The enormous repetitive Antarctic krill genome reveals environmental adaptations and population insights.

Antarctic krill (Euphausia superba) is Earth's most abundant wild animal, and its enormous biomass is vital to the Southern Ocean ecosystem. Here, we report a 48.01-Gb chromosome-level Antarctic krill genome, whose large genome size appears to have resulted from inter-genic transposable element expansions. Our assembly reveals the molecular architecture of the Antarctic krill circadian clock and uncovers expanded gene families associated with molting and energy metabolism, providing insights into adaptations to the cold and highly seasonal Antarctic environment. Population-level genome re-sequencing from four geographical sites around the Antarctic continent reveals no clear population structure but highlights natural selection associated with environmental variables. An apparent drastic reduction in krill population size 10 mya and a subsequent rebound 100 thousand years ago coincides with climate change events. Our findings uncover the genomic basis of Antarctic krill adaptations to the Southern Ocean and provide valuable resources for future Antarctic research.

Phase 3 trial of gilteritinib plus azacitidine vs azacitidine for newly diagnosed FLT3mut+ AML ineligible for intensive chemotherapy.

Treatment results for patients with newly diagnosed FMS-like tyrosine kinase 3 (FLT3)-mutated (FLT3mut+) acute myeloid leukemia (AML) ineligible for intensive chemotherapy are disappointing. This multicenter, open-label, phase 3 trial randomized (2:1) untreated adults with FLT3mut+ AML ineligible for intensive induction chemotherapy to receive gilteritinib (120 mg/d orally) and azacitidine (GIL + AZA) or azacitidine (AZA) alone. The primary end point was overall survival (OS). At the interim analysis (August 26, 2020), a total of 123 patients were randomized to treatment (GIL + AZA, n = 74; AZA, n = 49). Subsequent AML therapy, including FLT3 inhibitors, was received by 20.3% (GIL + AZA) and 44.9% (AZA) of patients. Median OS was 9.82 (GIL + AZA) and 8.87 (AZA) months (hazard ratio, 0.916; 95% CI, 0.529-1.585; P = .753). The study was closed based on the protocol-specified boundary for futility. Median event-free survival was 0.03 month in both arms. Event-free survival defined by using composite complete remission (CRc) was 4.53 months for GIL + AZA and 0.03 month for AZA (hazard ratio, 0.686; 95% CI, 0.433-1.087; P = .156). CRc rates were 58.1% (GIL + AZA) and 26.5% (AZA) (difference, 31.4%; 95% CI, 13.1-49.7; P < .001). Adverse event (AE) rates were similar for GIL + AZA (100%) and AZA (95.7%); grade ≥3 AEs were 95.9% and 89.4%, respectively. Common AEs with GIL + AZA included pyrexia (47.9%) and diarrhea (38.4%). Gilteritinib steady-state trough concentrations did not differ between GIL + AZA and gilteritinib. GIL + AZA resulted in significantly higher CRc rates, although similar OS compared with AZA. Results support the safety/tolerability and clinical activity of upfront therapy with GIL + AZA in older/unfit patients with FLT3mut+ AML. This trial was registered at www.clinicaltrials.gov as #NCT02752035.

Development of a generalized pharmacokinetic model to characterize clinical pharmacokinetics of monomethyl auristatin E-based antibody-drug conjugates.

