Biological Mixtures Research Articles

Liquid Hopfield model: Retrieval and localization in multicomponent liquid mixtures

Biological mixtures, such as the cellular cytoplasm, are composed of a large number of different components. From this heterogeneity, ordered mesoscopic structures emerge, such as liquid phases with controlled composition. The competition of these structures for the same components raises several questions: what types of interactions allow the retrieval of multiple ordered mesoscopic structures, and what are the physical limitations for the retrieval of said structures. In this work, we develop an analytically tractable model for multicomponent liquids capable of retrieving states with target compositions. We name this model the liquid Hopfield model in reference to corresponding work in the theory of associative neural networks. In this model, we show that nonlinear repulsive interactions are a general requirement for retrieval of target structures. We demonstrate that this is because liquid mixtures at low temperatures tend to transition to phases with few components, a phenomenon that we term localization. Taken together, our results reveal a trade-off between retrieval and localization phenomena in liquid mixtures, and pave the way for other connections between the phenomenologies of neural computation and liquid mixtures.

INTERACTIONS WITH POPULACES’ PERCEPTIONS OF THE POLICY FOR SOLVING PROBLEMS OF THE PM2.5 DUST TOXIC POLLUTION ON HEALTH AND THE IMPACT CONTAMINATION TO AFFECTED RESPIRATORY SYSTEM DISEASES

Science 2008, keep an eye on the Particulate Matter (PM 2.5) toxic dust situation including any chemical, physical, or biological agent mixture of solid and liquid particles suspended in the air. It has affected the health of Thai people with over 10 million patients each period in a year. The Thai government needs to solve the problem of PM2.5 dust pollution at its sources seriously. The effects of global and climate change are affected to impact the threat to human health by human activities in short-middle-and long terms: Spiration System Affected, Lung Cancer, Carcinogenicity, Brain Threats, Heart Hazards diseases. Creative the Document Research Methodology data was reviewed, the Qualitative Research method data was interviewed and observed, and the independent and dependent variables were associated with 400 populaces who used to be sick with PM2.5 dust in 2023. Creating The 36-item Questionnaire on Populaces and PM2.5 Affected Interaction (QPPAI) in six scales; each scale consisted of 6 items in five options (Never-Always); and the 10-item Attitudes on Solving-Problem PM2.5 Toxic Dust (ASPTD). These instruments are valid and reliable. The participants’ responses reveal that they know how to protect themselves from PM2.5 dust and get support from the government (KPSG), they understand the effects of PM2.5 toxic dust, which can be inhaled deep into the respiratory tract and lungs (UETD), their receiving care from the government for being a patient with PM2.5 dust pollution (RCGP), most of the participants are understanding of effects of PM2.5 toxic dust (UETD), however, their awareness of news from the media or government organizations for groups at risk of danger from PM2.5 dust, receiving advice on care and treatment (AGAT), and this situation has in shock because they don’t yet understand the health effects of PM2.5 dust on the respiratory system and lungs (UHER), respectively. The results have found that the R2 value indicates that 61% of the variance in populaces’ perceptions of their attitudes to the government policies was attributable to their perceptions of the health effects of the PM2.5 toxic dust pollution in the air environment. They are supported significantly by government policies.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0773/a.php" alt="Hit counter" /></p>

Revolutionizing sensing technologies: Crafting a green, ultra-sensitive bismuth optical sensor via fixation of 5-(2′,4′-dimethyl-phenylazo)-6-hydroxypyrimidine-2,4-dione on PVC membrane

