Diverse Biological Samples Research Articles

A prospective multicenter birth cohort in China: pregnancy health atlas.

The China Prospective Multi-Center Birth Cohort Study was launched in 2022. In collaboration with medical centers in 12 cities, it aims to establish a high-quality, multidimensional cohort comprising 20,000 natural pregnancy and assisted reproductive families. As of June 26, 2024, 12,911 pregnant women have participated in this study, and 161,122 biological samples have been collected. These samples cover four critical periods (early pregnancy, mid-pregnancy, late pregnancy, and postpartum) and comprise 10 different types such as serum, plasma, and urine. The study has collected comprehensive information from early pregnancy to newborns. The participants have an average age of 29.76years, an average height of 160.46cm, an average pre-pregnancy BMI of 23.11, and an average BMI of 27.25 before delivery. The cohort includes individuals from 26 ethnic groups, with 25 minority groups comprising 5.03% of the population. Guizhou Province exhibits the highest percentage of ethnic minorities at 24.96% and Guangdong Province owns the highest proportion (12.22%)of women with two or more children. The prevalence of thalassemia in Guangdong Province is seven times higher than in other provinces. Among pregnant women over 35years old, the prevalence of gestational diabetes mellitus is twice that of women under 35. Additionally, the prevalence of preeclampsia in women with assisted reproductive pregnancies is more than twice that of those with natural pregnancies. The study extensively collected diverse data and biological samples, making this cohort an ideal candidate for DOHaD field and multi-omics research.

Utility of Authentic 13C‐Labeled Disaccharide to Calibrate Hyaluronan Content Measurements by LC‐MS

ABSTRACTHyaluronan (hyaluronic acid, HA), a key glycosaminoglycan in the extracellular matrix, plays crucial roles in various physiological and pathological processes, including development, tissue hydration, inflammation, and tumor progression. Traditional methods for HA quantification, such as ELISA‐like assays, often have limitations in sensitivity and specificity, particularly for lower molecular weight HA. In this work, we introduce a coupled liquid chromatographic‐tandem mass spectrometric (LC‐MS/MS) method that employs a chemoenzymatically synthesized 13C‐labeled lyase‐derived authentic HA disaccharide calibrant for quantification of HA at the nanogram level. The method was validated against three HA polysaccharides with the sizes of ~33, 210, and 540 kDa. We applied this quantification technique to mouse tissues and plasma from both healthy and acetaminophen‐induced acute liver injury mice. Our data revealed a ~75‐fold increase in HA concentration in the liver of acetaminophen‐injured mice with a concomitant depletion from plasma. Overall, our method offers a robust, universal, and highly sensitive tool for HA analysis in diverse biological samples that will advance the investigation of the roles of this polysaccharide in human disease conditions.

DNARS: A safe, environmentally friendly and high-quality DNA extraction method suitable for various biological samples

The functional and interactional relationships between nucleic acids and proteins form the foundational framework for molecular biology studies. In this context, obtaining high-quality nucleic acids is a crucial step for successful downstream applications. This study aimed to develop a cost-effective, eco-friendly, and versatile DNA extraction method that yields high-quality DNA from diverse biological samples. We utilized three types of borosilicate-based recycled laboratory glass as a silica source, combined with sodium iodide as a chaotropic agent, creating an efficient system for cell lysis and DNA extraction. Quality control was performed by assessing the concentration and purity of the extracted DNA using spectrophotometry, and the results were compared to those obtained with a commercial kit. DNA integrity was evaluated via agarose gel electrophoresis. To verify the suitability of the extracted DNA for downstream applications, we conducted 16S rRNA and ITS PCR amplifications. Our findings demonstrated that our DNA extraction method produced significantly higher yields, better purity, and greater integrity compared to the commercial kit. Moreover, the extracted DNA was readily applicable in PCR-based procedures, confirming the method's effectiveness for molecular biology applications.

