Structured illumination microscopy for cancer identification in diagnostic breast biopsies.

Breast cancer is the second most common cancer diagnosed in women in the US with almost 280,000 new cases anticipated in 2023. Currently, on-site pathology for location guidance is not available during the collection of breast biopsies or during surgical intervention procedures. This shortcoming contributes to repeat biopsy and re-excision procedures, increasing the cost and patient discomfort during the cancer management process. Both procedures could benefit from on-site feedback, but current clinical on-site evaluation techniques are not commonly used on breast tissue because they are destructive and inaccurate. Ex-vivo microscopy is an emerging field aimed at creating histology-analogous images from non- or minimally-processed tissues, and is a promising tool for addressing this pain point in clinical cancer management. We investigated the ability structured illumination microscopy (SIM) to generate images from freshly-obtained breast tissues for structure identification and cancer identification at a speed compatible with potential on-site clinical implementation. We imaged 47 biopsies from patients undergoing a guided breast biopsy procedure using a customized SIM system and a dual-color fluorescent hematoxylin & eosin (H&E) analog. These biopsies had an average size of 0.92 cm2 (minimum 0.1, maximum 4.2) and had an average imaging time of 7:29 (minimum 0:22, maximum 37:44). After imaging, breast biopsies were submitted for standard histopathological processing and review. A board-certified pathologist returned a binary diagnostic accuracy of 96% when compared to diagnoses from gold-standard histology slides, and key tissue features including stroma, vessels, ducts, and lobules were identified from the resulting images.

From ultrasound to microscopy: Actualities in thyroid investigation in cattle.

Thyroid ultrasonography examination is widely used in human and small animal medicine. However, it has rarely been applied in cattle. The aim of this study was to determine whether the measurements of the thyroid gland by ultrasound examination correlate to those taken during post-mortem examination. A sample of 22 cows and 23 calves was selected for thyroid gland evaluation. An ultrasound scan was performed ante-mortem, followed by euthanasia (for medical reasons) or slaughtered in the food chain and the dissection of the thyroid gland was therefore performed. Post-mortem, the gland was weighed and its dimensions and volume measured. The volume and weight measurements were compared with the predicted ones on US using the formulas available in the literature. Finally, histological examination was performed on thyroid glands. The dimensions of the thyroid gland measured by ultrasonography were significantly different (p<0.05) from those observed post-mortem, except for lobe lengths in calves (p>0.1). However, in calves, there was no systematic bias between the ultrasound and post-mortem examination of the thyroid gland, which were concordant (with an average error of 18%). Cystic lesions were observed on ultrasound in 9/22 cows and could be found on histological examination in 7 of these. Other lesions, such as follicular hypoplasia and hyperplasia, were seen on histological examination but not on ultrasound. Although the ultrasound measurements did not significantly correlate with those taken post-mortem, this examination may allow to differentiate non-standard thyroids in the case of hyperplastic goiter, as demonstrated in other species. This study also describes and illustrates interesting lesions of the thyroid gland in cattle. These findings are innovative in the description of the use of thyroid ultrasound in cattle, although further studies are needed to allow deeper conclusions.

Non-telecentric photoacoustic microscopy for multi-scale imaging.

Optical-resolution photoacoustic microscopy (OR-PAM) excels in precisely imaging a biological tissue based on absorption contrast. However, existing OR-PAMs are confined by fixed compromises between spatial resolution and field of view (FOV), preventing the integration of large FOV and local high-resolution within one system. Here, we present a non-telecentric OR-PAM (nTC-PAM) that empowers efficient adaptation of FOV and spatial resolution to match the multi-scale requirement of diverse biological imaging. Our method allows for a large-scale transformation in FOV and even surpassing the nominal FOV of the objective with minimal marginal degradation of the lateral resolution. We demonstrate the advantage of nTC-PAM through multi-scale imaging of the leaf phantom, mouse ear, and cortex. The results reveal that nTC-PAM can switch the FOV and spatial resolution to meet the requirements of different biological tissues, such as large-scale imaging of the whole cerebral cortex and high-resolution imaging of microvascular structures in local brain regions.

