High-Throughput Mass Spectrometry Analysis of N-Glycans and Protein Markers after FUT8 Knockdown in the Syngeneic SW480/SW620 Colorectal Cancer Cell Model

Disruption of the glycosylation machinery is a common feature in many types of cancer, and colorectal cancer (CRC) is no exception. Core fucosylation is mediated by the enzyme fucosyltransferase 8 (FucT-8), which catalyzes the addition of α1,6-l-fucose to the innermost GlcNAc residue of N-glycans. We and others have documented the involvement of FucT-8 and core-fucosylated proteins in CRC progression, in which we addressed core fucosylation in the syngeneic CRC model formed by SW480 and SW620 tumor cell lines from the perspective of alterations in their N-glycosylation profile and protein expression as an effect of the knockdown of the FUT8 gene that encodes FucT-8. Using label-free, semiquantitative mass spectrometry (MS) analysis, we found noticeable differences in N-glycosylation patterns in FUT8-knockdown cells, affecting core fucosylation and sialylation, the Hex/HexNAc ratio, and antennarity. Furthermore, stable isotopic labeling of amino acids in cell culture (SILAC)-based proteomic screening detected the alteration of species involved in protein folding, endoplasmic reticulum (ER) and Golgi post-translational stabilization, epithelial polarity, and cellular response to damage and therapy. This data is available via ProteomeXchange with identifier PXD050012. Overall, the results obtained merit further investigation to validate their feasibility as biomarkers of progression and malignization in CRC, as well as their potential usefulness in clinical practice.

A Framework for Unsupervised Profiling of Malaria Vectors' Insecticide Resistance Using Machine Learning Technique

Background: There is a need to identify different insecticide resistance profiles that represent circumscription-encapsulation of knowledge about malaria vectors' insecticide resistance to increase our understanding of malaria vectors' insecticide resistance dynamics. Methods: Data used in this study are part of the aggregation of over 20,000 mosquito collections done between 1957 and 2018. We applied two data preprocessing steps. We developed three clustering machine learning models based on the K-means algorithm with three selected datasets. The elbow method was used to fine-tune the hyperparameters. We used the silhouette score to assess the clustering results produced by each of the three models. The proposed framework incorporates continuous learning, allowing the machine learning models to learn continuously. Results: For the first model, the optimal number of clusters (profiles) k was 17. For the second model, we found four profiles. For the third model, the optimal number of profiles was 7. Discussion: We found that the insecticide resistance profiles have dynamic resistance levels with respect to the insecticide component, species component, location component, and time component. This profiling task provided knowledge about the evolution of malaria vectors' insecticide resistance in the African continent by encapsulating the information on the complex interaction between the different dimensions of malaria vectors' insecticide resistance into different profiles. Policy makers can use the knowledge about the different profiles found from the analysis of available insecticide resistance monitoring data (through profiling) by using our proposed approach to set up malaria vector control strategies that consider the locations, species present in those locations, and potentially efficient insecticides.

Flagging unusual clusters based on linear mixed models using weighted and self-calibrated predictors

Statistical models incorporating cluster-specific intercepts are commonly used in hierarchical settings, for example, observations clustered within patients or patients clustered within hospitals. Predicted values of these intercepts are often used to identify or "flag" extreme or outlying clusters, such as poorly performing hospitals or patients with rapid declines in their health. We consider a variety of flagging rules, assessing different predictors, and using different accuracy measures. Using theoretical calculations and comprehensive numerical evaluation, we show that previously proposed rules based on the 2 most commonly used predictors, the usual best linear unbiased predictor and fixed effects predictor, perform extremely poorly: the incorrect flagging rates are either unacceptably high (approaching 0.5 in the limit) or overly conservative (eg, much <0.05 for reasonable parameter values, leading to very low correct flagging rates). We develop novel methods for flagging extreme clusters that can control the incorrect flagging rates, including very simple-to-use versions that we call "self-calibrated." The new methods have substantially higher correct flagging rates than previously proposed methods for flagging extreme values, while controlling the incorrect flagging rates. We illustrate their application using data on length of stay in pediatric hospitals for children admitted for asthma diagnoses.

Features of immunometabolic depression as predictors of antidepressant treatment outcomes: pooled analysis of four clinical trials

BACKGROUND

Profiling patients on a proposed 'immunometabolic depression' (IMD) dimension, described as a cluster of atypical depressive symptoms related to energy regulation and immunometabolic dysregulations, may optimise personalised treatment.

AIMS

To test the hypothesis that baseline IMD features predict poorer treatment outcomes with antidepressants.

METHOD

Data on 2551 individuals with depression across the iSPOT-D (n = 967), CO-MED (n = 665), GENDEP (n = 773) and EMBARC (n = 146) clinical trials were used. Predictors included baseline severity of atypical energy-related symptoms (AES), body mass index (BMI) and C-reactive protein levels (CRP, three trials only) separately and aggregated into an IMD index. Mixed models on the primary outcome (change in depressive symptom severity) and logistic regressions on secondary outcomes (response and remission) were conducted for the individual trial data-sets and pooled using random-effects meta-analyses.

RESULTS

Although AES severity and BMI did not predict changes in depressive symptom severity, higher baseline CRP predicted smaller reductions in depressive symptoms (n = 376, βpooled = 0.06, P = 0.049, 95% CI 0.0001-0.12, I2 = 3.61%); this was also found for an IMD index combining these features (n = 372, βpooled = 0.12, s.e. = 0.12, P = 0.031, 95% CI 0.01-0.22, I2= 23.91%), with a higher - but still small - effect size compared with CRP. Confining analyses to selective serotonin reuptake inhibitor users indicated larger effects of CRP (βpooled = 0.16) and the IMD index (βpooled = 0.20). Baseline IMD features, both separately and combined, did not predict response or remission.

CONCLUSIONS

Depressive symptoms of people with more IMD features improved less when treated with antidepressants. However, clinical relevance is limited owing to small effect sizes in inconsistent associations. Whether these patients would benefit more from treatments targeting immunometabolic pathways remains to be investigated.

Transcriptomic Profiling for Prognostic Biomarkers in Early-Stage Squamous Cell Lung Cancer (SqCLC)

Squamous cell lung carcinoma (SqCLC) is associated with high mortality and limited treatment options. Identification of therapeutic targets and prognostic biomarkers is still lacking. This research aims to analyze the transcriptomic profile of SqCLC samples and identify the key genes associated with tumorigenesis, overall survival (OS), and a profile of the tumor-infiltrating immune cells. Differential gene expression analysis, pathway enrichment analysis, and Gene Ontology analysis on RNA-seq data obtained from FFPE tumor samples (N = 23) and healthy tissues (N = 3) were performed (experimental cohort). Validation of the results was conducted on publicly available gene expression data using TCGA LUSC (N = 225) and GTEx healthy donors' cohorts (N = 288). We identified 1133 upregulated and 644 downregulated genes, common for both cohorts. The most prominent upregulated genes were involved in cell cycle and proliferation regulation pathways (MAGEA9B, MAGED4, KRT, MMT11/13), while downregulated genes predominately belonged to immune-related pathways (DEFA1B, DEFA1, DEFA3). Results of the survival analysis, conducted on the validation cohort and commonly deregulated genes, indicated that overexpression of HOXC4 (p < 0.001), LLGL1 (p = 0.0015), and SLC4A3 (p = 0.0034) is associated with worse OS in early-stage SqCLC patients. In contrast, overexpression of GSTZ1 (p = 0.0029) and LILRA5 (p = 0.0086) was protective, i.e., associated with better OS. By applying a single-sample gene-set enrichment analysis (ssGSEA), we identified four distinct immune subtypes. Immune cell distribution suggests that the memory T cells (central and effector) and follicular helper T cells could serve as important stratification parameters.

