Analytical Biochemistry

BackgroundThe clinical translation of molecularly targeted therapeutics and imaging agents represents a cornerstone of precision oncology, with the global theranostics market projected to exceed $25 billion by 2030. However, the development of theragnostic agents or diagnostic companions remains constrained by analytical bottlenecks in quality control, such as target-binding specificity, which are increasingly required by regulatory agencies as product release criteria during the translation process. Current methods, including enzyme-linked immunosorbent assay (ELISA), which require specialized resources or external CROs, or bead-based assays for radiolabeled compounds, which involve complex multi-step protocols; these limitations and others hamper their practical implementation in clinical manufacturing environments. Assay delays can postpone clinical trial initiation, increase development costs, and delay patient access to these agents. ResultsWe have developed and validated a rapid, size-exclusion high-performance liquid chromatography (SE-HPLC) method for the determination of target-binding fractions of labeled biologics. The method separates the unbound biologic from the larger antigen-bound complex, allowing for rapid quantification. We validated the method using a panel of fluorescently labeled antibodies (panitumumab-IRDye800CW, nivolumab-IRDye800CW) and radiolabeled biologics ([18F]GEH200521, [18F]NOTA-ABY-030), assessing linearity, specificity, and concentration independence. The SE-HPLC method achieved excellent separation of bound and unbound species with a resolution (Rs) of 3.2. A strong linear relationship (R2 = 0.999) was observed between the antigen-to-antibody ratio and the measured binding fraction. The method demonstrated high specificity, with no binding detected with non-target antigens. The total assay and analysis time was less than 35 minutes, a significant improvement over traditional methods. ConclusionsSE-HPLC provides a rapid, specific, and cost-effective alternative to traditional binding fraction assessment methods, reducing quality control timelines from weeks/hours to minutes. The methods compatibility with both fluorescent and radiolabeled biologics and integration with existing HPLC infrastructure represents a significant advancement in development workflows.

BackgroundDNA polymerase activity assays are required for enzyme quality control in biotechnology and diagnostics, but standard methods rely on specialist reagents, radioactivity and other hazardous materials, or real-time PCR instruments that are not widely accessible in resource-limited settings. This constrains local production of high quality, validated reagents and increases dependence on imported enzymes. MethodsBased on experiences derived from partnerships with scientists in several low and middle-income countries (LMICs) and stakeholder consultations, we adapted a commercial EvaGreen-based fluorometric DNA polymerase activity assay for isothermal operation using minimal equipment. Assay conditions were optimized using Design of Experiments (DOE) methodology, varying temperature, reaction volume, and MgCl2 concentration. To address reagent cost and supply-chain constraints, we developed detailed protocols for in-house synthesis of the off-patent AOAO-12 DNA dye (sold commercially as EvaGreen) and generation of single-stranded DNA templates via asymmetric PCR. ResultsOptimized isothermal assay conditions (40{degrees}C, 7.75 mM MgCl2) reliably quantified activity across multiple DNA polymerase families. In-house synthesized AOAO-12 dye exhibited comparable DNA-binding performance to commercial alternatives (R{superscript 2} = 0.95), reducing costs by more than an order of magnitude when normalized to working concentrations, enabling assay costs of approximately {pound}0.001 per reaction. The assay is effective across multiple polymerases (Bst-LF, OpenVent, Taq, Q5) and is compatible with both plate readers and qByte, a low-cost, open-source fluorometric device. ConclusionsThis stakeholder-informed assay provides an accessible, cost-effective solution for DNA polymerase quality control in resource-limited settings. The combination of optimized commercial protocols and in-house reagent synthesis offers flexibility for different resource contexts, potentially improving access to molecular biology tools globally.