Simultaneous deep ultraviolet transmission and scattering microscopy for virtual histology.

In recent years, the emergence of a variety of novel optical microscopy techniques has enabled the generation of virtual optical stains of unlabeled tissue specimens, which have the potential to transform existing clinical histopathology workflows. In this work, we present a simultaneous deep ultraviolet transmission and scattering microscopy system that can produce virtual histology images that show concordance to conventional gold-standard histological processing techniques. The results of this work demonstrate the system's diagnostic potential for characterizing unlabeled thin tissue sections and streamlining histological workflows.

Comparison of malaria diagnostic methods for detection of asymptomatic Plasmodium infections among pregnant women in northwest Ethiopia.

BACKGROUND: Malaria in pregnancy remains a major public health problem in the globe, especially in sub-Saharan Africa. In malaria endemic areas, most pregnant women remain asymptomatic, but malaria could still cause complications on the mother and her offspring; as well as serve as reservoirs to transmit infection. Despite these effects, no attention is given to the diagnosis of asymptomatic Plasmodium infections (APIs) using highly sensitive and specific laboratory diagnostic tools in Ethiopia. Therefore, the goal of this study was to compare the performance of Rapid Diagnostic Test (RDT), microscopy and real-time polymerase chain reaction (RT-PCR) to detect APIs among pregnant women. METHODS: A health facility based cross -sectional study was conducted among pregnant women attending antenatal care at Fendeka town health facilities Jawi district, northwest Ethiopia from February to March, 2019. A total of 166 participants were enrolled by using convenient sampling technique. Socio-demographic features were collected using a semi structured questionnaire. Dried blood spot (DBS) samples were collected for molecular analysis. Asymptomatic Plasmodium infection on pregnant women was diagnosed using RDT, microscopy and RT-PCR. Descriptive statistics were used to determine the prevalence of APIs. Method comparison was performed, and Cohen's kappa coefficient (k) was used to determine the degree of agreement among the diagnostic methods. Parasite densities were also calculated. RESULTS: The prevalence of API was 9.6%, 11.4% and 18.7% using RDT, microscopy and RT-PCR, respectively. The overall proportion of API was 19.3%. Sensitivity of the RDT was 83.3% as compared with microscopy. Rapid Diagnostic Test and microscopy also showed sensitivity of 50% and 60%, respectively, as compared with RT-PCR. The mean parasite density was 3213 parasites/µl for P falciparum and 1140 parasites/µl of blood for P. vivax. CONCLUSION: Prevalence of API in the study area was high. Both RDT and microscopy had lower sensitivity when compared with RT-PCR. Therefore, routine laboratory diagnosis of API among pregnant women should be given attention and done with better sensitive and specific laboratory diagnostic tools.

Comparative evaluation of the diagnostic accuracies of four different malaria rapid diagnostic test kits available in Ghana.

Malaria rapid diagnostic test (mRDT) kit is one of the techniques for diagnosing malaria. Due to its inherent advantages over the microscopy technique, several brands of the kit have flooded malaria endemic countries, without prior in-country evaluation. Two of such mRDT kits are Oscar (India) and Standard Q (Korea Republic). In this study, the performance of Oscar and Standard Q mRDT kits were compared to First Response (India) and CareStart (USA) mRDTs, which have been evaluated and deployed for use approved by the Ministry of Health (MOH). In this comparative study, whole blood samples were collected from patients suspected of malaria. Plasmodium falciparum was detected in each sample using nested polymerase chain reaction (nPCR), microscopy and the four mRDTs. The sensitivities, specificities, accuracies, positive and negative predictive values and accuracies of the mRDTs were determined using nPCR as a reference technique. Kappa statistic was used to determine the level of agreement among the techniques. Two hundred (200) blood samples were analyzed in this study. The overall detection rates of P. falciparum by microscopy, First Response, CareStart, Oscar-PfHRP2, Standard Q mRDT kits and nPCR were 31.5%, 34.5%, 33.5%, 32%, 31% and 43% (x2 = 6.1, p = 0.046), respectively. The accuracies of CareStart and First Response were comparable (90.5% vs. 89.5%). Further, comparing their sensitivities, Oscar-PfHRP2 was 74.4% (95% confidence interval (CI): 63.9-83.2) while that of Standard Q was 72.1% (95% CI: 61.4-81.2), with comparable accuracies (Oscar-PfHRP2-89% and Standard Q -88%). Apart from First Response that was 98.3% specific, the others were 100% specific. Kappa test revealed perfect diagnostic agreement (κ = 0.90-0.98) among the four mRDTs. That notwithstanding, Oscar-PfHRP2 agreed better with CareStart (κ = 0.94) and First Response (κ = 0.92) compared to the agreement between Standard Q and, CareStart (κ = 0.92) and First Response (κ = 0.90). Taken together, the diagnostic performance of the four mRDT kits were statistically similar. That notwithstanding, new mRDT kits should be evaluated prior to deployment for use.