Genetic Profiling Uncovers Genome-Wide Loss of Heterozygosity and Provides Insight into Mechanisms of Sarcomatoid Transformation in Chromophobe Renal Cell Carcinoma

Sarcomatoid transformation occurs in ∼8% of chromophobe renal cell carcinoma (chRCC) and is associated with aggressive clinical behavior. In recent years, several studies have identified genomic, transcriptomic, and epigenomic correlates of aggressive behavior in chRCC; however, the molecular mechanisms associated with sarcomatoid transformation remain incompletely understood. In this study, we analyzed paired conventional and sarcomatoid histologic components of individual chRCC to elucidate the genomic alterations that underlie sarcomatoid transformation in this tumor type. Massively parallel sequencing was performed on paired (conventional and sarcomatoid) components from 8 chRCCs. All cases harbored TP53 variants (87.5% showing TP53 variants in both components and 12.5% only in the sarcomatoid component). Intratumor comparisons revealed that TP53 variants were concordant in 71% and discordant in 29% of cases. Additional recurrent single-nucleotide variants were found in RB1 (37.5% of cases) and PTEN (25% of cases), with the remaining single-nucleotide variants detected in these tumors (PBRM1, NF1, and ASXL1) being nonrecurrent. Copy number variant analysis showed the characteristic pattern of chromosomal losses associated with chRCC (1, 2, 6, 10, 13, 17, and 21) in the conventional histologic components only. Interestingly, the sarcomatoid components of these tumors demonstrated widespread loss of heterozygosity but lacked the above chromosomal losses, likely as a consequence of whole-genome duplication/imbalanced chromosomal duplication events. Overall, the findings suggest that TP53 variants followed by whole-genome duplication/imbalanced chromosomal duplication events underlie sarcomatoid transformation in chRCC.

Inhibition of anti-tumor immunity by melanoma cell-derived Activin-A depends on STING

The transforming growth factor-β (TGF-β) family member activin A (hereafter Activin-A) is overexpressed in many cancer types, often correlating with cancer-associated cachexia and poor prognosis. Activin-A secretion by melanoma cells indirectly impedes CD8+ T cell-mediated anti-tumor immunity and promotes resistance to immunotherapies, even though Activin-A can be proinflammatory in other contexts. To identify underlying mechanisms, we here analyzed the effect of Activin-A on syngeneic grafts of Braf mutant YUMM3.3 mouse melanoma cells and on their microenvironment using single-cell RNA sequencing. We found that the Activin-A-induced immune evasion was accompanied by a proinflammatory interferon signature across multiple cell types, and that the associated increase in tumor growth depended at least in part on pernicious STING activity within the melanoma cells. Besides corroborating a role for proinflammatory signals in facilitating immune evasion, our results suggest that STING holds considerable potential as a therapeutic target to mitigate tumor-promoting Activin-A signaling at least in melanoma.

Potential for functional divergence in ectomycorrhizal fungal communities across a precipitation gradient

Functional traits influence the assembly of microbial communities, but identifying these traits in the environment has remained challenging. We studied ectomycorrhizal fungal (EMF) communities inhabiting Populus trichocarpa roots distributed across a precipitation gradient in the Pacific Northwest, USA. We profiled these communities using taxonomic (meta-barcoding) and functional (metagenomic) approaches. We hypothesized that genes involved in fungal drought-stress tolerance and fungal mediated plant water uptake would be most abundant in drier soils. We were unable to detect support for this hypothesis; instead, the abundance of genes involved in melanin synthesis, hydrophobins, aquaporins, trehalose-synthases, and other gene families exhibited no significant shifts across the gradient. Finally, we studied variation in sequence homology for certain genes, finding that fungal communities in dry soils are composed of distinct aquaporin and hydrophobin gene sequences. Altogether, our results suggest that while EMF communities exhibit significant compositional shifts across this gradient, coupled functional turnover, at least as inferred using community metagenomics is limited. Accordingly, the consequences of these distinct EMF communities on plant water uptake remain critically unknown, and future studies targeting the expression of genes involved in drought stress tolerance are required.

Profiling and Benchmarking Central Nervous System Infections in an Infectious Diseases Intensive Care Unit

BACKGROUND

There is little information comparing the performance of community acquired central nervous system infections (CNSI) treatment by intensive care units (ICUs) specialized in infectious diseases with treatment at other ICUs. Our objective was to reduce these gaps, creating bases for benchmarking and future case-mix classification.

METHODS

This is a retrospective observational cohort of 785 admissions with 82 cases of CNSI admitted to the ICU of an important Brazilian referral center for infectious diseases (INI) between January 2012 and January 2019. Comparisons were made to data retrospectively collected from the 303,500 intensive care admissions from the Brazilian state health care system included in the Epimed Monitor database. Clinical, epidemiologic, and performance indicators: the standardized mortality rate (SMR) and the standardized resource use rate per ICU surviving patient (SRU) were collected.

RESULTS

Case-mix infections profile and SMR/SRU data. SUS Mixed medical/surgical ICUs: SMR = 1.26, SRU = 1.59; SUS Neurological ICUs: SMR = 1.17, SRU = 2.23; INI ICU: SMR = 1.1, SRU = 1.1; INI ICU CNSI patients: SMR = 0.95, SRU = 1.01.

CONCLUSIONS

Severe patients with CNSI can be efficiently and effectively treated in an ICU specialized in infectious diseases when compared to mixed medical/surgical and neurological ICUs from the public health system. At the same time, we provided profiling and a case-mix that can help and encourage benchmarking by other institutions and other countries.

Peak instantaneous PlayerLoad metrics highlight movement strategy deficits in professional male soccer players

To investigate the influence of task, limb dominance and previous injury on single leg hop task performance and loading response, 25 professional male soccer players completed anterior, medial and lateral hop tests with an accelerometer at mid-calf. Performance outcome was defined as hop distance with loading response defined as the magnitude of, and time to peak instantaneous planar PlayerLoad. The performance was sensitive to task and previous injury (P < 0.001) but not limb dominance, with no evidence of bilateral asymmetry (P = 0.668). Despite impaired performance, previously injured players did not exhibit lower peak instantaneous PlayerLoad after impact in any plane (P ≥ 0.110). There was however a significantly (P = 0.001) longer time to peak medio-lateral loading after impact in previously injured players' affected limb. This observation was exacerbated when the injury was to the non-dominant limb (P = 0.041). Lower-limb accelerometry enhances understanding of movement strategy beyond task outcome, with practical implications in player screening and objective rehabilitation.

Cerebrospinal fluid biomarker profiling of diverse pathophysiological domains in Alzheimer's disease

INTRODUCTION

While Alzheimer's disease (AD) is defined by amyloid-β plaques and tau tangles in the brain, it is evident that many other pathophysiological processes such as inflammation, neurovascular dysfunction, oxidative stress, and metabolic derangements also contribute to the disease process and that varying contributions of these pathways may reflect the heterogeneity of AD. Here, we used a previously validated panel of cerebrospinal fluid (CSF) biomarkers to explore the degree to which different pathophysiological domains are dysregulated in AD and how they relate to each other.

METHODS

Twenty-five CSF biomarkers were analyzed in individuals with a clinical diagnosis of AD verified by positive CSF AD biomarkers (AD, n = 54) and cognitively unimpaired controls negative for CSF AD biomarkers (CU-N, n = 26) using commercial single- and multi-plex immunoassays.

RESULTS

We noted that while AD was associated with increased levels of only three biomarkers (MMP-10, FABP3, and 8OHdG) on a group level, half of all AD participants had increased levels of biomarkers belonging to at least two pathophysiological domains reflecting the diversity in AD. LASSO modeling showed that a panel of FABP3, 24OHC, MMP-10, MMP-2, and 8OHdG constituted the most relevant and minimally correlated set of variables differentiating AD from CU-N. Interestingly, factor analysis showed that two markers of metabolism and oxidative stress (24OHC and 8OHdG) contributed independent information separate from MMP-10 and FABP3 suggestive of two independent pathophysiological pathways in AD, one reflecting neurodegeneration and vascular pathology, and the other associated with metabolism and oxidative stress.

DISCUSSION

Better understanding of the heterogeneity among individuals with AD and the different contributions of pathophysiological processes besides amyloid-β and tau will be crucial for optimizing personalized treatment strategies.

Highlights

A panel of 25 highly validated biomarker assays were measured in CSF.MMP10, FABP3, and 8OHdG were increased in AD in univariate analysis.Many individuals with AD had increased levels of more than one biomarker.Markers of metabolism and oxidative stress contributed to an AD multianalyte profile.Assessing multiple biomarker domains is important to understand disease heterogeneity.

