Integrating single-cell and spatial analysis reveals MUC1-mediated cellular crosstalk in mucinous colorectal adenocarcinoma.

BACKGROUND: Mucinous colorectal adenocarcinoma (MCA) is a distinct subtype of colorectal cancer (CRC) with the most aggressive pattern, but effective treatment of MCA remains a challenge due to its vague pathological characteristics. An in-depth understanding of transcriptional dynamics at the cellular level is critical for developing specialised MCA treatment strategies. METHODS: We integrated single-cell RNA sequencing and spatial transcriptomics data to systematically profile the MCA tumor microenvironment (TME), particularly the interactome of stromal and immune cells. In addition, a three-dimensional bioprinting technique, canonical ex vivo co-culture system, and immunofluorescence staining were further applied to validate the cellular communication networks within the TME. RESULTS: This study identified the crucial intercellular interactions that engaged in MCA pathogenesis. We found the increased infiltration of FGF7+/THBS1+ myofibroblasts in MCA tissues with decreased expression of genes associated with leukocyte-mediated immunity and T cell activation, suggesting a crucial role of these cells in regulating the immunosuppressive TME. In addition, MS4A4A+ macrophages that exhibit M2-phenotype were enriched in the tumoral niche and high expression of MS4A4A+ was associated with poor prognosis in the cohort data. The ligand-receptor-based intercellular communication analysis revealed the tight interaction of MUC1+ malignant cells and ZEB1+ endothelial cells, providing mechanistic information for MCA angiogenesis and molecular targets for subsequent translational applications. CONCLUSIONS: Our study provides novel insights into communications among tumour cells with stromal and immune cells that are significantly enriched in the TME during MCA progression, presenting potential prognostic biomarkers and therapeutic strategies for MCA. KEY POINTS: Tumour microenvironment profiling of MCA is developed. MUC1+ tumour cells interplay with FGF7+/THBS1+ myofibroblasts to promote MCA development. MS4A4A+ macrophages exhibit M2 phenotype in MCA. ZEB1+ endotheliocytes engage in EndMT process in MCA.

Integrating predictive coding and a user-centric interface for enhanced auditing and quality in cancer registry data.

Data curation for a hospital-based cancer registry heavily relies on the labor-intensive manual abstraction process by cancer registrars to identify cancer-related information from free-text electronic health records. To streamline this process, a natural language processing system incorporating a hybrid of deep learning-based and rule-based approaches for identifying lung cancer registry-related concepts, along with a symbolic expert system that generates registry coding based on weighted rules, was developed. The system is integrated with the hospital information system at a medical center to provide cancer registrars with a patient journey visualization platform. The embedded system offers a comprehensive view of patient reports annotated with significant registry concepts to facilitate the manual coding process and elevate overall quality. Extensive evaluations, including comparisons with state-of-the-art methods, were conducted using a lung cancer dataset comprising 1428 patients from the medical center. The experimental results illustrate the effectiveness of the developed system, consistently achieving F1-scores of 0.85 and 1.00 across 30 coding items. Registrar feedback highlights the system's reliability as a tool for assisting and auditing the abstraction. By presenting key registry items along the timeline of a patient's reports with accurate code predictions, the system improves the quality of registrar outcomes and reduces the labor resources and time required for data abstraction. Our study highlights advancements in cancer registry coding practices, demonstrating that the proposed hybrid weighted neural-symbolic cancer registry system is reliable and efficient for assisting cancer registrars in the coding workflow and contributing to clinical outcomes.

Pyroptosis inhibitors MCC950 and VX-765 mitigate myocardial injury by alleviating oxidative stress, inflammation, and apoptosis in acute myocardial hypoxia.