Hyperspectral dark-field microscopy of human breast lumpectomy samples for tumor margin detection in breast-conserving surgery.

Significance: Hyperspectral dark-field microscopy (HSDFM) and data cube analysis algorithms demonstrate successful detection and classification of various tissue types, including carcinoma regions in human post-lumpectomy breast tissues excised during breast-conserving surgeries. Aim: We expand the application of HSDFM to the classification of tissue types and tumor subtypes in pre-histopathology human breast lumpectomy samples. Approach: Breast tissues excised during breast-conserving surgeries were imaged by the HSDFM and analyzed. The performance of the HSDFM is evaluated by comparing the backscattering intensity spectra of polystyrene microbead solutions with the Monte Carlo simulation of the experimental data. For classification algorithms, two analysis approaches, a supervised technique based on the spectral angle mapper (SAM) algorithm and an unsupervised technique based on the K-means algorithm are applied to classify various tissue types including carcinoma subtypes. In the supervised technique, the SAM algorithm with manually extracted endmembers guided by H&E annotations is used as reference spectra, allowing for segmentation maps with classified tissue types including carcinoma subtypes. Results: The manually extracted endmembers of known tissue types and their corresponding threshold spectral correlation angles for classification make a good reference library that validates endmembers computed by the unsupervised K-means algorithm. The unsupervised K-means algorithm, with no a priori information, produces abundance maps with dominant endmembers of various tissue types, including carcinoma subtypes of invasive ductal carcinoma and invasive mucinous carcinoma. The two carcinomas' unique endmembers produced by the two methods agree with each other within <2% residual error margin. Conclusions: Our report demonstrates a robust procedure for the validation of an unsupervised algorithm with the essential set of parameters based on the ground truth, histopathological information. We have demonstrated that a trained library of the histopathology-guided endmembers and associated threshold spectral correlation angles computed against well-defined reference data cubes serve such parameters. Two classification algorithms, supervised and unsupervised algorithms, are employed to identify regions with carcinoma subtypes of invasive ductal carcinoma and invasive mucinous carcinoma present in the tissues. The two carcinomas' unique endmembers used by the two methods agree to <2% residual error margin. This library of high quality and collected under an environment with no ambient background may be instrumental to develop or validate more advanced unsupervised data cube analysis algorithms, such as effective neural networks for efficient subtype classification.

Visualization of intracellular ice formation and growth in mouse oocytes.

