessary. In the era of precision cancer medicine, accurate prediction of prognosis or 12-month RFS rate is critical for distinguishing patient groups requiring heightened surveillance. Patients could significantly benefit from timely modifications to treatment regimens based on the outcomes of clinical monitoring. Urine is an ideal resource for disease surveillance purposes due to its easy accessibility. Furthermore, molecules excreted in urine are less complex and more stable than those in other liquid samples. In the current study, we identified candidate prognostic biomarkers in urine specimens from patients with HGSOC and constructed prediction models for the 12-month RFS rate.

Apurinic/apyrimidinic endodeoxyribonuclease 1 (APE1) promotes stress granule formation via YBX1 phosphorylation in ovarian cancer.

APE1 is an essential gene involved in DNA damage repair, the redox regulation of transcriptional factors (TFs) and RNA processing. APE1 overexpression is common in cancers and correlates with poor patient survival. Stress granules (SGs) are phase-separated cytoplasmic assemblies that cells form in response to environmental stresses. Precise regulation of SGs is pivotal to cell survival, whereas their dysregulation is increasingly linked to diseases. Whether APE1 engages in modulating SG dynamics is worthy of investigation. In this study, we demonstrate that APE1 colocalizes with SGs and promotes their formation. Through phosphoproteome profiling, we discover that APE1 significantly alters the phosphorylation landscape of ovarian cancer cells, particularly the phosphoprofile of SG proteins. Notably, APE1 promotes the phosphorylation of Y-Box binding protein 1 (YBX1) at S174 and S176, leading to enhanced SG formation and cell survival. Moreover, expression of the phosphomutant YBX1 S174/176E mimicking hyperphosphorylation in APE1-knockdown cells recovered the impaired SG formation. These findings shed light on the functional importance of APE1 in SG regulation and highlight the importance of YBX1 phosphorylation in SG dynamics.

Diagnosing and tracking depression based on eye movement in response to virtual reality.

Introduction: Depression is a prevalent mental illness that is primarily diagnosed using psychological and behavioral assessments. However, these assessments lack objective and quantitative indices, making rapid and objective detection challenging. In this study, we propose a novel method for depression detection based on eye movement data captured in response to virtual reality (VR). Methods: Eye movement data was collected and used to establish high-performance classification and prediction models. Four machine learning algorithms, namely eXtreme Gradient Boosting (XGBoost), multilayer perceptron (MLP), Support Vector Machine (SVM), and Random Forest, were employed. The models were evaluated using five-fold cross-validation, and performance metrics including accuracy, precision, recall, area under the curve (AUC), and F1-score were assessed. The predicted error for the Patient Health Questionnaire-9 (PHQ-9) score was also determined. Results: The XGBoost model achieved a mean accuracy of 76%, precision of 94%, recall of 73%, and AUC of 82%, with an F1-score of 78%. The MLP model achieved a classification accuracy of 86%, precision of 96%, recall of 91%, and AUC of 86%, with an F1-score of 92%. The predicted error for the PHQ-9 score ranged from -0.6 to 0.6.To investigate the role of computerized cognitive behavioral therapy (CCBT) in treating depression, participants were divided into intervention and control groups. The intervention group received CCBT, while the control group received no treatment. After five CCBT sessions, significant changes were observed in the eye movement indices of fixation and saccade, as well as in the PHQ-9 scores. These two indices played significant roles in the predictive model, indicating their potential as biomarkers for detecting depression symptoms. Discussion: The results suggest that eye movement indices obtained using a VR eye tracker can serve as useful biomarkers for detecting depression symptoms. Specifically, the fixation and saccade indices showed promise in predicting depression. Furthermore, CCBT demonstrated effectiveness in treating depression, as evidenced by the observed changes in eye movement indices and PHQ-9 scores. In conclusion, this study presents a novel approach for depression detection using eye movement data captured in VR. The findings highlight the potential of eye movement indices as biomarkers and underscore the effectiveness of CCBT in treating depression.

Proteomic profiling of ovarian clear cell carcinomas identifies prognostic biomarkers for chemotherapy.

