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Abstract Background Preclinical studies have demonstrated that VT1021, a first-in-class therapeutic agent, inhibits tumor growth via stimulation of thrombospondin-1 (TSP-1) and reprograms the tumor microenvironment. We recently reported data from the dose escalation part of a phase I study of VT1021 in solid tumors. Here, we report findings from the dose expansion phase of the same study. Methods We analyzed the safety and tolerability, clinical response, and biomarker profile of VT1021 in the expansion portion of the phase I study (NCT03364400). Safety/tolerability is determined by adverse events related to the treatment. Clinical response is determined by RECIST v1.1 and iRECIST. Biomarkers are measured by multiplexed ion beam imaging and enzyme-linked immunoassay (ELISA). Results First, we report the safety and tolerability data as the primary outcome of this study. Adverse events (AE) suspected to be related to the study treatment (RTEAEs) are mostly grade 1–2. There are no grade 4 or 5 adverse events. VT1021 is safe and well tolerated in patients with solid tumors in this study. We report clinical responses as a secondary efficacy outcome. VT1021 demonstrates promising single-agent clinical activity in recurrent GBM (rGBM) in this study. Among 22 patients with rGBM, the overall disease control rate (DCR) is 45% (95% confidence interval, 0.24-0.67). Finally, we report the exploratory outcomes of this study. We show the clinical confirmation of TSP-1 induction and TME remodeling by VT1021. Our biomarker analysis identifies several plasmatic cytokines as potential biomarkers for future clinical studies. Conclusions VT1021 is safe and well-tolerated in patients with solid tumors in a phase I expansion study. VT1021 has advanced to a phase II/III clinical study in glioblastoma (NCT03970447).

Ethical concerns about how artificial intelligence (AI) impacts individuals and society are increasing rapidly, but few studies have systematically investigated the public awareness of AI ethics. This research collected and analyzed data from a public poll in Taiwan, an Asian region with a developed economy and specific social conditions, to identify societal views on AI ethics. The analysis of 84 AI ethics guidelines worldwide provided the survey framework covering five ethical principles: transparency, fairness, privacy, nonmaleficence, and accountability. The overarching goal was to determine the commonalities and differences in the ethical concerns of Taiwanese laypersons toward AI. Participants aged from 20 to 70 ( $N =1$ ,200) completed a computer-assisted random-digit-dial telephone survey, which utilized ethical scenarios to capture social views, and item validity was confirmed using focus-group interviews. Results found that respondents concerned about nonmaleficence the most, emphasizing that AI applications should not harm humans. Taiwanese people therefore tended to support strict AI technology regulation. It was particularly interesting that different patterns of public concern emerged about accountability, with the opinions on attributing responsibility to stakeholders varying with scenarios and the public’s backgrounds. Those with higher education levels tended to attribute more responsibility to the industry, whereas those who had only received elementary-school education attributed accountability to AI developers. For self-driving cars, accountability was attributed to AI developers, whereas for medical decision-making, the accountability was attributed to the hospitals. These findings may help to elucidate the associations between societal views and the ethical principles of AI worldwide.

