Biological Insight from Super-Resolution Microscopy: What We Can Learn from Localization-Based Images.

Super-resolution optical imaging based on the switching and localization of individual fluorescent molecules [photoactivated localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), etc.] has evolved remarkably over the last decade. Originally driven by pushing technological limits, it has become a tool of biological discovery. The initial demand for impressive pictures showing well-studied biological structures has been replaced by a need for quantitative, reliable data providing dependable evidence for specific unresolved biological hypotheses. In this review, we highlight applications that showcase this development, identify the features that led to their success, and discuss remaining challenges and difficulties. In this context, we consider the complex topic of defining resolution for this imaging modality and address some of the more common analytical methods used with this data.

Opposing Effects of Cohesin and Transcription on CTCF Organization Revealed by Super-resolution Imaging.

CCCTC-binding factor (CTCF) and cohesin play critical roles in organizing mammalian genomes into topologically associating domains (TADs). Here, by combining genetic engineering with quantitative super-resolution stimulated emission depletion (STED) microscopy, we demonstrate that in living cells, CTCF forms clusters typically containing 2-8 molecules. A fraction of CTCF clusters, enriched for those with ≥3 molecules, are coupled with cohesin complexes with a characteristic physical distance suggestive of a defined molecular interaction. Acute degradation of the cohesin unloader WAPL or transcriptional inhibition (TI) result in increased CTCF clustering. Furthermore, the effect of TI on CTCF clusters is alleviated by the acute loss of the cohesin subunit SMC3. Our study provides quantitative characterization of CTCF clusters in living cells, uncovers the opposing effects of cohesin and transcription on CTCF clustering, and highlights the power of quantitative super-resolution microscopy as a tool to bridge the gap between biochemical and genomic methodologies in chromatin research.

Resolving m6A epitranscriptome with stoichiometry.

A recent study by Hu et al. describes N6-methyladenosine (m6A)-selective allyl chemical labeling and sequencing (m6A-SAC-seq), which allows for quantitative, stoichiometric, and positional analyses of m6A at single-nucleotide resolution across the whole transcriptome level. Information on the m6A stoichiometry will provide additional layers of gene regulatory pathways mediated by m6A modification during diverse molecular, cellular, and physiological events.

Point-of-care image-based quantitative urinalysis with commercial reagent strips: Design and clinical evaluation.

Urinalysis is a useful test as an indicator of health or disease and as such, is a part of routine health screening. Urinalysis can be undertaken in many ways, one of which is reagent strips used in the general evaluation of health and to aid in the diagnosis and monitoring of kidney disease. To be effective, the test must be performed properly, and the results interpreted correctly. However, different light conditions and colour perception can vary between users leading to ambiguous readings. This has led to camera devices being used to capture and generate the estimated biomarker concentrations, but image colour can be affected by variations in illumination and inbuilt image processing. Therefore, a new portable device with embedded image processing techniques is presented in this study to provide quantitative measurements that are invariant to changes in illumination. The device includes a novel calibration process and uses the ratio of RGB values to compensate for variations in illumination across an image and improve the accuracy of quantitative measurements. Results show that the proposed calibration method gives consistent homogeneous illumination across the whole image. Comparisons against other existing methods and clinical results show good performance with a correlation to the clinical values. The proposed device can be used for point-of-care testing to provide reliable results consistent with clinical values.

Quantified Metabolomics and Lipidomics Profiles Reveal Serum Metabolic Alterations and Distinguished Metabolites of Seven Chronic Metabolic Diseases.