Transforming Transcriptomics: The Impact of RNA Sequencing Technology

Aim: This study aimed to explore the advancements, methodologies, and applications of RNA sequencing (RNA-seq) technology, emphasizing its transformative impact on genomic research. Study Design: The research involved an in-depth review of RNA-seq technology, focusing on the steps of sample preparation, sequencing, and data analysis. Place and Duration of Study: Conducted through a detailed literature review over six months, at Hygia college of Pharmacy the study sourced information from various molecular biology and genomics publications. Methodology: Advanced computational techniques were utilized to map and quantify RNA sequences, facilitating a comprehensive analysis of gene expression patterns, alternative splicing, and novel transcript discovery. High-throughput sequencing platforms like Illumina and PacBio generated extensive datasets from diverse biological samples, including tissues, single cells, and environmental microbiomes. Results: The results highlighted RNA-seq's ability to provide a high-resolution view of the transcriptome, surpassing previous technologies in both sensitivity and accuracy. RNA-seq uncovered critical insights into differential gene expression, identifying significant pathways involved in development, disease, and environmental responses. The technology also discovered numerous previously unannotated transcripts and isoforms, contributing to the expansion of existing genomic databases. Conclusion: The study concludes that RNA-seq is a crucial advancement in molecular biology, offering unprecedented insights into gene regulation and expression. Its adoption has facilitated significant breakthroughs in understanding cellular processes, disease mechanisms, and therapeutic targets. As RNA-seq technology continues to evolve, it promises to drive further innovations and applications across diverse fields in the life sciences.

Hydrophilic molecularly imprinted thermal-responsive polymers based sorbent for ambient ionization mass spectrometric analysis of sulfonamide antibiotics from food samples

The thermal-responsive magnetic molecularly imprinted polymer (TrMMIP) sorbent was synthesized by surface imprinting method, and then used for magnetic solid-phase extraction (MSPE) and subsequent integrated into the ion source for elution and ionization. The shrinking-strength states change of the thermal-responsive polymer chain on TrMMIP alters the wettability of the sorbent when the working temperature crosses the lower critical solution temperature (LCST) of the polymer, and thus affects its behavior of in the extraction and clean-up process. The targeted analytes could be effectively extracted due to the high selectivity of MIPs and well dispersibility of polymer chain under the open state. Additionally, a hydrophilic polymer chain wrapped on the sorbent surface further protected target substances from co-elution during cleanup. Analytical methods for sulfonamide antibiotics (SAs) detection in complex food samples (milk, honey, fish) were developed, demonstrating potential for rapid and sensitive SAs analysis in diverse food and biological samples.

Three-Dimensional DNA Hydrogel Mediated Dual-Mode Sensing Method for Quantification of Epithelial Cell Adhesion Molecule in Biological Fluid Samples.

Monitoring changes in the expression of marker proteins in biological fluids is essential for biomarker-based disease diagnosis. Epithelial cell adhesion molecule (EpCAM) has been identified as a broad-spectrum biomarker for various chronic diseases and as a therapeutic target. However, the development of simple and reliable methods for quantifying EpCAM changes in biological fluids faces challenges due to the variability of its expression across different diseases, the presence of soluble forms, and matrix effects. In this paper, a surface-enhanced Raman scattering (SERS)-fluorescence (FL) dual-mode sensing method was established for quantification of trace EpCAM in biological fluids based on bimetallic Au@Ag nanoparticles and nitrogen-doped quantum dots encapsulated DNA hydrogel hybrid with graphene oxide (Au@Ag-NQDs/GO). The DNA hydrogel was constructed based on three-dimensional (3D) structure DNA-mediated strategy using an aptamer DNA (AptDNA) linker. The interaction of the AptDNA with EpCAM triggered the disassembly of the DNA hydrogel. Consequently, the release of Au@Ag nanoparticles induced an "on-off" switch in the SERS signal while the weakened FL quenching effect in Au@Ag-NQDs/GO system achieved "off-on" switch of FL signal, enabling the simultaneous SERS-FL quantification of EpCAM. The established dual-mode method exhibited outstanding sensitivity and stability in quantifying EpCAM in the range of 0.5-60.0 pg/mL, with the limits of detection (LODs) of SERS and FL as 0.17 and 0.35 pg/mL, respectively. When applied for real sample analysis, the method showed satisfactory specificity and recoveries in cancer cells lysate, serum, and urine samples with RSDs of 2.8-6.3%, 4.0-6.3%, and 2.8-5.7%, respectively. The developed SERS-FL sensing method offered a sensitive, reliable, and practical quantification strategy for trace EpCAM in diverse biological fluid samples, which would benefit the early diagnosis of disease and further health management.

Deciphering disease through glycan codes: leveraging lectin microarrays for clinical insights.