AIMS: This study aims to develop a generalized pharmacokinetic (PK) model for monomethyl auristatin E (MMAE)-based antibody-drug conjugates (ADCs) that can simultaneously capture the PK of multiple ADC analytes commonly measured in the clinic. METHODS: A comprehensive literature review was conducted to collect PK data on MMAE-based ADCs from clinical trials. From each study, PK profiles of total antibody, the ADC, conjugated MMAE, and unconjugated MMAE, were extracted. These data were pooled and dose-normalized to evaluate the generalizability of PK across various ADCs and dose levels. Upon confirming PK generalizability, a generalized PK model for MMAE-based ADCs was developed using the entire dataset. Furthermore, exposure metrics ( C max and AUC) reported across the range of doses were combined to establish linear relationships between dose and exposure metrics for MMAE-based ADCs. RESULTS: A total of 109 PK profiles from 18 distinct MMAE-based ADCs were gathered. The dose-normalized PK profiles supported the generalizability of PK for MMAE-based ADCs. A generalized PK model was developed, which enabled capturing the PK data for 4 ADC analytes across all collected MMAE-based ADCs. A linear relationship between dose and PK exposure metrics was established, enabling the prediction of typical exposure values across different doses for MMAE-based ADCs. CONCLUSIONS: This study comprehensively analysed clinical PK data from different valine-citrulline (vc)-MMAE-based ADCs. The generalized PK model developed here serves as an important tool for a priori prediction of the PK for multiple ADC analytes in clinical settings and lays the foundation for establishing generalized exposure-response and exposure-toxicity correlations for MMAE-based ADCs.

A basket trial design based on constrained hierarchical Bayesian model for latent subgroups.

It is well known a basket trial consisting of multiple cancer types has the potential of borrowing strength across the baskets defined by the cancer types, leading to an efficient design in terms of sample size and trial duration. The treatment effects in those baskets are often heterogeneous and categorized by the cancer types being sensitive or insensitive to the treatment. Hence, the assumption of exchangeability in many existing basket trials may be violated, and there is a need to design trials without this assumption. In this paper, we simplify the constrained hierarchical Bayesian model for latent subgroups (CHBM-LS) for two classifiers to deal with the potential heterogeneity of treatment effects due to the single classifier of the cancer type. Different baskets are aggregated into subgroups using a latent subgroup modeling approach. The treatment effects are similar and exchangeable to facilitate information borrowing within each latent subgroup. Applying the simplified CHBM-LS approach to the real basket trials where baskets defined by only cancer types shows better performance than other available approaches. Further simulation study also demonstrates this CHBM-LS approach outperforms other approaches with higher statistical power and better-controlled type I error rates under various scenarios.

Translational two-pore PBPK model to characterize whole-body disposition of different-size endogenous and exogenous proteins.

Two-pore physiologically based pharmacokinetic (PBPK) modeling has demonstrated its potential in describing the pharmacokinetics (PK) of different-size proteins. However, all existing two-pore models lack either diverse proteins for validation or interspecies extrapolation. To fill the gap, here we have developed and optimized a translational two-pore PBPK model that can characterize plasma and tissue disposition of different-size proteins in mice, rats, monkeys, and humans. Datasets used for model development include more than 15 types of proteins: IgG (150 kDa), F(ab)2 (100 kDa), minibody (80 kDa), Fc-containing proteins (205, 200, 110, 105, 92, 84, 81, 65, or 60 kDa), albumin conjugate (85.7 kDa), albumin (67 kDa), Fab (50 kDa), diabody (50 kDa), scFv (27 kDa), dAb2 (23.5 kDa), proteins with an albumin-binding domain (26, 23.5, 22, 16, 14, or 13 kDa), nanobody (13 kDa), and other proteins (110, 65, or 60 kDa). The PBPK model incorporates: (i) molecular weight (MW)-dependent extravasation through large and small pores via diffusion and filtration, (ii) MW-dependent renal filtration, (iii) endosomal FcRn-mediated protection from catabolism for IgG and albumin-related modalities, and (iv) competition for FcRn binding from endogenous IgG and albumin. The finalized model can well characterize PK of most of these proteins, with area under the curve predicted within two-fold error. The model also provides insights into contribution of renal filtration and lysosomal degradation towards total elimination of proteins, and contribution of paracellular convection/diffusion and transcytosis towards extravasation. The PBPK model presented here represents a cross-modality, cross-species platform that can be used for development of novel biologics.

Combined use of 3D printing and mixed reality technology for neurosurgical training: getting ready for brain surgery.