Clear cell ovarian carcinoma (CCOC) is a relatively rare subtype of ovarian cancer (OC) with high degree of resistance to standard chemotherapy. Little is known about the underlying molecular mechanisms, and it remains a challenge to predict its prognosis after chemotherapy. Here, we first analyzed the proteome of 35 formalin-fixed paraffin-embedded (FFPE) CCOC tissue specimens from a cohort of 32 patients with CCOC (H1 cohort) and characterized 8697 proteins using data-independent acquisition mass spectrometry (DIA-MS). We then performed proteomic analysis of 28 fresh frozen (FF) CCOC tissue specimens from an independent cohort of 24 patients with CCOC (H2 cohort), leading to the identification of 9409 proteins with DIA-MS. After bioinformatics analysis, we narrowed our focus to 15 proteins significantly correlated with the recurrence free survival (RFS) in both cohorts. These proteins are mainly involved in DNA damage response, extracellular matrix (ECM), and mitochondrial metabolism. Parallel reaction monitoring (PRM)-MS was adopted to validate the prognostic potential of the 15 proteins in the H1 cohort and an independent confirmation cohort (H3 cohort). Interferon-inducible transmembrane protein 1 (IFITM1) was observed as a robust prognostic marker for CCOC in both PRM data and immunohistochemistry (IHC) data. Taken together, this study presents a CCOC proteomic data resource and a single promising protein, IFITM1, which could potentially predict the recurrence and survival of CCOC.

NHC-Catalyzed Chemo- and Enantioselective Reaction between Aldehydes and Enals for Access to Axially Chiral Arylaldehydes.

A chiral carbene-catalyzed chemo- and enantioselective reaction with racemic biaryl aldehydes and α-bromoenals is developed for access to axially chiral 2-arylbenzaldehydes through atroposelective dynamic kinetic resolution (DKR) processes. This atroposelective DKR strategy can tolerate a broad scope of substrates with diverse functionalities. The axially chiral 2-aryl benzaldehyde products generally afford moderate to good yields and enantioselectivities. The axially chiral molecules afforded from the current approach are variable through simple transformations to afford axially chiral functional molecules with excellent optical purities.

A first-in-human study of Brozopentyl Sodium, following single and multiple ascending intravenous infusion in Chinese healthy volunteers.

BACKGROUND: Brozopentyl Sodium (BZP), a novel agent for ischemic stroke, has shown promising results in preclinical pharmacological studies, prompting the initiation of the first-in-human investigation. PURPOSE: This study aimed to assess the safety, tolerability, and pharmacokinetic (PK) characteristics of BZP in Chinese healthy volunteers. METHODS: The study consisted of two parts. Part I was a single-center, randomized, single-blinded, placebo-controlled, single-ascending study with six BZP dose cohorts (SAD: 25, 50, 100, 200, 300, and 400 mg). Part II was a single-center, randomized, single-blinded, placebo-controlled, multi-dose- and dose-elevated study with three BZP dose cohorts (MAD: 50, 100, and 200 mg). Doses were administered once daily on days 1 and 7 and twice daily on days 2-6. The PK properties of BZP and its bioactive metabolites, BNBP, were assessed. Safety and tolerability evaluations were also conducted. RESULTS: In the SAD study, BZP reached peak plasma concentrations (Tmax) at the end of administration, with median Tmax values ranging from 1 to 1.03 h, while BNBP reached Tmax between 1.25 to 1.38 h. The terminal half-lives (T1/2) were approximately 8 h for BZP and 15 h for BNBP. In the MAD study, steady-state plasma concentrations of BZP were reached by day 5. There was minimal accumulation of both BZP and BNBP after 7 days of administration. The area under the plasma concentration-time curve from 0 to time of the last measurable concentration (AUC0-t) and maximum plasma drug concentration (Cmax) showed dose-proportional increases for BZP but not for BNBP in both study parts. Single and multiple doses of BZP demonstrated a good safety profile and were well-tolerated. CONCLUSION: BZP displayed safety, good tolerability and predictable PK characteristics following both single and multiple ascending intravenous administrations. These findings provide a basis for further clinical development of BZP for ischemic stroke patients.

Exposure to Butylparaben Induces Craniofacial Bone Developmental Toxicity in Zebrafish (Danio rerio) Embryos.

