UNASSIGNED: 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.
UNASSIGNED: We expand the application of HSDFM to the classification of tissue types and tumor subtypes in pre-histopathology human breast lumpectomy samples.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.

The diagnosis of Lyme disease is becoming more common in Turkey. Nonetheless, some physicians are not aware of the diagnostic principles that should be followed when faced with a suspected patient and could use tests that are not recommended, such as darkfield microscopy. Dark field microscopy is a diagnostic technique to visualize the spirochetes that cause Lyme disease; however, it is not recommended for the diagnosis of Lyme disease. One of the main limitations of dark field microscopy is its low sensitivity. Another limitation is its high false-positivity rate, as other microorganisms and cellular debris can be mistaken for spirochetes, leading to a misdiagnosis thatmay result in unnecessary treatment. Therefore, this study aimed to review the literature on the role of dark field microscopy as a diagnostic method for Lyme disease and inform physicians about recommended approaches in line with the recommendations of national or international guidelines. An electronic search of Pubmed, Scopus, and Web of Science was performed using the following medical subject headings (MeSH) search terms: Lyme borreliosis, Lyme disease, Borrelia burgdorferi, diagnosis, and microscopy. With this narrative review, we aimed to inform physicians better and improve patient care for patients with suspected Lyme disease.

A novel approach for ultrasensitive ochratoxin A (OTA) detection is reported based on dark field microscope-based single nanoparticle identification coupled with a statistical analysis method. OTA aptamers were firstly hybridized with a single-stranded DNA (DNA1) to form an identification probe (DNA1-Apt). The aptamers separate from DNA1 in the presence of OTA and are released from the identification probe. Then, another single-stranded DNA (DNA2) hybridizes with DNA1 and result in the aggregation of gold nanoparticles (AuNPs). Therefore, the presence of AuNP aggregates is the evidence of the presence of OTA, while AuNP aggregates can be easily identified together with the monomers under dark field microscopic inspection. On the other hand, by counting the aggregation rate (the number of AuNP aggregates versus the number of AuNP monomers) with a statistical analysis method, OTA could be quantitatively detected. The detection range for OTA was 0.1 pg/mL ~ 30 ng/mL and the limit of detection was 0.1 pg/mL. The proposed sensor has comparative detection performance to sensors utilizing a number of signal amplification procedures, with the additional advantages of simplicity and high efficiency. The sensor can also be adopted for other target detection simply by replacing the identification probes. Graphical abstract The schematic of the AuNP aggregation for OTA detection. The OTA aptamers were competitively banded by OTA and induced form AuNP aggregation after adding DNA2 and AuNPs2. Subsequently, AuNPs were detected under dark field microscope and statistical analysis.

T4 polynucleotide kinase (T4 PNK) plays an essential role in DNA phosphorylation during the DNA repair process. Therefore, the sensitive, selective and convenient detection of T4 PNK activity is of great significance. In this work, we proposed a sensitive non-amplification strategy for the sensing of T4 PNK activity via dark field microscope (DFM) based on magnetic bead (MB)-gold nanoparticle (AuNP) hybrids probe, MB-dsDNA-AuNP (MDA). In the presence of T4 PNK, the 5\'-OH termini of DNA are phosphorylated and cleaved into oligonucleotides by lambda exonuclease (λexo), resulting in the destruction of the MDA probe and the separation of AuNP from the MB. Through automatic counting of AuNPs from DFM images, T4 PNK activity can be quantitatively measured. This strategy revealed a limit of detection (LOD) as low as 0.0058 U/mL and exhibited a dynamic range from 0.01 to 1 U/mL. The strategy presents an excellent ability to discriminate T4 PNK from the other proteins and enzymes. Notably, this strategy was applied to screen the T4 PNK inhibitors and test the activity in cell lysates, showing great potential for the discovery of new anticancer drugs and other related research field.

Development of sensitive methods for the determination of E. coli bacteria contamination in water distribution systems is of paramount importance to ensure the microbial safety of drinking water. This work presents a new sensing platform enabling the fast detection of bacteria in field samples by using specific antibodies as the biorecognition element and dark field microscopy as the detection technique. The development of the sensing platform was performed using non-pathogenic bacteria, with the E. coli DH5α strain as the target, and Bacillus sp. 9727 as the negative control. The identification of the captured bacteria was made by analyzing the dark field microscopy images and screening the detected objects by using object circularity and size parameters. Specificity tests revealed the low unspecific attachment of either E. coli over human serum albumin antibodies (negative control for antibody specificity) and of Bacillus sp. over E. coli antibodies. The system performance was tested using field samples, collected from a wastewater treatment plant, and compared with two quantification techniques (i.e., Colilert-18 test and quantitative polymerase chain reaction (qPCR)). The results showed comparable quantification capability. Nevertheless, the present method has the advantage of being faster, is easily adaptable to in-field analysis, and can potentially be extended to the detection of other bacterial strains.