OBJECTIVE: Learning surgical skills is an essential part of neurosurgical training. Ideally, these skills are acquired to a sufficient extent in an ex vivo setting. The authors previously described an in vitro brain tumor model, consisting of a cadaveric animal brain injected with fluorescent agar-agar, for acquiring a wide range of basic neuro-oncological skills. This model focused on haptic skills such as safe tissue ablation technique and the training of fluorescence-based resection. As important didactical technologies such as mixed reality and 3D printing become more readily available, the authors developed a readily available training model that integrates the haptic aspects into a mixed reality setup. METHODS: The anatomical structures of a brain tumor patient were segmented from medical imaging data to create a digital twin of the case. Bony structures were 3D printed and combined with the in vitro brain tumor model. The segmented structures were visualized in mixed reality headsets, and the congruence of the printed and the virtual objects allowed them to be spatially superimposed. In this way, users of the system were able to train on the entire treatment process from surgery planning to instrument preparation and execution of the surgery. RESULTS: Mixed reality visualization in the joint model facilitated model (patient) positioning as well as craniotomy and the extent of resection planning respecting case-dependent specifications. The advanced physical model allowed brain tumor surgery training including skin incision; craniotomy; dural opening; fluorescence-guided tumor resection; and dura, bone, and skin closure. CONCLUSIONS: Combining mixed reality visualization with the corresponding 3D printed physical hands-on model allowed advanced training of sequential brain tumor resection skills. Three-dimensional printing technology facilitates the production of a precise, reproducible, and worldwide accessible brain tumor surgery model. The described model for brain tumor resection advanced regarding important aspects of skills training for neurosurgical residents (e.g., locating the lesion, head position planning, skull trepanation, dura opening, tissue ablation techniques, fluorescence-guided resection, and closure). Mixed reality enriches the model with important structures that are difficult to model (e.g., vessels and fiber tracts) and advanced interaction concepts (e.g., craniotomy simulations). Finally, this concept demonstrates a bridging technology toward intraoperative application of mixed reality.

An automated ICU agitation monitoring system for video streaming using deep learning classification.

OBJECTIVE: To address the challenge of assessing sedation status in critically ill patients in the intensive care unit (ICU), we aimed to develop a non-contact automatic classifier of agitation using artificial intelligence and deep learning. METHODS: We collected the video recordings of ICU patients and cut them into 30-second (30-s) and 2-second (2-s) segments. All of the segments were annotated with the status of agitation as "Attention" and "Non-attention". After transforming the video segments into movement quantification, we constructed the models of agitation classifiers with Threshold, Random Forest, and LSTM and evaluated their performances. RESULTS: The video recording segmentation yielded 427 30-s and 6405 2-s segments from 61 patients for model construction. The LSTM model achieved remarkable accuracy (ACC 0.92, AUC 0.91), outperforming other methods. CONCLUSION: Our study proposes an advanced monitoring system combining LSTM and image processing to ensure mild patient sedation in ICU care. LSTM proves to be the optimal choice for accurate monitoring. Future efforts should prioritize expanding data collection and enhancing system integration for practical application.

Integrative Metabolomics, Enzymatic Activity, and Gene Expression Analysis Provide Insights into the Metabolic Profile Differences between the Slow-Twitch Muscle and Fast-Twitch Muscle of Pseudocaranx dentex.