An innovative and exceptionally responsive optical sensing device engineered to selectively identify Bi(III) ions in water-based solutions. The sensing component, 5-(2′,4′-dimethylphenylazo)-6-hydroxypyrimidine-2,4-dione (DMPAHPD), is incorporated into a plasticized polyvinyl chloride (PVC) membrane. The sensor demonstrates an exceptional selectivity for Bi(III) within a broad dynamic range spanning from 7.5 × 10−10 to 4.2 × 10−5 M at pH 2.25. Notably, it achieves lower quantification and detection limits of 7.25 × 10−10 and 2.15 × 10−10 M, respectively. The optode membrane’s response to Bi(III) proves to be entirely reversible, demonstrating remarkable selectivity for Bi(III) ions over a diverse range of other cations and anions. The sensor exhibits favorable performance characteristics, including good reversibility, a wide dynamic range, a prolonged lifespan, sustained response stability over the long term, and high reproducibility. This visual chemical sensor exhibits potential for real-world usage, offering consistent outcomes when assessing Bi(III) levels in matrices such as water, soil, plants, biological and synthetic mixtures. Importantly, the sensor’s performance is comparable to corresponding data achieved from inductively coupled plasma atomic emission spectroscopy (ICP-AES).

Selectivity of Complex Coacervation in Multiprotein Mixtures.

Liquid-liquid phase separation of biomolecules is increasingly recognized as being relevant to various cellular functions, and complex coacervation of biomacromolecules, particularly proteins, is emerging as a key mechanism for this phenomenon. Complex coacervation is also being explored as a potential protein purification method due to its potential scalability, aqueous operation, and ability to produce a highly concentrated product. However, to date, most studies of complex coacervation have evaluated the phase behavior of a binary mixture of two oppositely charged macromolecules. Therefore, a comprehensive understanding of the phase behavior of complex biological mixtures is yet to be established. To address this, a panel of engineered proteins was designed to allow for quantitative analysis of the complex coacervation of individual proteins within a multicomponent mixture. The behavior of individual proteins was evaluated using a defined mixture of proteins that mimics the charge profile of the Escherichia coli proteome. To allow for the direct quantification of proteins in each phase, spectrally separated fluorescent proteins were used to construct the protein mixture. From this quantitative analysis, we observed that protein coacervation was synchronized in the mixture, which was distinctive from the behavior when each protein was evaluated in a single-protein system. Subtle differences in biophysical properties between the proteins, such as the ionization of individual charged residues and overall charge density, became noticeable in the mixture, which allowed us to elucidate parameters for protein complex coacervation. With this understanding, we successfully designed methods to enrich a range of proteins of interest from a mixture of proteins.

Gábor Transform-Based Signal Isolation, Rapid Deconvolution, and Quantitation of Intact Protein Ions with Mass Spectrometry.

High-resolution mass spectrometry (HRMS) is a powerful technique for the characterization and quantitation of complex biological mixtures, with several applications including clinical monitoring and tissue imaging. However, these medical and pharmaceutical applications are pushing the analytical limits of modern HRMS techniques, requiring either further development in instrumentation or data processing methods. Here, we demonstrate new developments in the interactive Fourier-transform analysis for mass spectrometry (iFAMS) software including the first application of Gábor transform (GT) to protein quantitation. Newly added automation tools detect signals from minimal user input and apply thresholds for signal selection, deconvolution, and baseline correction to improve the objectivity and reproducibility of deconvolution. Additional tools were added to improve the deconvolution of highly complex or congested mass spectra and are demonstrated here for the first time. The "Gábor Slicer" enables the user to explore trends in the Gábor spectrogram with instantaneous ion mass estimates accurate to 10 Da. The charge adjuster allows for easy visual confirmation of accurate charge state assignments and quick adjustment if necessary. Deconvolution refinement utilizes a second GT of isotopically resolved data to remove common deconvolution artifacts. To assess the quality of deconvolution from iFAMS, several comparisons are made to deconvolutions using other algorithms such as UniDec and an implementation of MaxEnt in Agilent MassHunter BioConfirm. Lastly, the newly added batch processing and quantitation capabilities of iFAMS are demonstrated and compared to a common extracted ion chromatogram approach.

Sample-to-answer salivary miRNA testing: New frontiers in point-of-care diagnostic technologies.