Quantitative polymerase chain reaction (qPCR) is limited in measuring absolute nucleic acid copy numbers due to the inherent variability of calibrators. Here, we introduce the Quantal PCR (quPCR), a novel method that eliminates the need for calibrators by defining an intrinsic quantal unit derived from the thermodynamic and kinetic properties of the replication system. This approach first determines amplification efficiency at high template concentrations, which is then used as the replication probability to construct quantification cycle (Cq) distribution profiles. These profiles are compared with those from limiting dilution PCR to derive the Cq value for the minimal quantal-replication unit ("quCq"), enabling calculation of the sample copy number. Validation using a dual-target DNA template showed near-identical copy numbers using two distinct target-specific replication systems. Thus, quPCR represents a new method for absolute nucleic acid quantification at the single-molecule level, offering a calibrator-free alternative for absolute quantification.

The protein sample preparation methods for shotgun proteomics are nowadays well-established unlike the ones for whole protein analysis. The goal of my work has been to create a simple methodology which provides a single uncomplicated sample preparation tool for these two fields. Nowadays the bulk of proteomics work is done using detergents for protein solubilization. The presented concept, which is based on unspecific adsorption of protein molecules on wide pore materials, allows for protein capture and clean-up from solutions of the most commonly used sodium dodecyl sulfate detergent. It could also be applied to proteins in detergent-free solutions. After the capture and clean-up, proteins could be either cleaved for the downstream peptide analysis or eluted for the whole protein analysis. If required, the eluted whole proteins could be recaptured and cleaved into peptides. Depending on the experimental goals, the sample preparation device could be fitted with embedded proteolytic enzymes to simplify routine sample processing and/or reversed phase media for the downstream peptide or protein separation.

Aiming to develop a high-throughput fluorimetric assay for the activity CYP1A2, we introduced 6-Methoxy-2-naphthoic acid (MONA) as a new fluorogenic substrate for this important metabolizer of antidepressants and psychotropic drugs in human liver. We demonstrated that oxidative demethylation of MONA by liver microsomes results in a red shift and a substantial increase in fluorescence. This effect, which is exceptionally well pronounced at alkaline pH, allowed us to develop a sensitive and robust high-throughput assay of MONA metabolism. Probing the activity of 15 individual recombinant human P450 enzymes, we found that only two P450 species exhibited activity in MONA demethylation: CYP1A2 (kcat=11.9{+/-}2.2 min-1, KM=578{+/-}106 {micro}M) and CYP2A6 (kcat=0.48{+/-}0.07 min-1, KM=54{+/-}15 {micro}M). Since the KM values of the two enzymes are well resolved and the turnover rate observed with CYP2A6 is much lower than that of CYP1A2, this new fluorogenic substrate is useful as a specific probe for CYP1A2 activity in HLM. Importantly, MONA is not metabolized by CYP1A1 and CYP2C19, which distinguishes it from all known CYP1A2 fluorogenic substrates. We then used MONA to investigate the effects of chronic alcohol exposure on CYP1A2 activity using a series of 23 proteomically characterized individual HLM preparations from donors with various levels of alcohol consumption. The substrate saturation profiles (SSP) acquired with these preparations were subjected to global kinetic analysis by approximating them with combinations of two Michaelis-Menten equations with globally optimized KM values of 11 and 553 {micro}M. The amplitudes (Vmax values) of both components showed a pronounced increase with increasing alcohol exposure of the liver donors. The Vmax of the minor high-affinity component was best correlated with the abundance of alcohol-inducible CYP2E1 enzyme. The correlation was further improved by combining it with the abundances of CYP2A6 and CPR. This finding suggests that this minor component reflects the activity of CYP2A6 in the complex with alcohol-inducible CYP2E1 protein. In contrast, the Vmax of the predominant CYP1A2-catalyzed low-affinity component revealed a pronounced correlation with the abundances of CYP1A2 and NADPH cytochrome P450 reductase (CPR). These results suggest a considerable increase in the rate of metabolism of drug substrates of CYP1A2 by chronic alcohol exposure that takes place despite an alcohol-induced decrease in CYP1A2 expression.

