Influence of hematoxylin and eosin staining on the quantitative analysis of second harmonic generation imaging of fixed tissue sections

In silico, in vitro, and in vivo assessment of chitosan-diltiazem nanoparticles against pulmonary fibrosis

AIMS

Diltiazem (DIL), a calcium channel blocker, has demonstrated potential ininhibiting fibrosis-related processes, including TGF-β activation, collagen production, and epithelial-mesenchymal transition, making it a promising candidate for idiopathic pulmonary fibrosis (IPF). This study evaluates the anti-fibrotic efficacy of DIL-loaded chitosan (DIL-CHT) and trimethyl chitosan (DIL-TMC) nanoparticles through molecular and experimental approaches.

METHODS

DIL-CHT and DIL-TMC nanoformulations were developed and analyzed particle size, ζ-potential, entrapment efficiency, and in vitro release. Antifibrotic efficacy in bleomycin (BLM)-induced IPF rat model, was tested at subtherapeutic doses (3 mg/kg/day, i.t.) and DIL alone (10 mg/kg/day, p.o.). DFT (B3LYP/6-31 G**) optimization and molecular docking were conducted to assess electronic properties and interactions among CHT, TMC, and DIL.

RESULTS

DIL-TMC and DIL-CHT nanoparticles were 175.6 nm and 267.8 nm, with entrapment efficiencies of 81.72% and 66.0%, respectively; TMC showed a superior 24-hour sustained release. TMC's larger HOMO-LUMO gap (ΔE = -0.260 eV vs. -0.253 eV for CHT) suggests greater stability, supporting its enhanced interaction with DIL. TMC nanoparticles significantly reduced BLM-induced IPF symptoms, i.e. BLM induced increased lung index, hydroxyproline accumulation, oxidative stress in lung tissue, and blood pressure.

CONCLUSIONS

These findings indicate the strong therapeutic potential of DIL-TMC for IPF with minimal cardiovascular side effects.

Berberine Intervention Mitigates Myocardial Ischemia-Reperfusion Injury in a Rat Model: Mechanistic Insights via miR-184 Signaling

Background

Ischemia-reperfusion (I/R) injury is a major contributor to myocardial dysfunction and tissue damage. A natural alkaloid-Berberine having a wide range of pharmacological properties, has garnered interest for its potential cardioprotective properties. This study aimed to investigate the protective effects of berberine on myocardial tissue in a rat model of myocardial ischemia-reperfusion (I/R) injury. Additionally, the study explored the role of the miR-184/NOTCH1 signaling pathway in mediating these effects.

Methods

Male Wistar rats were randomly assigned to five groups: sham-operated control, I/R injury, I/R treated with berberine, I/R treated with inhibitor NC and I/R treated with a miR-184 inhibitor. The I/R injury was induced by ligating the left anterior descending (LAD) coronary artery for 30 minutes, followed by 2 hours of reperfusion. Berberine was administered orally at 100 mg/kg/day for 2 weeks, and the miR-184 inhibitor was administered via intraperitoneal injection. Hemodynamic parameters were recorded using a pressure sensor connected to a catheter inserted into the left ventricle. Myocardial infarct size was assessed using TTC staining, while histological and molecular changes were evaluated through H&E staining, TUNEL assay, and Western blotting. The expression levels of target genes were analyzed using quantitative real-time PCR (qRT-PCR).

Results

Berberine significantly reduced myocardial infarct size and improved hemodynamic parameters compared to the untreated I/R group. Additionally, berberine treatment attenuated apoptosis as evidenced by decreased TUNEL-positive cells. The miR-184 inhibitor also demonstrated protective effects by modulating key signaling pathways involved in myocardial injury. Western blot analysis revealed downregulation of NOTCH1 and HES1 expression in treated groups, indicating a potential mechanism for the observed cardio protection.

Conclusion

Berberine and miR-184 inhibition offer significant protection against myocardial ischemia-reperfusion injury. These findings suggest that targeting miR-184 and associated pathways may be a promising therapeutic strategy for reducing cardiac damage following ischemia-reperfusion.

Bambusa vulgaris leaf extract inhibits the inflammatory and oxidative pathways in streptozotocin-induced diabetic rats

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional and medicinal plant treatments for diabetes mellitus (DM) include Bambusa vulgaris (Shrad.), but little is known about the mechanism.

AIM OF THE STUDY

This study investigated the antioxidant and hepatoprotective effects of B. vulgaris.