MicroRNA (miRNA), crucial non-coding RNAs, have emerged as key biomarkers in molecular diagnostics, prognosis, and personalized medicine due to their significant role in gene expression regulation. Salivary miRNA, in particular, stands out for its non-invasive collection method and ease of accessibility, offering promising avenues for the development of point-of-care diagnostics for a spectrum of diseases, including cancer, neurodegenerative disorders, and infectious diseases. Such development promises rapid and precise diagnosis, enabling timely treatment. Despite significant advancements in salivary miRNA-based testing, challenges persist in the quantification, multiplexing, sensitivity, and specificity, particularly for miRNA at low concentrations in complex biological mixtures. This work delves into these challenges, focusing on the development and application of salivary miRNA tests for point-of-care use. We explore the biogenesis of salivary miRNA and analyze their quantitative expression and their disease relevance in cancer, infection, and neurodegenerative disorders. We also examined recent progress in miRNA extraction, amplification, and multiplexed detection methods. This study offers a comprehensive view of the development of salivary miRNA-based point-of-care testing (POCT). Its successful advancement could revolutionize the early detection, monitoring, and management of various conditions, enhancing healthcare outcomes. This article is categorized under: Diagnostic Tools > Biosensing Diagnostic Tools > Diagnostic Nanodevices.

Blood Plasma as a Sampling Model during Drug-induced Thrombocytopenia: Effects of Antioxidants

OBJECTIVE Blood plasma, a complex biological mixture, plays a part in a variety of roles including clotting, defense, and transport, and reflects the overall status of blood components. Drug-induced thrombocytopenia (DIT) is characterized by abnormally low platelet count (below ~150,000 per μL) which can be caused by adverse effects of medications. This study aims to address a basic question, can plasma be employed as a sampling model to assess the oxidative stress (OS) changes and antioxidant status during DIT? The objective was to analyze the antioxidant status and OS in plasma during DIT, and to determine the effects of antioxidant supplementation such as Caripill™, L-Carnitine (LC), and vanillic acid (VA) during DIT. METHODS Male Wistar rats were used as animal models and grouped into control groups (n=5) and thrombocytopenia groups (n=5). Antioxidants were given to the thrombocytopenic and the control rats (50 mg/kg body weight) once a day for 7 days. Blood plasma from both groups was evaluated for total antioxidant capacity, antioxidant enzymes, markers of lipid peroxidation, protein oxidation, and OS. RESULTS The antioxidants significantly increased the total antioxidant capacity (CUPRAC) and ferric-reducing antioxidant power (FRAP) of the plasma and decreased the levels of conjugate dienes. Caripill™ also reduced lipid peroxidation, significantly elevated protein sulfhydryl and nitrite/nitrate levels, LC elevated lactate dehydrogenase levels, and VA increased superoxide dismutase activity and attenuated lipid peroxidation during DIT. CONCLUSIONS The antioxidants Caripill™, vanillic acid, and L-carnitine were demonstrated to be beneficial during DIT and to have prospects in alternate therapeutics. This study confirms that plasma can be utilized as a sampling model to study changes during OS situations.

Rapid Characterization of Phospholipids from Biological Matrix Enabled by Indium Tin Oxide (ITO) Coated Slide Assisted Enrichment MALDI Mass Spectrometry.

Lipidomic analysis of human serum is essential to monitor the individual's health status. Herein, we develop a facile strategy for rapid characterization of phospholipids in human serum via indium tin oxide (ITO) coated glass slide solid phase extraction MALDI mass spectrometry (ITO-SPE-MALDI-MS). Phospholipid species are retained on ITO slide via solid phase extraction owing to the unique property of the ITO material; the measurement of phospholipid species from 1 μl human serum within 2 min is achievable. A comparison of ITO-SPE strategy with conventional extraction methods was further carried out using liquid chromatography-mass spectrometry (LC-MS) and ion-mobility mass spectrometry (IM-MS), resulting in a comparable enrichment performance for the phospholipid analysis. Furthermore, rapid lipidomic profiling of serum samples from human colorectal cancer patients and cell lines was demonstrated. Our results indicate that ITO-SPE-MALDI-MS provides a higher throughput strategy for the analysis of phospholipid species in complex biological mixtures, showcasing its potential for applications in the analysis of clinical biofluids.