Phytohormones are key players in the regulation of plant development and metabolism. The different phytohormone classes comprise numerous chemically very diverse compounds, which are often present at very low concentrations. The chemical properties of phytohormones range from acidic to basic and from polar to non-polar. Furthermore, concentration varies strongly among different phytohormones, between plant species, tissues and developmental stages. Challenges often arise when only small amounts of plant material are available and when plant species are investigated in which the phytohormone profile has not yet been characterized. To establish a method for comprehensive phytohormone analysis we addressed these challenges by choosing and optimizing a suitable extraction method followed by optimized HPLC separation. We compared the most widely-used mass spectrometric detection methods, multiple reaction monitoring (MRM) on a triple quad instrument with high-resolution mass spectrometry (HRMS) on a Q-TOF instrument, and discuss the advantages of both methods and their limitations. O_LIWe compared various methods described in literature for the extraction of six phytohormone classes by liquid-liquid extraction and solid phase extraction purification and describe our optimizations to the selected method. C_LIO_LIWe optimized HPLC separation for 50 different phytohormones. C_LIO_LIWe evaluated the application of MRM and HRMS detection strategies. C_LI

ObjectiveGeneration and testing of IGF1 reference materials (RM), suitable for the harmonization of immunoassay (IA) and LC-MS/MS methods for the IGF1 determination in blood. In addition, establishment of age related reference intervals for men and women. MethodsIn a split sample study of 42 patients, and 30 healthy volunteers we tested the commutability of four RMs for IGF1, using four commercial IAs and an LC-MS/MS method. A new set of age dependent reference intervals was established using Lifelines biobank samples, based on the IGF1 LC-MS/MS method. ResultsThe four RMs were found to be commutable, except the RM with the lowest concentration measured with the Siemens Immulite method. The value assignment of the RMs was based on the IGF1 LC-MS/MS method, which was calibrated against WHO international standard 02/254. LC-MS/MS results were on average about 0 to 60% lower than those of the immunoassays. Combining the recalculated IGF1 results in patient samples from a former study with the data from healthy volunteers in this study, showed a reduction in the variation of the data points (standard error of estimate) of 42% and 62% respectively. ConclusionCommutable RMs for IGF1 can be made from serum of healthy blood donors. However, it remains necessary to test the commutability of these RMs in IAs that were not included in this study. By harmonizing methods using the four RMs, the same age-related reference intervals can be used.

Phosphorus magnetic resonance spectroscopy (31P-MRS) enables non-invasive measurement of brain metabolism, yet its reproducibility in clinical settings remains unclear. We systematically assessed intra- and intersession variability as well as inter-individual differences of key phosphorus metabolites at 3 Tesla in healthy individuals and persons with Parkinsons disease under various experimental condition. Intersession variability, as measured by coefficients of variation (CoV) increased notably for longer scan intervals ([~]1 year), and metabolite ratios from well-resolved spectral signals (i.e., adenosine triphosphate (ATP), phosphocreatine (PCr), intracellular inorganic phosphate Pi) exhibited consistently higher stability compared to ratios calculated from metabolite signals overlapping on the spectrum (e.g., total nicotinamide adenine dinucleotide (tNAD), as well as phosphate monoesters (PMEs) and phosphate diesters (PDEs). Test-retest variability ranged from [~]5-25 CoV%, where PCr, ATP- and ATP-{gamma} were the most stable while glycerophosphocholine (GPC), glycerophosphoethanolamine (GPE), phosphoethanolamine (PE) and tNAD varied considerably. Inter-individual variability was found to be higher than intra-individual variability for all metabolite ratios, ranging from [~]9-33 CoV%. By systematically quantifying intra-individual and inter-individual variability, as well as providing explicit sample-size recommendations, this study facilitates more reliable longitudinal and cross-sectional clinical trials and translational studies of brain metabolism featuring 31P-MRS.

Dogma suggests protein quantification is a pre-requisite to LC-MS/MS based proteomics studies. Such quantification allows a standardized ratio of sample to digestion enzyme and enables physical normalization of protein digest loaded onto the mass spectrometer for analysis. Most proteomics studies include these steps. However, there are significant costs in time, money and experimental complexity, associated with performing protein quantification and physical normalization for every sample, especially for larger studies. Proteomics data analysis pipelines typically include computational normalization strategies to compensate for unavoidable systematic biases. These strategies also have the potential to compensate for avoidable variation such as omitting sample amount normalization. Here we investigate the effects of either physically normalizing the amount of protein for each individual sample or leaving it unnormalized. Our results show the relationship between increased protein amount variation in sample input, and the variance of quantified relative abundances of peptides and proteins output after data analysis. The experiments presented here suggest that protein quantification and physical normalization steps can be omitted from some quantitative proteomic experiments without incurring an unacceptable increase in measurement variability after computational normalization has been applied. This work will enable important time and cost saving optimizations to be made to many proteomics workflows.

