MicrobeTCM: A comprehensive platform for the interactions of microbiota and traditional Chinese medicine.

Thanks to the advancements in bioinformatics, drugs, and other interventions that modulate microbes to treat diseases have been emerging continuously. In recent years, an increasing number of databases related to traditional Chinese medicine (TCM) or gut microbes have been established. However, a database combining the two has not yet been developed. To accelerate TCM research and address the traditional medicine and micro ecological system connection between short board, we have developed the most comprehensive micro-ecological database of TCM. This initiative includes the standardization of the following advantages: (1) A repeatable process achieved through the standardization of a retrieval strategy to identify literature. This involved identifying 419 experiment articles from PubMed and six authoritative databases; (2) High-quality data integration achieved through double-entry extraction of literature, mitigating uncertainties associated with natural language extraction; (3) Implementation of a similar strategy aiding in the prediction of mechanisms of action. Leveraging drug similarity, target entity similarity, and known drug-target entity association, our platform enables the prediction of the effects of a new herb or acupoint formulas using the existing data. In total, MicrobeTCM includes 171 diseases, 725 microbes, 1468 herb-formulas, 1032 herbs, 15780 chemical compositions, 35 acupoint-formulas, and 77 acupoints. For further exploration, please visit https://www.microbetcm.com.

Flavobacterium adhaerens sp. nov. and Flavobacterium maritimum sp. nov., two novel flavobacteria isolated from the Pearl River Estuary.

Two strains, designated as SYSU M80004T and SYSU M80005T, were isolated from water sampled in the Pearl River Estuary, Guangzhou, Guangdong, PR China. The strains were Gram-stain-negative and aerobic. Strain SYSU M80004T could grow at pH 6.0-8.0 (optimum, pH 7.0), 22-30 °C (optimum, 28 °C) and in the presence of 0-1 % NaCl (w/v; optimum 0 %). Strain SYSU M80005T could grow at pH 6.0-8.0 (optimum, pH 7.0), 4-37 °C (optimum, 28 °C) and in the presence of 0-1 % NaCl (w/v; optimum 0%). Both strains contained MK-6 as the predominant menaquinone. C16 : 0 and iso-C15 : 0 were identified as the major fatty acids (>10 %) of strain SYSU M80004T while strain SYSU M80005T contained iso-C15 : 0 and iso-C17 : 0 3-OH as major fatty acids. Phosphatidylethanolamine was present as the major polar lipid in both strains. The average nucleotide identity and digital DNA-DNA hybridization values between these two strains and their closest relatives were 73.5-79.3 % and 19.6-23.2 %, respectively. Phylogenetic analysis based on the 16S rRNA gene and genomic sequences indicated they belonged to the genus Flavobacterium. Therefore, on the basis of phenotypic, physiological, chemotaxonomic and genomic evidence, two novel species, Flavobacterium adhaerens sp. nov. (type strain=SYSU M80004T=CDMCC 1.4522T=KCTC 102268T) and Flavobacterium maritimum sp. nov. (type strain=SYSU M80005T=CGMCC 1.4523T= KCTC 102269T) are proposed.

Bayesian hierarchical modeling in interim futility analysis for two parallel clinical trials.

Incorporating interim analysis into a trial design is gaining popularity in the field of confirmatory clinical trials, where two studies may be conducted in parallel (ie, twin studies) in order to provide substantial evidence per the requirement of FDA guidance. Interim futility analysis provides a chance to check for the "disaster" scenario when the treatment has a high probability to be not more efficacious than the control. Therefore, it is an efficient tool to mitigate risk of running a complete and expansive trial under such scenario. There is no agreement among trial designers that interim analysis should be based on individual study data or pooled data under the twin study scenario. In fact, it is a dilemma for most scientists when specifying the interim analysis strategy at the design stage as the true treatment effects of the twin studies are unknown no matter how similar they are intended to be. To address the issue, we developed a Bayesian hierarchical modeling method to allow dynamic data borrowing between twin studies and demonstrated a favorable characteristic of the new method over the separate and pooled analyses. We evaluated a wide spectrum of the heterogeneity hyperparameters and visualized its critical impact on the Bayesian model's characteristic. Based on the evaluation, we made a suggestion on the heterogeneity hyperparameter selection independent of any a priori knowledge. We also applied our method to a case study where predictive powers of different methods are compared.

Conditional bias adjusted estimator of treatment effect in 2-in-1 adaptive design.