The co-occurrence of multiple chronic metabolic diseases is highly prevalent, posing a huge health threat. Clarifying the metabolic associations between them, as well as identifying metabolites which allow discrimination between diseases, will provide new biological insights into their co-occurrence. Herein, we utilized targeted serum metabolomics and lipidomics covering over 700 metabolites to characterize metabolic alterations and associations related to seven chronic metabolic diseases (obesity, hypertension, hyperuricemia, hyperglycemia, hypercholesterolemia, hypertriglyceridemia, fatty liver) from 1626 participants. We identified 454 metabolites were shared among at least two chronic metabolic diseases, accounting for 73.3% of all 619 significant metabolite-disease associations. We found amino acids, lactic acid, 2-hydroxybutyric acid, triacylglycerols (TGs), and diacylglycerols (DGs) showed connectivity across multiple chronic metabolic diseases. Many carnitines were specifically associated with hyperuricemia. The hypercholesterolemia group showed obvious lipid metabolism disorder. Using logistic regression models, we further identified distinguished metabolites of seven chronic metabolic diseases, which exhibited satisfactory area under curve (AUC) values ranging from 0.848 to 1 in discovery and validation sets. Overall, quantitative metabolome and lipidome data sets revealed widespread and interconnected metabolic disorders among seven chronic metabolic diseases. The distinguished metabolites are useful for diagnosing chronic metabolic diseases and provide a reference value for further clinical intervention and management based on metabolomics strategy.

30 Years of MRI-based cartilage & bone morphometry in knee osteoarthritis: From correlation to clinical trials.

OBJECTIVE: The first publication on morphometric analysis of articular cartilage using magnetic resonance imaging (MRI) in 1994 set the scene for a game change in osteoarthritis (OA) research. The current review highlights milestones in cartilage and bone morphometry, summarizing the rapid progress made in imaging, its application to understanding joint (patho-)physiology, and its use in interventional clinical trials. METHODS: Based on a Pubmed search of articles from 1994 to 2023, the authors subjectively selected representative work illustrating important steps in the development or application of magnetic resonance-based cartilage and bone morphometry, with a focus on studies in humans, and on the knee. Research on OA-pathophysiology is addressed only briefly, given length constraints. Compositional and semi-quantitative assessment are not covered here. RESULTS: The selected articles are presented in historical order as well as by content. We review progress in the technical aspects of image acquisition, segmentation and analysis, advances in understanding tissue growth, physiology, function, and adaptation, and a selection of clinical trials examining the efficacy of interventions on knee cartilage and bone. A perspective is provided of how lessons learned may be applied to future research and clinical management. CONCLUSIONS: Over the past 30 years, MRI-based morphometry of cartilage and bone has contributed to a paradigm shift in understanding articular tissue physiology and OA pathophysiology, and to the development of new treatment strategies. It is likely that these technologies will continue to play a key role in the development and (accelerated) approval of therapy, potentially targeted to different OA phenotypes.

Green light is similarly effective in promoting plant biomass as red/blue light - a meta-analysis.

Whether green light promotes or represses plant growth is an unresolved but important question, warranting a global meta-analysis of published data. We collected 136 datasets from 48 publications on 17 crop species, and calculated the green light effect for a range of plant traits. For each trait the effect was calculated as the ratio between the trait value attained under a red/blue background light plus green, divided by the value attained under the background light only, both having the same light intensity. Generally, green light strongly increased intrinsic water use efficiency (15%), the shoot-to-root ratio (13%), and decreased stomatal conductance (-15%). Moreover, green light increased fresh weight to a small extent (4%), but not plant dry weight, resulting in a reduced dry matter content (-2%). Hence, green light is similarly effective at increasing biomass as red and blue light. Green light also showed to increase leaf area (7%) and specific leaf area (4%; i.e., thinner leaves). Furthermore, effects of green light were species-dependent, with positive effects on biomass for lettuce and microgreens, and negative effects in basil and tomato. Our data suggest that future research should focus on the role of green light in modulating water loss, its putative role as a shade signal, and the causes for its species-specific effects on crop biomass.

Artificial intelligence-based analysis of the spatial distribution of abnormal computed tomography patterns in SARS-CoV-2 pneumonia: association with disease severity.