Acute myocardial infarction (AMI) is a prevalent cardiovascular disease with high morbidity and mortality rates worldwide. Pyroptosis is an inflammatory form of programmed cell death that has been linked to various pathological conditions. However, its exact contribution to the onset and progression of heart injury in AMI has not yet fully elucidated. Herein, we established mouse AMI model by ligating the left anterior descending artery and performed transcriptome analysis during the early phase of AMI. Mouse HL-1 and human AC-16 cardiomyocytes were subjected to hypoxia to simulate ischemic injury in vitro. Our results revealed a significant activation of the inflammatory response at 3 h post-ligation, as confirmed by RNA sequencing. We identified the occurrence of NLRP3 inflammasome-mediated pyroptosis in the cardiac tissues of human cases with AMI, as well as in mouse models of AMI and hypoxia-induced cardiomyocytes, using immunohistochemistry staining and Western blotting assays. Concurrently, pharmacological inhibition of NLRP3 inflammasome-mediated pyroptosis with MCC950 and VX-765 effectively decreased hypoxia-induced cardiomyocytes injury, while mitigating myocardial oxidative stress, apoptosis and inflammation caused by hypoxia. Moreover, the circulating levels of gasdermin D (GSDMD), the pyroptosis executor, were remarkably elevated in the plasma of mice with early AMI and in the supernatant of hypoxia-exposed cardiomyocytes in a time-dependent manner using ELISA and Western blotting. Furthermore, the change in circulating GSDMD positively correlated with Creatine Kinase-MB (CK-MB) in the plasma of early-stage AMI mouse. In summary, these findings indicated a critical role for NLRP3 inflammasome-mediated pyroptosis in the progression of AMI, the administration of MCC950 and VX-765 may be attractive candidate therapeutic approaches for cardiac injury caused by acute hypoxia or even AMI. Additionally, the circulating GSDMD exhibits potential as a newly diagnostic biomarker for AMI.

Predicting locus-specific DNA methylation levels in cancer and paracancer tissues.

Aim: To predict base-resolution DNA methylation in cancerous and paracancerous tissues. Material & methods: We collected six cancer DNA methylation datasets from The Cancer Genome Atlas and five cancer datasets from Gene Expression Omnibus and established machine learning models using paired cancerous and paracancerous tissues. Tenfold cross-validation and independent validation were performed to demonstrate the effectiveness of the proposed method. Results: The developed cross-tissue prediction models can substantially increase the accuracy at more than 68% of CpG sites and contribute to enhancing the statistical power of differential methylation analyses. An XGBoost model leveraging multiple correlating CpGs may elevate the prediction accuracy. Conclusion: This study provides a powerful tool for DNA methylation analysis and has the potential to gain new insights into cancer research from epigenetics.

Anaphylactic deaths: A retrospective study of forensic autopsy cases from 2009 to 2019 in Shanghai, China.

Anaphylaxis is a rare but well-known cause of sudden unexpected death, although data from forensic autopsies in anaphylactic deaths are limited. Herein, a retrospective study of a series of allergic deaths from 2009 through 2019 in Shanghai, China, was conducted to investigate the demographic, medical, and forensic pathological characteristics of fatal anaphylaxis to improve medicolegal understanding on anaphylactic death. Sixty-two autopsy cases of anaphylactic death were registered in this study. Males dominated the cases (74.2%) against females (25.8%), with an average age of 38.8 years. Medications (98.4%), particularly antibiotics (72.6%), were the most frequent cause of anaphylaxis, and 44 cases (71.0%) occurred in clinics administered illegally by unlicensed clinicians. The anaphylactic symptoms began within a few minutes to less than 1 h in 53 cases, with dyspnea (56.5%) and sudden shock (46.8%) being the most common clinical signs. Thirty cases (48.4%) of anaphylaxis resulted in death within 1 h. Laryngeal edema and multiple tissue eosinophil infiltration (85.5%) were the most prevalent autopsy findings, followed by pulmonary edema and congestion (24.2%), which were considered to be non-specific but suggestive. The comorbidities were mainly cardiovascular disease (33.9%), pneumonia (8.1%) and asthma (8.1%). Serum IgE were measured in 11 of 62 cases, ranging from 43.3 to 591 IU/ml, severed as a helpful marker. Therefore, we suggested a thorough analysis of allergen exposure, clinical history and autopsy findings is required for the diagnosis of anaphylactic death currently.