Deconvoluting multi-person biological mixtures and accurate characterization and identification of separated contributors using non-targeted single-cell DNA sequencing

The genetic characterization and identification of individuals who contributed to biological mixtures are complex and mostly unresolved tasks. These tasks are relevant in various fields, particularly in forensic investigations, which frequently encounters crime scene stains generated by more than one person. Currently, forensic mixture deconvolution is mostly performed subsequent to forensic DNA profiling at the level of the mixed DNA profiles, which comes with several limitations. Some previous studies attempted at separating single cells prior to forensic DNA profiling. However, these approaches are biased at selection of the cells and, due to their targeted DNA analysis on low template DNA, provide incomplete and unreliable forensic DNA profiles. We recently demonstrated the feasibility of performing mixture deconvolution prior to forensic DNA profiling through the utilization of a non-targeted single-cell transcriptome sequencing (scRNA-seq). In addition to individual-specific mixture deconvolution, this approach also allowed accurate characterisation of biological sex, biogeographic ancestry and individual identification of the separated mixture contributors. However, RNA has the forensic disadvantage of being prone to degradation, and sequencing RNA - focussing on coding regions - limits the number of single nucleotide polymorphisms (SNPs) utilized for genetic mixture deconvolution, characterization, and identification. These limitations can be overcome by performing single-cell sequencing on the level of DNA instead of RNA. Here, for the first time, we applied non-targeted single-cell DNA sequencing (scDNA-seq) by applying the scATAC-seq (Assay for Transposase-Accessible Chromatin with sequencing) technique to address the challenges of mixture deconvolution in the forensic context. We demonstrated that scATAC-seq, together with our recently developed De-goulash data analysis pipeline, is capable of deconvoluting complex blood mixtures of five individuals from both sexes with varying biogeographic ancestries. We further showed that our approach achieved correct genetic characterization of the biological sex and the biogeographic ancestry of each of the separated mixture contributors and established their identity. Furthermore, by analysing in-silico generated scATAC-seq data mixtures, we demonstrated successful individual-specific mixture deconvolution of i) highly complex mixtures of 11 individuals, ii) balanced mixtures containing as few as 20 cells (10 per each individual), and iii) imbalanced mixtures with a ratio as low as 1:80. Overall, our proof-of-principle study demonstrates the general feasibility of scDNA-seq in general, and scATAC-seq in particular, for mixture deconvolution, genetic characterization and individual identification of the separated mixture contributors. Furthermore, it shows that compared to scRNA-seq, scDNA-seq detects more SNPs from fewer cells, providing higher sensitivity, that is valuable in forensic genetics.