Quantitative measuring the population-level diversity-scaling of human microbiomes is different from conventional approach to traditional individual-level diversity analysis, and it is of obvious significance. For example, it is well known that individuals are of significant heterogeneity with their microbiome diversities, and the population-level analysis can effectively capture such kind of individual differences. Here we reanalyze a dozen datasets of 2,115 human breast milk microbiome (BMM) samples with diversity-area relationship (DAR) to tackle the previous questions. Our focus on BMM is aimed to offer insights for supplementing the gut microbiome research from nutritional perspective. DAR is an extension to classic species-area relationship, which was discovered in the 19th century and established as one of a handful fundamental laws in community ecology. Our DAR modeling revealed the following numbers, all approximately: (i) The population-level potential diversity of BMM is 1,108 in terms of species richness (number of total species), and 67 in terms of typical species. (ii) On average, an individual carry 17% of population-level diversity in terms of species richness, and 61% in terms of typical species. (iii) The similarity (overlap) between individuals according to pair-wise diversity overlap (PDO) should be approximately 76% in terms of total species, and 92% in terms of typical species, which symbolizes the inter-individual heterogeneity. (iv) The average individual (alpha-) diversity of BMM is approximately 188 (total-species) and 37 (typical-species). (v) To deal with the potential difference among 12 BMM datasets, we conducted DAR modeling separately for each dataset, and then performed permutation tests for DAR parameters. It was found that the DAR scaling parameter that measures inter-individual heterogeneity in diversity is invariant (constant), but the population potential diversity is different among 30% of the pair-wise comparison between 12 BMM datasets. These results offer comprehensive biodiversity analyses of the BMM from host individual, inter-individual, and population level perspectives.

Abstract Background Ulcerative colitis (UC) is one of the primary types of inflammatory bowel disease (IBD), the occurrence of which has been increasing worldwide. Although IBD is an intensively studied human microbiome-associated disease, research on Chinese populations remains relatively limited, particularly on the mucosal microbiome. The present study aimed to analyze the changes in the mucosal microbiome associated with UC from the perspectives of medical ecology and complex network analysis. Results In total, 56 mucosal microbiome samples were collected from 28 Chinese UC patients and their healthy family partners, followed by amplicon sequencing. Based on sequencing data, we analyzed species diversity, shared species, and inter-species interactions at the whole community, main phyla, and core/periphery species levels. We identified four opportunistic “pathogens” (i.e., Clostridium tertium, Odoribacter splanchnicus, Ruminococcus gnavus, and Flavonifractor plautii) with potential significance for the diagnosis and treatment of UC, which were inhibited in healthy individuals, but unrestricted in the UC patients. In addition, we also discovered in this study: (i) The positive-to-negative links (P/N) ratio, which measures the balance of species interactions or inhibition effects in microbiome networks, was significantly higher in UC patients, indicating loss of inhibition against potentially opportunistic “pathogens” associated with dysbiosis. (ii) Previous studies have reported conflicting evidence regarding species diversity and composition between UC patients and healthy controls. Here, significant differences were found at the major phylum and core/periphery scales, but not at the whole community level. Thus, we argue that the paradoxical results found in existing studies are due to the scale effect. Conclusions Our results reveal changes in the ecology and network structure of the gut mucosal microbiome that might be associated with UC, and these changes might provide potential therapeutic mechanisms of UC. The four opportunistic pathogens that were identified in the present study deserve further investigation in future studies.

Diversity-disease relationship (DDR) is a de facto standard analysis in the studies of human microbiome associated diseases (MADs). For example, the species richness or Shannon entropy are routinely compared between the healthy and diseased groups. Nevertheless, the basic scale of the standard diversity analysis is individual subject rather than a cohort or population because the diversity is computed for individual samples, not for the group. Here we aim to expand the current DDR study from individual focus to population level, which can offer important insights for understanding the epidemiology of MADs. We analyzed the diversity-disease relationship at cohort scale based on a collection of 23 datasets covering the major human MADs. Methodologically, we harness the power of a recent extension to the classic species-area relationship (SAR), i.e., the diversity-area relationship (DAR), to achieve the expansion from individual DDR to inter-subject diversity scaling analysis. Specifically, we apply the DAR analysis to estimate and compare the potentially maximal accrual diversities of the healthy and diseases groups, as well as the inter-subject diversity scaling parameters and the individual-to-population diversity ratios. It was shown that, except for the potential diversity (Dmax) at the cohort level in approximately 5.4% cases of MADs, DAR parameters displayed no significant differences between healthy and diseased treatments. That is, the DAR parameters are rather resilient against MADs, except for the potential diversity in some diseases. We compared our population-level DDR with the existing individual-level DDR patterns and proposed a hypothesis to interpret their differences.