Use of Compressed Sensing Accelerated, Low-Velocity Encoded, Isotropic Resolution, Phase Contrast Magnetic Resonance Angiography for SEEG Electrode Implantation.

OBJECTIVE: We assessed the feasibility of using compressed sensing accelerated, low-velocity encoded, isotropic resolution phase contrast (CLIP) magnetic resonance angiography (MRA) for avascular trajectory planning of stereoelectroencephalography. METHODS: Ten healthy subjects (1 woman and 9 men; age, 33.6 ± 9.0 years) and 20 consecutive patients (12 female patients; age, 22 ± 13.6 years) were enrolled in the present study. The healthy subjects underwent CLIP-MRA, and 3 other phase contrast MRA protocols with conventional parallel imaging (PI) acceleration, including low resolution with twofold PI (PI2), high resolution (HR) with fivefold PI (PI5), and HR-PI2. The patients underwent CLIP-MRA and computed tomography angiography (CTA). The image qualities were evaluated. The numbers and locations of trajectory-vessel conflict detected using CLIP-MRA were noted. RESULTS: With similar scan durations, CLIP-MRA achieved higher spatial resolution compared with low resolution with PI2 and detected significantly more branches compared with HR-PI5. With the same spatial resolution, the signal/noise and contrast/noise ratios of CLIP-MRA were higher than those with HR-PI2 with a shorter scan duration. For the 12 adult patients (10 female patients; 28.8 ± 12.7 years), CLIP-MRA had better signal/noise and contrast/noise ratios than CTA. The trajectory had required modification for 14 of the 20 patients (70%), with a proportion of trajectory modification of 10.7% (23 of 215 electrodes). The middle meningeal artery, cortical vessel, and skull vessel were the main vessels with conflict (n = 11, n = 7, and n = 5, respectively). CONCLUSIONS: In the present study, CLIP-MRA provided a clear cortical vascular display noninvasively without intravascular contrast and radiation. The middle meningeal artery and diploic and emissary veins were the main conflict vessels and could be clearly displayed using CLIP-MRA but not CTA.

Insight study of rare earth elements in PM2.5 during five years in a Chinese inland city: Composition variations, sources, and exposure assessment.

The booming development of rare earth industry and the extensive utilization of its products accompanied by urban development have led to the accelerated accumulation of rare earth elements (REEs) as emerging pollutants in atmospheric environment. In this study, the variation of REEs in PM2.5 with urban (a non-mining city) transformation was investigated through five consecutive years of sample collection. The compositional variability and provenance contribution of REEs in PM2.5 were characterized, and the REEs exposure risks of children and adults via inhalation, ingestion and dermal absorption were also evaluated. The results showed an increase in the total REEs concentration from 46.46 ± 35.16 mg/kg (2017) to 81.22 ± 38.98 mg/kg (2021) over the five-year period, with Ce and La making the largest contribution. The actual increment of industrial and traffic emission source among the three pollution sources was 1.34 ng/m3. Coal combustion source displayed a downward trend. Ingestion was the main exposure pathway for REEs in PM2.5 for both children and adults. Ce contributed the most to the total intake of REEs in PM2.5 among the population, followed by La and Nd. The exposure risks of REEs in PM2.5 in the region were relatively low, but the trend of change was of great concern. It was strongly recommended to strengthen the concern about traffic-related non-exhaust emissions of particulate matter.

Free-breathing simultaneous native myocardial T1, T2 and T1ρ mapping with Cartesian acquisition and dictionary matching.

