Being able to image the microstructure of growth cartilage is important for understanding the onset and progression of diseases such as osteochondrosis and osteoarthritis, as well as for developing new treatments and implants. Studies of cartilage using conventional optical brightfield microscopy rely heavily on histological staining, where the added chemicals provide tissue-specific colours. Other microscopy contrast mechanisms include polarization, phase- and scattering contrast, enabling non-stained or \'label-free\' imaging that significantly simplifies the sample preparation, thereby also reducing the risk of artefacts. Traditional high-performance microscopes tend to be both bulky and expensive.Computational imagingdenotes a range of techniques where computers with dedicated algorithms are used as an integral part of the image formation process. Computational imaging offers many advantages like 3D measurements, aberration correction and quantitative phase contrast, often combined with comparably cheap and compact hardware. X-ray microscopy is also progressing rapidly, in certain ways trailing the development of optical microscopy. In this study, we first briefly review the structures of growth cartilage and relevant microscopy characterization techniques, with an emphasis on Fourier ptychographic microscopy (FPM) and advanced x-ray microscopies. We next demonstrate with our own results computational imaging through FPM and compare the images with hematoxylin eosin and saffron (HES)-stained histology. Zernike phase contrast, and the nonlinear optical microscopy techniques of second harmonic generation (SHG) and two-photon excitation fluorescence (TPEF) are explored. Furthermore, X-ray attenuation-, phase- and diffraction-contrast computed tomography (CT) images of the very same sample are presented for comparisons. Future perspectives on the links to artificial intelligence, dynamic studies andin vivopossibilities conclude the article.

Fourier ptychographic microscopy (FPM) emerged as a prominent imaging technique in 2013, attracting significant interest due to its remarkable features such as precise phase retrieval, expansive field of view (FOV), and superior resolution. Over the past decade, FPM has become an essential tool in microscopy, with applications in metrology, scientific research, biomedicine, and inspection. This achievement arises from its ability to effectively address the persistent challenge of achieving a trade-off between FOV and resolution in imaging systems. It has a wide range of applications, including label-free imaging, drug screening, and digital pathology. In this comprehensive review, we present a concise overview of the fundamental principles of FPM and compare it with similar imaging techniques. In addition, we present a study on achieving colorization of restored photographs and enhancing the speed of FPM. Subsequently, we showcase several FPM applications utilizing the previously described technologies, with a specific focus on digital pathology, drug screening, and three-dimensional imaging. We thoroughly examine the benefits and challenges associated with integrating deep learning and FPM. To summarize, we express our own viewpoints on the technological progress of FPM and explore prospective avenues for its future developments.

Stroke represents a core area of study in neurosciences and public health due to its global contribution toward mortality and disability. The intricate pathophysiology of stroke, including ischemic and hemorrhagic events, involves the interruption in oxygen and nutrient delivery to the brain. Disruption of these crucial processes in the central nervous system leads to metabolic dysregulation and cell death. Fourier transform infrared (FTIR) spectroscopy can simultaneously measure total protein and lipid content along with a number of key biomarkers within brain tissue that cannot be observed using conventional techniques. FTIR imaging provides the opportunity to visualize this information in tissue which has not been chemically treated prior to analysis, thus retaining the spatial distribution and in situ chemical information. Here we present a review of FTIR imaging methods for investigating the biomarker responses in the post-stroke brain.

Halogenated organic compounds (HOCs), widely present in various environments, are generally formed by natural processes (e.g., photochemical halogenation) and anthropogenic activities (e.g., water disinfection and anthropogenic discharge of HOCs), posing health and environmental risks. Therefore, in-depth knowledge of the molecular composition, transformation, and fate of HOCs is crucial to regulate and reduce their formation. Because of the extremely complex nature of HOCs and their precursors, the molecular composition of HOCs remains largely unknown. The Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) offers the most powerful resolution and mass accuracy for the simultaneous molecular-level characterization of HOCs and their precursors. However, there is still a paucity of reviews regarding the comprehensive characterization of HOCs by FT-ICR MS. Based on the FT-ICR MS, the formation mechanism, sample pretreatment, and analysis methods were summarized for two typical HOCs classes, namely halogenated disinfection byproducts and per- and polyfluoroalkyl substances in this review. Moreover, we have highlighted data analysis methods and some typical applications of HOCs using FT-ICR MS and proposed suggestions for current issues. This review will deepen our understanding of the chemical characterization of HOCs and their formation mechanisms and transformation at the molecular level in aquatic systems, facilitating the application of the state-of-the-art FT-ICR MS in environmental and geochemical research.