Butylparaben (BuP) is a common antibacterial preservative utilized extensively in food, medical supplies, cosmetics, and personal care products. The current study reports the use of Zebrafish (Danio rerio) embryos to investigate potential developmental toxicity caused by exposure to BuP. The development of Neural crest cells (NCCs) is highly active during gastrulation in Zebrafish embryos. Thus, we utilized 0.5 mg/L, 0.75 mg/L, and 1 mg/L BuP solutions, respectively, in accordance with the international safety standard dosage. We observed severe craniofacial cartilage deformities, periocular edema, cardiac dysplasia, and delayed otolith development in the Zebrafish larvae 5 days after exposure. The oxidative stress response was significantly enhanced. In addition, the biochemical analysis revealed that the activities of catalase (CAT) and superoxide dismutase (SOD) were significantly reduced relative to the control group, whereas the concentration of malondialdehyde (MDA) was significantly elevated. Furthermore, ALP activity, a marker of osteoblast activity, was also reduced. Moreover, the RT-qPCR results indicated that the expression of chondrocyte marker genes sox9a, sox9b, and col2a1a was down-regulated. In addition, the morphology of maxillofacial chondrocytes was altered in Zebrafish larvae, and the proliferation of cranial NCCs was inhibited. Accordingly, our findings indicate that strong oxidative stress induced by BuP inhibits the proliferation of NCCs in larval Zebrafish, leading to craniofacial deformities.

The Development of Aldehyde Catalytic System.

Aldehyde catalysts have proven to be highly effective in facilitating and accelerating a wide range of challenging transformations in organic chemistry. This article is structured into three main sections, focusing on the utilization of aldehydes as organocatalysts, the aldehydes/transition metals catalytic systems, and photochemical initiators. Finally, we provide a concise summary of the advancements in this fascinating research field, offering our perspectives and insights.

DPHL v.2: An updated and comprehensive DIA pan-human assay library for quantifying more than 14,000 proteins.

A comprehensive pan-human spectral library is critical for biomarker discovery using mass spectrometry (MS)-based proteomics. DPHL v.1, a previous pan-human library built from 1,096 data-dependent acquisition (DDA) MS data of 16 human tissue types, allows quantifying of 10,943 proteins. Here, we generated DPHL v.2 from 1,608 DDA-MS data. The data included 586 DDA-MS data acquired from 18 tissue types, while 1,022 files were derived from DPHL v.1. DPHL v.2 thus comprises data from 24 sample types, including several cancer types (lung, breast, kidney, and prostate cancer, among others). We generated four variants of DPHL v.2 to include semi-tryptic peptides and protein isoforms. DPHL v.2 was then applied to two colorectal cancer cohorts. The numbers of identified and significantly dysregulated proteins increased by at least 21.7% and 14.2%, respectively, compared with DPHL v.1. Our findings show that the increased human proteome coverage of DPHL v.2 provides larger pools of potential protein biomarkers.

Resistance prediction in high-grade serous ovarian carcinoma with neoadjuvant chemotherapy using data-independent acquisition proteomics and an ovary-specific spectral library.

High-grade serous ovarian carcinoma (HGSOC) is the most common subtype of ovarian cancer with 5-year survival rates below 40%. Neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) is recommended for patients with advanced-stage HGSOC unsuitable for primary debulking surgery (PDS). However, about 40% of patients receiving this treatment exhibited chemoresistance of uncertain molecular mechanisms and predictability. Here, we built a high-quality ovary-specific spectral library containing 130 735 peptides and 10 696 proteins on Orbitrap instruments. Compared to a published DIA pan-human spectral library (DPHL), this spectral library provides 10% more ovary-specific and 3% more ovary-enriched proteins. This library was then applied to analyze data-independent acquisition (DIA) data of tissue samples from an HGSOC cohort treated with NACT, leading to 10 070 quantified proteins, which is 9.73% more than that with DPHL. We further established a six-protein classifier by parallel reaction monitoring (PRM) to effectively predict the resistance to additional chemotherapy after IDS (Log-rank test, P = 0.002). The classifier was validated with 57 patients from an independent clinical center (P = 0.014). Thus, we have developed an ovary-specific spectral library for targeted proteome analysis, and propose a six-protein classifier that could potentially predict chemoresistance in HGSOC patients after NACT-IDS treatment.

Proteomic analysis reveals CAAP1 negatively correlates with platinum resistance in ovarian cancer.