The purpose of this study was to identify the risk factors associated with paternal perinatal mental distress in a sample of Australian men. A mixed-methods design was used. The qualitative component ( N = 13) using thematic analysis identified maternal depression, marital distress, masculine gender role stress, unplanned pregnancy, work–family conflict, and sleep disturbance as risk factors for paternal perinatal mental distress. The quantitative component ( N = 525) expanded on the qualitative findings and examined the associations between the identified risk factors and mental distress of fathers in the perinatal period measured by Edinburgh postnatal depression scale. Hierarchical multiple regression analysis revealed six significant predictors of paternal perinatal mental distress with masculine gender role stress being the most significant risk factor for paternal perinatal mental distress. The results from this study provide an insight into how masculine gender role may affect the expression and experience of mental distress in fathers within the perinatal period. Implications of research findings are discussed.

Although Lactobacillus dominance is one of the commonest characteristics of many healthy vaginal microbiomes, a significant proportion of healthy women lack an appreciable amount of Lactobacillus in their microbiome. Indeed, the vaginal microbiomes of many BV (bacterial vaginosis) patients lack the dominance by Lactobacillus. One would wonder what are special with those healthy non-Lactobacillus dominated vaginal microbiomes (nLDVM)? Here we re-analyzed the vaginal microbiome datasets of 1107 postpartum women in rural Malawi Doyle et al. (2018) using species dominance network (SDN) analysis. We discovered that: (i) The DN of the nLDVM is predominantly mutualistic, where most competitive (negative) relationships were from bacterial vaginosis-associated bacteria (BVAB), >60% occurred between BVAB and non-BVAB genera. Gardnerella was inhibited by a mutualistic combination of 23 genera, and Lactobacillus by 15 genera. These may be possible mechanisms by which the microbiome maintains high diversity but avoids dominance by Gardnerella or Lactobacillus. Gardnerella and Lactobacillus were only cooperated with a few genera, but they were positively connected with each other. The suppressed Lactobacillus species positively associated with Gardnerella was Lactobacillus iners, indicating that L. iners might act as an “enemy” in the Lactobacillus-poor vaginal microbiome, and inhibition of Gardnerella and L. iners might be a self-protective mechanism to maintain stability and health of this microbiome. (ii) We identified skeletons of the DNs and separate pathways consisting of high salience skeletons. Finegoldia species and Staphylococcus epidermidis were the hubs of the skeleton network. The roles that they play in the nLDVM deserve more attention of future studies.

Objective: Several members of the angiopoietin-like (ANGPTL) family of proteins, including ANGPTL3 and ANGPTL8, regulate lipoprotein lipase (LPL) activity. Deficiency in either ANGPTL3 or ANGPTL8 reduces plasma triglyceride levels and increases LPL activity, whereas overexpression of either protein does the opposite. Recent studies suggest that ANGPTL8 may functionally interact with ANGPTL3 to alter clearance of plasma triglycerides; however, the nature of this interaction has remained elusive. We tested the hypothesis that ANGPTL8 forms a complex with ANGPTL3 and that this complex is necessary for the inhibition of vascular LPL by ANGPTL3. Methods: We analyzed the interactions of ANGPTL3 and ANGPTL8 with each other and with LPL using co-immunoprecipitation, western blotting, lipase activity assays, and the NanoBiT split-luciferase system. We also used adenovirus injection to overexpress ANGPTL3 in mice that lacked ANGPTL8. Results: We found that ANGPTL3 or ANGPTL8 alone could only inhibit LPL at concentrations that far exceeded physiological levels, especially when LPL was bound to its endothelial cell receptor/transporter GPIHBP1 (glycosylphosphatidylinositol-anchored high-density lipoprotein binding protein 1). Physical interaction was observed between ANGPTL3 and ANGPTL8 when the proteins were co-expressed, and co-expression with ANGPTL3 greatly enhanced the secretion of ANGPTL8. Importantly, ANGPTL3–ANGPTL8 complexes had a dramatically increased ability to inhibit LPL compared to either protein alone. Adenovirus experiments showed that 2-fold overexpression of ANGPTL3 significantly increased plasma triglycerides only in the presence of ANGPTL8. Protein interaction assays showed that ANGPTL8 greatly increased the ability of ANGPTL3 to bind LPL. Conclusions: Together, these data indicate that ANGPTL8 binds to ANGPTL3 and that this complex is necessary for ANGPTL3 to efficiently bind and inhibit LPL.