MATERIALS AND METHODS

DM was induced by intraperitoneal injection of streptozotocin (60 mg/kg). Thirty (30) male Wistar rats were then divided into six groups: control; diabetic control; metformin (100 mg/kg); 50, 100, and 200 mg/kg of B. vulgaris (BV) treated. Fasting blood glucose and weights of rats were monitored at three-day intervals and sacrifice was done after twenty-one days. The activities of SOD, CAT, and liver marker enzymes were investigated. The expressions of insulin-sensitive (TGR5, GLP-1), pro-inflammatory cytokines (TNF-α, IL-1β, IL-6, ICAM), and antioxidant genes (SOD, CAT) were investigated using RT-PCR. Schrödinger suites and Auto-Dock Vina were used for docking B. vulgaris phytocompounds identified from works of literature with TGR-5. The liver's histology was also assessed.

RESULTS

BV increased antioxidant activities and reduced liver marker activities in the serum. BV downregulated the expressions of genes associated with inflammation and upregulated antioxidant and insulin-sensitive genes relative to diabetic control. BV regenerated the liver architectural tissue degenerated by inflammation due to STZ. B. vulgaris phytocompounds like farobin A (-11.493 kcal/mol), orientin (-12.296 kcal/mol), and rutin (-12.581 kcal/mol) have better binding energy with TGR5 than metformin (-1.961 kcal/mol).

CONCLUSION

The hepatoprotective and ameliorative effect of B. vulgaris in DM could be due to its ability to boost antioxidant status and insulin secretion and reduce inflammation.

Broccoli (Brassica oleracea var. italica) leaves exhibit significant antidiabetic potential in alloxan-induced diabetic rats: the putative role of ABC vacuolar transporter for accumulation of Quercetin and Kaempferol

Background

The global prevalence of diabetes among adults over 18 years of age is expected to increase from 10.5% to 12.2% (between 2021 and 2045). Plants can be a cost-effective source of flavonoids like quercetin and kaempferol with anti-diabetic properties.

Methodology

We aimed to assess the antidiabetic potential of leaves of Brassica oleracea cvs. Green Sprout and Marathon. Further, flavonoid contents were measured in broccoli leaves grown under light and dark conditions. The methanolic extracts of Green Sprout (GSL-M) and Marathon (ML-M) were first evaluated in vitro for their α-amylase and α-glucosidase inhibitory potential and then for antidiabetic activity in vivo in alloxan-induced diabetic rat models.

Results

Treatment with plant extracts promoted the reduced glutathione (GSH) content and CAT, POD, and SOD activities in the pancreas, liver, kidney, heart, and brain of diabetic rats, whereas lowered lipid peroxidation, H2O2, and nitrite concentrations. The histopathological studies revealed the protective effect of plant extracts at high dose (300 mg/kg), which could be due to broccoli's rich content of chlorogenic acid, quercetin, and kaempferol. Strikingly, etiolated leaves of broccoli manifested higher levels of quercetin and kaempferol than green ones. The putative role of an ABC transporter in the accumulation of quercetin and kaempferol in etiolated leaves was observed as evaluated by qRT-PCR and in silico analyses.

Conclusion

In conclusion, the present study shows a strong link between the antidiabetic potential of broccoli due to the presence of chlorogenic acid, quercetin, and kaempferol and the role of an ABC transporter in their accumulation within the vacuole.

Interpretable dimensionality reduction and classification of mass spectrometry imaging data in a visceral pain model via non-negative matrix factorization

Mass spectrometry imaging (MSI) is a powerful scientific tool for understanding the spatial distribution of biochemical compounds in tissue structures. In this paper, we introduce three novel approaches in MSI data processing to perform the tasks of data augmentation, feature ranking, and image registration. We use these approaches in conjunction with non-negative matrix factorization (NMF) to resolve two of the biggest challenges in MSI data analysis, namely: 1) the large file sizes and associated computational resource requirements and 2) the complexity of interpreting the very high dimensional raw spectral data. There are many dimensionality reduction techniques that address the first challenge but do not necessarily result in readily interpretable features, leaving the second challenge unaddressed. We demonstrate that NMF is an effective dimensionality reduction algorithm that reduces the size of MSI datasets by three orders of magnitude with limited loss of information, yielding spatial and spectral components with meaningful correlation to tissue structure that may be used directly for subsequent data analysis without the need for additional clustering steps. This analysis is demonstrated on an MSI dataset from female Sprague-Dawley rats for an animal model of comorbid visceral pain hypersensitivity (CPH). We find that high-dimensional MSI data (∼ 100,000 ions per pixel) can be reduced to 20 spectral NMF components with < 20% loss in reconstruction accuracy. The resulting spatial NMF components are reproducible and correlate well with H&E-stained tissue images. These components may also be used to generate images with enhanced specificity for different tissue types. Small patches of NMF data (i.e., 20 spatial NMF components over 20 × 20 pixels) provide an accuracy of ∼ 87% in classifying CPH vs naïve control subjects. This paper presents the novel data processing methodologies that were used to produce these results, encompassing novel data processing pipelines for data augmentation to support training for classification, ranking of features according to their contribution to classification, and image registration to enhance tissue-specific imaging.