BACKGROUND: T1, T2 and T1ρ are well-recognized parameters for quantitative cardiac MRI. Simultaneous estimation of these parameters allows for comprehensive myocardial tissue characterization, such as myocardial fibrosis and edema. However, conventional techniques either quantify the parameters individually with separate breath-hold acquisitions, which may result in unregistered parameter maps, or estimate multiple parameters in a prolonged breath-hold acquisition, which may be intolerable to patients. We propose a free-breathing multi-parametric mapping (FB-MultiMap) technique that provides co-registered myocardial T1, T2 and T1ρ maps in a single efficient acquisition. METHODS: The proposed FB-MultiMap performs electrocardiogram-triggered single-shot Cartesian acquisition over 16 consecutive cardiac cycles, where inversion, T2 and T1ρ preparations are introduced for varying contrasts. A diaphragmatic navigator was used for prospective through-plane motion correction and the in-plane motion was corrected retrospectively with a group-wise image registration method. Quantitative mapping was conducted through dictionary matching of the motion corrected images, where the subject-specific dictionary was created using Bloch simulations for a range of T1, T2 and T1ρ values, as well as B1 factors to account for B1 inhomogeneities. The FB-MultiMap was optimized and validated in numerical simulations, phantom experiments, and in vivo imaging of 15 healthy subjects and six patients with suspected cardiac diseases. RESULTS: The phantom T1, T2 and T1ρ values estimated with FB-MultiMap agreed well with reference measurements with no dependency on heart rate. In healthy subjects, FB-MultiMap T1 was higher than MOLLI T1 mapping (1218 ± 50 ms vs. 1166 ± 38 ms, p < 0.001). The myocardial T2 and T1ρ estimated with FB-MultiMap were lower compared to the mapping with T2- or T1ρ-prepared 2D balanced steady-state free precession (T2: 41.2 ± 2.8 ms vs. 42.5 ± 3.1 ms, p = 0.06; T1ρ: 45.3 ± 4.4 ms vs. 50.2 ± 4.0, p < 0.001). The pathological changes in myocardial parameters measured with FB-MultiMap were consistent with conventional techniques in all patients. CONCLUSION: The proposed free-breathing multi-parametric mapping technique provides co-registered myocardial T1, T2 and T1ρ maps in 16 heartbeats, achieving similar mapping quality to conventional breath-hold mapping methods.

A dual-stage partially interpretable neural network for joint suppression of bSSFP banding and flow artifacts in non-phase-cycled cine imaging.

PURPOSE: To develop a partially interpretable neural network for joint suppression of banding and flow artifacts in non-phase-cycled bSSFP cine imaging. METHODS: A dual-stage neural network consisting of a voxel-identification (VI) sub-network and artifact-suppression (AS) sub-network is proposed. The VI sub-network provides identification of artifacts, which guides artifact suppression and improves interpretability. The AS sub-network reduces banding and flow artifacts. Short-axis cine images of 12 frequency offsets from 28 healthy subjects were used to train and test the dual-stage network. An additional 77 patients were retrospectively enrolled to evaluate its clinical generalizability. For healthy subjects, artifact suppression performance was analyzed by comparison with traditional phase cycling. The partial interpretability provided by the VI sub-network was analyzed via correlation analysis. Generalizability was evaluated for cine obtained with different sequence parameters and scanners. For patients, artifact suppression performance and partial interpretability of the network were qualitatively evaluated by 3 clinicians. Cardiac function before and after artifact suppression was assessed via left ventricular ejection fraction (LVEF). RESULTS: For the healthy subjects, visual inspection and quantitative analysis found a considerable reduction of banding and flow artifacts by the proposed network. Compared with traditional phase cycling, the proposed network improved flow artifact scores (4.57 ± 0.23 vs 3.40 ± 0.38, P = 0.002) and overall image quality (4.33 ± 0.22 vs 3.60 ± 0.38, P = 0.002). The VI sub-network well identified the location of banding and flow artifacts in the original movie and significantly correlated with the change of signal intensities in these regions. Changes of imaging parameters or the scanner did not cause a significant change of overall image quality relative to the baseline dataset, suggesting a good generalizability. For the patients, qualitative analysis showed a significant improvement of banding artifacts (4.01 ± 0.50 vs 2.77 ± 0.40, P < 0.001), flow artifacts (4.22 ± 0.38 vs 2.97 ± 0.57, P < 0.001), and image quality (3.91 ± 0.45 vs 2.60 ± 0.43, P < 0.001) relative to the original cine. The artifact suppression slightly reduced the LVEF (mean bias = -1.25%, P = 0.01). CONCLUSIONS: The dual-stage network simultaneously reduces banding and flow artifacts in bSSFP cine imaging with a partial interpretability, sparing the need for sequence modification. The method can be easily deployed in a clinical setting to identify artifacts and improve cine image quality.