Whole Blood Reactivity to Viral and Bacterial Pathogens after Non-Emergent Cardiac Surgery during the Acute and Convalescence Periods Demonstrates a Distinctive Profile of Cytokines Production Compared to the Preoperative Baseline in Cohort of 108 Patients, Suggesting Immunological Reprogramming during the 28 Days Traditionally Recognized as the Post-Surgical Recovery Period

The release of danger signals from tissues in response to trauma during cardiac surgery creates conditions to reprogram the immune system to subsequent challenges posed by pathogens in the postoperative period. To demonstrate this, we tested immunoreactivity before surgery as the baseline (tbaseline), followed by subsequent challenges during the acute phase (t24h), convalescence (t7d), and long-term recovery (t3m). For 108 patients undergoing elective heart surgery, whole blood was stimulated with lipopolysaccharide (LPS), Influenza A virus subtype N2 (H3N2), or the Flublok™ vaccine to represent common pathogenic challenges. Leukocytosis, platelet count, and serum C-reactive protein (CRP) were used to measure non-specific inflammation. Cytokines were measured after 18 h of stimulation to reflect activation of the various cell types (activated neutrophils-IL-8; activated T cells-IL-2, IFNγ, activated monocyte (MO)-TNFα, IL-6, and deactivated or atypically activated MO and/or T cells-M-CSF, IL-10). IL-2 and IL-10 were increased at t7d, while TNFα was suppressed at t24h when LPS was utilized. Interestingly, M-CSF and IL-6 production was elevated at seven days in response to all stimuli compared to baseline. While some non-specific markers of inflammation (white cell count, IL-6, and IL-8) returned to presurgical levels at t3m, CRP and platelet counts remained elevated. We showed that surgical stimulus reprograms leukocyte response to LPS with only partial restoration of non-specific markers of inflammation.

Application of a Two-Dimensional Mapping-Based Visualization Technique: Nutrient-Value-Based Food Grouping

Worldwide, several food-based dietary guidelines, with diverse food-grouping methods in various countries, have been developed to maintain and promote public health. However, standardized international food-grouping methods are scarce. In this study, we used two-dimensional mapping to classify foods based on their nutrient composition. The Standard Tables of Food Composition in Japan were used for mapping with a novel technique-t-distributed stochastic neighbor embedding-to visualize high-dimensional data. The mapping results showed that most foods formed food group-based clusters in the Standard Tables of Food Composition in Japan. However, the beverages did not form large clusters and demonstrated scattered distribution on the map. Green tea, black tea, and coffee are located within or near the vegetable cluster whereas cocoa is near the pulse cluster. These results were ensured by the k-nearest neighbors. Thus, beverages made from natural materials can be categorized based on their origin. Visualization of food composition could enable an enhanced comprehensive understanding of the nutrients in foods, which could lead to novel aspects of nutrient-value-based food classifications.

Genomic profiling for non-small cell lung cancer: Clinical relevance in staging and prognosis

Lung cancer is one of the most common cancers prevalent and around 80% of all cases are non-small cell lung cancer (NSCLC). Due to high recurrence rates, the mortality of NSCLC is high. Conventional staging systems allowed risk classification of patients in order to simplify the patient selection for adjuvant chemotherapy. Gene expression analysis has been shown to possess advantage over conventional staging systems in NSCLC in terms of patients risk classification. This article reviews the evidences on the genomic profiling of NSCLC patients into high and low-risk groups based on the expression of genes involved in various proliferative pathways.

Profiles of Victimized Outpatients with Severe Mental Illness in India

Persons with severe mental illness (PwSMI) are at risk of being victimized due to persistent cognitive, emotional, and behavioral symptoms, which can become potential threats for effective reintegration into the community. A total of 217 PwSMI, receiving outpatient psychiatric treatment from a tertiary hospital, were screened for abuse, and if they were identified as abuse, then information about contextual factors contributing to abuse, sociodemographic, family, and clinical and legal profiles was created. Overall, 150 PwSMI were victimized, of which 56% were females, 50.7% were married, 20.7% were educated up to middle school, and 31.4% were homemaker. The most common form of diagnosis was schizophrenia (43.3%), with a mean duration of illness of 14 years. All the victimized PwSMI were subjected to emotional abuse. PwSMI were more likely to be victimized by multiple family members due to poor knowledge and understanding about illness (24%). The majority of the PwSMI had disclosed abuse (62.7%) to nonformal sources (33.3%) with no documentation in the clinical file (82.7%). PwSMI experience ongoing abuse and are more likely to be re-victimized, which increases the need for regular screening and culturally sensitive and comprehensive community-coordinated care and support.

Identifying Profiles of Patients With Uncontrolled Type 2 Diabetes Who Would Benefit From Referral to an Endocrinologist

OBJECTIVE

To compare the outcomes of glycemic uncontrolled diabetes mellitus type 2 patients receiving treatment from endocrinologists with those treated by primary care physicians. Additionally, this research aims to identify patient profiles that would benefit from personalized referral-a novel medical approach that aims to match the most suitable specialist for effectively managing patient while considering the patient's profile.

METHODS

This retrospective cohort study uses the Maccabi Healthcare Services diabetes registry to match 508 pairs of glycemic uncontrolled diabetes mellitus type 2 patients treated by endocrinologists (EndoG) and primary care physicians (PcPG). Using a generalized additive model, we analyzed the hemoglobin A1c (HbA1c) trend over 1 year for each group. We employed the odds ratio (OR) from conditional logistic regression to determine the likelihood of favorable outcomes in the EndoG compared to the PcPG, using the entire cohort and subcohort profiles.

RESULTS

The generalized additive model comparison indicated an improvement in HbA1c levels in both groups, with the EndoG outperforming the PcPG. Furthermore, the EndoG group had an OR = 2.27 (95% confidence interval, 1.6 to 3.2) for reducing HbA1c by at least 1% within a year and an OR = 1.68 (95% confidence interval, 1.02 to 2.76) for achieving low-density lipoprotein levels< 100 mg/dl. We identified 96 profiles with positive outcomes, all favoring treatment by endocrinologists.

CONCLUSIONS

EndoG demonstrated superior HbA1c control over time and achieved better outcomes compared to PcPG. The identification of 96 profiles benefiting from endocrinologist referral emphasizes the potential of personalized referral.

Breast cancer risk factors based on reproductive and nonreproductive profiling of Pakistani women: A hospital based case control study

Breast cancer (BC) is a global public health problem attributed to varying risk factors. The designing of a targeted screening program focused on at-risk women can be cost-effective in reducing its burden. A hospital based case control study was conducted on 138 cases of breast cancer and 169 healthy controls to investigate the reproductive and non-reproductive risk factors for breast cancer in Pakistani women. The odds ratios (ORs) and 95% confidence intervals (CIs) were computed with unconditional logistic regression. Almost all i.e. 97.83% of cases were married (OR=5.03),70.29% were illiterate (OR=1.88), 73.19% were aged >35 years (OR=0.632) and 81.16% belonged to the poor class(OR=1.81). Early age at menarche (OR, 2.55; 95% CI 1.50-4.31, P=0.0001), hormone replacement therapy (OR=2.057, 95% CI 1.283-3.295, P= 0.002) early pregnancy (OR,2.23, 95% CI 1.29-3.88, P=0.004), history of miscarriage (OR, 2.11, 95% CI 1.32-3.39,P=0.002) & oral contraceptive use (OR, 2.76, 95% CI 1.54-4.92, P= 0.006) were significantly associated with BC. The study highlights the dire need for effective public health programs for high-risk women to address this highly fatal disease.

High-throughput autoantibody screening identifies differentially abundant autoantibodies in autism spectrum disorder

Introduction

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by defects in two core domains, social/communication skills and restricted/repetitive behaviors or interests. There is no approved biomarker for ASD diagnosis, and the current diagnostic method is based on clinical manifestation, which tends to vary vastly between the affected individuals due to the heterogeneous nature of ASD. There is emerging evidence that supports the implication of the immune system in ASD, specifically autoimmunity; however, the role of autoantibodies in ASD children is not yet fully understood.

Materials and methods

In this study, we screened serum samples from 93 cases with ASD and 28 healthy controls utilizing high-throughput KoRectly Expressed (KREX) i-Ome protein-array technology. Our goal was to identify autoantibodies with differential expressions in ASD and to gain insights into the biological significance of these autoantibodies in the context of ASD pathogenesis.

Result

Our autoantibody expression analysis identified 29 differential autoantibodies in ASD, 4 of which were upregulated and 25 downregulated. Subsequently, gene ontology (GO) and network analysis showed that the proteins of these autoantibodies are expressed in the brain and involved in axonal guidance, chromatin binding, and multiple metabolic pathways. Correlation analysis revealed that these autoantibodies negatively correlate with the age of ASD subjects.

Conclusion

This study explored autoantibody reactivity against self-antigens in ASD individuals' serum using a high-throughput assay. The identified autoantibodies were reactive against proteins involved in axonal guidance, synaptic function, amino acid metabolism, fatty acid metabolism, and chromatin binding.