The skeletal muscles of teleost fish encompass heterogeneous muscle types, termed slow-twitch muscle (SM) and fast-twitch muscle (FM), characterized by distinct morphological, anatomical, histological, biochemical, and physiological attributes, driving different swimming behaviors. Despite the central role of metabolism in regulating skeletal muscle types and functions, comprehensive metabolomics investigations focusing on the metabolic differences between these muscle types are lacking. To reveal the differences in metabolic characteristics between the SM and FM of teleost, we conducted an untargeted metabolomics analysis using Pseudocaranx dentex as a representative model and identified 411 differential metabolites (DFMs), of which 345 exhibited higher contents in SM and 66 in FM. KEGG enrichment analysis showed that these DFMs were enriched in the metabolic processes of lipids, amino acids, carbohydrates, purines, and vitamins, suggesting that there were significant differences between the SM and FM in multiple metabolic pathways, especially in the metabolism of energy substances. Furthermore, an integrative analysis of metabolite contents, enzymatic activity assays, and gene expression levels involved in ATP-PCr phosphate, anaerobic glycolysis, and aerobic oxidative energy systems was performed to explore the potential regulatory mechanisms of energy metabolism differences. The results unveiled a set of differential metabolites, enzymes, and genes between the SM and FM, providing compelling molecular evidence of the FM achieving a higher anaerobic energy supply capacity through the ATP-PCr phosphate and glycolysis energy systems, while the SM obtains greater energy supply capacity via aerobic oxidation. These findings significantly advance our understanding of the metabolic profiles and related regulatory mechanisms of skeletal muscles, thereby expanding the knowledge of metabolic physiology and ecological adaptation in teleost fish.

Mitochondrial Homeostasis Regulating Mitochondrial Number and Morphology Is a Distinguishing Feature of Skeletal Muscle Fiber Types in Marine Teleosts.

Fishes' skeletal muscles are crucial for swimming and are differentiated into slow-twitch muscles (SM) and fast-twitch muscles (FM) based on physiological and metabolic properties. Consequently, mitochondrial characteristics (number and morphology) adapt to each fiber type's specific functional needs. However, the mechanisms governing mitochondrial adaptation to the specific bioenergetic requirements of each fiber type in teleosts remain unclear. To address this knowledge gap, we investigated the mitochondrial differences and mitochondrial homeostasis status (including biogenesis, autophagy, fission, and fusion) between SM and FM in teleosts using Takifugu rubripes as a representative model. Our findings reveal that SM mitochondria are more numerous and larger compared to FM. To adapt to the increased mitochondrial number and size, SM exhibit elevated mitochondrial biogenesis and dynamics (fission/fusion), yet show no differences in mitochondrial autophagy. Our study provides insights into the adaptive mechanisms shaping mitochondrial characteristics in teleost muscles. The abundance and elongation of mitochondria in SM are maintained through elevated mitochondrial biogenesis, fusion, and fission, suggesting an adaptive response to fulfill the bioenergetic demands of SM that rely extensively on OXPHOS in teleosts. Our findings enhance our understanding of mitochondrial adaptations in diverse muscle types among teleosts and shed light on the evolutionary strategies of bioenergetics in fishes.

Diagnosis and management of Neuro-Behçet disease with isolated intracranial hypertension: a case report and literature review.

BACKGROUND: Neuro-Behçet's disease (NBD), characterized by isolated intracranial hypertension, is a rarely encountered condition, especially in children. In this study, we describe the treatment of a pediatric patient with NBD, who exhibited isolated intracranial pressure elevation as indicated by the initial manifestation of diplopia and physical examination finding of papilledema. CASE PRESENTATION: An 8-year-old boy was admitted to the hospital with a confirmed diagnosis of Behçet's disease (BD) over eight months. The patient also presented with the symptom of diplopia for three days. The evaluation of the patient's nervous system did not reveal any apparent abnormalities. The measurement of cerebrospinal fluid pressure yielded a reading of 470 mm H2O. The examination of the fundus indicated papilledema, and imaging scans revealed evidence of focal demyelination. The symptoms of the child showed alleviation after the administration of mannitol, methylprednisolone, and azathioprine. Furthermore, this study involved a comprehensive analysis of 18 cases of NBD with isolated intracranial hypertension, comprising one case reported herein and 17 cases from the literature review. Three cases were children, and an equal distribution of males and females 9:9 was noted. The average age at the onset of symptoms was 24.7 years (8-38 years). Headache (90%) was the most commonly reported clinical manifestation, followed by blurred vision or diplopia (80%). The ocular manifestations included papilledema (100%), abducent nerve paralysis (20%) and local eye hemorrhages in the retina (30%). Notably, 88.9% of these ocular manifestations were relieved or cured after treatment. CONCLUSION: This study presents the first reported case of NBD with isolated intracranial hypertension in the pediatric population of China. In a child with Bechet's disease presenting with features of raised intracranial pressure, it is important to be aware of neuro Bechet's presenting with intracranial hypertension without other neurological abnormalities. This will help make early diagnosis, institute treatment and prevent sequelae resulting from untreated raised intracranial pressure.