Post-mortem genetic analysis of sudden unexplained death in a young cohort: a whole-exome sequencing study.

Sudden unexplained death (SUD) constitutes a considerable portion of unexpected sudden death in the young. Molecular autopsy has proved to be an efficient diagnostic tool in the multidisciplinary management of SUD. Yet, many cases remain undiagnosed using the widely adopted targeted genetic screening strategies. Here, we investigated the genetic substrates of a young SUD cohort (18-40 years old) from China using whole-exome sequencing (WES), with the primary aim to identify novel SUD susceptibility genes. Within 255 previously acknowledged SUD-associated genes, 21 variants with likely functional effects (pathogenic/likely pathogenic) were identified in 51.9% of the SUD cases. More importantly, a set of 33 candidate genes associated with myopathy were identified to be novel susceptibility genes for SUD. Comparative analysis of the cumulative PHRED-scaled CADD score and polygenetic burden score showed that the amount and deleteriousness of variants in the 255 SUD-associated genes and the 33 candidate genes identified by this study were significantly higher compared with 289 randomly selected genes. A significantly higher genetic burden of rare variants (MAF < 0.1%) in the 33 candidate genes also highlighted putative roles of these genes in SUD. After incorporating these novel genes, the genetic testing yields of the current SUD cohort elevated from 51.9 to 66.7%. Our study expands understanding of the genetic variants underlying SUD and presents insights that improve the utility of genetic screenings.

Efficient immobilization and detoxification of gaseous elemental mercury by nanoflower/rod WSe2/halloysite composite: Performance and mechanisms.

Gaseous mercury pollution control technologies with low stability and high releasing risks always face with great challenges. Herein, we developed one halloysite nanotubes (HNTs)-supported tungsten diselenide (WSe2) composite (WSe2/HNTs) by one-pot solvothermal approach, curing Hg0 from complicated flue gas (CFG) and reducing second environment risks. WSe2 as a monolayer with nano-flower structure and HNTs with rod shapes in the as-prepared sorbent exhibited outstanding synergy efficiency, resulting in exceptional performance for Hg0 removal with high capture capacity of 30.6 mg·g-1 and rate of 9.09 µg·g-1·min-1, which benefited from the high affinity of selenium and mercury (1 ×1045) and the adequate exposure of Se-terminated. The adsorbent showed beneficial tolerance to high amount of NOx and SOx. An online lab-built thermal decomposition system (TPD-AFS) was employed to explore Hg species on the used-sorbent, finding that the adsorbed-mercury species were principally mercury selenide (HgSe). Density functional theory calculations indicated that the hollow-sites were the major adsorption sites and exhibited excellent selectivity for Hg0, as well as HgSe generation needed to overcome the 0.32 eV energy barrier. The adsorbed mercury displayed high environmental stability after the leaching toxicity test, which significantly decreased its secondary environmental risks. With these advantages, WSe2/HNTs possess enormous potential to achieve the effective and permanent immobilization of gaseous mercury from CFG in the future.