Glycosylation, a crucial posttranslational modification, plays a significant role in numerous physiological and pathological processes. Lectin microarrays, which leverage the high specificity of lectins for sugar binding, are ideally suited for profiling the glycan spectra of diverse and complex biological samples. In this review, we explore the evolution of lectin detection technologies, as well as the applications and challenges of lectin microarrays in analyzing the glycome profiles of various clinical samples, including serum, saliva, tissues, sperm, and urine. This review not only emphasizes significant advancements in the high-throughput analysis of polysaccharides but also provides insight into the potential of lectin microarrays for diagnosing and managing diseases such as tumors, autoimmune diseases, and chronic inflammation. We aim to provide a clear, concise, and comprehensive overview of the use of lectin microarrays in clinical settings, thereby assisting researchers in conducting clinical studies in glycobiology.

Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo

With the advent of modern technologies for cryo-electron tomography (cryo-ET), high-quality tilt series are more rapidly acquired than processed and analyzed. Thus, a robust and fast-automated alignment for batch processing in cryo-ET is needed. While different software packages have made available several approaches for automated marker-based alignment of tilt series, manual user intervention remains necessary for many datasets, thus preventing high-throughput tomography. We have developed a MATLAB-based framework integrated into the Dynamo software package for automatic detection of fiducial markers that generates a robust alignment model with minimal input parameters. This approach allows high-throughput, unsupervised volume reconstruction. This new module extends Dynamo with a large repertory of tools for tomographic alignment and reconstruction, as well as specific visualization browsers to rapidly assess the biological relevance of the dataset. Our approach has been successfully tested on a broad range of datasets that include diverse biological samples and cryo-ET modalities.

Viscoelasticity of diverse biological samples quantified by Acoustic Force Microrheology (AFMR)

In the context of soft matter and cellular mechanics, microrheology - the use of micron-sized particles to probe the frequency-dependent viscoelastic response of materials – is widely used to shed light onto the mechanics and dynamics of molecular structures. Here we present the implementation of active microrheology in an Acoustic Force Spectroscopy setup (AFMR), which combines multiplexing with the possibility of probing a wide range of forces ( ~ pN to ~nN) and frequencies (0.01–100 Hz). To demonstrate the potential of this approach, we perform active microrheology on biological samples of increasing complexity and stiffness: collagen gels, red blood cells (RBCs), and human fibroblasts, spanning a viscoelastic modulus range of five orders of magnitude. We show that AFMR can successfully quantify viscoelastic properties by probing many beads with high single-particle precision and reproducibility. Finally, we demonstrate that AFMR to map local sample heterogeneities as well as detect cellular responses to drugs.

A ratiometric fluorescent probe for cysteine and glutathione differentiation and its application for cysteine detection in foods

Cysteine (Cys) and glutathione (GSH) are crucial biothiols implicated in cellular redox balance, necessitating accurate detection methods. Herein, we developed a novel fluorescent probe based on the fluorescent dye pyronin (PYR), capable of monitoring both Cys-and GSH using ratiometric fluorescence signals. The probe, named PYR-CG, where "C" stands for Cys-and "G" stands for GSH, demonstrates selective detection capabilities for Cys-and GSH. UV absorption and fluorescence emission spectra changes revealed distinct shifts upon interaction with Cys-and GSH. Theoretical and experimental studies validated PYR-CG's responsiveness to Cys-and GSH, elucidating its mechanism as a ratiometric probe. Notably, PYR-CG exhibited rapid response kinetics for Cys-and GSH, with low detection limits of 88 nM and 164 nM, respectively. Importantly, PYR-CG demonstrated exceptional selectivity for Cys-and GSH over interfering analytes. Screening of molecules with similar structures to Cys-further affirmed PYR-CG's specificity, particularly towards N-terminal Cys-in peptides. Furthermore, recovery experiments underscored PYR-CG's reliability for quantitative Cys-detection in complex food samples. Our findings highlight the innovative design and practical applicability of PYR-CG, offering a valuable tool for sensitive and selective detection of Cys-in diverse biological and food samples.

Revolutionizing medicine: Molecularly imprinted polymers as precision tools in cancer diagnosis and antibiotic detection.