Clinical validation of translational antibody PBPK model using tissue distribution data generated with 89Zr-immuno-PET imaging.

The main objective of this manuscript was to validate the ability of the monoclonal antibody physiologically-based pharmacokinetic (PBPK) model to predict tissue concentrations of antibodies in the human. To accomplish this goal, preclinical and clinical tissue distribution and positron emission tomography imaging data generated using zirconium-89 (89Zr) labeled antibodies were obtained from the literature. First, our previously published translational PBPK model for antibodies was expanded to describe the whole-body biodistribution of 89Zr labeled antibody and the free 89Zr, as well as residualization of free 89Zr. Subsequently, the model was optimized using mouse biodistribution data, where it was observed that free 89Zr mainly residualizes in the bone and the extent of antibody distribution in certain tissues (e.g., liver and spleen) may be altered by labeling with 89Zr. The mouse PBPK model was scaled to rat, monkey, and human by simply changing the physiological parameters, and a priori simulations performed by the model were compared with the observed PK data. It was found that model predicted antibody PK in majority of the tissues in all the species superimposed over the observed data, and the model was also able to predict the PK of antibody in human tissues reasonably well. As such, the work presented here provides unprecedented evaluation of the antibody PPBK model for its ability to predict tissue PK of antibodies in the clinic. This model can be used for preclinical-to-clinical translation of antibodies and for prediction of antibody concentrations at the site-of-action in the clinic.

An adaptive biomarker basket design in phase II oncology trials.

The phase II basket trial in oncology is a novel design that enables the simultaneous assessment of treatment effects of one anti-cancer targeted agent in multiple cancer types. Biomarkers could potentially associate with the clinical outcomes and re-define clinically meaningful treatment effects. It is therefore natural to develop a biomarker-based basket design to allow the prospective enrichment of the trials with the adaptive selection of the biomarker-positive (BM+) subjects who are most sensitive to the experimental treatment. We propose a two-stage phase II adaptive biomarker basket (ABB) design based on a potential predictive biomarker measured on a continuous scale. At Stage 1, the design incorporates a biomarker cutoff estimation procedure via a hierarchical Bayesian model with biomarker as a covariate (HBMbc). At Stage 2, the design enrolls only BM+ subjects, defined as those with the biomarker values exceeding the biomarker cutoff within each cancer type, and subsequently assesses the early efficacy and/or futility stopping through the pre-defined interim analyses. At the end of the trial, the response rate of all BM+ subjects for each cancer type can guide drug development, while the data from all subjects can be used to further model the relationship between the biomarker value and the clinical outcome for potential future research. The extensive simulation studies show that the ABB design could produce a good estimate of the biomarker cutoff to select BM+ subjects with high accuracy and could outperform the existing phase II basket biomarker cutoff design under various scenarios.

Linked selection, differential introgression and recombination rate variation promote heterogeneous divergence in a pair of yellow croakers.

Understanding the mechanisms underlying heterogeneous genomic divergence is of particular interest in evolutionary biology. Highly differentiated genomic regions, known as genomic islands, often evolve between diverging lineages. These genomic islands may be related to selection promoting adaptation or reproductive isolation. Based on whole genome assembly and genome-wide RAD sequencing in a pair of yellow croakers (genus: Larimichthys), we investigated the evolutionary processes shaping genomic landscapes of divergence. Demographic modelling indicated that the two species diverged following a secondary contact scenario, where differential introgression and linked selection were suggested to be involved in heterogeneous genomic divergence. We identified reduced recombination rate in genomic islands and a relatively good conservation of both genetic diversity and recombination landscapes between species, which highlight the roles of linked selection and recombination rate variation in promoting heterogeneous divergence in the common ancestral lineage of the two species. In addition, we found a positive correlation between differentiation (FST ) and absolute sequence divergence (Dxy ), and elevated Dxy in genomic islands, indicating that the genomic landscape of divergence was not shaped by linked selection alone. Restricted gene flow in highly differentiated regions has probably remodelled the landscape of heterogeneous genomic divergence. This study highlights that highly differentiated genomic regions can also arise from a combination of linked selection and differential gene flow in interaction with varying recombination rates.