Abstract Microgenderome or sexual dimorphism in microbiome refers to the bidirectional interactions between microbiotas, sex hormones, and immune systems, and it is highly relevant to disease susceptibility. A critical step in exploring microgenderome is to dissect the sex differences in key community ecology properties, which has not been systematically analyzed. This study aims at filling the gap by reanalyzing the Human Microbiome Project datasets with two objectives: (i) dissecting the sex differences in community diversity and their intersubject scaling, species composition, core/periphery species, and high‐salience skeletons (species interactions); (ii) offering mechanistic interpretations for (i). Conceptually, the Vellend–Hanson synthesis of community ecology that stipulates selection, drift, speciation, and dispersal as the four processes driving community dynamics is followed. Methodologically, seven approaches reflecting the state‐of‐the‐art research in medical ecology of human microbiomes are harnessed to achieve the objectives. It is postulated that the revealed microgenderome characteristics (categorized as seven aspects of differences/similarities) exert far reaching influences on disease susceptibility, and are primarily due to the sex difference in selection effects (deterministic fitness differences in microbial species and/or species interactions with each other or with their hosts), which are, in turn, shaped/modulated by host physiology (immunity, hormones, gut–brain communications, etc.).

Background: The implications of gut microbiome to obesity have been extensively investigated in recent years although the exact mechanism is still unclear. The question whether or not obesity influences gut microbiome assembly has not been addressed. The question is significant because it is fundamental for investigating the diversity maintenance and stability of gut microbiome, and the latter should hold a key for understanding the etiological implications of gut microbiome to obesity.Methods: In this study, we adopt a dual neutral theory modeling strategy to address this question from both species and community perspectives, with both discrete and continuous neutral theory models. The first neutral theory model we apply is Hubbell's neutral theory of biodiversity that has been extensively tested in macro-ecology of plants and animals, and the second we apply is Sloan's neutral theory model that was developed particularly for microbial communities based on metagenomic sequencing data. Both the neutral models are complementary to each other and integrated together offering a comprehensive approach to more accurately revealing the possible influence of obesity on gut microbiome assembly. This is not only because the focus of both neutral theory models is different (community vs. species), but also because they adopted two different modeling strategies (discrete vs. continuous).Results: We test both the neutral theory models with datasets from Turnbaugh et al. (2009). Our tests showed that the species abundance distributions of more than ½ species (59–69%) in gut microbiome satisfied the prediction of Sloan's neutral theory, although at the community level, the number of communities satisfied the Hubbell's neutral theory was negligible (2 out of 278).Conclusion: The apparently contradictory findings above suggest that both stochastic neutral effects and deterministic environmental (host) factors play important roles in shaping the assembly and diversity of gut microbiome. Furthermore, obesity may just be one of the host factors, but its influence may not be strong enough to tip the balance between stochastic and deterministic forces that shape the community assembly. Finally, the apparent contradiction from both the neutral theories should not be surprising given that there are still near 30–40% species that do not obey the neutral law.