A New Biomarker Profiling Strategy for Gut Microbiome Research: Valid Association of Metabolites to Metabolism of Microbiota Detected by Non-Targeted Metabolomics in Human Urine

The gut microbiome is of tremendous relevance to human health and disease, so it is a hot topic of omics-driven biomedical research. However, a valid identification of gut microbiota-associated molecules in human blood or urine is difficult to achieve. We hypothesize that bowel evacuation is an easy-to-use approach to reveal such metabolites. A non-targeted and modifying group-assisted metabolomics approach (covering 40 types of modifications) was applied to investigate urine samples collected in two independent experiments at various time points before and after laxative use. Fasting over the same time period served as the control condition. As a result, depletion of the fecal microbiome significantly affected the levels of 331 metabolite ions in urine, including 100 modified metabolites. Dominating modifications were glucuronidations, carboxylations, sulfations, adenine conjugations, butyrylations, malonylations, and acetylations. A total of 32 compounds, including common, but also unexpected fecal microbiota-associated metabolites, were annotated. The applied strategy has potential to generate a microbiome-associated metabolite map (M3) of urine from healthy humans, and presumably also other body fluids. Comparative analyses of M3 vs. disease-related metabolite profiles, or therapy-dependent changes may open promising perspectives for human gut microbiome research and diagnostics beyond analyzing feces.

Functional Profiling of Soft Tissue Sarcoma Using Mechanistic Models

Soft tissue sarcoma is an umbrella term for a group of rare cancers that are difficult to treat. In addition to surgery, neoadjuvant chemotherapy has shown the potential to downstage tumors and prevent micrometastases. However, finding effective therapeutic targets remains a research challenge. Here, a previously developed computational approach called mechanistic models of signaling pathways has been employed to unravel the impact of observed changes at the gene expression level on the ultimate functional behavior of cells. In the context of such a mechanistic model, RNA-Seq counts sourced from the Recount3 resource, from The Cancer Genome Atlas (TCGA) Sarcoma project, and non-diseased sarcomagenic tissues from the Genotype-Tissue Expression (GTEx) project were utilized to investigate signal transduction activity through signaling pathways. This approach provides a precise view of the relationship between sarcoma patient survival and the signaling landscape in tumors and their environment. Despite the distinct regulatory alterations observed in each sarcoma subtype, this study identified 13 signaling circuits, or elementary sub-pathways triggering specific cell functions, present across all subtypes, belonging to eight signaling pathways, which served as predictors for patient survival. Additionally, nine signaling circuits from five signaling pathways that highlighted the modifications tumor samples underwent in comparison to normal tissues were found. These results describe the protective role of the immune system, suggesting an anti-tumorigenic effect in the tumor microenvironment, in the process of tumor cell detachment and migration, or the dysregulation of ion homeostasis. Also, the analysis of signaling circuit intermediary proteins suggests multiple strategies for therapy.

Profiling Somatosensory Impairment after Stroke: Characterizing Common "Fingerprints" of Impairment Using Unsupervised Machine Learning-Based Cluster Analysis of Quantitative Measures of the Upper Limb

Altered somatosensory function is common among stroke survivors, yet is often poorly characterized. Methods of profiling somatosensation that illustrate the variability in impairment within and across different modalities remain limited. We aimed to characterize post-stroke somatosensation profiles ("fingerprints") of the upper limb using an unsupervised machine learning cluster analysis to capture hidden relationships between measures of touch, proprioception, and haptic object recognition. Raw data were pooled from six studies where multiple quantitative measures of upper limb somatosensation were collected from stroke survivors (n = 207) using the Tactile Discrimination Test (TDT), Wrist Position Sense Test (WPST) and functional Tactile Object Recognition Test (fTORT) on the contralesional and ipsilesional upper limbs. The Growing Self Organizing Map (GSOM) unsupervised machine learning algorithm was used to generate a topology-preserving two-dimensional mapping of the pooled data and then separate it into clusters. Signature profiles of somatosensory impairment across two modalities (TDT and WPST; n = 203) and three modalities (TDT, WPST, and fTORT; n = 141) were characterized for both hands. Distinct impairment subgroups were identified. The influence of background and clinical variables was also modelled. The study provided evidence of the utility of unsupervised cluster analysis that can profile stroke survivor signatures of somatosensory impairment, which may inform improved diagnosis and characterization of impairment patterns.

Authentication of Cocoa Products Based on Profiling and Fingerprinting Approaches: Assessment of Geographical, Varietal, Agricultural and Processing Features

Cocoa and its derivative products, especially chocolate, are highly appreciated by consumers for their exceptional organoleptic qualities, thus being often considered delicacies. They are also regarded as superfoods due to their nutritional and health properties. Cocoa is susceptible to adulteration to obtain illicit economic benefits, so strategies capable of authenticating its attributes are needed. Features such as cocoa variety, origin, fair trade, and organic production are increasingly important in our society, so they need to be guaranteed. Most of the methods dealing with food authentication rely on profiling and fingerprinting approaches. The compositional profiles of natural components -such as polyphenols, biogenic amines, amino acids, volatile organic compounds, and fatty acids- are the source of information to address these issues. As for fingerprinting, analytical techniques, such as chromatography, infrared, Raman, and mass spectrometry, generate rich fingerprints containing dozens of features to be used for discrimination purposes. In the two cases, the data generated are complex, so chemometric methods are usually applied to extract the underlying information. In this review, we present the state of the art of cocoa and chocolate authentication, highlighting the pros and cons of the different approaches. Besides, the relevance of the proposed methods in quality control and the novel trends for sample analysis are also discussed.

Profiling the Physical Performance of Young Boxers with Unsupervised Machine Learning: A Cross-Sectional Study

Mexico City is the location with the largest number of boxers in Mexico; in fact, it is the first city in the country to open a Technological Baccalaureate in Education and Sports Promotion with a pugilism orientation. This cross-sectional study aimed to determine the physical-functional profile of applicants for admission to the baccalaureate in sports. A total of 227 young athletes (44F; 183M; 15.65 (1.79) years; 63.66 (14.98) kg; >3 years of boxing experience) participated in this study. Body mass (BM), maximal isometric handgrip (HG) strength, the height of the countermovement jump (CMJ), the velocity of straight boxing punches (PV), and the rear hand punch impact force (PIF) were measured. The young boxers were profiled using unsupervised machine learning algorithms, and the probability of superiority (ρ) was calculated as the effect size of the differences. K-Medoids clustering resulted in two sex-independent significantly different groups: Profile 1 (n = 118) and Profile 2 (n = 109). Except for BM, Profile 2 was statistically higher (p < 0.001) with a clear distinction in terms of superiority on PIF (ρ = 0.118), the PIF-to-BM ratio (ρ = 0.017), the PIF-to-HG ratio (ρ = 0.079) and the PIF-to-BM+HG ratio (ρ = 0.008). In general, strength levels explained most of the data variation; therefore, it is reasonable to recommend the implementation of tests aimed at assessing the levels of isometric and applied strength in boxing gestures. The identification of these physical-functional profiles might help to differentiate training programs during sports specialization of young boxing athletes.

Microbiome maps: Hilbert curve visualizations of metagenomic profiles

Abundance profiles from metagenomic sequencing data synthesize information from billions of sequenced reads coming from thousands of microbial genomes. Analyzing and understanding these profiles can be a challenge since the data they represent are complex. Particularly challenging is their visualization, as existing techniques are inadequate when the taxa number is in the thousands. We present a technique, and accompanying software, for the visualization of metagenomic abundance profiles using a space-filling curve that transforms a profile into an interactive 2D image. We created Jasper, an easy to use tool for the visualization and exploration of metagenomic profiles from DNA sequencing data. It orders taxa using a space-filling Hilbert curve, and creates a "Microbiome Map", where each position in the image represents the abundance of a single taxon from a reference collection. Jasper can order taxa in multiple ways, and the resulting microbiome maps can highlight "hot spots" of microbes that are dominant in taxonomic clades or biological conditions. We use Jasper to visualize samples from a variety of microbiome studies, and discuss ways in which microbiome maps can be an invaluable tool to visualize spatial, temporal, disease, and differential profiles. Our approach can create detailed microbiome maps involving hundreds of thousands of microbial reference genomes with the potential to unravel latent relationships (taxonomic, spatio-temporal, functional, and other) that could remain hidden using traditional visualization techniques. The maps can also be converted into animated movies that bring to life the dynamicity of microbiomes.