IntroductionRetinoids are bioactive vitamin A derivatives that regulate cellular differentiation and gene expression, yet their reliable quantification remains challenging due to low abundance, structural isomerism, and sensitivity to ionization conditions while handling. ObjectivesIn this study, we performed a systematic optimization of liquid chromatography-mass spectrometry (LC-MS)-based detection of retinoids across tissues and biofluids. MethodsChromatographic separation, adduct formation, ionization parameters, fragmentation behavior, and extraction procedures were evaluated in an integrated workflow. ResultsChromatographic conditions influenced not only retention time but also the ionic species detected, affecting precursor selection for MS{superscript 2} analysis. Retinoids exhibited compound-dependent responses to electrospray ionization and collision energy, requiring tailored acquisition parameters. Extraction experiments demonstrated differential recovery among retinoid classes and revealed matrix-dependent behavior, indicating that protocols used for tissues cannot be directly transferred to low-abundance biofluids. Using optimized conditions, retinoids were detected in mouse cerebrospinal fluid (CSF) at concentrations approaching the analytical detection limit, where MS{superscript 2} confirmation was necessary for reliable identification. ConclusionTogether, our results provide a framework for reproducible retinoid profiling across biological matrices and enables comparative studies of retinoid biology in low-volume and low-abundance biofluids.

Peptide-level analyses are becoming increasingly popular in mass spectrometry-based proteomics and are being applied, for example, in immunopeptidomics, structural proteomics, and analyses of post-translational modifications. In such analyses, peptides that are not biologically meaningful but instead arise as artifacts prior to mass spectrometry analysis pose the risk of data misinterpretation. Here, we describe an approach based on retention time analysis and precise chromatographic peak matching to identify peptides generated by in-source fragmentation (ISF), which occurs between chromatographic separation of peptide mixtures and the first mass filter of a tandem mass spectrometer (MS). To understand the prevalence and properties of ISF, we generated 13 proteomics datasets and analyzed them along with additional 25 previously published datasets spanning a broad range of sample types, MS, and proteomics approaches including classical bottom-up proteomics, immunopeptidomics, structural proteomics, and phosphoproteomics. We found that, in typical trypsin-digested samples on average 1 % of fully-tryptic peptides and 22 % of semi-tryptic peptides originated from ISF. However, we observed large variations between datasets, and in-source fragments exceeded, in some cases, a third of the total peptide identifications. The extent of ISF was dependent on the peptide sequence, the instrument, method parameters, and sample complexity. Although ISF did not impair relative quantification across samples, it generated peptides that could be misinterpreted qualitatively, inflated peptide identifications, and comprised up to 37 percent of peptides shorter than 9 amino acids in immunopeptidomics datasets. We propose that, for peptide-centric applications, our open-source ISF detection approach be used to re-annotate peptides generated by ISF and remove them to avoid misinterpretation of data. ISF is an increasing concern with improving mass spectrometers, as they enable detection of an ever-increasing number of m/z features, including low abundance features like ISF products. Our work thus addresses a growing issue in proteomics and presents solutions to mitigate the impact of in-source fragment peptides. In the future, improved feature detection algorithms may enable elucidation of new ISF patterns affecting side chains that have been missed so far, which could contribute to explaining the vast space of as-yet unannotated proteomics data.