Molecularly imprinted polymers (MIPs) are pivotal in medicine, mimicking biological receptors with enhanced specificity and affinity. Comprising templates, functional monomers, and cross-linkers, MIPs form stable three-dimensional polymer networks. Synthetic templates like glycan and aptamers improve efficiency, guiding the molecular imprinting process. Cross-linking determines MIPs' morphology and mechanical stability, with printable hydrogels offering biocompatibility and customizable properties, mimicking native extracellular matrix (ECM) microenvironments. Their versatility finds applications in tissue engineering, soft robotics, regenerative medicine, and wastewater treatment. In cancer research, MIPs excel in both detection and therapy. MIP-based detection systems exhibit superior sensitivity and selectivity for cancer biomarkers. They target nucleic acids, proteins, and exosomes, providing stability, sensitivity, and adaptability. In therapy, MIPs offer solutions to challenges like multidrug resistance, excelling in drug delivery, photodynamic therapy, photothermal therapy, and biological activity regulation. In microbiology, MIPs serve as adsorbents in solid-phase extraction (SPE), efficiently separating and enriching antibiotics during sample preparation. They contribute to bacterial identification, selectively capturing specific strains or species. MIPs aid in detecting antibiotic residues using fluorescent nanostructures and developing sensors for sulfadiazine detection in food samples. In summary, MIPs play a pivotal role in advancing medical technologies with enhanced sensitivity, selectivity, and versatility. Applications range from biomarker detection to innovative cancer therapies, making MIPs indispensable for the accurate determination and monitoring of diverse biological and environmental samples.

Development of an advanced liquid chromatography–tandem mass spectrometry measurement system for simultaneous sphingolipid analysis

Mass spectrometry-based lipidomics approaches offer valuable tools for the detection and quantification of various lipid species, including sphingolipids. The present study aimed to develop a new method to simultaneously detect various sphingolipid species that applies to diverse biological samples. We developed and validated a measurement system by employing a single-column liquid chromatography-mass spectrometry system utilizing a normal-phase separation mode with positive ionization. The measurement system provided precision with a coefficient of variant below 20% for sphingolipids in all types of samples, and we observed good linearity in diluted serum samples. This system can measure the following sphingolipids: sphingosine 1-phosphate (S1P), sphingosine (Sph), dihydroS1P (dhS1P), dihydroSph (dhSph), ceramide 1-phosphate (Cer1P), hexosylceramide (HexCer), lactosylceramide (LacCer), dh-ceramide, deoxy-ceramide, deoxy-dh-ceramide, and sphingomyelin (SM). By measuring these sphingolipids in cell lysates where S1P lyase expression level was modulated, we could observe significant and dynamic modulations of sphingolipids in a comprehensive manner. Our newly established and validated measurement system can simultaneously measure many kinds of sphingolipids in biological samples. It holds great promise as a valuable tool for laboratory testing applications to detect overall modulations of sphingolipids, which have been proposed to be involved in pathogenesis processes in a series of elegant basic research studies.

Metabolomics and Risk of Dementia: A Systematic Review of Prospective Studies

BackgroundThe projected increase in the prevalence of dementia has sparked interest in understanding the pathophysiology and underlying causal factors in its development and progression. Identifying novel biomarkers in the preclinical or prodromal phase of dementia may be important for predicting early disease risk. Applying metabolomic techniques to prediagnostic samples in prospective studies provides the opportunity to identify potential disease biomarkers. ObjectiveThe objective of this systematic review was to summarize the evidence on the associations between metabolite markers and risk of dementia and related dementia subtypes in human studies with a prospective design. DesignWe searched PubMed, PsycINFO, and Web of Science databases from inception through December 8, 2023. Thirteen studies (mean/median follow-up years: 2.1–21.0 y) were included in the review. ResultsSeveral metabolites detected in biological samples, including amino acids, fatty acids, acylcarnitines, lipid and lipoprotein variations, hormones, and other related metabolites, were associated with risk of developing dementia. Our systematic review summarized the adjusted associations between metabolites and dementia risk; however, our findings should be interpreted with caution because of the heterogeneity across the included studies and potential sources of bias. Further studies are warranted with well-designed prospective cohort studies that have defined study populations, longer follow-up durations, the inclusion of additional diverse biological samples, standardization of techniques in metabolomics and ascertainment methods for diagnosing dementia, and inclusion of other related dementia subtypes. ConclusionsThis study contributes to the limited systematic reviews on metabolomics and dementia by summarizing the prospective associations between metabolites in prediagnostic biological samples with dementia risk. Our review discovered additional metabolite markers associated with the onset of developing dementia and may help aid in the understanding of dementia etiology.The protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (https://www.crd.york.ac.uk/prospero/; registration ID: CRD42022357521).