The present study sought to investigate the correlation between CAAP1 and platinum resistance in ovarian cancer and to preliminarily explore the potential biological function of CAAP1. Proteomic analysis was used to analyze differentially expressed proteins in platinum-sensitive and -resistant tissue samples of ovarian cancer. The Kaplan-Meier plotter was used for prognostic analysis. Immunohistochemistry assay and chi-square test were employed to explore the relationship between CAAP1 and platinum resistance in tissue samples. Lentivirus transfection, immunoprecipitation-mass spectrometry, and bioinformatics analysis were used to determine the potential biological function of CAAP1. Based on results, the expression level of CAAP1 was significantly higher in platinum-sensitive tissues compared to that in resistant tissues. Chi-square test demonstrated that there is a negative correlation between high expression of CAAP1 and platinum resistance. Overexpression of CAAP1 increased cis­platinum sensitivity of the A2780/DDP cell line likely via the mRNA splicing pathway by interacting with the splicing factor AKAP17A. In summary, there is a negative correlation between high expression of CAAP1 and platinum resistance. CAAP1 might be a potential biomarker for platinum resistance in ovarian cancer. SIGNIFICANCE: Platinum resistance is a key factor affecting the survival of ovarian cancer patients. Understanding the mechanisms of platinum resistance is highly important for ovarian cancer management. Here, we performed the DIA- and DDA-based proteomics to analyze differentially expressed proteins in tissue and cell samples of ovarian cancer. We found that the protein identified as CAAP1, which was first reported to be involved in the regulation of apoptosis, may be negatively correlates with platinum resistance in ovarian cancer. In addition, we also found that CAAP1 enhanced the sensitivity of platinum-resistant cells to cis­platinum via the mRNA splicing pathway by interacting with the splicing factor AKAP17A. Our data would be useful to reveal novel molecular mechanisms of platinum resistance in ovarian cancer.

Shikonin and cisplatin synergistically overcome cisplatin resistance of ovarian cancer by inducing ferroptosis via upregulation of HMOX1 to promote Fe2+ accumulation.

BACKGROUND: Cisplatin-based chemotherapy often results in ovarian cancer (OC) chemical resistance and treatment failure. The combination of natural compounds with platinum-based agents is a new strategy for overcoming cisplatin resistance. At present, the synergistic effects and mechanism of combination of shikonin and cisplatin to overcome cisplatin resistance in OC are still unknown. PURPOSE: This study was to evaluate the synergistic effects of shikonin and cisplatin on cisplatin-resistant OC cells and to assess the underlying molecular basis for these effects. METHODS: Cell counting kit-8 assay, colony-formation assay, proteomic analysis, reactive oxygen species (ROS) detection, lipid peroxidation (LPO) detection, Fe2+ detection, western blot, and quantitative real-time reverse transcription PCR (qRT-PCR) were performed to evaluate the effects of shikonin and cisplatin on cisplatin-resistant OC cells. Underlying mechanisms of action were investigated in vitro using small molecule inhibitors and siRNA. In vivo, the effect of shikonin and cisplatin combination on tumor growth in BALB/c nude mice was evaluated, with tumor immunohistochemical (IHC) staining performed to detect ferroptosis-related proteins. RESULTS: In vitro, shikonin and cisplatin were shown to synergistically reduce the viability of cisplatin-resistant OC cells. Proteomic results demonstrated that the combination of the two drugs induced a ferroptotic process, as evidenced by increased levels of ROS, LPO, and Fe2+, with downregulation of glutathione peroxidase 4 (GPX4). Heme oxygenase 1 (HMOX1) inhibition and siRNA interference attenuated the combined effect of the two drugs on cell viability. Accumulation of Fe2+ was attenuated by siRNA interference of HMOX1. In vivo, combination treatment significantly inhibited the growth of subcutaneous tumors in BALB/c nude mice and increased the expression of ferroptosis-related proteins in tumor tissue. CONCLUSION: We report for the first time that the co-treatment of shikonin and cisplatin overcomes cisplatin resistance in OC through ferroptosis. Mechanistic analysis reveals the co-treatment induces ferroptosis through upregulation of HMOX1 that promotes Fe2+ accumulation.

The proteomics and metabolomics studies of GZU001 on promoting the Merisis of maize (Zea mays L.) roots.