Machine learning-based diagnostics of capsular invasion in thyroid nodules with wide-field second harmonic generation microscopy

Papillary thyroid carcinoma (PTC) is one of the most common, well-differentiated carcinomas of the thyroid gland. PTC nodules are often surrounded by a collagen capsule that prevents the spread of cancer cells. However, as the malignant tumor progresses, the integrity of this protective barrier is compromised, and cancer cells invade the surroundings. The detection of capsular invasion is, therefore, crucial for the diagnosis and the choice of treatment and the development of new approaches aimed at the increase of diagnostic performance are of great importance. In the present study, we exploited the wide-field second harmonic generation (SHG) microscopy in combination with texture analysis and unsupervised machine learning (ML) to explore the possibility of quantitative characterization of collagen structure in the capsule and designation of different capsule areas as either intact, disrupted by invasion, or apt to invasion. Two-step k-means clustering showed that the collagen capsules in all analyzed tissue sections were highly heterogeneous and exhibited distinct segments described by characteristic ML parameter sets. The latter allowed a structural interpretation of the collagen fibers at the sites of overt invasion as fragmented and curled fibers with rarely formed distributed networks. Clustering analysis also distinguished areas in the PTC capsule that were not categorized as invasion sites by the initial histopathological analysis but could be recognized as prospective micro-invasions after additional inspection. The characteristic features of suspicious and invasive sites identified by the proposed unsupervised ML approach can become a reliable complement to existing methods for diagnosing encapsulated PTC, increase the reliability of diagnosis, simplify decision making, and prevent human-related diagnostic errors. In addition, the proposed automated ML-based selection of collagen capsule images and exclusion of non-informative regions can greatly accelerate and simplify the development of reliable methods for fully automated ML diagnosis that can be integrated into clinical practice.

Cross-modality sub-image retrieval using contrastive multimodal image representations

In tissue characterization and cancer diagnostics, multimodal imaging has emerged as a powerful technique. Thanks to computational advances, large datasets can be exploited to discover patterns in pathologies and improve diagnosis. However, this requires efficient and scalable image retrieval methods. Cross-modality image retrieval is particularly challenging, since images of similar (or even the same) content captured by different modalities might share few common structures. We propose a new application-independent content-based image retrieval (CBIR) system for reverse (sub-)image search across modalities, which combines deep learning to generate representations (embedding the different modalities in a common space) with robust feature extraction and bag-of-words models for efficient and reliable retrieval. We illustrate its advantages through a replacement study, exploring a number of feature extractors and learned representations, as well as through comparison to recent (cross-modality) CBIR methods. For the task of (sub-)image retrieval on a (publicly available) dataset of brightfield and second harmonic generation microscopy images, the results show that our approach is superior to all tested alternatives. We discuss the shortcomings of the compared methods and observe the importance of equivariance and invariance properties of the learned representations and feature extractors in the CBIR pipeline. Code is available at: https://github.com/MIDA-group/CrossModal_ImgRetrieval .

Histological staining alters circular dichroism SHG measurements of collagen

Circular dichroism second harmonic generation microscopy (CDSHG) is a powerful imaging technique, which allows three-dimensional visualization of collagen fibril orientation in tissues. However, recent publications have obtained contradictory results on whether CDSHG can be used to reveal the relative out-of-plane polarity of collagen fibrils. Here we compare CDSHG images of unstained tendon and tendon which has been stained with hematoxylin and eosin. We find significant differences in the CDSHG between these two conditions, which explain the recent contradictory results within the literature.