BACKGROUND: Characterization of intracellular ice formation (IIF) in oocytes during the freezing and thawing processes will contribute to optimizing their cryopreservation. However, the observation of the ice formation process in oocytes is limited by the spatiotemporal resolution of the cryomicroscope systems. OBJECTIVE: To observe the intracellular icing of oocytes during cooling and rewarming, and to study the mechanism of formation and growth of intracellular ice in oocytes. MATERIALS AND METHODS: Mouse oocytes were frozen at different cooling rates to induce intracellular ice formation using a cryomicroscopy system consisting of a microscope equipped with a cryogenic cold stage, an automatic cooling system, a temperature control system, and a high-speed camera. The growth patterns of intracellular ice in oocytes were analyzed from the images recorded. Finally, the growth rate of intracellular ice formation in oocytes was calculated using an automatic intracellular ice tracking method. RESULTS: The IIF temperature decreased gradually with the increase in cooling rate. Initiation sites of IIF could be classified into three categories: marginal type, internal type and coexisting type. There was a strong predominance for ice crystal initiation site in the oocytes, with up to 80% of the initiation sites located in the marginal region. The intracellular ice growth modes of darkening and twitching cells were characterized by "spreading" and "clustering", respectively. In addition, twitching cells started to recrystallize during rewarming, while darkening cells did not. The instantaneous maximal growth rate of ice crystals in twitching cells was about 10 times higher than that in darkening cells. CONCLUSION: By visualising the growth of ice crystals in mouse oocytes during cooling and rewarming, we obtained valuable information on the kinetics of ice formation and melting in these cells. This information can help us understand how ice formation and melting affect the viability and quality of oocytes after cryopreservation. Doi.org/10.54680/fr24310110412.

Using Dimensionality Reduction to Visualize Phenotypic Changes in High-Throughput Microscopy.

High-throughput microscopy has enabled screening of cell phenotypes at unprecedented scale. Systematic identification of cell phenotype changes (such as cell morphology and protein localization changes) is a major analysis goal. Because cell phenotypes are high-dimensional, unbiased approaches to detect and visualize the changes in phenotypes are still needed. Here, we suggest that changes in cellular phenotype can be visualized in reduced dimensionality representations of the image feature space. We describe a freely available analysis pipeline to visualize changes in protein localization in feature spaces obtained from deep learning. As an example, we use the pipeline to identify changes in subcellular localization after the yeast GFP collection was treated with hydroxyurea.

Art under the Microscope.

In March 2018, Greece issued five commemorative stamps that show a beautiful mélange of art and science. Images are, however, genuine views captured through light microscopy of stained human tissue during histopathological examination. Many will remember having drawn such diagrams in their histology and pathology journals during their medical school years. The microscopic images are photographed beautifully by Dr Maria Lambropaulou. She is an Associate Professor of Histology-embryology at the Medical Department of the Democritus University of Thrace, Greece.

Laser speckle rheological microscopy reveals wideband viscoelastic spectra of biological tissues.

Viscoelastic transformation of tissue drives aberrant cellular functions and is an early biomarker of disease pathogenesis. Tissues scale a range of viscoelastic moduli, from biofluids to bone. Moreover, viscoelastic behavior is governed by the frequency at which tissue is probed, yielding distinct viscous and elastic responses modulated over a wide frequency band. Existing tools do not quantify wideband viscoelastic spectra in tissues, leaving a vast knowledge gap. We present wideband laser speckle rheological microscopy (WB-SHEAR) that reveals elastic and viscous response over sub-megahertz frequencies previously not investigated in tissue. WB-SHEAR uses an optical, noncontact approach to quantify wideband viscoelastic spectra in specimens spanning a range of moduli from low-viscosity fibrin to highly elastic bone. Via laser scanning, micromechanical imaging is enabled to access wideband viscoelastic spectra in heterogeneous tumor specimens with high spatial resolution (25 micrometers). The ability to interrogate the viscoelastic landscape of diverse biospecimens could transform our understanding of mechanobiological processes in various diseases.

Molecular tools are crucial for malaria elimination.

The eradication of Plasmodium parasites, responsible for malaria, is a daunting global public health task. It requires a comprehensive approach that addresses symptomatic, asymptomatic, and submicroscopic cases. Overcoming this challenge relies on harnessing the power of molecular diagnostic tools, as traditional methods like microscopy and rapid diagnostic tests fall short in detecting low parasitaemia, contributing to the persistence of malaria transmission. By precisely identifying patients of all types and effectively characterizing malaria parasites, molecular tools may emerge as indispensable allies in the pursuit of malaria elimination. Furthermore, molecular tools can also provide valuable insights into parasite diversity, drug resistance patterns, and transmission dynamics, aiding in the implementation of targeted interventions and surveillance strategies. In this review, we explore the significance of molecular tools in the pursuit of malaria elimination, shedding light on their key contributions and potential impact on public health.