Full Profiling of GE81112A, an Underexplored Tetrapeptide Antibiotic with Activity against Gram-Negative Pathogens

After the first total synthesis combined with structure revision, we performed thorough in vitro and in vivo profiling of the underexplored tetrapeptide GE81112A. From the determination of the biological activity spectrum and physicochemical and early absorption-distribution-metabolism-excretion-toxicity (eADMET) properties, as well as in vivo data regarding tolerability and pharmacokinetics (PK) in mice and efficacy in an Escherichia coli-induced septicemia model, we were able to identify the critical and limiting parameters of the original hit compound. Thus, the generated data will serve as the basis for further compound optimization programs and developability assessments to identify candidates for preclinical/clinical development derived from GE81112A as the lead structure. IMPORTANCE The spread of antimicrobial resistance (AMR) is becoming a more and more important global threat to human health. With regard to current medical needs, penetration into the site of infection represents the major challenge in the treatment of infections caused by Gram-positive bacteria. Considering infections associated with Gram-negative bacteria, resistance is a major issue. Obviously, novel scaffolds for the design of new antibacterials in this arena are urgently needed to overcome this crisis. Such a novel potential lead structure is represented by the GE81112 compounds, which inhibit protein synthesis by interacting with the small 30S ribosomal subunit using a binding site distinct from that of other known ribosome-targeting antibiotics. Therefore, the tetrapeptide antibiotic GE81112A was chosen for further exploration as a potential lead for the development of antibiotics with a new mode of action against Gram-negative bacteria.

Can latent fingerprint disclose the sex of the donor? A preliminary test study using GC-MS analysis of latent fingerprints

While fingerprints are a highly used means of identification, not every fingerprint left behind on a potential crime scene can be used for identification purposes. In some cases, the fingerprint may be smudged, partially preserved or overlapping with other prints hence distorting the ridge pattern and may therefore be not appropriate for identification. Further, fingermark residue yields a very low abundance of genetic material for DNA analysis. In such cases, the fingermark may be used to retrieve basic donor information such as sex. The focus of this paper was to assess the possibility of differentiating between the sexes of the donor of latent fingermarks. Analytical method was GC-MS analysis of the chemical compounds of latent fingermarks using 22 male and 22 female donors. Results showed 44 identified compounds. Two alcohols, octadecanol C₁₈ and eicosanol C₂₀ , were found to show a difference that was statistically significant between male and female donors. There is also some evidence for the possibility of distinguishing sex of the fingermark donor based on the distribution of branched chain fatty acids, as free compounds or esterified in wax esters.

Spatially Correlated Nuclear Magnetic Resonance Profiles as a Tool for Precision Agriculture

Nuclear magnetic resonance (NMR) profiling, sample georeferentiaton, and geostatistics are applied to evaluate the spatial variability of metabolic expression of durum wheat in fields managed by precision agriculture. Durum wheat at three different vegetation stages, grown in two different places of the Basilicata region, in Italy, is analyzed by NMR. The spatial variability, within each field, of metabolites, quantified by NMR, is evidenced by appropriate geostatistic tools through the definition of a suitable metabolic index. Metabolic maps are compared to highlight the effects of soil and farming strategies.

Interpreting Image-based Profiles using Similarity Clustering and Single-Cell Visualization

Image-based profiling quantitatively assesses the effects of perturbations on cells by capturing a breadth of changes via microscopy. Here, we provide two complementary protocols to help explore and interpret data from image-based profiling experiments. In the first protocol, we examine the similarity among perturbed cell samples using data from compounds that cluster by their mechanisms of action. The protocol includes steps to examine feature-driving differences between samples and to visualize correlations between features and treatments to create interpretable heatmaps using the open-source web tool Morpheus. In the second protocol, we show how to interactively explore images together with the numerical data, and we provide scripts to create visualizations of representative single cells and image sites to understand how changes in features are reflected in the images. Together, these two tutorials help researchers interpret image-based data to speed up research. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Exploratory analysis of profile similarities and driving features Basic Protocol 2: Image and single-cell visualization following profile interpretation.

Ganglioside analysis in body fluids by liquid-phase separation techniques hyphenated to mass spectrometry

The expression of gangliosides in central nervous system is a few times higher than in the extraneural tissue, a characteristic highlighting their major role at this level. Although in very low amounts, gangliosides are ubiquitously distributed in body fluids too, where, depending on many factors, including pathological states, their composition fluctuates, thus having diagnostic value. Ganglioside investigation in biological fluids, which, except for cerebrospinal fluid (CSF), may be sampled noninvasively, was for years impeded by the limited sensitivity of the analytical instrumentation available in glycomics. However, because the last decade has witnessed significant developments in biological mass spectrometry (MS) and the hyphenated separation techniques, marked by a major increase in sensitivity, reproducibility, and data reliability, ganglioside research started to be focused on biofluid analysis by separation techniques coupled to MS. In this context, our review presents the achievements in this emerging field of gangliosidomics, with a particular emphasis on modern liquid chromatography (LC), thin-layer chromatography, hydrophilic interaction LC, and ion mobility separation coupled to high-performance MS, as well as the results generated by these systems and allied experimental procedures in profiling and structural analysis of gangliosides in healthy or diseased body fluids, such as CSF, plasma/serum, and milk.

Speeding up Smartphone-Based Dew Computing: In Vivo Experiments Setup Via an Evolutionary Algorithm

Dew computing aims to minimize the dependency on remote clouds by exploiting nearby nodes for solving non-trivial computational tasks, e.g., AI inferences. Nowadays, smartphones are good candidates for computing nodes; hence, smartphone clusters have been proposed to accomplish this task and load balancing is frequently a subject of research. Using the same real-i.e., in vivo-testbeds to evaluate different load balancing strategies based on energy utilization is challenging and time consuming. In principle, test repetition requires a platform to control battery charging periods between repetitions. Our Motrol hard-soft device has such a capability; however, it lacks a mechanism to assure and reduce the time in which all smartphone batteries reach the level required by the next test. We propose an evolutionary algorithm to execute smartphone battery (dis)charging plans to minimize test preparation time. Charging plans proposed by the algorithm include charging at different speeds, which is achieved by charging at maximum speed while exercising energy hungry components (the CPU and screen). To evaluate the algorithm, we use various charging/discharging battery traces of real smartphones and we compare the time-taken for our method to collectively prepare a set of smartphones versus that of individually (dis)charging all smartphones at maximum speed.

MicroRNA Gene Signature for Predicting Mechanisms in Nasopharyngeal Carcinoma: A Case Study on the Potential Application of Circulating Biomarkers

BACKGROUND AND AIM

Nasopharyngeal Carcinoma (NPC) is an upper respiratory tract cancer prevalent in Southeast Asia and related to chronic EBV infection. microRNAs (miRNAs) regulate gene expression implicated in NPC's carcinogenesis. However, this circulating RNA molecule's role and clinical utility remain unknown. Therefore, this study examined the circulation of miRNAs and their association with clinical data.

METHODS

160 plasma samples of NPC and 80 non-tumor samples were extracted to evaluate and validate the gene expressions. Quantification expression was performed using relative quantification of qPCR analysis level expression methods. The intrinsic cellular roles involving biological signaling in NPC's oncogenesis using Ingenuity Pathways Analysis (IPA) were also used.

RESULTS

The results of the quantification significance profiling of NPC samples revealed decreased miR- 29c-3p (fold change 1.16; p<0.05) and increased 195-5p expression (fold change 1.157; p<0.05). Furthermore, the validation of hsa-miR-29c-3p expression on plasma NPC with known tumor vs. non-tumor and significant changes was also performed using a fold change of 4.45 (medians of 31.45 ± 1.868 and 24.96 ± 1.872, respectively; p<0.0005). miR-29c had a 2.14 fold change correlated with T primary status with a median of 31.99±1.319 and 31.35±2.412, respectively (p<0.05). Stage status with fold change 1.99 also had median levels of 31.98±1.105 and 31.21 ± 2.355, respectively (p-value <0.05). Furthermore, the node's status for the lower expression of miR-29c with fold change 1.17 had median levels of 32.78 ± 2.221 and 31.33 ± 1.689, respectively (p-value of 0.7). Bioinformatics analysis established the roles and functions of miR-29 in NPC progression, cell death and survival, cellular development, cellular function, and cell maintenance by inhibiting COL4A, PI3K, VEGFA, JUN, and CDK6.

CONCLUSION

Overall, we conclude that decreased miR-29c expression is associated with poor clinical status and might inhibit NPC's five target genes.