A human body hosts a relatively independent microbiome including five major regional biomes (i.e., airway, oral, gut, skin, and urogenital). Each of them may possess different regional characteristics with important implications to our health and diseases (i.e., so-termed microbiome associated diseases). Nevertheless, these regional microbiomes are connected with each other through diffusions and migrations. Here, we investigate the within-body (intra-individual) distribution feature of microbiome diversity via diversity area relationship (DAR) modeling, which, to the best of our knowledge, has not been systematically studied previously. We utilized the Hill numbers for measuring alpha and beta-diversities and built 1,200 within-body DAR models with to date the most comprehensive human microbiome datasets of 18 sites from the human microbiome project (HMP) cohort. We established the intra-DAR profile (z-q pattern: the diversity scaling parameter z of the power law (PL) at diversity order q = 0–3), intra-PDO (pair-wise diversity overlap) profile (g-q), and intra-MAD (maximal accrual diversity) profile (Dmax-q) for the within-body biogeography of the human microbiome. These profiles constitute the “maps” of the within-body biogeography, and offer important insights on the within-body distribution of the human microbiome. Furthermore, we investigated the heterogeneity among individuals in their biogeography parameters and found that there is not an “average Joe” that can represent majority of individuals in a cohort or population. For example, we found that most individuals in the HMP cohort have relatively lower maximal accrual diversity (MAD) or in the “long tail” of the so-termed power law distribution. In the meantime, there are a small number of individuals in the cohort who possess disproportionally higher MAD values. These findings may have important implications for personalized medicine of the human microbiome associated diseases in practice, besides their theoretical significance in microbiome research such as establishing the baseline for the conservation of human microbiome.

A sample of 324 55–90-year-old Australian adults participated in a survey on elderly substance abuse using the Clinical Assessment Scales for the Elderly. Overall, males had a higher prevalence rate of substance abuse than females. Significant differences in substance abuse mean scores were found for gender, age, income, community involvement, and retirement. The findings also reveal that being a female, involved in community groups, being a retiree, and being a non-baby boomer are protective factors of substance abuse. Being an upper medium income earner appears to be a risk factor of substance abuse.

Drawing on ecological perspectives, this study investigates changes in the bilingual education of ethnic Koreans in China in the context of globalization. Focusing on two Chosonjuk (ethnic Korean in China, ?????, ???) schools in Northeast China that experienced challenges due to declining enrollment as a result of the increasing popularity of attending "Han" (ethnic Han Chinese, ??) schools, this study discusses the ways in which these two schools repositioned their bilingual programs to leverage the Korean (Chosonmal, ???) and "Mandarin" (Putonghua, ???) languages as linguistic capital and the ways in which such repositioning affected the school choices of Chosonjuk families and other student families. Our findings show that these two schools implemented a series of changes, including the provision of individualized instruction to students to meet their specific needs and the enrollment of "Han" students and international students from South Korea who were interested in learning the Korean or "Mandarin languages." These practices increased the attractiveness of the two schools to families with a variety of needs and concurrently created an inclusive educational environment for the students.

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Abstract Rationale Research studies typically quantify acute respiratory exacerbation episodes (AECOPD) among people with chronic obstructive pulmonary disease (COPD) based on self-report elicited by survey questionnaire. However, AECOPD quantification by self-report could be inaccurate, potentially rendering it an imprecise tool for identification of those with exacerbation tendency. Objective Determine the agreement between self-reported and health records-documented quantification of AECOPD and their association with airway inflammation. Methods We administered a questionnaire to elicit the incidence and severity of respiratory exacerbations in the three years preceding the survey among current or former heavy smokers with or without diagnosis of COPD. We then examined electronic health records (EHR) of those with COPD and those without (tobacco-exposed persons with preserved spirometry or TEPS) to determine whether the documentation of the three-year incidence of moderate to very severe respiratory exacerbations was consistent with self-report using Kappa Interrater statistic. A subgroup of participants also underwent bronchoalveolar lavage (BAL) to quantify their airway inflammatory cells. We further used multivariable regressions analysis to estimate the association between respiratory exacerbations and BAL inflammatory cell composition with adjustment for covariates including age, sex, height, weight, smoking status (current versus former) and burden (pack-years). Results Overall, a total of 511 participants completed the questionnaire, from whom 487 had EHR available for review. Among the 222 participants with COPD (70 ± 7 years-old; 96% male; 70 ± 38 pack-years smoking; 42% current smoking), 57 (26%) reported having any moderate to very severe AECOPD (m/s-AECOPD) while 66 (30%) had EHR documentation of m/s-AECOPD. However, 42% of those with EHR-identified m/s-AECOPD had none by self-report, and 33% of those who reported m/s-AECOPD had none by EHR, suggesting only moderate agreement (Cohen’s Kappa = 0.47 ± 0.07; P