Two cases with discrepancy in the quantitative cytological assessment of cerebrospinal fluid in neonatal samples using light microscopy in comparison with Sysmex XN-1000.

We present two cases from the neonatal department with cerebrospinal fluid examination. We revealed a striking discrepancy in polymorphonuclear (PMN) and mononuclear (MN) cell counts using conventional light microscopy in comparison with automated analyzer Sysmex XN-1000 (PMNs - 13 vs. 173x106/L, MNs - 200 vs. 67x106/L in case 1 and PMNs - 13 vs. 372x106/L, MNs - 411 vs. 179x106/L in case 2). We revealed the dominant presence of hemosiderophages in both cases in cytospin slide. Even though Sysmex XN-1000 offers fast examination with a low sample volume, there is possibility of misdiagnosis, with negative impact on the patient.

Dilated Heterogeneous Convolution for Cell Detection and Segmentation Based on Mask R-CNN.

Owing to the variable shapes, large size difference, uneven grayscale, and dense distribution among biological cells in an image, it is very difficult to accurately detect and segment cells. Especially, it is a serious challenge for some microscope imaging devices with limited resources owing to a large number of learning parameters and computational burden when using the standard Mask R-CNN. In this work, we propose a mask R-DHCNN for cell detection and segmentation. More specifically, Dilation Heterogeneous Convolution (DHConv) is proposed by designing a novel convolutional kernel structure (i.e., DHConv), which integrates the strengths of the heterogeneous kernel structure and dilated convolution. Then, the traditional homogeneous convolution structure of the standard Mask R-CNN is replaced with the proposed DHConv module to it adapt to shape and size differences encountered in cell detection and segmentation tasks. Finally, a series of comparison and ablation experiments are conducted on various biological cell datasets (such as U373, GoTW1, SIM+, and T24) to verify the effectiveness of the proposed method. The results show that the proposed method can obtain better performance than some state-of-the-art methods in multiple metrics (including AP, Precision, Recall, Dice, and PQ) while maintaining competitive FLOPs and FPS.

Label-Free Techniques for Probing Biomolecular Condensates.

Biomolecular condensates play important roles in a wide array of fundamental biological processes, such as cellular compartmentalization, cellular regulation, and other biochemical reactions. Since their discovery and first observations, an extensive and expansive library of tools has been developed to investigate various aspects and properties, encompassing structural and compositional information, material properties, and their evolution throughout the life cycle from formation to eventual dissolution. This Review presents an overview of the expanded set of tools and methods that researchers use to probe the properties of biomolecular condensates across diverse scales of length, concentration, stiffness, and time. In particular, we review recent years' exciting development of label-free techniques and methodologies. We broadly organize the set of tools into 3 categories: (1) imaging-based techniques, such as transmitted-light microscopy (TLM) and Brillouin microscopy (BM), (2) force spectroscopy techniques, such as atomic force microscopy (AFM) and the optical tweezer (OT), and (3) microfluidic platforms and emerging technologies. We point out the tools' key opportunities, challenges, and future perspectives and analyze their correlative potential as well as compatibility with other techniques. Additionally, we review emerging techniques, namely, differential dynamic microscopy (DDM) and interferometric scattering microscopy (iSCAT), that have huge potential for future applications in studying biomolecular condensates. Finally, we highlight how some of these techniques can be translated for diagnostics and therapy purposes. We hope this Review serves as a useful guide for new researchers in this field and aids in advancing the development of new biophysical tools to study biomolecular condensates.

[Preliminary Study on the Identification of Aerobic Vaginitis by Artificial Intelligence Analysis System]. / 人工智能分析系统对需氧菌性阴道炎的判读方法初探.