DEPArray™ single-cell technology: A validation study for forensic applications

In forensics investigations, it is common to encounter biological mixtures consisting of homogeneous or heterogeneous components from multiple individuals and with different genetic contributions. One promising mixture deconvolution strategy is the DEPArray™ technology, which enables the separation of cell populations before genetic analysis. While technological advances are fundamental, their reliable validation is crucial for successful implementation and use for casework. Thus, this study aimed to 1) systematically validate the DEPArray™ system concerning specificity, sensitivity, repeatability, and contamination occurrences for blood, epithelial, and sperm cells, and 2) evaluate its potential for single-cell analysis in the field of forensic science. Our findings confirmed the effective identification of different cell types and the correct assignment of successfully genotyped single cells to their respective donor(s). Using the NGM Detect™ Amplification Kit, the average profile completeness for diploid cells was approximately 80%, with ∼ 290 RFUs. In contrast, haploid sperm analysis yielded an average completeness of 51% referring to the haploid reference profile, accompanied by mean peak heights of ∼ 176 RFUs. Although certain alleles of heterozygous loci in diploid cells showed strong imbalances, the overall peak balances yielded acceptable values above ≥ 60% with a mean value of 72% ± 0.21, a median of 77%, but with a maximum imbalance of 9% between heterozygous peaks. Locus dropouts were considered stochastic events, exhibiting variations among donors and cell types, with a notable failure incidence observed for TH01. Within the wet-lab experimentation with >500 single cells for the validation, profiling was performed using the consensus approach, where profiles were selected randomly from all data to better mirror real casework results. Nevertheless, complete profiles could be achieved with as few as three diploid cells, while the average success rate increased to 100% when using profiles of 6–10 cells. For sperms, however, a consensus profile with completeness >90% of the autosomal diploid genotype could be attained using ≥15 cells. In addition, the robustness of the consensus approach was evaluated in the absence of the respective reference profile without severe deterioration. Here, increased stutter peaks (≥ 15%) were found as the main artifact in single-cell profiles, while contamination and drop-ins were ascertained as rare events. Lastly, the technique’s potential and limitations are discussed, and practical guidance is provided, particularly valuable for cold cases, multiple perpetrator rapes, and analyses of homogeneous mixed evidence.

Effect of the presence of carbendazim on imidacloprid degradation in a biological organic mixture

ABSTRACT The biological organic mixture (BOM) is a major component of a biopurification system (BPS), which provides an ample substrate for many microbes. Fungi present in BOM predominantly degrade pesticides through co-metabolism. We assume that the application of fungicides could have an impact on the fungal growth as well as the depuration ability of the BPS. This study is conducted to evaluate the efficiency of BOM in degrading imidacloprid in the presence of carbendazim, a commonly used fungicide. Both pesticides degraded at a faster rate when treated separately with the BOM, but their half-lives increased when applied in combination. The applied quantity of carbendazim (100 times of field recommended dose) was degraded within 60 days of the experiment. Approximately 75% of applied imidacloprid was dissipated within first 15 days of the experiment. Although carbendazim degraded at a faster rate, it had a negative impact on imidacloprid degradation during the experiment. Imidacloprid residue did not produce a negative effect on carbendazim degradation. Microbial and major soil enzyme activities were suppressed when BOM was exposed to the combination of pesticides in comparison to their single applications. Application of carbendazim was lethal to fungal population and may be the reason behind the increased persistence of imidacloprid in BOM.

Evaluation of the Microbiome Identification of Forensically Relevant Biological Fluids: A Pilot Study.

In forensic sciences, body fluids, or biological traces, are a major source of information, and their identification can play a decisive role in criminal investigations. Currently, the nature of biological fluids is assessed using immunological, physico-chemical, mRNA and epigenetic methods, but these have limits in terms of sensitivity and specificity. The emergence of next-generation sequencing technologies offers new opportunities to identify the nature of body fluids by determining bacterial communities. The aim of this pilot study was to assess whether analysis of the bacterial communities in isolated and mixed biological fluids could reflect the situation observed in real forensics labs. Several samples commonly encountered in forensic sciences were tested from healthy volunteers: saliva, vaginal fluid, blood, semen and skin swabs. These samples were analyzed alone or in combination in a ratio of 1:1. Sequencing was performed on the Ion Gene StudioTM S5 automated sequencer. Fluids tested alone revealed a typical bacterial signature with specific bacterial orders, enabling formal identification of the fluid of interest, despite inter-individual variations. However, in biological fluid mixtures, the predominance of some bacterial microbiomes inhibited interpretation. Oral and vaginal microbiomes were clearly preponderant, and the relative abundance of their bacterial communities and/or the presence of common species between samples made it impossible to detect bacterial orders or genera from other fluids, although they were distinguishable from one another. However, using the beta diversity, salivary fluids were identified and could be distinguished from fluids in combination. While this method of fluid identification is promising, further analyses are required to consolidate the protocol and ensure reliability.