An Overview of Global, Local, and Base-Resolution Methods for the Detection of 5-Hydroxymethylcytosine in Genomic DNA.

The discovery of 5-hydroxymethylcytosine (5hmC) as a common DNA modification in mammalian genomes has ushered in new areas of inquiry regarding the dynamic epigenome. The balance between 5hmC and its precursor, 5-methylcytosine (5mC), has emerged as a determinant of key processes including cell fate specification, and alterations involving these bases have been implicated in the pathogenesis of various diseases. The identification of 5hmC separately from 5mC initially posed a challenge given that legacy epigenetic sequencing technologies could not discriminate between these two most abundant modifications, a significant blind spot considering their potentially functionally opposing roles. The growing interest in 5hmC, as well as in the Ten-Eleven Translocation (TET) familyenzymes that catalyze its generation and further oxidation to 5-formylcytosine (5fC) and 5-carboxycytosine (5caC), has spurred the development of versatile methods for 5hmC detection. These methods enable the quantification and localization of 5hmC in diverse biological samples and, in some cases, at the resolution of individual nucleotides. However, navigating this growing toolbox of methods for 5hmC detection can be challenging. Here, we detail existing and emerging methods for the detection, quantification, and localization of 5hmC at global, locus-specific, and base resolutionlevels. These methods are discussed in the context of their advantages and limitations, with the goal of providing a framework to help guide researchers in choosing the level of resolution and the associated method that could be most suitable for specific needs.

Quantitation of MUC5AC and MUC5B by Stable Isotope Labeling Mass Spectrometry.

Mucins MUC5AC and MUC5B are large glycoproteins that play an essential role in the innate defense of epithelial surfaces and their quantitation in biological samples would be informative about the health status of the tissue/samples they are derived from. However, they are difficult to study and quantify with traditional methods such as ELISA and western blot, due to their size, heterogeneity, and high degree of glycosylation. We successfully implemented a stable isotope labeling mass spectrometry approach for absolute quantification of mucin macromolecules. Here, in detail, we describe this accurate and sensitive liquid chromatography and mass spectrometry (LC-MS) method applied for both MUC5AC and MUC5B quantification in diverse and complex biological samples.

CRNDE: A Pivotal Oncogenic Long Non-Coding RNA in Cancers.

Colorectal Neoplasia Differentially Expressed (CRNDE), a long non-coding RNA that was initially identified as aberrantly expressed in colorectal cancer (CRC) has also been observed to exhibit elevated expression in various other human malignancies. Recent research has accumulated substantial evidence implicating CRNDE as an oncogenic player, exerting influence over critical cellular processes linked to cancer progression. Particularly, its regulatory interactions with microRNAs and proteins have been shown to modulate pathways that contribute to carcinogenesis and tumorigenesis. This review will comprehensively outline the roles of CRNDE in colorectal, liver, glioma, lung, cervical, gastric and prostate cancer, elucidating the mechanisms involved in modulating proliferation, apoptosis, migration, invasion, angiogenesis, and radio/chemoresistance. Furthermore, the review highlights CRNDE's potential as a multifaceted biomarker, owing to its presence in diverse biological samples and stable properties, thereby underscoring its diagnostic, therapeutic, and prognostic applications. This review aims to provide comprehensive insights of CRNDE-mediated oncogenesis and identify CRNDE as a promising target for future clinical interventions.

Optical projection tomography reconstruction with few views using highly-generalizable deep learning at sinogram domain.

Optical projection tomography (OPT) reconstruction using a minimal number of measured views offers the potential to significantly reduce excitation dosage and greatly enhance temporal resolution in biomedical imaging. However, traditional algorithms for tomographic reconstruction exhibit severe quality degradation, e.g., presence of streak artifacts, when the number of views is reduced. In this study, we introduce a novel domain evaluation method which can evaluate the domain complexity, and thereby validate that the sinogram domain exhibits lower complexity as compared to the conventional spatial domain. Then we achieve robust deep-learning-based reconstruction with a feedback-based data initialization method at sinogram domain, which shows strong generalization ability that notably improves the overall performance for OPT image reconstruction. This learning-based approach, termed SinNet, enables 4-view OPT reconstructions of diverse biological samples showing robust generalization ability. It surpasses the conventional OPT reconstruction approaches in terms of peak-signal-to-noise ratio (PSNR) and structural similarity (SSIM) metrics, showing its potential for the augment of widely-used OPT techniques.