Objective: To develop an artificial intelligence vaginal secretion analysis system based on deep learning and to evaluate the accuracy of automated microscopy in the clinical diagnosis of aerobic vaginitis (AV). Methods: In this study, the vaginal secretion samples of 3769 patients receiving treatment at the Department of Obstetrics and Gynecology, West China Second Hospital, Sichuan University between January 2020 and December 2021 were selected. Using the results of manual microscopy as the control, we developed the linear kernel SVM algorithm, an artificial intelligence (AI) automated analysis software, with Python Scikit-learn script. The AI automated analysis software could identify leucocytes with toxic appearance and parabasal epitheliocytes (PBC). The bacterial grading parameters were reset using standard strains of lactobacillus and AV common isolates. The receiver operating characteristic (ROC) curve analysis was used to determine the cut-off value of AV evaluation results for different scoring items were obtained by using the results of manual microscopy as the control. Then, the parameters of automatic AV identification were determined and the automatic AV analysis scoring method was initially established. Results: A total of 3769 vaginal secretion samples were collected. The AI automated analysis system incorporated five parameters and each parameter incorporated three severity scoring levels. We selected 1.5 µm as the cut-off value for the diameter between Lactobacillus and common AV bacterial isolates. The automated identification parameter of Lactobacillus was the ratio of bacteria ≥1.5 µm to those <1.5 µm. The cut-off scores were 2.5 and 0.5, In the parameter of white blood cells (WBC), the cut-off value of the absolute number of WBC was 103 µL－1 and the cut-off value of WBC-to-epithelial cell ratio was 10. The automated identification parameter of toxic WBC was the ratio of toxic WBC toWBC and the cut-off values were 1% and 15%. The parameter of background flora was bacteria<1.5 µm and the cut-off values were 5×103 µL－1 and 3×104 µL－1. The parameter of the parabasal epitheliocytes was the ratio of PBC to epithelial cells and the cut-off values were 1% and 10%. The agreement rate between the results of automated microscopy and those of manual microscopy was 92.5%. Out of 200 samples, automated microscopy and manual microscopy produced consistent scores for 185 samples, while the results for 15 samples were inconsistent. Conclusion: We developed an AI recognition software for AV and established an automated vaginal secretion microscopy scoring system for AV. There was good overall concordance between automated microscopy and manual microscopy. The AI identification software for AV can complete clinical lab examination with rather high objectivity, sensitivity, and efficiency, markedly reducing the workload of manual microscopy.

Speckle Variance Photoacoustic Microscopy for Microhemodynamic Imaging.

Relying on the strong optical absorption of hemoglobin to pulsed laser energy, photoacoustic microscopy provides morphological and functional information on microvasculature label-freely. Here, we propose speckle variance photoacoustic microscopy (SV-PAM), which harnesses intrinsic imaging contrast from temporal-varied photoacoustic signals of moving red blood cells in blood vessels, for recovering three-dimension hemodynamic images down to capillary-level resolution within the microcirculatory tissue beds in vivo. Calculating the speckle variance of consecutive photoacoustic B-scan frames acquired at the same lateral position enables accurate identification of blood perfusion and occlusion, which provides interpretations of dynamic blood flow in the microvasculature, in addition to the microvascular anatomic structures. We demonstrate high-resolution hemodynamic imaging of vascular occlusion and reperfusion in the microvasculature of mice ears in vivo. The results suggest that our SV-PAM is potentially invaluable for biomedical hemodynamic investigations, for example, imaging ischemic stroke and hemorrhagic stroke.

Plasmonic Imaging of Single DNA with Charge Sensitive Monolayer WS2.

Imaging the surface charge of biomolecules such as proteins and DNA, is crucial for comprehending their structure and function. Unfortunately, current methods for label-free, sensitive, and rapid imaging of the surface charge of single DNA molecules are limited. Here, we propose a plasmonic microscopy strategy that utilizes charge-sensitive single-crystal monolayer WS2 materials to image the local charge density of a single λ-DNA molecule. Our study reveals that WS2 is a highly sensitive charge-sensitive material that can accurately measure the local charge density of λ-DNA with high spatial resolution and sensitivity. The consistency of the surface charge density values obtained from the single-crystal monolayer WS2 materials with theoretical simulations demonstrates the reliability of our approach. Our findings suggest that this class of materials has significant implications for the development of label-free, scanning-free, and rapid optical detection and charge imaging of biomolecules.