Magic-angle spinning (MAS) solid-state NMR (SSNMR) has been widely used to determine amyloid fibril structures at atomic resolution. Such studies typically rely on homogeneous fibril preparations that produce narrow linewidths and high spectral resolution, enabling reliable resonance assignment and structural analysis. However, many biologically relevant amyloid aggregates are structurally heterogeneous, resulting in spectral broadening and reduced sensitivity that hinder atomic-resolution characterization. Lipids are known to modulate amyloid aggregation pathways and promote the formation of toxic species that are often less homogeneous, further complicating NMR-based investigations. Here, we evaluate the feasibility of utilizing the benefits associated with high-field (1.1 GHz) SSNMR for studying ganglioside GD3-catalyzed A{beta}42 aggregates. Uniformly-13C,15N-labeled A{beta}42 was incubated with GD3 to generate lipid-associated aggregates and analyzed under MAS conditions. 13C cross-polarization magic-angle spinning (CPMAS) spectra and 2D 13C-13C chemical shift correlation experiments using CORD (COmbined R2nv-Driven) mixing were acquired and compared with data collected at 600 MHz. Despite the heterogeneous nature of the GM1-associated assemblies, the 1.1 GHz spectra exhibit enhanced sensitivity and improved spectral resolution. Better resolved resonances corresponding to selectively structured regions of A{beta}42 are observed, indicating the presence of an ordered core within the lipid-associated aggregates. These results demonstrate that ultrahigh-field SSNMR significantly improves the characterization of heterogeneous amyloid assemblies and provides a promising approach for atomic-level investigation of biologically relevant, lipid-modulated A{beta} aggregates.

A common task in analysis of multidimensional NMR is the mapping of cross-peaks from one spectrum to another. In some situations, only a subset of coordinates of cross-peaks are to be matched such as in comparing corresponding dimensions of triple resonance assignment spectra. In other cases, the sample is perturbed in some way, and the task is to map corresponding cross-peaks that potentially change in any and all dimensions. This exercise is commonly done "by hand" and is both time-consuming and subjective. It is difficult for an individual to consider all possible interpretations of deviations between two multidimensional NMR spectra. Furthermore, in regions of high degeneracy, cross-peak matchings between spectra can be ambiguous. Ideally, a mapping algorithm should reflect a confidence of its matchings to indicate the reliability of proposed matchings and should do so while harmonizing all potential mappings in the spectrum. Critically, this process should be automated using criteria that are both well-defined, consistent and provide a measure of reliability. Here we develop a novel model describing the distribution of apparent deviations between cross-peaks of two multidimensional NMR spectra to random noise and true deviations to harmonize the cross-peak matching. Bayesian inference is employed to provide confidence estimates. The resulting algorithm (pHarmony) is tested in a variety of ways such as mapping between pairs of triple resonance spectra and between two- and three-dimensional heteronuclear NMR spectra generated by a fragment-based ligand discovery screen.

Abstract1IUGR is associated with increased risk of fetal compromise, yet can be difficult to detect and phenotype with routine clinical surveillance. Given placental insufficiency and hypoxia can remodel placental energy metabolism, methods that directly assess placental metabolic function may improve identification and phenotyping of growth-restricted pregnancies. We combined structural, body composition, and hyperpolarized metabolic MRI to characterize a near-term spontaneous IUGR (spIUGR) phenotype in the guinea pig. Twenty-two pregnant guinea pig sows (71 fetuses) underwent 1H and hyperpolarized 13C MRI at 60 {+/-} 1 days gestation to quantify fetal and placental volumes, maternal/fetal body composition, and quantify placental pyruvate metabolism. Fetuses were classified as spIUGR when [≥] 3 of 5 established markers were present (body weight, brain-body, brain-liver, brain-placenta ratios, and body weight relative to pregnancy mean); corresponding volume cut-offs were derived from weight cut-offs. MRI-derived fetal and placental volumes correlated strongly with collection weights and classified spIUGR consistently with weight-based criteria. Maternal adiposity (subcutaneous and visceral) was inversely associated with fetal adipose tissue volume, and maternal visceral fat PDFF was negatively associated with fetal adipose PDFF. Hyperpolarized MRI demonstrated IUGR phenotype-dependent placental pyruvate routing: LPR increased with asymmetric (brain-sparing) growth, showing a positive association with brain-body volume ratio (p = 0.02) and brain-body weight ratio (p = 0.04). In contrast, BPR was not significantly related to brain-body ratios (p = 0.09-0.11) but was inversely associated with absolute fetal size (body volume and weight, p = 0.02). These findings validate MRI volumetry for non-invasive identification of placental insufficiency spIUGR and link growth restriction severity and asymmetry to distinct placental metabolic signatures measurable in vivo.