BACKGROUND: The substantial heterogeneity of clinical presentations in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia still requires robust chest computed tomography analysis to identify high-risk patients. While extension of ground-glass opacity and consolidation from peripheral to central lung fields on chest computed tomography (CT) might be associated with severely ill conditions, quantification of the central-peripheral distribution of ground glass opacity and consolidation in assessments of SARS-CoV-2 pneumonia remains unestablished. This study aimed to examine whether the central-peripheral distributions of ground glass opacity and consolidation were associated with severe outcomes in patients with SARS-CoV-2 pneumonia independent of the whole-lung extents of these abnormal shadows. METHODS: This multicenter retrospective cohort included hospitalized patients with SARS-CoV-2 pneumonia between January 2020 and August 2021. An artificial intelligence-based image analysis technology was used to segment abnormal shadows, including ground glass opacity and consolidation. The area ratio of ground glass opacity and consolidation to the whole lung (GGO%, CON%) and the ratio of ground glass opacity and consolidation areas in the central lungs to those in the peripheral lungs (GGO(C/P)) and (CON(C/P)) were automatically calculated. Severe outcome was defined as in-hospital death or requirement for endotracheal intubation. RESULTS: Of 512 enrolled patients, the severe outcome was observed in 77 patients. GGO% and CON% were higher in patients with severe outcomes than in those without. Multivariable logistic models showed that GGO(C/P), but not CON(C/P), was associated with the severe outcome independent of age, sex, comorbidities, GGO%, and CON%. CONCLUSION: In addition to GGO% and CON% in the whole lung, the higher the ratio of ground glass opacity in the central regions to that in the peripheral regions was, the more severe the outcomes in patients with SARS-CoV-2 pneumonia were. The proposed method might be useful to reproducibly quantify the extension of ground glass opacity from peripheral to central lungs and to estimate prognosis.

PARP-1, EpCAM, and FRα as potential targets for intraoperative detection and delineation of endometriosis: a quantitative tissue expression analysis.

BACKGROUND: Endometriosis is a gynecological disease characterized by the presence of endometrial tissue in abnormal locations, leading to severe symptoms, inflammation, pain, organ dysfunction, and infertility. Surgical removal of endometriosis lesions is crucial for improving pain and fertility outcomes, with the goal of complete lesion removal. This study aimed to analyze the location and expression patterns of poly (ADP-ribose) polymerase 1 (PARP-1), epithelial cell adhesion molecule (EpCAM), and folate receptor alpha (FRα) in endometriosis lesions and evaluate their potential for targeted imaging. METHODS: Gene expression analysis was performed using the Turku endometriosis database (EndometDB). By immunohistochemistry, we investigated the presence and distribution of PARP-1, EpCAM, and FRα in endometriosis foci and adjacent tissue. We also applied an ad hoc platform for the analysis of images to perform a quantitative immunolocalization analysis. Double immunofluorescence analysis was carried out for PARP-1 and EpCAM, as well as for PARP-1 and FRα, to explore the expression of these combined markers within endometriosis foci and their potential simultaneous utilization in surgical treatment. RESULTS: Gene expression analysis revealed that PARP-1, EpCAM, and FOLR1 (FRα gene) are more highly expressed in endometriotic lesions than in the peritoneum, which served as the control tissue. The results of the immunohistochemical study revealed a significant increase in the expression levels of all three biomarkers inside the endometriosis foci compared to the adjacent tissues. Additionally, the double immunofluorescence analysis consistently demonstrated the presence of PARP-1 in the nucleus and the expression of EpCAM and FRα in the cell membrane and cytoplasm. CONCLUSION: Overall, these three markers demonstrate significant potential for effective imaging of endometriosis. In particular, the results emphasize the importance of PARP-1 expression as a possible indicator for distinguishing endometriotic lesions from adjacent tissue. PARP-1, as a potential biomarker for endometriosis, offers promising avenues for further investigation in terms of both pathophysiology and diagnostic-therapeutic approaches.

Oculomotor and Vestibular Deficits in Friedreich Ataxia - Systematic Review and Meta-Analysis of Quantitative Measurements.