Mathematical Models to Characterize the Absorption, Distribution, Metabolism, and Excretion of Protein Therapeutics.

Therapeutic proteins (TPs) have ranked among the most important and fastest-growing classes of drugs in the clinic, yet the development of successful TPs is often limited by unsatisfactory efficacy. Understanding pharmacokinetic (PK) characteristics of TPs is key to achieving sufficient and prolonged exposure at the site of action, which is a prerequisite for eliciting desired pharmacological effects. PK modeling represents a powerful tool to investigate factors governing in vivo disposition of TPs. In this mini-review, we discuss many state-of-the-art models that recapitulate critical processes in each of the absorption, distribution, metabolism/catabolism, and excretion pathways of TPs, which can be integrated into the physiologically-based pharmacokinetic framework. Additionally, we provide our perspectives on current opportunities and challenges for evolving the PK models to accelerate the discovery and development of safe and efficacious TPs. SIGNIFICANCE STATEMENT: This minireview provides an overview of mechanistic pharmacokinetic (PK) models developed to characterize absorption, distribution, metabolism, and elimination (ADME) properties of therapeutic proteins (TPs), which can support model-informed discovery and development of TPs. As the next-generation of TPs with diverse physicochemical properties and mechanism-of-action are being developed rapidly, there is an urgent need to better understand the determinants for the ADME of TPs and evolve existing platform PK models to facilitate successful bench-to-bedside translation of these promising drug molecules.

Constrained hierarchical Bayesian model for latent subgroups in basket trials with two classifiers.

The basket trial in oncology is a novel clinical trial design that enables the simultaneous assessment of one treatment in multiple cancer types. In addition to the usual basket classifier of the cancer types, many recent basket trials further contain other classifiers like biomarkers that potentially affect the clinical outcomes. In other words, the treatment effects in those baskets are often categorized by not only the cancer types but also the levels of other classifiers. Therefore, the assumption of exchangeability is often violated when some baskets are more sensitive to the targeted treatment, whereas others are less. In this article, we propose a constrained hierarchical Bayesian model for latent subgroups (CHBM-LS) to deal with potential heterogeneity of treatment effects due to both the cancer type (first classifier) and another classifier (second classifier) in basket trials. Different baskets defined by multiple cancer types and multiple levels of the second classifier are aggregated into subgroups using a latent subgroup modeling approach. Within each latent subgroup, the treatment effects are similar and approximately exchangeable to borrow information. The CHBM-LS approach evaluates the treatment effect for each basket while allowing adaptive information borrowing across the baskets by identifying latent subgroups. The simulation study shows that the CHBM-LS approach outperforms other approaches with higher statistical power and better-controlled type I error rates under various scenarios with heterogeneous treatment effects across baskets.

TITE-gBOIN: Time-to-event Bayesian optimal interval design to accelerate dose-finding accounting for toxicity grades.

The new therapeutic agents, such as molecular targeted agents and immuno-oncology therapies, appear more likely to induce multiple toxicities at different grades than dose-limiting toxicities defined in traditional dose-finding trials. In addition, it is often challenging to make adaptive decisions on dose escalation and de-escalation on time because of the fast accrual rate and/or the late-onset toxicity outcomes, causing the potential suspension of the enrollment and the delay of the trials. To address these issues, we propose a time-to-event Bayesian optimal interval design to accelerate the dose-finding process utilizing toxicity grades based on both cumulative and pending toxicity outcomes. The proposed design, named "TITE-gBOIN" design, is a nonparametric and model-assisted design and has the virtues of robustness, simplicity and straightforward to implement in actual oncology dose-finding trials. A simulation study shows that the TITE-gBOIN design has a higher probability of selecting the MTDs correctly and allocating more patients to the MTDs across various realistic settings while reducing the trial duration significantly, therefore can accelerate early-stage dose-finding trials.