Congenital heart diseases (CHDs) and forensic investigations: Searching for the cause of death

Congenital Heart Diseases (CHDs) are a group of structural abnormalities or defects of the heart that are present at birth. CHDs could be connected to sudden death (SD), defined by the WHO (World Health Organization) as "death occurring within 24 h after the onset of the symptoms" in an apparently "healthy" subject. These conditions can range from relatively mild defects to severe, life-threatening anomalies. The prevalence of CHDs varies across populations, but they affect millions of individuals worldwide. This article aims to discuss the post-mortem investigation of death related to CHDs, exploring the forensic approach, current methodologies, challenges, and potential advancements in this challenging field. A further goal of this article is to provide a guide for understanding these complex diseases, highlighting the pivotal role of autopsy, histopathology, and genetic investigations in defining the cause of death, and providing evidence about the translational use of autopsy reports. Forensic investigations play a crucial role in understanding the complexities of CHDs and determining the cause of death accurately. Through collaboration between medical professionals and forensic experts, meticulous examinations, and analysis of evidence, valuable insights can be gained. These insights not only provide closure to the families affected but also contribute to the prevention of future tragedies.

The gut microbiota facilitate their host tolerance to extreme temperatures

BACKGROUND

Exposure to extreme cold or heat temperature is one leading cause of weather-associated mortality and morbidity in animals. Emerging studies demonstrate that the microbiota residing in guts act as an integral factor required to modulate host tolerance to cold or heat exposure, but common and unique patterns of animal-temperature associations between cold and heat have not been simultaneously examined. Therefore, we attempted to investigate the roles of gut microbiota in modulating tolerance to cold or heat exposure in mice.

RESULTS

The results showed that both cold and heat acutely change the body temperature of mice, but mice efficiently maintain their body temperature at conditions of chronic extreme temperatures. Mice adapt to extreme temperatures by adjusting body weight gain, food intake and energy harvest. Fascinatingly, 16 S rRNA sequencing shows that extreme temperatures result in a differential shift in the gut microbiota. Moreover, transplantation of the extreme-temperature microbiota is sufficient to enhance host tolerance to cold and heat, respectively. Metagenomic sequencing shows that the microbiota assists their hosts in resisting extreme temperatures through regulating the host insulin pathway.

CONCLUSIONS

Our findings highlight that the microbiota is a key factor orchestrating the overall energy homeostasis under extreme temperatures, providing an insight into the interaction and coevolution of hosts and gut microbiota.

Advances in cellular and tissue-based imaging techniques for sarcoid granulomas

Sarcoidosis embodies a complex inflammatory disorder spanning multiple systems, with its origin remaining elusive. It manifests as the infiltration of inflammatory cells that coalesce into distinctive noncaseous granulomas within afflicted organs. Unraveling this disease necessitates the utilization of cellular or tissue-based imaging methods to both visualize and characterize the biochemistry of these sarcoid granulomas. Although hematoxylin and eosin stain, standard in routine use alongside cytological stains have found utility in diagnosis within clinical contexts, special stains such as Masson's trichrome, reticulin, methenamine silver, and Ziehl-Neelsen provide additional varied perspectives of sarcoid granuloma imaging. Immunohistochemistry aids in pinpointing specific proteins and gene expressions further characterizing these granulomas. Finally, recent advances in spatial transcriptomics promise to divulge profound insights into their spatial orientation and three-dimensional (3-D) molecular mapping. This review focuses on a range of preexisting imaging methods employed for visualizing sarcoid granulomas at the cellular level while also exploring the potential of the latest cutting-edge approaches like spatial transcriptomics and matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI), with the overarching goal of shedding light on the trajectory of sarcoidosis research.

Evaluation of antibody-based single cell type imaging techniques coupled to multiplexed imaging of N-glycans and collagen peptides by matrix-assisted laser desorption/ionization mass spectrometry imaging

The integration of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) with single cell spatial omics methods allows for a comprehensive investigation of single cell spatial information and matrisomal N-glycan and extracellular matrix protein imaging. Here, the performance of the antibody-directed single cell workflows coupled with MALDI-MSI are evaluated. Miralys™ photocleavable mass-tagged antibody probes (MALDI-IHC, AmberGen, Inc.), GeoMx DSP® (NanoString, Inc.), and Imaging Mass Cytometry (IMC, Standard BioTools Inc.) were used in series with MALDI-MSI of N-glycans and extracellular matrix peptides on formalin-fixed paraffin-embedded tissues. Single cell omics protocols were performed before and after MALDI-MSI. The data suggests that for each modality combination, there is an optimal order for performing both techniques on the same tissue section. An overall conclusion is that MALDI-MSI studies may be completed on the same tissue section as used for antibody-directed single cell modalities. This work increases access to combined cellular and extracellular information within the tissue microenvironment to enhance research on the pathological origins of disease.