Molybdenum(V)-mediated switching of the C(sp2)-Se bond of phenylselenyl-functionalized arenes or heterocycles under mild conditions.

Molybdenum(V)-mediated cleavage of C(sp2)-Se bond and C(sp2)-H bond as well as intramolecular oxidative C(sp2)-Se coupling reaction of phenylselenyl-functionalized arenes or heterocycles has been developed. Three kinds of benzoselenophene frameworks were constructed through this reaction with yields up to 94%. This new C(sp2)-Se bond-switching methodology may provide a new strategy for interesting applications of phenylselenyl-substituted aromatic compounds in the synthesis of selenium-containing heterocycles and natural products.

Decryption analysis of antimony pollution sources in PM2.5 through a multi-source isotope mixing model based on lead isotopes.

Antimony (Sb) in PM2.5 has attracted close attention as a new air pollutant due to its extensive use in daily life. The identification of antimony sources in PM2.5 by scientific methods is important to control its pollution. In this study, the Sb and other elements concentrations and Pb isotopic compositions in PM2.5 and possible pollution sources (soil, road dust, traffic emission, coal-fired fly ash, local factory emission dust and cement dust) were analyzed. The results showed that the Sb in the PM2.5 samples had seasonal change. The enrichment factors of Sb in PM2.5 samples were all above 100 in four seasons, which indicated anthropogenic pollution. The average value of potential ecological risk index was at extremely high-risk level greater than 320. Based on Pearson correlation coefficient and hierarchical cluster analysis results, the pollution sources of antimony and lead in PM2.5 samples were highly consistent which means that Pb isotopes might be a new and feasible tracer for Sb pollution in air. The sources analysis results based on Pb isotopes indicated that the proportion of Pb and Sb from coal-fired fly ash was the highest in winter (47.7%) and inclined to road dust in spring (34.5%), but it was mainly from traffic emissions in summer and autumn (34.2% and 32.8%). This study showed that Pb isotope tracing can be applied to predict the potential pollution sources, and it was also a feasible substitute for tracing Sb pollution in PM2.5.

Facile fabrication of Fe/Zr binary MOFs for arsenic removal in water: High capacity, fast kinetics and good reusability.

A water-stable bimetallic Fe/Zr metal-organic framework [UiO-66(Fe/Zr)] for exceptional decontamination of arsenic in water was fabricated through a facile one-step strategy. The batch adsorption experiments revealed the excellent performances with ultrafast adsorption kinetics due to the synergistic effects of two functional centers and large surface area (498.33 m2/g). The absorption capacity of UiO-66(Fe/Zr) for arsenate [As(V)] and arsenite [As(III)] reached as high as 204.1 mg/g and 101.7 mg/g, respectively. Langmuir model was suitable to describe the adsorption behaviors of arsenic on UiO-66(Fe/Zr). The fast kinetics (adsorption equilibrium in 30 min, 10 mg/L As) and pseudo-second-order model implied the strong chemisorption between arsenic ions and UiO-66(Fe/Zr), which was further confirmed by DFT theoretical calculations. The results of FT-IR, XPS analysis and TCLP test demonstrated that arsenic was immobilized on the surface of UiO-66(Fe/Zr) through Fe/Zr-O-As bonds, and the leaching rates of the adsorbed As(III) and As(V) from the spent adsorbent were only 5.6% and 1.4%, respectively. UiO-66(Fe/Zr) can be regenerated for five cycles without obvious removal efficiency decrease. The original arsenic (1.0 mg/L) in lake and tap water was effectively removed in 2.0 hr [99.0% of As(III) and 99.8% of As(V)]. The bimetallic UiO-66(Fe/Zr) has great potentials in water deep purification of arsenic with fast kinetics and high capacity.

Serum SELENBP1 and VCL Are Effective Biomarkers for Clinical and Forensic Diagnosis of Coronary Artery Spasm.