For implementation of adaptive design, the adjustment of bias in treatment effect estimation becomes an increasingly important topic in recent years. While adaptive design literature traditionally focuses on the control of type I error rate and the adjustment of overall unconditional bias, the research on adjusting conditional bias has been limited. This paper proposes a conditional bias adjustment estimator of treatment effect under the context of 2-in-1 adaptive design and aims to provide a comprehensive investigation on their statistical properties including bias, mean squared error and coverage probability of confidence intervals. It demonstrated that conditional bias adjusted estimators greatly reduce the conditional bias and have similarly negligible unconditional bias compared with mean and median (unconditional) unbiased estimators. In addition, the test statistics is constructed based on the conditional bias adjustment estimators and compared with the naive unadjusted test.

Strategies for successful dose optimization in oncology drug development: a practical guide.

Dose optimization is a critical challenge in drug development. Historically, dose determination in oncology has followed a divergent path from other non-oncology therapeutic areas due to the unique characteristics and requirements in Oncology. However, with the emergence of new drug modalities and mechanisms of drugs in oncology, such as immune therapies, radiopharmaceuticals, targeted therapies, cytostatic agents, and others, the dose-response relationship for efficacy and toxicity could be vastly varied compared to the cytotoxic chemotherapies. The doses below the MTD may demonstrate similar efficacy to the MTD with an improved tolerability profile, resembling what is commonly observed in non-oncology treatments. Hence, alternate strategies for dose optimization are required for new modalities in oncology drug development. This paper delves into the historical evolution of dose finding methods from non-oncology to oncology, highlighting examples and summarizing the underlying drivers of change. Subsequently, a practical framework and guidance are provided to illustrate how dose optimization can be incorporated into various stages of the development program. We provide the following general recommendations: 1) The objective for phase I is to identify a dose range rather than a single MTD dose for subsequent development to better characterize the safety and tolerability profile within the dose range. 2) At least two doses separable by PK are recommended for dose optimization in phase II. 3) Ideally, dose optimization should be performed before launching the confirmatory study. Nevertheless, innovative designs such as seamless II/III design can be implemented for dose selection and may accelerate the drug development program.

Cereibacter flavus sp. nov., a novel member of the family Rhodobacteraceae isolated from seawater of the South China Sea and reclassification of Rhodobacter alkalitolerans as Cereibacter alkalitolerans comb. nov.

A Gram-stain-negative, aerobic, motile, ovoid-shaped and yellow-coloured strain, designated SYSU M79828T, was isolated from seawater collected from the South China Sea. Growth of this strain was observed at 4-37 °C (optimum, 28 °C), pH 6.0-8.0 (optimum, pH 7.0) and with 0-6% NaCl (optimum, 3.0 %, w/v). The respiratory quinone was found to be Q-10. Major fatty acid constituents were C18 : 1 ω7c/C18 : 1 ω6c, C18 : 1 ω7c11-methyl and C18 : 0 (>5 % of total). The major polar lipids were phosphatidylethanolamine, phosphatidylglycerol, diphosphatidylglycerol, phosphatidylcholine, phosphoglycolipid, two unidentified phospholipid, one unidentified lipid and an unidentified glycolipid. The genomic DNA G+C content was 64.5 mol%. Phylogenetic analyses based on 16S rRNA gene sequences and core genes indicated that strain SYSU M79828T belonged to the genus Cereibacter and had the highest sequences similarity to 'Rhodobacter xinxiangensis' TJ48T (98.41 %). Based on 16S rRNA gene phylogeny, physiological and chemotaxonomic characterizations, we consider that strain SYSU M79828T represents a novel species of the genus Cereibacter, for which the name Cereibacter flavus sp. nov. is proposed. The type strain is SYSU M79828T (=GDMCC 1.3803T=KCTC 92893T). In addition, according to the results of phylogenetic analysis and similar taxonomic characteristics, we propose that Rhodobacter alkalitolerans should be reclassified as Cereibacter alkalitolerans comb. nov.

Ectobacillus ponti sp. nov., a novel bacterium isolated from Pearl River Estuary.