Intra and Inter-Rater Reliability of a Novel Isometric Test of Neck Strength

There is no single, universally accepted method of measuring isometric neck strength to inform exercise prescription and injury risk prediction. This study aimed to establish the inter- and intra-rater reliability of a commercially available fixed frame dynamometer in measuring peak isometric neck strength. A convenience sample of male (n = 16) and female (n = 20) university students performed maximal isometric contractions for flexion (Flex), extension (Ext), left- (LSF) and right-side flexion (RSF) in a quadruped position over three sessions. The intra-rater reliability results were good-to-excellent for both males (ICC = 0.83−0.90) and females (ICC = 0.86−0.94) and acceptable (CV < 15%) across all directions for both males and females. The inter-rater reliability results were excellent (ICC = 0.96−0.97) and acceptable (CV < 11.1%) across all directions. Findings demonstrated a significant effect for sex (p ≤ 0.05): males were stronger in all four directions, and a significant effect for direction (p ≤ 0.05): Ext tested stronger (193 N) than Flex (176 N), LSF (130 N) and RSF (125 N). The findings show that the VALD fixed frame dynamometer can reliably assess isometric neck strength and can provides reference values for healthy males and females.

Multimodal single-cell profiling of intrahepatic cholangiocarcinoma defines hyperactivated Tregs as a potential therapeutic target

BACKGROUND & AIMS

The landscape and function of the immune infiltrate of intrahepatic cholangiocarcinoma (iCCA), a rare, yet aggressive tumor of the biliary tract, remains poorly characterized, limiting development of successful immunotherapies. Herein, we aimed to define the molecular characteristics of tumor-infiltrating leukocytes with a special focus on CD4+ regulatory T cells (Tregs).

METHODS

We used high-dimensional single-cell technologies to characterize the T-cell and myeloid compartments of iCCA tissues, comparing these with their tumor-free peritumoral and circulating counterparts. We further used genomics and cellular assays to define the iCCA-specific role of a novel transcription factor, mesenchyme homeobox 1 (MEOX1), in Treg biology.

RESULTS

We found poor infiltration of putative tumor-specific CD39+ CD8+ T cells accompanied by abundant infiltration of hyperactivated CD4+ Tregs. Single-cell RNA-sequencing identified an altered network of transcription factors in iCCA-infiltrating compared to peritumoral T cells, suggesting reduced effector functions by tumor-infiltrating CD8+ T cells and enhanced immunosuppression by CD4+ Tregs. Specifically, we found that expression of MEOX1 was highly enriched in tumor-infiltrating Tregs, and demonstrated that MEOX1 overexpression is sufficient to reprogram circulating Tregs to acquire the transcriptional and epigenetic landscape of tumor-infiltrating Tregs. Accordingly, enrichment of the MEOX1-dependent gene program in Tregs was strongly associated with poor prognosis in a large cohort of patients with iCCA.

CONCLUSIONS

We observed abundant infiltration of hyperactivated CD4+ Tregs in iCCA tumors along with reduced CD8+ T-cell effector functions. Interfering with hyperactivated Tregs should be explored as an approach to enhance antitumor immunity in iCCA.

LAY SUMMARY

Immune cells have the potential to slow or halt the progression of tumors. However, some tumors, such as intrahepatic cholangiocarcinoma, are associated with very limited immune responses (and infiltration of cancer-targeting immune cells). Herein, we show that a specific population of regulatory T cells (a type of immune cell that actually suppresses the immune response) are hyperactivated in intrahepatic cholangiocarcinoma. Targeting these cells could enable cancer-targeting immune cells to act more effectively and should be looked at as a potential therapeutic approach to this aggressive cancer type.

In-Depth Chemical and Optoelectronic Analysis of Triple-Cation Perovskite Thin Films by Combining XPS Profiling and PL Imaging

The investigation of chemical and optoelectronic properties of halide perovskite layers and associated interfaces is crucial to harness the full potential of perovskite solar cells. Depth-profiling photoemission spectroscopy is a primary tool to study the chemical properties of halide perovskite layers at different scales from the surface to the bulk. The technique employs ionic argon beam thinning that provides accurate layer thicknesses. However, there is an urgent need to corroborate the reliability of data on chemical properties of halide perovskite thin films to better assess their stability. The present study addresses the question of the Ar⁺ sputtering thinning on the surface chemical composition and the optoelectronic properties of the triple-cation mixed-halide perovskite by combining X-ray photoemission spectroscopy (XPS) and photoluminescence (PL) spectroscopy. First, XPS profiling is performed by Ar⁺ beam sputtering on a half-cell: glass/FTO/c-TiO₂/perovskite. The resulting profiles show a very homogeneous and reproducible element distribution until near the buried interface; therefore, the layer is considered as quasihomogeneous all over its thickness, and the sputtering process is stable. Second, we evaluated a set of thinned perovskite layers representative of selected steps along the profile by means of PL imaging optical measurements in both steady-state and transient regimes to assess possible perturbation of the optical properties from the surface to bulk. Obtained PL spectra inside the resulting craters show no peak shift nor phase segregation. Accordingly, the transient PL measurements do not reveal any changes of the surface recombination rate in the sputtered areas. This demonstrates that there is no cumulative effect of sputtering nor drastic chemical and optoelectronic modifications, validating the determination of the in-depth composition of the perovskite layer. Combining XPS profiling with PL characterization can be a precise tool to be applied for an extensive study of the multiple layers and mixed organic/inorganic interfaces of photovoltaic devices.

Validity and Reliability of Strategy Metrics to Assess Countermovement Jump Performance using the Newly Developed My Jump Lab Smartphone Application

The aim of the present study was to analyse the validity and reliability of the newly developed My Jump Lab smartphone app, which includes the option to calculate time to take-off and the reactive strength index modified (RSI_Mod - calculated as jump height divided by time to take-off), in addition to jump height. Twenty-seven postgraduate sport science students attended a single test session and performed three maximal effort countermovement jumps (CMJ) on twin force plates, whilst concurrently being filmed using the app. Results showed no significant differences in jump height between measurement methods (g = 0.00) or RSI_Mod (g = -0.49), although a significant difference was evident for time to take-off (g = 0.68). When a correction factor was applied to time to take-off data, no meaningful differences were evident (g = 0.00), which also had a knock-on effect for RSI_Mod (g = 0.10). Bland-Altman analysis showed near perfect levels of agreement for jump height with a bias estimate of 0.001 m, whilst time to take-off reported a bias estimate of 0.075 s initially and, 0.000 s once the correction factor was applied. For RSI_Mod, bias estimate was initially -0.048, and 0.006 once calculated with the corrected time to take-off data. Pearson's r correlations were: 0.98 for jump height, 0.81 for time to take-off, and 0.85 for RSI_Mod. Based on the findings from the present study, and with the inclusion of the newly embedded correction factor, My Jump Lab can now be used as both a valid and reliable means of measuring time to take-off and RSI_Mod in the CMJ.

Metaprofiling of the bacterial community in sorghum silages inoculated with lactic acid bacteria

AIMS

to characterize the fermentation process and bacterial diversity of sorghum silage inoculated with Lactiplantibacillus plantarum LpAv, Pediococcus pentosaceus PpM and Lacticaseibacillus paracasei LcAv.

METHODS AND RESULTS

chopped sorghum was ensiled using the selected strains. Physicochemical parameters (Ammonia Nitrogen/Total Nitrogen, Dry Matter, Crude Protein, Acid Detergent Fiber, Neutral Detergent Fiber, Acid Detergent Lignin, Ether Extract and Ashes), bacterial counts, cell cytometry and 16sRNA sequencing were performed to characterize the ensiling process and an animal trial (BALB/c mice) was conducted in order to preliminary explore the potential of sorghum silage to promote animal gut health. After 30 days of ensiling, the genus Lactobacillus comprised 68.4 ± 2.3 % and 73.5 ± 1.8 % of relative abundance, in control and inoculated silages respectively. Richness (Chao1 index) in inoculated samples, but not in control silages, diminished along ensiling, suggesting the domination of fermentation by the inoculated LAB. A trend in conferring enhanced protection against Salmonella infection was observed in the mouse model used to explore the potential to promote gut health of sorghum silage.

CONCLUSIONS

the LAB strains used in this study were able to dominate sorghum fermentation.

SIGNIFICANCE AND IMPACT OF THE STUDY

this is the first report using metaprofiling of 16sRNA to characterize sorghum silage, showing a microbiological insight where resident and inoculated LAB strains overwhelmed the epiphytic microbiota, inhibiting potential pathogens of the genus Klebsiella.