Background: Near-peer teaching (NPT) involves teaching by peers who are at a close, but not the same, level of training. This study investigated whether a novel surgical NPT workshop, designed and delivered by junior doctors using simulation models for acute otolaryngology conditions, improved the knowledge and confidence level of senior medical students. Methods: A one-day NPT workshop was held for medical students in their third year of a four-year postgraduate medical degree at the University of Notre Dame, Sydney, Australia. Four acute otolaryngology/head and neck surgery problems that might be encountered by junior doctors and require prompt management were chosen. These were post-operative neck swelling, epistaxis, and tracheostomy management (obstruction and bleeding). Six junior doctors facilitated didactic tutorials and practical skills training using models. Multiple choice question mini-tests and questionnaires were administered before and after the workshop to assess changes in students' knowledge and confidence in assessment, management, and practical skills. Results: The most common reason for participation was to acquire knowledge and practical skills (93.2 %). Mean correct MCQ mini-test knowledge scores increased significantly from 60 % pre-workshop to 83.9 % post-workshop (p

IntroductionCryptosporidium parvum (C. parvum) is the most prevalent enteric protozoan parasite causing infectious diarrhea in neonatal calves worldwide with a direct negative impact on their health and welfare. This study utilized next-generation sequencing (NGS) to deepen our understanding of intestinal epithelial barriers and transport mechanisms in the pathophysiology of infectious diarrhea in neonatal calves, which could potentially unveil novel solutions for treatment.MethodsAt day 1 of life, male Holstein-Friesian calves were either orally infected (n = 5) or not (control group, n = 5) with C. parvum oocysts (in-house strain LE-01-Cp-15). On day 8 after infection, calves were slaughtered and jejunum mucosa samples were taken. The RNA was extracted from collected samples and subjected to sequencing. Differentially expressed genes (DEG) between the infected and CTRL groups were assessed using DESeq2 at a false discovery rate < 0.05 and used for gene ontology (GO) and pathway enrichment analysis in Cytoscape (v3.9.1).Results and discussionTo study the pathophysiology of infectious diarrhea on intestinal permeability, 459 genes related to epithelial cell barrier integrity and paracellular and transmembrane transport systems were selected from 12,908 identified genes in mucus. Among, there were 61 increased and 109 decreased gene transcripts belonged to adhesion molecules (e.g. ADGRD1 and VCAM1), ATP-binding cassette (ABC, e.g. ABCC2 and ABCD1) and solute carrier (SLC, e.g. SLC28A2 and SLC38A3) transporters, and ion channels (e.g. KCNJ15). Our results suggest deregulation of cellular junctions and thus a possibly increased intestinal permeability, whereas deregulation of ABC and SLC transporters and ion channels may influence the absorption/secretion of amino acids, carbohydrates, fats, and organic compounds, as well as acid-based balance and osmotic hemostasis. Besides pathogen-induced gene expression alterations, part of the DEG may have been triggered or consequently affected by inflammatory mechanisms. The study provided a deeper understanding of the pathophysiology of infectious diarrhea in neonatal calves and the host-pathogen interactions at the transcript level. For further studies with a particular focus on the transport system, these results could lead to a new approach to elucidating pathophysiological regulatory mechanisms.