Super-resolution re-scan second harmonic generation microscopy

Second harmonic generation microscopy (SHG) is generally acknowledged as a powerful tool for the label-free three-dimensional visualization of tissues and advanced materials, with one of its most popular applications being collagen imaging. Despite the great need, progress in super-resolved SHG imaging lags behind the developments reported over the past years in fluorescence-based optical nanoscopy. In this work, we demonstrate super-resolved re-scan SHG, qualitatively and quantitatively showing on collagenous tissues the available resolution advantage over the diffraction limit. We introduce as well super-resolved re-scan two-photon excited fluorescence microscopy, an imaging modality not explored to date.

PSHG-TISS: A collection of polarization-resolved second harmonic generation microscopy images of fixed tissues

Second harmonic generation (SHG) microscopy is acknowledged as an established imaging technique capable to provide information on the collagen architecture in tissues that is highly valuable for the diagnostics of various pathologies. The polarization-resolved extension of SHG (PSHG) microscopy, together with associated image processing methods, retrieves extensive image sets under different input polarization settings, which are not fully exploited in clinical settings. To facilitate this, we introduce PSHG-TISS, a collection of PSHG images, accompanied by additional computationally generated images which can be used to complement the subjective qualitative analysis of SHG images. These latter have been calculated using the single-axis molecule model for collagen and provide 2D representations of different specific PSHG parameters known to account for the collagen structure and distribution. PSHG-TISS can aid refining existing PSHG image analysis methods, while also supporting the development of novel image processing and analysis methods capable to extract meaningful quantitative data from the raw PSHG image sets. PSHG-TISS can facilitate the breadth and widespread of PSHG applications in tissue analysis and diagnostics.

Measurement(s)	Type I Collagen
Technology Type(s)	multi-photon laser scanning microscopy
Factor Type(s)	second order susceptibility tensor elements
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Environment	laboratory environment
Sample Characteristic - Location	Romania

Assessment of Ultra-Early-Stage Liver Fibrosis in Human Non-Alcoholic Fatty Liver Disease by Second-Harmonic Generation Microscopy

Non-alcoholic fatty liver disease (NAFLD) is associated with the chronic progression of fibrosis. In general, the progression of liver fibrosis is determined by a histopathological assessment with a collagen-stained section; however, the ultra-early stage of liver fibrosis is challenging to identify because of the low sensitivity in the collagen-selective staining method. In the present study, we demonstrate the feasibility of second-harmonic generation (SHG) microscopy in the histopathological diagnosis of the liver of NAFLD patients for the quantitative assessment of the ultra-early stage of fibrosis. We investigated four representative NAFLD patients with early stages of fibrosis. SHG microscopy visualised well-matured fibrotic structures and early fibrosis diffusely involving liver tissues, whereas early fibrosis is challenging to be identified by conventional histopathological methods. Furthermore, the SHG emission directionality analysis revealed the maturation of each collagen fibre of each patient. As a result, SHG microscopy is feasible for assessing liver fibrosis on NAFLD patients, including the ultra-early stage of liver fibrosis that is difficult to diagnose by the conventional histopathological method. The assessment method of the ultra-early fibrosis by using SHG microscopy may serve as a crucial means for pathological, clinical, and prognostic diagnosis of NAFLD patients.

Second-Harmonic Generation Imaging Reveals Changes in Breast Tumor Collagen Induced by Neoadjuvant Chemotherapy

Breast cancer is the most common invasive cancer in women, with most deaths attributed to metastases. Neoadjuvant chemotherapy (NACT) may be prescribed prior to surgical removal of the tumor for subsets of breast cancer patients but can have diverse undesired and off-target effects, including the increased appearance of the 'tumor microenvironment of metastasis', image-based multicellular signatures that are prognostic of breast tumor metastasis. To assess whether NACT can induce changes in two other image-based prognostic/predictive signatures derived from tumor collagen, we quantified second-harmonic generation (SHG) directionality and fiber alignment in formalin-fixed, paraffin-embedded sections of core needle biopsies and primary tumor excisions from 22 human epidermal growth factor receptor 2-overexpressing (HER2+) and 22 triple-negative breast cancers. In both subtypes, we found that SHG directionality (i.e., the forward-to-backward scattering ratio, or F/B) is increased by NACT in the bulk of the tumor, but not the adjacent tumor-stroma interface. Overall collagen fiber alignment is increased by NACT in triple-negative but not HER2+ breast tumors. These results suggest that NACT impacts the collagenous extracellular matrix in a complex and subtype-specific manner, with some prognostic features being unchanged while others are altered in a manner suggestive of a more metastatic phenotype.