Characterization of 17 unknown ketamine manufacturing by-product impurities by UHPLC-QTOF-MS

This study initially reported the selection and characterization of 17 unknown impurities attributed to the manufacture process of ketamine. A total of 150 seized ketamine samples were investigated through ultra-high-performance liquid chromatography-quadrupole-time of flight (UHPLC-Q-TOF). Seventeen characteristic impurities were selected in accordance with four criteria: The compound was detected in over 10% of all 150 seized ketamine samples, the compound had at least one nitrogen, the unsaturation of the compound was more than 5, and the compound was stable in the dilution solvent solution for 48 h. The accurate masses of the protonated molecules and product ions of the target impurities were obtained based on the full scan mode and the product ion mode of Q-TOF, respectively. Lastly, the possible structures of the above impurities were tentatively elucidated in accordance with the synthetic route of ketamine, protonated molecules, and MS2 product ions. All 17 impurities had the same skeleton of deschloroketamine (DCK), but were substituted with additional chlorine, hydroxyl, methyl, cyclohexane, and o-chlorophenyl cyclopentyl ketone substituents. Under the electrospray ionization (ESI), the above impurities showed similar characteristic fragment ions through the dissociation of the CH3 NH2, C2 H6 NH, H2 O, CO, C2 H4 O, C4 H6 , and C2 H2 moieties. The above impurities have been routinely used for the profiling analysis of seized ketamine samples in the National Narcotics Laboratory of China and employed to establish the tactical intelligence for law enforcement agencies.

They might all be marauders

Circle theory predicts most offenders will reside within the smallest circle that encloses a pattern of offense locations, which defines the offender's crime range. Those who reside within the crime range reflect a marauder decision pattern, with the remainder reflecting a commuter decision pattern. Random simulations of marauders were conducted to determine the failure rate of the smallest circle to correctly identify a marauder decision pattern. Failure rates were higher as the number of offenses was reduced, but were systematic and predictable. Moreover, the published rates of the marauder vs commuter patterns correspond well with the predicted failure rate. A method for estimating the true size of an offender's criminal territory is presented and it is suggested that the vast majority of offenders are likely to be adopting a marauder decision pattern, and that true commuters may be far less than indicated by the circle test.

Targeted Metabolomics With a Chemometric Study of Oxygenated Heterocyclic Aglycones as a Tool for Preliminary Authenticity Assessment of Orange and Grapefruit Juices

Profiles of citrus juice oxygenated heterocyclic aglycones (OHAs), which are notable marker secondary metabolites, were used to assess the authenticity of sweet orange and grapefruit juices in situations where mandarin and pomelo juices might be adulterants. Thirty-nine known OHAs, including 10 methoxyflavones, 13 coumarins, and 16 furanocoumarins, as well as 13 tentatively screened OHAs, were analyzed in orange, mandarin, grapefruit and pomelo juices using our newly developed high-resolution HPLC-UV and fluorescence detection method. Quantitative OHA profiles from 158 pure juice samples were obtained to establish a purity discriminant model using an omics strategy. Reduction of OHA variables showed that three important methoxyflavones, i.e. isosinensetin, tangeretin and sinensetin provided the best discrimination ability between sweet orange and mandarin juices. There are two subtypes of pomelos, Shatianyou Group and Wendan Group, of which juices should be separately compared to grapefruit juice. Five OHAs, namely meranzin, 3,5,6,7,8,3',4'-heptamethoxyflavone, osthole, 6',7'-epoxybergamottin, and bergamottin were found to discriminate Shatianyou Group of pomelo juice from grapefruit juice; whereas three OHAs, namely bergaptol, isomeranzin, and 6',7'-dihydroxybergamottin were able to discriminate Wendan Group of pomelo juice from grapefruit juice. The established partial least squares discriminant analysis (PLS-DA) models were capable of detecting as little as 10% mandarin juice in sweet orange juice and 10% pomelo juice in grapefruit juice, allowing for fast prescreening of excess addition with good reliability (root mean square error of prediction, RMSEP < 5%).

Next Generation Sequencing-based DNA metabarcoding for animal species profiling in fish feed

The expansion of worldwide aquaculture has been accompanied by extensive growth in the fish feed industry. However, improper labelling of many commercially available fish feeds has raised security and safety concerns over the species' origin of the ingredients. The inclusion of ruminants-derived ingredients in fish feed is prohibited according to EU legislation while porcine inclusion in fish feed has been a great concern among Muslim farmers. In contrast to the limited species that could be simultaneously determined using multiplex PCR, this study utilised Next Generation Sequencing-based DNA metabarcoding assay to determine the compositional profiles of animal species in fish feed samples in a more holistic manner. In relation to the religious issue associated with porcine-derived ingredients in fish feed, this study firstly aimed to determine the sensitivity of the methods in profiling fish feed adulterated with porcine blood and muscle tissues. Next, 10 commercially available fish feed samples were analysed. As a result, a detection limit of as low as 3% (w/w) porcine muscle and blood in the laboratory-prepared fish feed was obtained. The analysis of 10 commercial fish feeds shows surprising findings: 50% of the feeds contain Sus scrofa and 80% contain Bos taurus, a ruminant. Only one commercial fish feed was found to be solely composed of marine species. This study shows that commercial fish feeds sold in Malaysia contain undesirable animal species, and emphasises the need for accurate and legally enforced labelling of mammalian species in fish feed products.

An investigation into the association between cannibalism and serial killers

The aim of the current study was to compare and contrast non-cannibalistic and cannibalistic serial killers. Using case study data, the present study assessed common patterns among the life histories of cannibalistic serial killers compared to those of a control sample of serial killers that did not commit cannibalism. These include but are not limited to childhood experiences, socio-economic status, biological abnormalities and life events. Results indicated that factors that may differentiate cannibals from non-cannibals likely result from childhood influences, rather than influences at the time of the kill. Findings may be used to identify potential warning signs or triggers for cannibalistic behaviour.

Methylation classifiers: brain tumors, sarcomas and what's next

Tumor classification has evolved over the last decades with technical progress contributing much to our current concepts. Among diagnostic hallmark novelties were immunostaining, Fluorescence in situ hybridization, Sanger sequencing followed by massive parallel DNA sequencing and recently, epigenetic analyses have entered the stage. Although each of these techniques was revolutionary and, in some way, also disruptive in certain diagnostic fields, it took years to decades for broad implementation into standard pathological-diagnostic algorithms. In contrast, DNA methylation profiling has been accepted in short time as a game changer with lasting impact on brain tumor classification and with potential for classification of other tumor types. This review provides a brief introduction in DNA methylation-based tumor classification. We present why DNA methylation signatures are attractive diagnostic biomarkers, discuss present achievements and future aims and explain the integration of methylation-based classifiers in diagnostic procedure. Finally, we provide an outlook on the challenges and opportunities associated with DNA methylation-based tumor profiling. This article is protected by copyright. All rights reserved.

Extracellular Vesicles Secreted by Glioma Stem Cells Are Involved in Radiation Resistance and Glioma Progression

Glioblastoma is the most aggressive brain tumour with short survival, partly due to resistance to conventional therapy. Glioma stem cells (GSC) are likely to be involved in treatment resistance, by releasing extracellular vesicles (EVs) containing specific molecular cargoes. Here, we studied the EVs secreted by glioma stem cells (GSC-EVs) and their effects on radiation resistance and glioma progression. EVs were isolated from 3 GSCs by serial centrifugation. NanoSight measurement, cryo-electron microscopy and live imaging were used to study the EVs size, morphology and uptake, respectively. The non-GSC glioma cell lines LN229 and U118 were utilised as a recipient cell model. Wound healing assays were performed to detect cell migration. Colony formation, cell viability and invadopodium assays were conducted to detect cell survival of irradiated recipient cells and cell invasion post GSC-EV treatment. NanoString miRNA global profiling was used to select for the GSC-EVs’ specific miRNAs. All three GSC cell lines secreted different amounts of EVs, and all expressed consistent levels of CD9 but different level of Alix, TSG101 and CD81. EVs were taken up by both LN229 and U118 recipient cells. In the presence of GSC-EVs, these recipient cells survived radiation exposure and initiated colony formation. After GSC-EVs exposure, LN229 and U118 cells exhibited an invasive phenotype, as indicated by an increase in cell migration. We also identified 25 highly expressed miRNAs in the GSC-EVs examined, and 8 of these miRNAs can target PTEN. It is likely that GSC-EVs and their specific miRNAs induced the phenotypic changes in the recipient cells due to the activation of the PTEN/Akt pathway. This study demonstrated that GSC-EVs have the potential to induce radiation resistance and modulate the tumour microenvironment to promote glioma progression. Future therapeutic studies should be designed to interfere with these GSC-EVs and their specific miRNAs.