A Gram-staining-positive, aerobic, motile, and rod-shaped strain, designated SYSU M60031T, was isolated from a Pearl River Estuary sediment sample, Guangzhou, Guangdong, China. The isolate could grow at pH 5.0-8.0 (optimum, pH 7.0), 25-37 °C (optimum, 28 °C) and in the presence of 0-1 % (w/v) NaCl (optimum, 0 %). The predominant respiratory menaquinone of SYSU M60031T was MK-7. The cellular polar lipids were diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, one unidentified aminophospholipid, and one unidentified aminolipid. The major fatty acids (>10 % of total) were iso-C14 : 0, iso-C15 : 0, anteiso-C15 : 0, iso-C16 : 0, and C16 : 0. The genomic DNA G+C content was 51.2 %. Phylogenetic analyses based on 16S rRNA gene sequences and core genes indicated that strain SYSU M60031T belonged to the genus Ectobacillus and showed the highest sequence similarity to Ectobacillus funiculus NAF001T (96.16%), followed by Ectobacillus antri SYSU K30001T (95.08 %). Based on the phenotypic, genotypic, and phylogenetic data, strain SYSU M60031T should be considered to represent a novel species of the genus Ectobacillus, for which the name Ectobacillus ponti sp. nov. is proposed. The type strain of the proposed novel isolate is SYSU M60031T (=CGMCC 1.19243T =NBRC 115614T).

Alsobacter ponti sp. nov., a novel denitrification and sulfate reduction bacterium isolated from Pearl River sediment.

A Gram-staining negative, aerobic, motile, and short rods strain, designated SYSU M60028T, was isolated from a Pearl River sediment sample in Guangzhou, Guangdong, China. The isolate could be able to grow at pH 6.0-8.0 (optimum, pH 7.0), 25-37 °C (optimum, 28 °C) and in the presence of 0-2% (w/v) NaCl (optimum, 0% NaCl). The cellular polar lipids of this strain were phosphatidylethanolamine, diphosphatidylglycerol, phosphatidylglycerol, phosphatidylcholine, one unidentified aminolipid and three unidentified lipids. The respiratory quinone of SYSU M60028T was found to be Q-10. The major fatty acids (> 5% of total) were summed feature 8, C16:0, and C18:1 ω7c 11-methy1. The genomic DNA G + C content was 69.9%. Phylogenetic analyses based on 16S rRNA gene sequences and core genes indicated that strain SYSU M60028T belonged to the genus Alsobacter and had the highest sequences similarities to Alsobacter metallidurans SK200a-9T (96.87%) and Alsobacter soli SH9T (96.87%). Based on the phenotypic, genotypic, and phylogenetic data, strain SYSU M0028T should be considered to represent a novel species of the genus Alsobacter, for which the name Alsobacter ponti sp. nov. is proposed. The type strain is SYSU M60028T (= CGMCC 1.19341T = KCTC 92046T).

Bayesian hierarchical model for dose-finding trial incorporating historical data.

The Multiple Comparison Procedure and Modelling (MCPMod) approach has been shown to be a powerful statistical technique that can significantly improve the design and analysis of dose-finding studies under model uncertainty. Due to its frequentist nature, however, it is difficult to incorporate information into MCPMod from historical trials on the same drug. BMCPMod, a recently introduced Bayesian version of MCPMod, is designed to take into account historical information on the placebo dose group. We introduce a Bayesian hierarchical framework capable of incorporating historical information on an arbitrary number of dose groups, including both placebo and active ones, taking into account the relationship between responses of these dose groups. Our approach can also model both prognostic and predictive between-trial heterogeneity and is particularly useful in situations where the effect sizes of two trials are different. Our goal is to reduce the necessary sample size in the dose-finding trial while maintaining its target power.

Habitat-dependent prokaryotic microbial community, potential keystone species, and network complexity in a subtropical estuary.

Microbes (e.g., bacteria and archaea) are indispensable components for the key biological processes of estuarine ecosystems and three main habitats (sediment, particle, and water) are harboring diverse estuarine microbes. However, we still know little about how the microbial community structures, potential keystone species, and network properties change among these three habitats in estuarine ecosystems. In this study, we collected size-fractioned water and sediment samples from the Pearl River Estuary to reveal their microbial diversity, community structures, network properties, and potential keystone taxa. We found that the sediment microbial community was remarkably more diverse than particle-attached (PA) and free-living (FL) communities, whereas its ecological network was less complex in terms of node distance and connectivity. TOC was determined as the main driver of sediment community, while the PA and FL communities were predominantly shaped by NO2-, non-ionic ammonia (NH) and pH. Among the bulk water, there were no significant differences between PA and FL communities in diversity, community structure, and network complexity. However, the PA community was more susceptible to metal elements, suggesting their higher level of involvement in physiological metabolism. Potential keystone taxa among community networks were taxonomically divergent in three habitats. Specifically, Synechococcales (Cyanobacteria) and Actinomarinales (Actinobacteria) exclusively served as the module-hubs in FL network, while members from phylum Proteobacteria and Bacteroidetes were the module-hubs and connectors in PA network. Potential keystone taxa in sediment network were more diverse and covered 9 phyla, including the only archaeal lineage Bathyarchaeia (Crenarchaeota). Overall, our study provided more detailed information about estuarine microbial communities in three habitats, especially the potential keystone species, which provided new perspectives on evaluating further effects of anthropogenic disturbances on estuarine microbes and facilitated the environment monitoring based on microbial community.