Disease-specific oculomotor assessments play a crucial role in the early diagnosis of hereditary cerebellar ataxias. Whereas several studies have reported on quantitative oculomotor and vestibular measurements in Friedreich's Ataxia (FRDA), the value of specific oculomotor paradigms remains unclear. We aimed to address this knowledge gap through a systematic literature review and providing disease-specific recommendations for a tailored set of eye-movement recordings in FRDA. MEDLINE and Embase were searched for studies reporting on quantitative oculomotor and/or vestibular measurements in FRDA-patients. Data on oculomotor and vestibular parameters were extracted and correlations with a range of clinical parameters were sought. Included studies (n = 17) reported on 185 patients. Abnormalities observed included the presence of saccadic intrusions (143/161) such as square-wave jerks (SWJ, 90/109) and ocular flutter (21/43), impaired eccentric gaze-holding (40/104), abnormal pursuit (81/93) and angular vestibulo-ocular reflex (aVOR) deficits (39/48). For visually-guided saccades (VGS), we frequently observed increases in saccade latency (27/38) and dysmetric saccades (71/93), whereas saccade velocity was more often preserved (37/43). Augmented anti-saccade (AS) latency, downbeat nystagmus and frequent macro-SWJ correlated with disease duration. Increased AS-latency and VGS-latency, frequent macro-SWJ, reduced aVOR-gain and augmented aVOR peak-latency correlated with disease severity. A broad range of oculomotor and vestibular deficits are documented in the literature. Impairments in pursuit, saccades and aVOR-responses are most commonly reported, and as such, should be prioritized as disease markers. Quantitative oculomotor testing in FRDA may facilitate early diagnosis and prove valuable in monitoring disease progression and treatment response.

Surrogacy in the United States: analysis of sociodemographic profiles and motivations of surrogates.

RESEARCH QUESTION: What is the profile of women in the USA who become surrogates, and what is their power of decision and motivations? DESIGN: This quantitative study was performed with 231 participants in the USA, given the country's long history of surrogacy, to help clarify the profile of women who become surrogates, their power of decision and motivations. RESULTS: Descriptive and multivariate cluster analyses showed that women who become surrogates earn above the average income for their state of residency, have a high level of education, have health insurance, are employed, and decide to become a surrogate for prosocial/altruistic reasons. CONCLUSIONS: In contrast to the premise of both radical feminism and ultra-conservative Catholicism, this study found that altruism and empathy are the primary motivations for participating in surrogacy processes, and that a woman's decision to become a surrogate is not motivated by social conditioning relating to poverty or social status.

Analysis of unsaturated alginate oligosaccharides using high-performance anion exchange chromatography coupled with mass spectrometry.

Alginate is a commercially important polysaccharide composed of mannuronic acid and its C5 differential isomer guluronic acid. Comprehensive research on alginate and alginate lyases requires efficient and precise analytical methods for alginate oligosaccharides. In this research, high-performance anion exchange chromatography (HPAEC) in parallel with pulsed amperometric detection (PAD) and mass spectrometry (MS) was applied to the analysis of oligosaccharides obtained by alginate lyase. By optimizing the chromatographic conditions including mobile phase concentration, flow rate, and elution gradient, the analysis of a single sample could be completed in 30 min. Seven unsaturated alginate oligosaccharides were separated and identified through their analysis time observed with PAD, including all structurally different unsaturated disaccharides and trisaccharides. The quantitative analysis of seven oligosaccharides was performed based on the quantitative capability of PAD. The method exhibited adequate linearity and precision parameters. All the calibration curves showed good linearity at least in the concentration range of 0.002 to 0.1 mg/mL. The HPAEC-PAD/MS method provides a general and efficient online method to analyze alginate oligosaccharides.

One-point calibration and matrix-matching concept for quantification of potentially toxic elements in wood by LA-ICP-MS.