Septic acute kidney injury (AKI) is the most common complication of septic shock and increases mortality. A large body of experimental data suggests alterations in renal perfusion occur, but this is yet to be fully assessed in humans. The aim of the current study is to observe the macro and microcirculations in both the systemic and renal circulations in a cohort of patients with early septic shock.
Single-centre, prospective, longitudinal, observational study of 50 patients with septic shock. Renal microcirculatory assessment will be performed with contrast-enhanced ultrasound, the sublingual microcirculation assessed with incident dark field microscopy and transthoracic echocardiography used to assess global flow. Patients will be enrolled as soon as possible after admission to the intensive care unit and then at +24,+48 and +96 hours. Blood samples of circulatory and renal biomarkers will be collected. Sample groups will be defined by the presence or absence of AKI and then subclassified by the severity (Kidney Disease Improving Global Outcomes (KDIGO) criteria), variables will be compared within and between groups over time.
Research Ethics Committee (REC) approval has been granted for this study by Yorkshire and the Humber, Leeds West Research Ethics Committee (18/YH/0371) and due to the nature of the patients enrolled with septic shock, capacity for informed consent is likely to be lacking. Therefore, a personal consultee (friend or relative) will be consulted or a nominated consultee (clinician) in their absence. After capacity is regained, consent will then be sought from the patient in accordance with the Mental Capacity Act, UK (2005). This consent process has been approved following REC review. Results will be published in a relevant peer-reviewed journal and presented at academic meetings.

Gold nanoparticles (AuNPs) have been commonly used in molecular sensing, in the form of observation of the color change from red to blue of the AuNP solution, caused by target-molecule-induced AuNP aggregation. In this work, the changes in absorbance and scattering spectra caused by AuNP aggregation were studied using thrombin-induced AuNP aggregation as a model. We demonstrated for the first time that scattering spectra is more sensitive to the changes owing to AuNP aggregation than absorbance spectra. Moreover, a digital color analysis of darkfield images using dark field microscopy (DFM) facilitated a simple method for detection of AuNPs aggregation without the use of spectroscopic analysis. Furthermore, we demonstrated that DFM is useful for detecting AuNPs aggregation in a colored solution, in which the color change by AuNPs aggregation is not visible.

Photothermal therapy (PTT) takes advantage of unique properties of gold nanoparticles (AuNPs) (nanospheres, nanoshells (AuNSs), nanorods (AuNRs)) to destroy cancer cells or tumor tissues. This is made possible thanks principally to both to the so-called near-infrared biological transparency window, characterized by wavelengths falling in the range 700⁻1100 nm, where light has its maximum depth of penetration in tissue, and to the efficiency of cellular uptake mechanisms of AuNPs. Consequently, the possible identification of intracellular AuNPs plays a key role for estimating the effectiveness of PTT treatments. Here, we review the recognized detection techniques of such intracellular probes with a special emphasis to the exploitation of near-infrared biological transparency window.

We use near-infrared dark-field optical microscopy to probe isothermal time variation of the volume fraction of naturally-occurring, subsurface microstructures in PG 64-22 asphalt binders at temperature T=30∘C, following a rapid heating (cooling) increment |ΔT|=20∘C from initial temperature T0=10∘C(50∘C). We compare these microstructure variations with isothermal time variations of the magnitude |G30∗(t)| of the bulk complex shear modulus measured for identical sample conditions with a Dynamic Shear Rheometer. The main findings are: (1) Microstructure volume fraction (inferred from intensity I(t) of near-infrared optical scatter) and |G∗(t)| both continue to change appreciably long after measurable changes of binder temperature cease. Moreover, delayed time variations in I(t) and |G∗(t)| (2) correlate closely with each other; (3) evolve on three distinct time scales - several minutes, ∼1 h, >1 day; (4) depend on binder aging; (5) are more pronounced after a cooling step (ΔT=-20∘C) than after a heating step (ΔT=+20∘C); and (6) account for hysteresis in I(t) and |G∗(t)| curves observed during heating-cooling cycles.

This paper reported a new method to observe the catalytic progress of the natural horseradish peroxidase (HRP) in-situ on single gold nanoparticles (GNPs) by the combination of dark field imaging and plasmonic resonance scattering spectra. The produced single HRP-GNP exhibited localized catalytic property toward H2O2-Diaminobenzidine (DAB), which could be used to detect the concentration of H2O2 in micro/nanospace. The linear range for H2O2 sensing was from 0.01 μM to 5 μM with a detection limit of 10 nM. The new design strategy could be applied for a broader bioanalysis situation by substituting the HRP with other specified biocatalyst.