Optical detection strategies for Ni(II) ion using metal-organic chemosensors: from molecular design to environmental applications.

Nickel is an important element utilized in various industrial/metallurgical processes, such as surgical and dental prostheses, Ni-Cd batteries, paint pigments, electroplating, ceramics, computer magnetic tapes, catalysis, and alloy manufacturing. However, its extensive use and associated waste production have led to increased nickel pollution in soils and water bodies, which adversely affects human health, animals and plants. This issue has prompted researchers to develop various optical probes, hereafter luminescent/colorimetric sensors, for the facile, sensitive and selective detection of nickel, particularly in biological and environmental contexts. In recent years, numerous functionalized chemosensors have been reported for imaging Ni2+, both in vivo and in vitro. In this context, metal-based receptors offer clear advantages over conventional organic sensors (viz., organic ligands, polymers, and membranes) in terms of cost, durability, stability, water solubility, recyclability, chemical flexibility and scope. This review highlights recent advancements in the design and fabrication of hybrid receptors (i.e., metal complexes and MOFs) for the specific detection of Ni2+ ions in complex environmental and biological mixtures.

Intact quantitation and evaluation of a PEG-glycosulfopeptide as a therapeutic P-selectin antagonist.

Peptide-based therapeutics are recognized as potent and selective molecules but are often limited by short circulating half-lives, instability towards enzymatic degradation, and immunogenicity. To address these limitations and improve their pharmacological properties, peptides are commonly modified by the covalent attachment of polyethylene glycol (PEG). However, the large molecular weight and polydispersity of PEG chains complicate the interpretation of the full structure of PEGylated peptide therapeutics using standard analytical techniques. Here, we developed a mass spectrometric-based workflow in negative ion mode to identify and quantify GSnP-6, a P-selectin antagonist, with a linear 10 kDa PEG (PEG10) attached at the N-terminus of the glycopeptide. Intact mass analysis with multiple microscans allowed accurate measurements of precursor ions in complex biological mixtures with baseline resolution. Utilizing stepped collision energies improved sequence coverage and enabled identification of key amino acid modifications. We show the utility of this approach in evaluating the properties of PEG10-GSnP-6 in vitro and in vivo. Inhibitory capacity was preserved while extending the half-life of this glycopeptide, as shown by the reduction of P-selectin/PSGL-1 binding. By sustaining effective circulating concentrations, PEG conjugation of a P-selectin glycopeptide antagonist represents a promising therapeutic strategy to target diseases linked to inflammatory processes.

Hyperpolarization-Enhanced NMR Spectroscopy of Unaltered Biofluids Using Photo-CIDNP.

The direct and unambiguous detection and identification of individual metabolite molecules present in complex biological mixtures constitute a major challenge in (bio)analytical research. In this context, nuclear magnetic resonance (NMR) spectroscopy has proven to be particularly powerful owing to its ability to provide both qualitative and quantitative atomic-level information on multiple analytes simultaneously in a noninvasive manner. Nevertheless, NMR suffers from a low inherent sensitivity and, moreover, lacks selectivity regarding the number of individual analytes to be studied in a mixture of a myriad of structurally and chemically very different molecules, e.g., metabolites in a biofluid. Here, we describe a method that circumvents these shortcomings via performing selective, photochemically induced dynamic nuclear polarization (photo-CIDNP) enhanced NMR spectroscopy on unmodified complex biological mixtures, i.e., human urine and serum, which yields a single, background-free one-dimensional NMR spectrum. In doing this, we demonstrate that photo-CIDNP experiments on unmodified complex mixtures of biological origin are feasible, can be performed straightforwardly in the native aqueous medium at physiological metabolite concentrations, and act as a spectral filter, facilitating the analysis of NMR spectra of complex biofluids. Due to its noninvasive nature, the method is fully compatible with state-of-the-art metabolomic protocols providing direct spectroscopic information on a small, carefully selected subset of clinically relevant metabolites. We anticipate that this approach, which, in addition, can be combined with existing high-throughput/high-sensitivity NMR methodology, holds great promise for further in-depth studies and development for use in metabolomics and many other areas of analytical research.