The aim of this work is to evaluate two quantitative methods, based on the external calibration applied in laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) analysis, known as (i) analytical curve and (ii) one-point calibration, using the concept of matrix matching to quantify three potentially toxic elements (PTEs) in wood samples. These can biologically register changes in the abiotic environment and be applied to monitoring climate change or environmental toxicity. In this case, standard sample preparation was evaluated to prepare the standard pellets using Pinus taeda species as a matrix-matching concept. Six pellets of P. taeda, with different Pb, Cd, and Ba concentrations, were prepared to build the analytical curve and one-point calibration strategies. The LA-ICP-MS parameters were optimised for 206Pb, 208Pb, 112Cd, 114Cd, 137Ba, and 138Ba isotope analysis in wood samples. The two calibration strategies provided 74-110% analytical recovery from certified reference materials and similar results to those obtained by ICP-MS through the acid digestion of environmental wood samples from São Paulo City (Brazil). This demonstrated the applicability of the one-point calibration strategy in quantifying PTEs in wood samples, which could be used with environmental analyses. Differences observed between the Ba isotope results obtained via LA-ICP-MS and ICP-MS quantification were related to sampling by LA-ICP-MS and the ICP-MS sample introduction, as well as to laser matrix and transport effects because of the difference between the wood species evaluated.

Evaluating imaging repeatability of fully self-service fundus photography within a community-based eye disease screening setting.

PURPOSE: This study aimed to investigate the imaging repeatability of self-service fundus photography compared to traditional fundus photography performed by experienced operators. DESIGN: Prospective cross-sectional study. METHODS: In a community-based eye diseases screening site, we recruited 65 eyes (65 participants) from the resident population of Shanghai, China. All participants were devoid of cataract or any other conditions that could potentially compromise the quality of fundus imaging. Participants were categorized into fully self-service fundus photography or traditional fundus photography group. Image quantitative analysis software was used to extract clinically relevant indicators from the fundus images. Finally, a statistical analysis was performed to depict the imaging repeatability of fully self-service fundus photography. RESULTS: There was no statistical difference in the absolute differences, or the extents of variation of the indicators between the two groups. The extents of variation of all the measurement indicators, with the exception of the optic cup area, were below 10% in both groups. The Bland-Altman plots and multivariate analysis results were consistent with results mentioned above. CONCLUSIONS: The image repeatability of fully self-service fundus photography is comparable to that of traditional fundus photography performed by professionals, demonstrating promise in large-scale eye disease screening programs.

Toxic element characterization against a typical high geology background: Pollution enrichment, source tracking, spatial distribution, and ecological risk assessment.

The geological environment determines the initial content of various elements in soil, while the late input of toxic elements produced through weathering and leaching is a persistent threat to food security and human health. In this study, we selected the Lou Shao Basin, a black rock system background, and combined geostatistical analysis and multivariate statistics to quantify the specific contribution of weathering of the black rock system, and to analyze the source traces, spatial distributions, and ecological risks of the soil toxicity of elements. The results show that the soils in the study area are acidic, which is related to the weathering of sulfides in the black rock system. The concentrations of most elements in the soil were determined to exceed the soil background values, and the Cd, Se and N contents, exceeded more than five times, especially Se, Mo nearly as high as 13 times. Strong positive correlation between Se, Cu, V and P, low correlation between N and Se, Cu, V, P, Ni and Cd.72.52%, 43%, 77.79%, 82%, 77%, and 44.1% of Cd, Se, Ni, Cu, B, and Mo came from the black rock system, respectively, which were greatly affected by geogenic weathering; V, Zn, Pb, and As are mainly from biomass burning sources; N and P are mainly from agricultural surface sources. Comparison found that the Cd and Se elements in the rocks in the study area were 16.78 times and 1.36 times higher than the world shale average, respectively, and need to pay attention to the weathering process of the two, and the spatial distribution of the 12 elements in soils showed a striped and centralized block distribution pattern, specifically around the distribution of carbonate and metamorphic rocks and other high-geology blocks. The ecological risk results showed that Cd was the main element causing high ecological risk, followed by Se and N, which were at moderate to high ecological risk levels, and Se and N showed similar ecological risk patterns, which may be related to the fact that selenium can promote the uptake and transformation of nitrogen. The present results add to the endogenous sources of toxic elements, quantify the source contributions of toxic elements in soils with high geologic backgrounds, fill this knowledge gap, and provide new insights for pollution control and ecological protection in areas with high geochemical backgrounds.