Bayesian MCPMod.

Multiple comparison procedures and modeling (MCPMod) has established itself as a method for dose-finding under model uncertainty. A downside of MCPMod is that due to its frequentist nature in particular with respect to the multiple comparison part it is tough to incorporate historical information in a systematic fashion. A typical situation where such historical information is available is existing data for the placebo group from previous trials. There are multiple Bayesian concepts for integrating historical data in a systematic and even dynamic fashion like the meta-analytic prior approach. In this article, we define Bayesian MCPMod (BMCPMod) that is build upon these two aspects. BMCPMod is able to mimic the results of the classical MCPMod for non-informative priors. At the same time, it allows for the inclusion of historical data in a systematic fashion. After the definition of BMCPMod related characteristics for a Bayesian approach similar to the MCP-testing part are derived. The BMCPMod is compared to classical MCPMod/non-informative priors via simulations. Aspects of mixture priors, optimal contrast vectors, and impact of allocation ratios are discussed and an example for designing a BMPCMod trial is given.

Estimation of treatment effect in 2-in-1 adaptive design and some of its extensions.

The 2-in-1 adaptive design allows seamless expansion of an ongoing Phase II trial into a Phase III trial to expedite a drug development program. Since its publication, it has generated a lot of interest. So far, most of the related research focused on type I error control. Similar to most adaptive designs, 2-in-1 design could also pose a great challenge on estimation of treatment effect due to the data-driven adaptation. In addition, the use of intermediate endpoint for interim adaptive decision-making is a less well-studied field. In this paper, we investigate the bias and variances in estimation for 2-in-1 design and some of its extensions, and propose some bias-adjusted estimators for 2-in-1 design. The properties of the proposed estimators are further studied theoretically and/or numerically, so as to provide guidance on how to interpret the estimated treatment effect of 2-in-1 design.

Multiplicity issues for platform trials with a shared control arm.

This paper provides in-depth discussion about different types of error generated in platform trials with a common control arm, and how they compare to the ones arisen from standard independent trials. We provide our views on some of the popular "myths" associated with such design, under the frequentist framework. It is found that platform trial generally performs quite well in terms of type I error rate, false discovery rate, and power. In most cases, these operating characteristics of a platform trial are comparable to or even better than running individual trials.

Empirical profile Bayesian estimation for extrapolation of historical adult data to pediatric drug development.

For pediatric drug development, the clinical effectiveness of the study medication for the adult population has already been demonstrated. Given the fact that it is usually not feasible to enroll a large number of pediatric patients, appropriately leveraging historical adult data into pediatric evaluation may be critical to success of pediatric drug development. In this manuscript, we propose a new empirical Bayesian approach, profile Bayesian estimation, to dynamically borrow adult information to the evaluation of treatment effect in pediatric patients. The new approach demonstrates an attractive balance between type I error control and power gain under the transfer-ability assumption that the pediatric treatment effect size may differ from the adult treatment effect size. The decision making boundary mimics the real-world practice in pediatric drug development. In addition, the posterior mean of the proposed empirical profile Bayesian is an unbiased estimator of the true pediatric treatment effect. We compare our approach to robust mixture prior with prior weight for informative borrowing set to 0.5 or 0.9, regular Bayesian approach, and frequentist for both type I error and power.

Power and sample size for dose-finding studies with survival endpoints under model uncertainty.

Multiple comparison procedures combined with modeling techniques (MCP-Mod) (Bretz et al., 2005) is an efficient and robust statistical methodology for the model-based design and analysis of dose-finding studies with an unknown dose-response model. With this approach, multiple comparison methods are used to identify statistically significant contrasts corresponding to a set of candidate dose-response models, and the best model is then used to estimate the target dose. Power and sample size calculations for this methodology require knowledge of the covariance matrix for the estimators of the (placebo-adjusted) mean responses among the dose groups. In this article, we consider survival endpoints and derive an analytic form of the covariance matrix for the estimators of the log hazard ratios as a function of the total number of events in the study. We then use this closed-form expression of the covariance matrix to derive the power and sample size formulas. We discuss practical considerations in the application of these formulas. In addition, we provide an illustration with a motivating example on chronic obstructive pulmonary disease. Finally, we demonstrate through simulation studies that the proposed formulas are accurate enough for practical use.