Coronary artery spasm (CAS) plays an important role in the pathogenesis of many ischemic heart entities; however, there are no established diagnostic biomarkers for CAS in clinical and forensic settings. This present study aimed to identify such serum biomarkers by establishing a rabbit CAS provocation model and integrating quantitative serum proteomics, parallel reaction monitoring/mass spectrometry-based targeted proteomics, and partial least-squares discriminant analysis (PLS-DA). Our results suggested that SELENBP1 and VCL were potential candidate biomarkers for CAS. In independent clinical samples, SELENBP1 and VCL were validated to be significantly lower in serum but not blood cells from CAS patients, with the reasons for this possibly due to the decreased secretion from cardiomyocytes. The areas under the curve of the receiver operating characteristics (ROC) analysis were 0.9384 for SELENBP1 and 0.9180 for VCL when diagnosing CAS. The CAS risk decreased by 32.3% and 53.6% for every 10 unit increases in the serum SELENBP1 and VCL, respectively. In forensic samples, serum SELENBP1 alone diagnosed CAS-induced deaths at a sensitivity of 100.0% and specificity of 72.73%, and its combination with VCL yielded a diagnostic specificity of 100.0%, which was superior to the traditional biomarkers of cTnI and CK-MB. Therefore, serum SELENBP1 and VCL could be effective biomarkers for both the clinical and forensic diagnosis of CAS.

CD47: Beyond an immune checkpoint in cancer treatment.

The transmembrane protein, CD47, is recognized as an important innate immune checkpoint, and CD47-targeted drugs have been in development with the aim of inhibiting the interaction between CD47 and the regulatory glycoprotein SIRPα, for antitumor immunotherapy. Further, CD47 mediates other essential functions such as cell proliferation, caspase-independent cell death (CICD), angiogenesis and other integrin-activation-dependent cell phenotypic responses when bound to thrombospondin-1 (TSP-1) or other ligands. Mounting strategies that target CD47 have been developed in pre-clinical and clinical trials, including antibodies, small molecules, siRNAs, and peptides, and some of them have shown great promise in cancer treatment. Herein, the authors endeavor to provide a retrospective of ligand-mediated CD47 regulatory mechanisms, their roles in controlling antitumor intercellular and intracellular signal transduction, and an overview of CD47-targetd drug design.

Multi-omics analysis unravels dysregulated lysosomal function and lipid metabolism involved in sub-chronic particulate matter-induced pulmonary injury.

Particulate matter (PM) is a huge environmental threat and is of major public concern. Oxidative stress and systemic inflammation are known factors that contribute to PM- related damage; however, a systematic understanding of the deleterious pulmonary effects of PM using multi-omics analysis is lacking. In this study, we performed transcriptomic, proteomic, and metabolomic analyses in a mouse model exposed to PM for three months to identify molecular changes in lung tissues. We identified 1690 genes, 326 proteins, and 67 metabolites exhibiting significant differences between PM-challenged and control mice (p < 0.05). Differentially expressed genes and proteins regulated in PM-challenged mice were involved in lipid metabolism and in the immune and inflammatory response processes. Moreover, a comprehensive analysis of transcript, protein, and metabolite datasets revealed that the genes, proteins, and metabolites in the PM-treated group were involved in lysosomal function and lipid metabolism. Specifically, Cathepsin D (Ctsd), Ferritin light chain (Ftl), Lactotransferrin (Ltf), Lipocalin 2 (Lcn2), and Prosaposin (Psap) were major proteins/genes associated with PM-induced pulmonary damage, while two lipid molecules PC (18:1(11Z)/16:0) and PA (16:0/18:1(11Z)) were major metabolites related to PM-induced pulmonary injury. In summary, lipid metabolism might be used as successful precautions and therapeutic targets in PM-induced pulmonary injury to maintain the stability of cellular lysosomal function.

Non/mini-invasive monitoring of diabetes-induced myocardial damage by Fourier transform infrared spectroscopy: Evidence from biofluids.