Rapid isolation of anti-idiotype aptamers for quantification of human monoclonal antibodies against SARS-CoV-2 spike protein

Therapeutic antibodies that block viral entry have already proven to be important, first line drugs for treatments of viral infections. In the case of SARS-CoV-2, combinations of multiple therapeutic antibodies may need to be rapidly identified and formulated in a way that blocks each new, predominant variant of the virus. For efficient introduction of any new antibody combination into patients, it is important to be able to monitor patient-specific pharmacokinetics of individual antibodies, which would include the time course of their specific capacity to block the viral spike proteins. Here, we present three examples of microfluidic-based rapid isolation of companion reagents useful for establishing combination antibody therapies. These reagents are specific three-dimensional imprints of variable regions of individual human monoclonal antibodies against the -spike protein of SARS-CoV-2 virus in the form of oligonucleotide-based ligands (aptamers). We implement these anti-idiotypic aptamers as bioreceptors in graphene-based field-effect transistor sensors to accomplish label free, rapid, and sensitive detection of matching antibodies within minutes. Through this work we have demonstrated the general applicability of anti-idiotype aptamers as capture reagents in quantification of active forms of monoclonal antibodies in complex biological mixtures.

Pesticide Exposure and Effects on Non-Apis Bees.

Bees are essential pollinators of many crops and wild plants, and pesticide exposure is one of the key environmental stressors affecting their health in anthropogenically modified landscapes. Until recently, almost all information on routes and impacts of pesticide exposure came from honey bees, at least partially because they were the only model species required for environmental risk assessments (ERAs) for insect pollinators. Recently, there has been a surge in research activity focusing on pesticide exposure and effects for non-Apis bees, including other social bees (bumble bees and stingless bees) and solitary bees. These taxa vary substantially from honey bees and one another in several important ecological traits, including spatial and temporal activity patterns, foraging and nesting requirements, and degree of sociality. In this article, we review the current evidence base about pesticide exposure pathways and the consequences of exposure for non-Apis bees. We find that the insights into non-Apis bee pesticide exposure and resulting impacts across biological organizations, landscapes, mixtures, and multiple stressors are still in their infancy. The good news is that there are many promising approaches that could be used to advance our understanding, with priority given to informing exposure pathways, extrapolating effects, and determining how well our current insights (limited to very few species and mostly neonicotinoid insecticides under unrealistic conditions) can be generalized to the diversity of species and lifestyles in the global bee community. We conclude that future research to expand our knowledge would also be beneficial for ERAs and wider policy decisions concerning pollinator conservation and pesticide regulation.

Improved analysis of derivatized steroid hormone isomers using ion mobility-mass spectrometry (IM-MS).