Optimization and evaluation of ultra-trace amounts of lead in real samples using sol–gel based optical sensor coupled with colorimetry

The entrapment of the sensitive reagent 5-(2′-bromophenylazo)-6‑hydroxy-pyrimidine-2,4‑dione (BPAHPD) in a silica sol-gel thin film coated on a glass substrate has been investigated for the development of a highly sensitive and selective optode for the determination of lead ions. The fabrication of thin films requires tetraethoxysilane as a precursor, a sol-gel pH of 2.75, a water: alkoxide ratio of 5:1, and a BPAHPD concentration of 4.0 × 10–4 M. The effect of sol-gel parameters on the optode's sensing performance was investigated. The fabricated optode is utilized for lead ion detection over a dynamic range of 4.00–144 ng mL–1 with detection and quantification limits of 1.20 and 3.95 ng mL–1, respectively. It gave repeatable results with relative standard deviation (RSD) values of 1.90% and 1.15% for lead concentrations of 40.0 and 80.0 ng mL–1, respectively, and a response time of two minutes. Through capturing BPAHPD in a sol-gel matrix and appropriately modifying the structure of doped sol-gel, interference studies have determined that lead exhibits a high degree of selectivity. To ascertain total lead, Pb4+ was reduced to Pb2+ using a few drops of 6.00 M hydrochloric acid and a freshly prepared sodium azide solution of 2.50 % (w/v). The optode can be easily regenerated with 0.15 M of nitric acid solution. The optode has complete reversibility. Optode detection of lead in diverse vegetable, food, biological, water, and soil samples yielded favorable results when compared to other techniques.

Data Mining of Microarray Datasets in Translational Neuroscience.

Data mining involves the computational analysis of a plethora of publicly available datasets to generate new hypotheses that can be further validated by experiments for the improved understanding of the pathogenesis of neurodegenerative diseases. Although the number of sequencing datasets is on the rise, microarray analysis conducted on diverse biological samples represent a large collection of datasets with multiple web-based programs that enable efficient and convenient data analysis. In this review, we first discuss the selection of biological samples associated with neurological disorders, and the possibility of a combination of datasets, from various types of samples, to conduct an integrated analysis in order to achieve a holistic understanding of the alterations in the examined biological system. We then summarize key approaches and studies that have made use of the data mining of microarray datasets to obtain insights into translational neuroscience applications, including biomarker discovery, therapeutic development, and the elucidation of the pathogenic mechanisms of neurodegenerative diseases. We further discuss the gap to be bridged between microarray and sequencing studies to improve the utilization and combination of different types of datasets, together with experimental validation, for more comprehensive analyses. We conclude by providing future perspectives on integrating multi-omics, to advance precision phenotyping and personalized medicine for neurodegenerative diseases.

Tailoring the Amphiphilicity of Fluorescent Protein Chromophores to Detect Intracellular Proteome Aggregation in Diverse Biological Samples.

The formation of amorphous misfolded and aggregated proteins is a hallmark of proteome stress in diseased cells. Given its lack of defined targeting sites, the rational design of intracellular proteome aggregation sensors has been challenging. Herein, we modulate the amphiphilicity of fluorescent protein chromophores to enable selective detection of aggregated proteins in different biological samples, including recombinant proteins, stressed live cells, intoxicated mouse liver tissue, and human hepatocellular carcinoma tissue. By tuning the number of hydroxyl groups, we optimize the selectivity of fluorescent protein chromophores toward aggregated proteins in these biological samples. In recombinant protein applications, the most hydrophobic P0 (cLogP = 5.28) offers the highest fold change (FC = 31.6), sensitivity (LLOD = 0.1 μM), and brightness (Φ = 0.20) upon binding to aggregated proteins. In contrast, P4 of balanced amphiphilicity (cLogP = 2.32) is required for selective detection of proteome stresses in live cells. In mouse and human liver histology tissues, hydrophobic P1 exhibits the best performance in staining the aggregated proteome. Overall, the amphiphilicity of fluorescent chromophores governs the sensor's performance by matching the diverse nature of different biological samples. Together with common extracellular amyloid sensors (e.g., Thioflavin T), these sensors developed herein for intracellular amorphous aggregation complement the toolbox to study protein aggregation.