Early identification of diabetic cardiomyopathy (DCM) can help clinicians develop targeted treatment plans and forensic pathologists make accurate postmortem diagnoses. In the present study, diabetes-induced metabolic abnormalities in the myocardium and biofluids (plasma, urine, and saliva) of db/db mice of various ages (7, 12, and 21 weeks) were investigated by attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy. The results indicated that the diabetic and control groups had significantly different changes in the function groups of lipids, phosphate macromolecules (mostly nucleic acids), protein compositions and conformations, and carbohydrates (primarily glucose) in the myocardium and biofluids. The prediction model for quantifying DCM severity was developed on db/db mice's myocardial spectra using a genetic algorithm (GA)-partial least squares (PLS) regression method. Following that, the linear correlations between the predicted values for DCM severity and spectra for db/db biofluids were evaluated using the GA-PLS regression algorithm. The results showed there were good linear correlations between the predicted values for DCM severity and spectra for plasma (R2 = 0.929), saliva (R2 = 0.967), urine (R2 = 0.954), and combination of plasma and saliva (R2 = 0.980). This study provides a novel perspective on detecting diabetes-related biofluid and cardiac metabolic abnormalities and demonstrates the potential of biofluid infrared spectro-diagnostic models for non/mini-invasive assessment of DCM.

Investigation of early biochemical alterations in myocardia of the diabetic db/db mice by FTIR microspectroscopy combined with machine learning.

Diabetic cardiomyopathy (DbCM) is a serious complication of diabetes that affects about 12% of the diabetic population. Sensitive detection of diabetes-induced biochemical changes in the heart before symptoms appear can assist clinicians in developing targeted treatment plans and forensic pathologists in making accurate postmortem diagnoses. The Fourier transform infrared (FTIR) spectroscopy-based approach allows for the analysis of the sample biomolecular composition and variations. In the current study, the myocardial tissues of mouse models of type 2 diabetes mellitus (T2DM) at various ages (7, 12, and 21 weeks) were analyzed using FTIR microspectroscopy (FTIRM) in combination with machine learning algorithms. The carbonyl esters, olefinic=CH and CH2 groups of lipids, total lipids, saccharides, and ß-sheet to α-helix conformational transition in proteins increased significantly in diabetic mice myocardial tissues compared to healthy mice. Furthermore, partial least-squares discriminant analysis and random forest-guided partial least-squares discriminant analysis revealed the time-dependent progression of the spectral lipidomic profiles during the development of DbCM. Finally, a random forest classifier was developed for diagnosing DbCM, with 97.1% accuracy. This study demonstrates that FTIRM is a novel method for monitoring early biochemical changes in the myocardia of mice with T2DM.

Post-mortem evaluation of the pathological degree of myocardial infarction by Fourier transform infrared microspectroscopy.

In clinical and forensic investigations, accurate post-mortem diagnosis of the pathological degree of myocardial infarction (MI) is critical. However, because of the observer variability, the diagnosis cannot be made objectively. Many studies have shown that Fourier transform infrared (FTIR) microspectroscopy is non-invasive, observer-independent, and label-free when analyzing biological tissues. In this study, we used FTIR microspectroscopy in combination with intelligent algorithms to identify the pathological phases in human infarcted cardiac tissues, including ischemia, necrotic, granulation, and fibrotic stages. First, a comparison of infrared spectra corresponding to infarcted tissue pathological categories revealed various spectral properties. The results of unsupervised principal component analysis (PCA) revealed a clear distinction between these four pathological stages and the normal stage. Then, to identify these five stages, an automatic artificial neural network (ANN) classifier was effectively created. Finally, two-dimensional pseudo-color images of two infarcted cardiac tissue sections visualized via the ANN classifier showed great agreement with their histological images. These findings demonstrate that FTIR microspectroscopy has the potential for the post-mortem evaluation of the pathological degree of MI.