BackgroundMetabolic reprogramming is a hallmark of breast cancer (BrCa), with alterations in glycolysis, glutamine metabolism, and the urea cycle contributing to tumour progression. Dichloroacetate (DCA), a pyruvate dehydrogenase kinase (PDK) inhibitor, shifts metabolism toward oxidative phosphorylation and has been proposed as a therapeutic agent. While isotope tracing is well-established, natural isotope abundance ({delta}{superscript 1}3C, {delta}{superscript 1}N) is emerging as a biomarker of metabolic alterations in cancer. MethodsWe investigated the relationship between isotope composition and metabolism in BrCa using two BALB/c mouse mammary tumour models (V14 and 4T1) and assessed the effects of DCA treatment using metabolomics, lipidomics and isotopomics. ResultsV14 and 4T1 tumours exhibited isotopic patterns similar to human tumours, with {delta}{superscript 1}3C enrichment and {delta}{superscript 1}N depletion relative to non-cancerous mammary tissue. V14 tumours were more {delta}{superscript 1}N-depleted than 4T1, reflecting differences in nitrogen metabolism. Multivariate analysis integrating isotopic, metabolomic, and lipidomic data revealed isotopic features as key discriminators between tumours and normal tissues. Compared to V14, 4T1 tumours were enriched in TCA intermediates, sphingolipids, and amino acids, whereas V14 tumours showed elevated glutaminolytic and nitrogenous metabolites. DCA treatment differentially affected tumour growth, with V14 tumours more sensitive than 4T1. DCA altered nitrogen metabolism, increasing the arginine-to-ornithine ratio, and modulating {delta}{superscript 1}N values in a tumour-specific manner increasing V14 and decreasing 4T1 {delta}{superscript 1}N values. DCA had little effect on {delta}{superscript 1}3C. {delta}{superscript 1}3C values were primarily determined by the balance between lipid and TCA cycle metabolites, rather than glycolytic flux. {delta}{superscript 1}N variation was linked to nitrogen metabolism, including urea cycle intermediates and sphingolipid composition, with a potential role for choline-related fractionation in {delta}{superscript 1}N depletion. Altered gene expression of Hacd2 and Acot12 in V14 tumours after DCA treatment was reflected in shorter fatty acid tails in phosphatidyl cholines, supporting the lipidomics data. ConclusionsThese findings support the hypothesis that cancer-associated metabolic reprogramming influences natural isotope abundance. Correlations between isotope shifts and metabolic signatures highlight the potential of lipid-derived {delta}{superscript 1}N as a biomarker of tumour metabolic state, with implications for noninvasive metabolic profiling in BrCa. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/710495v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1589d0eorg.highwire.dtl.DTLVardef@af2ad4org.highwire.dtl.DTLVardef@24e67forg.highwire.dtl.DTLVardef@98da7f_HPS_FORMAT_FIGEXP M_FIG C_FIG