Evaluation of the key ingredient from the main production areas of Phellodendri Amurensis Cortex using ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry and ultra-high-performance liquid chromatography coupled to triple-quadrupole mass spectrometry.

Phellodendri Amurensis Cortex (PAC) is a medicinal herb that has been generally used to treat diarrhea and jaundice. In order to comprehensively evaluate the PAC in the main production areas quality, a qualitative and quantitative method with highly effective, sensitive, and reliable was developed. The chemical compositions of PAC were analyzed, and fingerprints were established by ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS). Then, the determination of berberine, canthin-6-one, dictamnine, γ-fagarine, and magnoflorine from PAC samples was simultaneously performed using UPLC-QQQ-MS. Furthermore, the chemical components of PAC from different regions were compared and analyzed by combining hierarchical cluster analysis, principal component analysis, and orthogonal partial least squares discriminant analysis. A total of 58 compounds were identified, including 36 alkaloids, four phenylpropanoids, seven terpenoids, four flavonoids and their glycosides, an organic acid compound, and six other components. The fingerprint results show that samples have good similarity. Meanwhile, the content of the five ingredients in different habitats is quite different. By multivariate statistical analysis, 18 batches of PAC could be divided into three categories, and 20 components were identified as differential markers of various origins. A comprehensive method of PAC quality evaluation and chemical composition difference analysis was established, which provided the scientific basis for quality evaluation and further pharmacological mechanism research.

Liquid chromatography-mass spectrometry-based strategy for systematic profiling of chemical components and associated quantitative analysis of quality markers in Qi-Wei-Tong-Bi oral liquid.

Qi-Wei-Tong-Bi oral liquid (QWTB), a famous Chinese medicine preparation composed of seven crude drugs has a good therapeutic effect on rheumatoid arthritis and is widely used in China. However, its chemical composition and quality control have not been comprehensively and systematically investigated. In this study, high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was employed for its chemical profiling. As a result, 100 components were chemically characterized. Additionally, high-performance liquid chromatography coupled with a quadrupole linear ion trap mass spectrometry method was developed to simultaneously quantify nine bioactive components (hyperoside, ononin, quercetin, sinomenine, magnoflorine, gallic acid, protocatechuic acid, monotropein, and cyclo-(Pro-Tyr)) in multiple-reaction monitoring mode. After successful validation in terms of linearity, precision, repeatability, and recovery, the assay method was applied for the determination of 10 batches of QWTB. The results showed that QWTB was enriched in sinomenine and magnoflorine with the highest amount up to hundreds or even thousands of µg/mL, while quercetin, ononin, cyclo-(Pro-Tyr), and hyperoside were much lower with the lowest content below 10 µg/mL. This study work would help to reveal the chemical profiling and provide a valuable and reliable approach for quality evaluation and even pharmacodynamic material basis studies of QWTB.

Chemical profiling of Simiao pill and quantification of main effective constituents in it by ultra-high-performance liquid chromatography coupled with Q Exactive Orbitrap and triple quadrupole mass spectrometry.