Transcriptome Profiling and Expression Localization of Key Sex-Related Genes in a Socially-Controlled Hermaphroditic Clownfish, Amphiprion clarkii.

Clownfish can be an excellent research model for investigating the socially-controlled sexual development of sequential hermaphrodite teleosts. However, the molecular cascades underlying the social cues that orchestrate the sexual development process remain poorly understood. Here, we performed a comparative transcriptomic analysis of gonads from females, males, and nonbreeders of Amphiprion clarkii, which constitute a complete social group, allowing us to investigate the molecular regulatory network under social control. Our analysis highlighted that the gonads of nonbreeders and males exhibited high similarities but were far from females, both in global transcriptomic profiles and histological characteristics, and identified numerous candidate genes involved in sexual development, some well-known and some novel. Significant upregulation of cyp19a1a, foxl2, nr5a1a, wnt4a, hsd3b7, and pgr in females provides strong evidence for the importance of steroidogenesis in ovarian development and maintenance, with cyp19a1a playing a central role. Amh and sox8 are two potential key factors that may regulate testicular tissue development in early and late stages, respectively, as they are expressed at higher levels in males than in females, but with slightly different expression timings. Unlike previous descriptions in other fishes, the unique expression pattern of dmrt1 in A. clarkii implied its potential function in both male and female gonads, and we speculated that it might play promoting roles in the early development of both testicular and ovarian tissues.

Divergent above- and below-ground biodiversity pathways mediate disturbance impacts on temperate forest multifunctionality.

Biodiversity plays a fundamental role in provisioning and regulating forest ecosystem functions and services. Above-ground (plants) and below-ground (soil microbes) biodiversity could have asynchronous change paces to human-driven land-use impacts. Yet, we know very little how they affect the provision of multiple forest functions related to carbon accumulation, water retention capacity and nutrient cycling simultaneously (i.e. ecosystem multifunctionality; EMF). We used a dataset of 22,000 temperate forest trees from 260 plots within 11 permanent forest sites in Northeastern China, which are recovering from three post-logging disturbances. We assessed the direct and mediating effects of multiple attributes of plant biodiversity (taxonomic, phylogenetic, functional and stand structure) and soil biodiversity (bacteria and fungi) on EMF under the three disturbance levels. We found the highest EMF in highly disturbed rather than undisturbed mature forests. Plant taxonomic, phylogenetic, functional and stand structural diversity had both positive and negative effects on EMF, depending on how the EMF index was quantified, whereas soil microbial diversity exhibited a consistent positive impact. Biodiversity indices explained on average 45% (26%-58%) of the variation in EMF, whereas climate and disturbance together explained on average 7% (0.4%-15%). Our result highlighted that the tremendous effect of biodiversity on EMF, largely overpassing those of both climate and disturbance. While above- (ß = 0.02-0.19) and below-ground (ß = 0.16-0.26) biodiversity had direct positive effects on EMF, their opposite mediating effects (ß = -0.22 vs. ß = 0.35 respectively) played as divergent pathways to human disturbance impacts on EMF. Our study sheds light on the need for integrative frameworks simultaneously considering above- and below-ground attributes to grasp the global picture of biodiversity effects on ecosystem functioning and services. Suitable management interventions could maintain both plant and soil microbial biodiversity, and thus guarantee a long-term functioning and provisioning of ecosystem services in an increasing disturbance frequency world.

Adventitious roots support population expansion of the invasive plant Mikania micrantha Kunth.