Anthropometric and Power-Related Attributes Differ Between Competition Levels in Age-Matched Under-19-Year-Old Male Basketball Players

PURPOSE

To compare anthropometric and power-related attributes between competition levels in under-19-year-old (U19) male basketball players.

METHODS

National-level (n = 7; age: 17.7 [0.5] y), first-division state-level (n = 8; 17.4 [0.4] y), and second-division state-level (n = 8; 17.1 [0.4] y) players from Australian basketball programs participated in this pilot study. Players had various anthropometric attributes (height, standing reach height, wingspan, and body mass) and power-related attributes (isometric midthigh pull, linear sprint, countermovement jump, 1-step vertical jump, standing long jump, repeated lateral bound, and Modified Agility T Test) measured in the preseason. Differences between groups were assessed using 1-way analyses of variance with Tukey post hoc tests and effect sizes (ES) interpreted as trivial, <0.20; small, 0.20 to 0.59; moderate, 0.60 to 1.19; large, 1.20 to 1.99; and very large, ≥2.00.

RESULTS

Regarding anthropometric attributes, national-level players possessed greater (P < .05, large-very large) height (ES = 2.09), standing reach height (ES = 1.54), wingspan (ES = 1.45), and body mass (ES = 1.77) than second-division state-level players. For power-related attributes, national-level players possessed greater (P < .05, large-very large) isometric midthigh-pull peak force (ES = 1.46-2.57), sprint momentum (ES = 1.17-2.18), and countermovement jump peak force (ES = 1.73-2.01) than state-level players. Moreover, national-level players demonstrated greater (P < .05) 1-step vertical jump height (ES = 1.95, large) than second division state-level players.

CONCLUSIONS

Specific anthropometric and power-related attributes clearly differ between competition levels in U19 male basketball players. This information can inform development of testing protocols, reference ranges, and training programs in practice. Further research is encouraged on this topic to confirm our findings across larger samples of basketball players.

Sprint acceleration force-velocity-power characteristics in drafted vs non-drafted junior Australian football players: preliminary results

This investigation aimed to compare the maximal sprint acceleration profiles of drafted and non-drafted elite junior Australian football (AF) players. Nineteen players (10 drafted and 9 non-drafted) from an elite junior AF state team participated in this study. Instantaneous velocity was measured via radar gun during maximal 30 m sprints. The velocity-time data were analysed to derive individual force-velocity-power characteristics and sprint times. No significant differences existed between groups, however drafted players reached moderately faster maximum velocity (Hedges' g = 0.70 [-0.08; 1.48] and theoretical maximum velocity (g = 0.65 [-0.13; 1.42]) than non-drafted players indicating a superior ability to apply higher amounts of force at increasing sprinting velocity. Further, drafted players produced moderately higher absolute theoretical maximum force (g = 0.72 [-0.06; 1.50]) and absolute maximum power (g = 0.83 [0.04; 1.62]) which reflects their moderately higher body mass (g = 0.61[-0.16;1.38]). Although not significant, in this sample of elite junior AF players, those drafted into the AFL displayed greater absolute sprint acceleration characteristics and maximal velocity capabilities than their non-drafted counterparts (moderate effect size). Whether force-velocity-power characteristics can be more beneficial in differentiating sprint performance of elite junior Australian footballers compared to the traditional sprint time approach warrants further investigation with a larger sample size.

Morphological profiling by means of the Cell Painting assay enables identification of tubulin-targeting compounds

In phenotypic compound discovery, conclusive identification of cellular targets and mode of action are often impaired by off-target binding. In particular, microtubules are frequently targeted in cellular assays. However, in vitro tubulin binding assays do not correctly reflect the cellular context, and conclusive high-throughput phenotypic assays monitoring tubulin binding are scarce, such that tubulin binding is rarely identified. We report that morphological profiling using the Cell Painting assay (CPA) can efficiently detect tubulin modulators in compound collections with a high throughput, including annotated reference compounds and unannotated compound classes with unrelated chemotypes and scaffolds. Small-molecule tubulin binders share similar CPA fingerprints, which enables prediction and experimental validation of microtubule-binding activity. Our findings suggest that CPA or a related morphological profiling approach will be an invaluable addition to small-molecule discovery programs in chemical biology and medicinal chemistry, enabling early identification of one of the most frequently observed off-target activities.

Clustering Accelerometer Activity Patterns from the UK Biobank Cohort

Many researchers are beginning to adopt the use of wrist-worn accelerometers to objectively measure personal activity levels. Data from these devices are often used to summarise such activity in terms of averages, variances, exceedances, and patterns within a profile. In this study, we report the development of a clustering utilising the whole activity profile. This was achieved using the robust clustering technique of k-medoids applied to an extensive data set of over 90,000 activity profiles, collected as part of the UK Biobank study. We identified nine distinct activity profiles in these data, which captured both the pattern of activity throughout a week and the intensity of the activity: "Active 9 to 5", "Active", "Morning Movers", "Get up and Active", "Live for the Weekend", "Moderates", "Leisurely 9 to 5", "Sedate" and "Inactive". These patterns are differentiated by sociodemographic, socioeconomic, and health and circadian rhythm data collected by UK Biobank. The utility of these findings are that they sit alongside existing summary measures of physical activity to provide a way to typify distinct activity patterns that may help to explain other health and morbidity outcomes, e.g., BMI or COVID-19. This research will be returned to the UK Biobank for other researchers to use.

The Framing Preference for Large and Increasing Components in Static and Dynamic Descriptions

Describing sets in terms of a two-valued variable, either value can be chosen: exam results may be referred to by pass rates or fail rates. What determines such framing choices? Building on work by McKenzie and colleagues on reference points in the production and interpretation of framed information, we investigate two determinants of frame choice. One is that speakers tend to focus on the component that has increased vis-à-vis a previous state, the other is the tendency to choose the component larger than 50%. We propose to view reference points as pointing to different kinds of communicative relevance. Hence the use of the previous state and the 50% reference points by speakers is not just a function of the information, but is co-determined by a communicative cue in the context: the question being asked about this information. This line of thought is supported by two experiments containing items offering two-sided distribution information at two points in time. Our first experiment employs a static task, requiring a description of the most recent situation. The second experiment uses a dynamic task, asking participants to describe the development between the two time points. We hypothesize that in static tasks the component size is the strongest frame choice determinant, while in dynamic tasks frame choice is mainly driven by whether a component has increased. The experiments consist of 16 different scenarios, both with symmetrical contrasts (i.e., dogs vs. cats) and with asymmetrical ones (i.e., winning vs. losing). Both experiments support the hypotheses. In the static task, the size effect is the only consistent effect; in the dynamic task, the effect of direction of change is much larger than that of size. This pattern of differences between size and change effects applies across symmetrical and asymmetrical contrasts. Our experiments shed light on cognitive and communicative regularities involved in the production of framed messages: people do tend to prefer larger and increasing components when choosing a frame, but the relative strength of both these preferences depends on the communicative task.

Profiles of psychosocial factors: Can they be used to predict injury risk?

The creation of risk profiles using the model of stress and athletic injury (J Appl Sport Psychol. 1998;10(1):5) represents a proposed shift from the reductionism paradigm to the complex sport approach in an attempt to formulate prevention strategies to combat the increasing number of injuries being reported in sporting populations. As a result, the primary purpose of this study was to: (a) identify different risk profiles based on psychosocial factors associated with the Williams and Andersen's model of stress and athletic injury model; and (b) examine potential differences in the frequency of injuries across these risk profiles. A prospective research design was utilized with a sample of 117 competitive soccer players (81 males and 36 females) from Sweden and the United States of America. Data was collected at two time points over the course of three months. At time 1 (beginning of the season) - a demographic information sheet, the Life Event Survey for Collegiate Athletes (LESCA), Sport Competitive Anxiety Test (SCAT), and Brief Cope were administered. At time two (T2), three months after the initial data collection, participants' traumatic injuries were recorded. Latent profile analysis (LPA) showed that 3 profiles solution showed best fit to data. Players in profile 1 and 2 reported fewer injuries compared to players in profile 3. However, whereas individuals in profile 1 had a lower predictive risk of sustaining an injury when compared to those in profile 3, both profiles had similar anxiety levels and use of coping strategies with differing stress levels. These findings suggest that the interaction between different proposed risk factors might influence injury risk.