Simiao pill is one of the most commonly used prescriptions in traditional Chinese medicine for the treatment of hyperuricemia and gout. However, methods based on more accurate and comprehensive qualitative and quantitative analyses of the active ingredients are not yet perfect due to limited methodology. This not only hinders the elucidation of the pharmacological mechanism of Simiao pill, but also its comprehensive clinical development and utilization. In this study, we employed ultra-high-performance liquid chromatography-Q Exactive Orbitrap-mass spectrometry technology to perform rapid analysis and identification of the chemical constituents in Simiao pill. A total of 101 chemical components were identified, including 26 alkaloids, 15 terpenoids, 11 flavonoids, eight steroids, six fatty acids, five limonoids, four saponins, five phenylpropanoids, and 21 other compounds. In addition, we established a new method by high-throughput ultra-high-performance liquid chromatography-Q Exactive Orbitrap-mass spectrometry combined with ultra-high-performance liquid chromatography-triple quadrupole-tandem mass spectrometry technology for quantification of 14 main active ingredients, such as adenosine (1), phellodendrine (2), mangnoflorine (3), ß-ecdysterone (4), 25R-inokosterone (5), 25S-inokosterone (6), jatrorrhizine (7), palmatine (8), chikusetsu saponin IVa (9), limonin (10), atractylenolide III (11), atractylenolide I (12), obacunone (13), and atractylenolide II (14) in Simiao pill. This work laid a foundation for further analysis and quality control of effective components in Simiao pill.

Application of apical myocardial perfusion quantitative analysis by contrast-enhanced ultrasound utilizing high-frequency linear probe.

BACKGROUND: Due to insufficient near-field resolution and artifacts, it is challenging to evaluate the left ventricular apical perfusion with phased-array probes. By combining high-frequency linear probe and contrast-enhanced ultrasound (CEUS), imaging of apical myocardial perfusion could be improved. The study aims to evaluate the preliminary application of CEUS by high-frequency linear probes to assess the apical perfusion. METHODS: The study enrolled retrospectively 91 patients to test the feasibility of the novel method. In protocol 1, patients were stratified into a group with left anterior descending artery (LAD) stenosis (N = 40) and a group without LAD stenosis or coronary artery disease (N = 41) based on the degree of coronary artery narrowing, quantified by >50% stenosis in coronary angiography. Receiver operating characteristics (ROC) analysis was performed to test the diagnostic value of perfusion parameters. In protocol 2, the reproducibility of high-frequency linear probe in apical perfusion analysis was compared with the conventional phased-array probe in 30 patients. RESULTS: (1) The novel method is feasible in 81(89.01%) patients. (2) In protocol 1, to detect LAD stenosis, the best cut-off of ß, T, A, and MBF were 10.32, 3.28, 9.39, and 4.99, respectively. Area under the curve of ß, T, A, and MBF were .880, .881, .761, and .880, respectively. (3) In protocol 2, compared with phased-array probe, the quantitative analysis of high-frequency linear probe is of high reproducibility and could get good curve fitting (R2 = .29 vs. R2 = .71, P < .01). CONCLUSION: Observation of apical perfusion using this method is feasible and quantitative analysis allows an accurate and convenient identification of LAD stenosis. This method provides an alternative for patients who have difficulties in visualizing the apical region with a phased-array probe.

Glycosort: A Computational Solution to Post-process Quantitative Large-Scale Intact Glycopeptide Analyses.

Protein glycosylation is a post-translational modification involving the addition of carbohydrates to proteins and plays a crucial role in protein folding and various biological processes such as cell recognition, differentiation, and immune response. The vast array of natural sugars available allows the generation of plenty of unique glycan structures in proteins, adding complexity to the regulation and biological functions of glycans. The diversity is further increased by enzymatic site preferences and stereochemical conjugation, leading to an immense amount of different glycan structures. Understanding glycosylation heterogeneity is vital for unraveling the impact of glycans on different biological functions. Evaluating site occupancies and structural heterogeneity aids in comprehending glycan-related alterations in biological processes. Several software tools are available for large-scale glycoproteomics studies; however, integrating identification and quantitative data to assess heterogeneity complexity often requires extensive manual data processing. To address this challenge, we present a python script that automates the integration of Byonic and MaxQuant outputs for glycoproteomic data analysis. The script enables the calculation of site occupancy percentages by glycans and facilitates the comparison of glycan structures and site occupancies between two groups. This automated tool offers researchers a means to organize and interpret their high-throughput quantitative glycoproteomic data effectively.