Over the last decade, applications of ion mobility-mass spectrometry (IM-MS) have exploded due primarily to the widespread commercialization of robust instrumentation from several vendors. Unfortunately, the modest resolving power of many of these platforms (~40-60) has precluded routine separation of constitutional and stereochemical isomers. While instrumentation advances have pushed resolving power to >150 in some cases, chemical approaches offer an alternative for increasing resolution with existing IM-MS instrumentation. Herein we explore the utility of two reactions, derivatization by Girard's reagents and 1,1-carbonyldiimidazole (CDI), for improving IM separation of steroid hormone isomers. These reactions are fast (≤30min), simple (requiring only basic lab equipment/expertise), and low-cost. Notably, these reactions are structurally selective in that they target carbonyl and hydroxyl groups, respectively, which are found in all naturally occurring steroids. Many steroid hormone isomers differ only in the number, location, and/or stereochemistry of these functional groups, allowing these reactions to "amplify" subtle structural differences and improve IM resolution. Our results show that resolution was significantly improved amongst CDI-derivatized isomer groups of hydroxyprogesterone (two-peak resolution of Rpp = 1.10 between 21-OHP and 11B-OHP), deoxycortisone (Rpp = 1.47 between 11-DHC and 21-DOC), and desoximetasone (Rpp = 1.98 between desoximetasone and fluocortolone). Moreover, characteristic collision cross section (DTCCSN2) measurements can be used to increase confidence in the identification of these compounds in complex biological mixtures. To demonstrate the feasibility of analyzing the derivatized steroids in complex biological matrixes, the reactions were performed following steroid extraction from urine and yielded similar results. Additionally, we applied a software-based approach (high-resolution demultiplexing) that further improved theresolving power (>150). Overall, our results suggest that targeted derivatization reactions coupled with IM-MS can significantly improve the resolution of challenging isomer groups, allowing for more accurate and efficient analysis of complex mixtures.

Hydrophobic Matching Dictates over the Linear Rule of Mixtures in Binary Lipid Membranes.

Biological membranes feature heterogeneous mixtures of lipids with different head and tail characteristics. Their biophysical properties are dictated by the intimate interaction among different constituent lipids. Previous studies suggest that the membrane area-per-lipid (APL) deviates from the linear rule of mixtures (LRM) for binary lipid membranes, but the underlying mechanism remains elusive. Our molecular dynamics (MD) simulations of binary lipid membranes consisting of lipids with different tail characteristics reveal a competitive mechanism whereby lipids tend to deform each other to minimize the hydrophobic mismatch between their tails. Depending on the relative tail lengths and saturation levels, this may result in an either positive or negative deviation of APL from the LRM. As lipid packing plays an essential role in membrane fusion and peptide-membrane binding, our findings may help guide the selection of lipids for the effective rational design of nanoliposomes and membrane-targeting peptides.

Differentiation of vaginal cells from epidermal cells using morphological and autofluorescence properties: Implications for sexual assault casework involving digital penetration

Analysis of DNA mixtures from sexual assault evidence is an ongoing challenge for DNA casework laboratories. To assist the forensic scientist address source and activity level propositions there is a significant need for new techniques that can provide information as to the source of DNA, particularly for sexual assault samples that do not involve semen. The goal of this study was to develop a new biological signature system that provides additional probative value to samples comprised of mixtures of epidermal and vaginal cells, as may be observed in cases involving digital penetration. Signatures were based on morphological and autofluorescence properties of individual cells collected through Imaging Flow Cytometry (IFC). Comparisons to reference cell populations from vaginal tissue and epidermal cells collected from hands showed strong multivariate differences across > 80 cellular measurements. These differences were used to build a predictive framework for classifying unknown cell populations as originating from epithelial cells associated with digital penetration or epidermal tissue. As part of the classification scheme, posterior probabilities of specific tissue group membership were calculated for each cell, along with multivariate similarity to that tissue type. We tested this approach on cell populations from reference tissue as well as mock casework samples involving hand swabbings following digital vaginal penetration. Many more cells classifying as non-epidermal tissue were detected in digital penetration hand swab samples than control hand swabbings. Minimum interpretation thresholds were developed to minimize false positives; these thresholds were also effective when screening licked hands, indicating the potential utility of this method for a variety of biological mixture types and depositional events relevant to forensic casework. Results showed that samples collected subsequent to digital penetration possessed markedly higher numbers of cells classifying as vaginal tissue as well as higher posterior probabilities for vaginal tissue (≥ 0.90) compared to cell populations collected from hands without prior contact with vaginal tissue. Additionally, digital penetration cell populations may be resolved from saliva cell populations and other non-target tissue types.