Applying CHW method to 2-in-1 design: gain or lose?

The 2-in-1 design allows the possibility of seamlessly expanding a phase II study to confirmatory phase III study and controls type I error without multiplicity adjustment. In this paper, we applied the CHW method to the 2-in-1 design strategy, and compared it with the unweighted conventional test statistics. It shows that when the interim decision threshold is high enough, the CHW method is slightly more powerful. Otherwise, results based on the CHW method can be difficult to interpret when the estimated treatment effects differ notably between interim and final analysis, which may be avoided by using the conventional test statistic.

Dynamic development paths for expanding a proof-of-concept study to explore dose range.

In Phase II clinical development of a new drug, the two most important deliverables are proof of concept (PoC) and dose ranging. Traditionally, a PoC study is designed as the first Phase II clinical trial. In this PoC, there are two treatment groups-a high dose of the study medication, against the placebo control. After the concept is proven, the next Phase II study is a dose-ranging design with many test doses. This paper proposes a two-stage design with the first stage attempting to generate an early signal of efficacy. If successful, the second stage will adopt a "Go Fast" plan to expand the current study and add lower study doses of the test drug to explore the efficacy dose range. Otherwise, a "Go Slow" strategy is triggered, and the study will stop at a reduced sample size with high dose and placebo only.

Deciphering the pathogenic risks of microplastics as emerging particulate organic matter in aquatic ecosystem.

Microplastics are accumulating rapidly in aquatic ecosystems, providing habitats for pathogens and vectors for antibiotic resistance genes (ARGs), potentially increasing pathogenic risks. However, few studies have considered microplastics as particulate organic matter (POM) to elucidate their pathogenic risks and underlying mechanisms. Here, we performed microcosm experiments with microplastics and natural POM (leaves, algae, soil), thoroughly investigating their distinct effects on the community compositions, functional profiles, opportunistic pathogens, and ARGs in Particle-Associated (PA) and Free-Living (FL) bacterial communities. We found that both microplastics and leaves have comparable impacts on microbial community structures and functions, enriching opportunistic pathogens and ARGs, which may pose potential environmental risks. These effects are likely driven by their influences on water properties, including dissolved organic carbon, nitrate, DO, and pH. However, microplastics uniquely promoted pathogens as keystone species and further amplified their capacity as hosts for ARGs, potentially posing a higher pathogenic risk than natural POM. Our research also emphasized the importance of considering both PA and FL bacteria when assessing microplastic impacts, as they exhibited different responses. Overall, our study elucidates the role and underlying mechanism of microplastics as an emerging POM in intensifying pathogenic risks of aquatic ecosystems in comparison with conventional natural POM.

[Mutation of the envelope stress-responsive protein CpxA capable of regulating the antimicrobial resistance and virulence of bacteria].

CpxA is a key member of the envelope stress-responsive Cpx two-component system ubiquitous in Gram-negative bacteria. It is responsible for signal sensing and has dual activities of phosphatase and kinase. CpxA has been revealed to participate in the regulation of physiological processes such as virulence and antimicrobial resistance of bacteria. In recent years, the development of novel antimicrobials targeting CpxA has attracted much attention. Drugs developed based on inhibition of the phosphatase activity of CpxA have shown effectiveness in the treatment of urinary tract infections caused by Escherichia coli. This review introduces the structure and functional domains of CpxA and the activation of Cpx pathways by CpxA. Furthermore, it summarizes the roles of CpxA in the development of antimicrobial resistance and the regulation of bacterial virulence and reviews the latest progress in the development of new antimicrobials targeting this protein. It is expected to assist in the exploration of CpxA-targeting anti-infection strategies for severely antimicrobial-resistant bacteria whose clinical infections are of urgent need to be controlled.

Nanostructures in Chinese herbal medicines (CHMs) for potential therapy.

With its long clinical history, traditional Chinese medicine (TCM) has gained acceptance for its specific efficacy and safety in the treatment of multiple diseases. Nano-sized materials study of Chinese herbal medicines (CHMs) leads to an increased understanding of assessing TCM therapies, which may be a promising way to illustrate the material basis of CHMs through their processing and extraction. In this review, we provide an overview of the nanostructures of natural and engineered CHMs, including extracted CHMs, polymer nanoparticles, liposomes, micelles, and nanofibers. Subsequently, the applications of these CHM-derived nanostructures to particular diseases are summarized and discussed. Additionally, we discuss the advantages of these nanostructures for studying the therapeutic efficacy of CHMs. Finally, the key challenges and opportunities for the development of these nanostructures are outlined.