BACKGROUND: Plant growth regulators are chemicals that regulate plant growth and development, which can regulate hormonal balance and affect plant growth, thereby increasing crop yield and improving crop quality. Our studies have revealed a new compound, GZU001, which could be used as a plant growth regulator. This compound has been observed to affect root elongation in maize significantly. However, the exact mechanism of this phenomenon is still being investigated. RESULTS: Metabolomics and proteomics were used in unison in this study to explore the response pathway and regulation mechanism of GZU001 in promoting maize root elongation. From the appearance, we can see that both roots and plants of maize treated with GZU001 are significantly improved. Maize root metabolism revealed 101 differentially abundant proteins and 79 differentially expressed metabolites. The current study identified altered proteins and metabolites associated with physiological and biochemical processes. GZU001 treatment has been demonstrated to promote primary metabolism, essential for carbohydrates, amino acids, energy, and secondary metabolism. The result suggests that the stimulation of primary metabolism is beneficial for the growth and development of maize and plays a significant role in sustaining metabolism and growth. CONCLUSIONS: This study recorded the changes of related proteins and metabolites in maize roots after GZU001 treatment and provided evidence for this compound's action mode and mechanism in plants.

Sustainable alginate lyases catalyzed degradation of bio-based carbohydrates.

Alginate is a water-soluble and acidic polysaccharide derived from the cell wall and intercellular substance of brown algae. It is widely distributed in brown algae, such as Laminaria, Sargassum, and Macrocystis, etc. Alginate lyase can catalytically degrade alginate in a ß-eliminating manner, and its degradation product-alginate oligosaccharide (AOS) has been widely used in agriculture, medicine, cosmetics and other fields due to its wide range of biological activities. This article is mainly to make a brief introduction to the classification, source and application of alginate lyase. We hope this minireview can provide some inspirations for its development and utilization.

Genome Analysis of a Novel Polysaccharide-Degrading Bacterium Paenibacillus algicola and Determination of Alginate Lyases.

Carbohydrate-active enzymes (CAZymes) are an important characteristic of bacteria in marine systems. We herein describe the CAZymes of Paenibacillus algicola HB172198T, a novel type species isolated from brown algae in Qishui Bay, Hainan, China. The genome of strain HB172198T is a 4,475,055 bp circular chromosome with an average GC content of 51.2%. Analysis of the nucleotide sequences of the predicted genes shows that strain HB172198T encodes 191 CAZymes. Abundant putative enzymes involved in the degradation of polysaccharides were identified, such as alginate lyase, agarase, carrageenase, xanthanase, xylanase, amylases, cellulase, chitinase, fucosidase and glucanase. Four of the putative polysaccharide lyases from families 7, 15 and 38 were involved in alginate degradation. The alginate lyases of strain HB172198T exhibited the maximum activity 152 U/mL at 50 °C and pH 8.0, and were relatively stable at pH 7.0 and temperatures lower than 40 °C. The average degree of polymerization (DP) of the sodium alginate oligosaccharide (AOS) degraded by the partially purified alginate lyases remained around 14.2, and the thin layer chromatography (TCL) analysis indicated that it contained DP2-DP8 oligosaccharides. The complete genome sequence of P. algicola HB172198T will enrich our knowledge of the mechanism of polysaccharide lyase production and provide insights into its potential applications in the degradation of polysaccharides such as alginate.

Design, synthesis, and bioactivity of ferulic acid derivatives containing an ß-amino alcohol.

BACKGROUND: Plant diseases caused by viruses and bacteria cause huge economic losses due to the lack of effective control agents. New potential pesticides can be discovered through biomimetic synthesis and structural modification of natural products. A series of ferulic acid derivatives containing an ß-amino alcohol were designed and synthesized, and their biological activities were evaluated. RESULT: Bioassays results showed that the EC50 values of compound D24 against Xanthomonas oryzae pv. oryzae (Xoo) was 14.5 µg/mL, which was better than that of bismerthiazol (BT, EC50 = 16.2 µg/mL) and thiodiazole copper (TC, EC50 = 44.5 µg/mL). The in vivo curative and protective activities of compound D24 against Xoo were 50.5% and 50.1%, respectively. The inactivation activities of compounds D2, D3 and D4 against tobacco mosaic virus (TMV) at 500 µg/mL were 89.1, 93.7 and 89.5%, respectively, superior to ningnanmycin (93.2%) and ribavirin (73.5%). In particular, the EC50 value of compound D3 was 38.1 µg/mL, and its molecular docking results showed that compound D3 had a strong affinity for TMV-CP with a binding energy of - 7.54 kcal/mol, which was superior to that of ningnanmycin (- 6.88 kcal /mol). CONCLUSIONS: The preliminary mechanism research results indicated that compound D3 may disrupt the three-dimensional structure of the TMV coat protein, making TMV particles unable to self-assemble, which may provide potential lead compounds for the discovery of novel plant antiviral agents.