AimsThe development of a method for isolating mitochondria from a specific cell type within a given tissue, while preserving their structural and functional integrity to the greatest possible extent, remains an ongoing challenge. The aim of this study was to establish a protocol for the isolation of mitochondria from rodent cardiomyocytes, characterized by minimal contamination with other cell types and a high yield of mitochondrial fractions originating from distinct subcellular regions of cardiomyocytes. Methods and resultsIn the present study, cardiomyocytes from guinea pig and rat hearts were isolated using a standard enzymatic digestion protocol in a Langendorff heart perfusion system. Traditionally, the isolation of organelles, including mitochondria, from whole cardiac tissue as well as from cardiomyocytes has relied primarily on mechanical tissue homogenization These conventional approaches involve the localized application of high pressure to cells, which may potentially damage delicate organelles, particularly mitochondria. Moreover, such homogenization preferentially releases mitochondria located in the subsarcolemmal region of cardiomyocytes rather than representing the entire mitochondrial population. In our study, we employed an alternative approach based on the gentle mechanical disruption of cardiomyocytes by passing the cell suspension through selected cell strainers using a cell scraper. This strategy facilitated mild disruption of cellular structures, significantly increasing the yield of mitochondria released from interfibrillar regions while preserving mitochondrial functionality. Moreover, this method decrease probability of sample contamination with mitochondria from other cells, based on cell size differences. The effectiveness of this method was confirmed by transmission electron microscopy, and high-resolution respirometry, which revealed no evidence of outer mitochondrial membrane damage, as indicated by the lack of response to the addition of exogenous cytochrome c to the incubation chamber. Moreover, mitochondrial oxygen consumption increased by 7.39 {+/-} 1.25-fold following the addition of 100 {micro}M ADP, reflecting efficient ADP-stimulated respiration. Furthermore, fluorescence measurements were performed. to assess changes in the mitochondrial inner membrane potential ({Delta}{Psi}). The isolated mitochondria were also suitable for electrophysiological studies using the single-channel patch-clamp technique. Additionally, mitochondria isolated using the protocol developed in our laboratory exhibited a high capacity for transplantation into H9c2 cells. ConclusionIn summary, our mitochondrial isolation method is rapid, efficient, and yields functionally competent mitochondria. These preparations are suitable for a wide range of downstream applications, including patch-clamp electrophysiology, analyses of oxygen consumption under various pharmacological conditions, as well as mitochondrial transplantation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=162 HEIGHT=200 SRC="FIGDIR/small/716092v1_ufig1.gif" ALT="Figure 1"> View larger version (85K): org.highwire.dtl.DTLVardef@613495org.highwire.dtl.DTLVardef@1c34338org.highwire.dtl.DTLVardef@722900org.highwire.dtl.DTLVardef@e1f7a6_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundBreast cancer-related lymphedema (BCRL) is a common complication following breast cancer treatment. While lymphoscintigraphy is considered the diagnostic gold standard, it is unsuitable for routine periodic monitoring or assessment of treatment efficacy. Shear wave elastography (SWE) offers a possible alternative, but traditional modes of operation limit its potential. Proposed SolutionsThe Holder-Optimized Elastography (HOE) method is introduced to eliminate pressure issues introduced by manual operation of ultrasound probes by stabilizing them above the cutis. MethodsThe HOE method was used to acquire ARFI images of high-velocity areas (HVAs, with shear wave velocity greater than 7 m/s) in limbs with and without BCRL (as confirmed and characterized by lymphoscintigraphy) in two cohorts of 15 and 125 patients. ResultsThe HOE method enabled ARFI elastography to directly and consistently visualize the effects caused by both obstructed lymphatic vessels and intraluminal lymphatic fluid as HVAs, whereas traditional hand-held methods did not. Inter-limb differences in HVA burden showed moderate diagnostic performance for detecting BCRL and grading obstruction with modest sensitivity. However, there was systematic underestimation of both early and confluent advanced lesions. ConclusionHOE-based HVA imaging has potential for rapid and non-invasive monitoring of lymphedema course and treatment response and may serve as a useful adjunct to existing diagnostic tools for BCRL. However, further technical refinements and quantitative analytic methods will be required to fully exploit the richer SWV information provided by HOE and to enhance the diagnostic utility of HVAs. Summary StatementThe Holder-Optimized Elastography method ("HOE" method) increases the diagnostic capability of ARFI elastography for breast cancer-related lymphedema, allowing for the non-invasive detection of some lymphatic obstructions but not all. Key ResultsThe Holder-Optimized Elastography (HOE) method revealed the effects caused by fluid-filled lymphatic vessels as "High-Velocity Areas" (HVAs), which are difficult to detect by conventional methods. HVA counts for detecting lymphedema (any obstruction vs. no obstruction) showed high specificity (0.86-1.00) but low sensitivity (0.57-0.67). Conversely, HVA counts for staging lymphedema (i.e. total vs. partial obstruction) showed high sensitivity (up to 1.00) but low specificity (0.48-0.66). The inter-limb difference of HVAs counted in whole-limb scans between affected and unaffected limbs (aka, the "Global Mean Difference") provided the most balanced diagnostic performance (sensitivity 0.67-0.79, specificity 0.88-0.89).