Mikania micrantha Kunth is a serious invasive alien plant characterized by the formation of an adventitious root system in its prostrate growth form. Unlike the initial roots from seed germination, adventitious roots gradually appear above the stem and branch nodes. Little is known about adventitious roots play on plant growth and population expansion of M. micrantha. We hypothesized that adventitious roots provide an advantage for plant growth and nutrient availability. To test this hypothesis, plant growth, physiology, and nutrition characteristics of M. micrantha were measured under four soil surface conditions allowing various plant parts to touch the soil to stimulate variable adventitious root formation. The results showed that the biomass, stem length, branch number, and adventitious root biomass of M. micrantha were significantly increased (P < 0.05) with increasing nodes bearing adventitious roots. As the number of nodes with adventitious roots increased, the net photosynthetic rate, antioxidant enzyme activities like superoxide dismutase, catalase, peroxidase, and malondialdehyde, chlorophyll content, and plant nutrient contents (N, P, and K) of M. micrantha were increased (P < 0.05), with higher values in main stem leaves than in those of branch leaves. The concentrations of soil organic matter, total N, total P, total K, available N, available P, and available K were greater (P < 0.05) in initial soil (CK) than in treatment soil (with M. micrantha) and were significantly reduced by adventitious roots. Our study was the first to show that plant growth, physiology and nutrition status of M. micrantha were strongly promoted by adventitious roots in the prostrate growth form.

The Influence of Fluid Intake Behavior on Cognition and Mood among College Students in Baoding, China.

INTRODUCTION: Water is a critical nutrient, and it is important for the maintenance of the physiological function of the human body [1-3]. In addition to fluid amounts, fluid intake frequency is also important for hydration status [4, 5]. At present, only few guidelines mention fluid intake behavior that recommend drinking water frequently while in small quantities, however, there is no scientific evidence to support it. Therefore, it is necessary to explore the appropriate fluid intake behavior. OBJECTIVE: The objective of this study is to evaluate the influence of different fluid intake behavior on cognition and mood, to provide scientific basis for proposing the appropriate fluid intake behavior. METHODS: A double-blinded randomized controlled trial was designed and implemented among college students aged 18-23 years in Baoding, China. Subjects were randomly assigned into each of 3 groups using a random number generated by computer software: the subjects consuming plain water 200 mL/2 h, that is, 1,600 mL during whole day (group 1), 100 mL/2 h, that is, 800 mL during whole day (group 2), and 110 mL/1 h, that is, 1,650 mL during whole day (group 3), respectively. Subjects were asked to fast from 11:00 p.m., without consuming any foods or drinks the day before the intervention. From 8:00 a.m. to 10:00 p.m. of the first study day, subjects consumed water according to the instructions and repeated it from 8:00 a.m. to 4:00 p.m. of the second study day. Cognition, mood, and urine osmolality were collected twice at 10:00 a.m. (time 1) and 4:00 p.m. (time 2) of the second study day (shown in Fig. 1). RESULTS: A total of 92 subjects (46 males, 46 females) completed this study. It was found that the increasing fluid intake amounts lead to an increase in urine output and a decrease in urine osmolality (p < 0.05). Use the mixed models to compare measurements for groups 1 and 2, which showed that when compared with those drinking 800 mL per day, people who drank 1,600 mL per day scored higher in vigor (11.8 vs. 9.1, p < 0.05) and portrait memory test (22.6 vs. 20.8, p < 0.05) but lower in total mood disturbance (90.8 vs. 97.8, p < 0.05). By comparing groups 1 and 3, the results indicated that compared with drinking 8 times per day, people who drank 15 times per day scored lower in portrait memory test (21.8 vs. 22.6, p < 0.05) and hunger (3.3 vs. 3.6, p < 0.05). CONCLUSIONS: Reasonable fluid intake behavior may be beneficial to improve the cognition and mood of college students. The fluid intake behavior, which is consuming water 200 mL each time and 8 times per day, is recommended. More studies are needed to advise people to have health-beneficial fluid intake behavior.