Background/ObjectivesDevelopability assessment is a critical step in advancing antibody-based molecules toward clinical application. This evaluation typically begins during clinical candidate selection and continues throughout all modifications of the molecule during development. It is guided by the target product profile, which includes the intended administration route and regimen, formulation parameters, and process conditions encountered during manufacturing, storage, and delivery. While developability testing is well established for conventional therapeutic antibodies, strategies for assessing single-domain antibodies (sdAbs) and their conjugates remain underexplored. Here we present a strategy to test the developability of sdAbs as a case study for two clinical candidates intended as precursors for the production of diagnostic tracers for clinical imaging. MethodsAssays were developed to evaluate chemical and thermodynamic stability, target binding affinity and capacity, and chelation efficiency ("chelatability"). Accelerated stability studies were conducted for both unconjugated sdAbs and their chelator conjugated forms following incubation at two pH conditions, at multiple time points, and after twelve freeze-thaw cycles to simulate process conditions and long-term storage. Analytical assays were applied stepwise in a hierarchical approach to minimized experimental effort and material consumption. Candidates exhibiting critical developability features were selectively addressed by assays with increasing precision. ResultsA tailored panel of analytical assays optimized for low molecular weight proteins was established and applied to the two clinical candidates, identifying instability hotspots as well as potential mitigation strategies. Successful engineering of a candidate with an initially critical developability profile was achieved. ConclusionThis study demonstrates the implementation of a structured developability assessment strategy for sdAb conjugates. The approach integrates physicochemical and functional stability evaluations, supporting robust candidate selection, formulation development, and method optimization for this class of molecules.

Synthetic 6-Br-Q0C10 has been shown to exhibit a partial electron transfer activity of native coenzyme Q in the isolated mitochondria. It reduces energy coupling efficiency by approximately 30%, suggesting that it may be useful in modulating cell growth in tissue culture. Whether or not it behaves in the same way in the whole cells, or animal, however, has not yet been fully examined. Recently we have investigated the effect of 6-Br-Q0C10 across multiple cell lines using three detection methods. Treatment with 6-Br-Q0C10 reduces cell proliferation in all cell lines tested, with different effectiveness. Obesity-related cell lines were the most susceptible, and a pronounced inhibitory effect was also observed in cancer cell lines. These results strengthen the idea of using 6-Br-Q0C10 to manage obesity or to retard the growth of rate cancer cells and thus prolonging life.

Mitochondrial diseases are a diverse group of inherited neuromuscular disorders leading to progressive disability and early mortality. Mitochondrial myopathy is a common feature of mitochondrial disorders, affecting most patients. Assessment of disease progression and treatment efficacy in mitochondrial disease trials has often relied on muscle biopsies, however, these are increasingly considered unfavourable by patients. Imaging biomarkers of disease could reduce the patient burden, enabling non-invasive longitudinal monitoring of molecular information. Photoacoustic imaging combines the molecular sensitivity of light absorption with the deep tissue imaging capabilities of ultrasound, enabling a safe and fast imaging technique. Tuning the wavelength of light allows for the detection of molecular constituents such as oxy- and deoxy-haemoglobin, lipids, and water. These signatures may reflect underlying pathophysiological alterations and serve as valuable indicators of disease state and progression. We conducted an exploratory study of a photoacoustic imaging dataset in patients with mitochondrial myopathy due to the m.3243A>G mt-tRNALeu mutation and compared to healthy volunteers. We generated photoacoustic measurements at wavelengths in the near infrared, comparing absolute values and ratios derived in the bicep muscle. Confounding factors such as skin colour and sex were considered, and we ensured that these parameters were matched in healthy volunteers and patients. We identified significant differences between patients and controls, revealing changes in ratios between water and total haemoglobin, lipid and total haemoglobin, and lipid and water content. This study highlights the promise of photoacoustic imaging as a novel imaging biomarker in mitochondrial myopathies, paving the way for larger scale studies.