The biogeochemical cycling of soil organic matter (SOM) plays a central role in regulating soil health, water quality, carbon storage, and greenhouse gas emissions. Thus, many studies have been conducted to reveal how anthropogenic and climate variables affect carbon sequestration and nutrient cycling. Among the analytical techniques used to better understand the speciation and transformation of SOM, Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) is the only technique that has sufficient mass resolving power to separate and accurately assign elemental compositions to individual SOM molecules. The global increase in the application of FTICR MS to address SOM complexity has highlighted the many challenges and opportunities associated with SOM sample preparation, FTICR MS analysis, and mass spectral interpretation. Here, we provide a critical review of recent strategies for SOM characterization by FTICR MS with emphasis on SOM sample collection, preparation, analysis, and data interpretation. Data processing and visualization methods are presented with suggested workflows that detail the considerations needed for the application of molecular information derived from FTICR MS. Finally, we highlight current research gaps, biases, and future directions needed to improve our understanding of organic matter chemistry and cycling within terrestrial ecosystems.

Intravascular photoacoustics (IV-PA) is an emerging atherosclerosis imaging modality that provides chemical-specific optical information of arterial walls with acoustic depth penetration and resolution. As lipid composition of atherosclerotic plaques is considered to be one of the primary indicators for plaque vulnerability, many IV-PA applications are calibrated so as to target plaque necrotic cores. Based on the mode of optical excitation and the corresponding signal processing technique, IV-PA is categorized into two different modalities. The pulse-based IV-PA has been the universal IV-PA imaging mode with its high peak power and straightforward time-domain signal processing technique. As an alternative, the low power continuous-wave (CW)-based IV-PA has been under intense development as a radar-like frequency-domain signal processing modality. The two state-of-the-art types of IV-PA are reviewed in terms of their physics and imaging capabilities, with major emphasis on frequency-swept CW-based IV-PA that has been recently introduced in the field.

This paper summarizes results from two large lung cancer studies comprising over 700 samples that demonstrate the ability of spectral histopathology (SHP) to distinguish cancerous tissue regions from normal tissue, to differentiate benign lesions from normal tissue and cancerous lesions, and to classify lung cancer types. Furthermore, malignancy-associated changes can be identified in cancer-adjacent normal tissue. The ability to differentiate a multitude of normal cells and tissue types allow SHP to identify tumor margins and immune cell infiltration. Finally, SHP easily distinguishes small cell lung cancer (SCLC) from non-SCLC (NSCLC) and provides a further differentiation of NSCLC into adenocarcinomas and squamous cell carcinomas with an accuracy comparable of classical histopathology combined with immunohistochemistry. Case studies are presented that demonstrates that SHP can resolve interobserver discrepancies in standard histopathology.

The basis and reliability for timely diagnosis of cardiovascular diseases depend on the robust and accurate detection of QRS complexes along with the fiducial points in the electrocardiogram (ECG) signal. Despite, the several QRS detection algorithms reported in the literature, the development of an efficient QRS detector remains a challenge in the clinical environment. Therefore, this article summarizes the performance analysis of various QRS detection techniques depending upon three assessment factors which include robustness to noise, computational load, and sensitivity validated on the benchmark MIT-BIH arrhythmia database. Moreover, the limitations of these algorithms are discussed and compared with the standard signal processing algorithms, followed by the future suggestions to develop a reliable and efficient QRS methodology. Further, the suggested method can be implemented on suitable hardware platforms to develop smart health monitoring systems for continuous and long-term ECG assessment for real-time applications.

Optical coherence tomography provides sections of tissues in a noncontact and noninvasive manner. The device measures the time delay and intensity of the light scattered or reflected from biological tissues, which results in tomographic imaging of their internal structure. This is achieved by scanning tissues at a resolution ranging from 1 to 15 μm. OCT enables real-time in situ imaging of tissues without the need for biopsy, histological procedures, or the use of X-rays, so it can be used in many fields of medicine. Its properties are not only particularly used in ophthalmology, in the diagnosis of all layers of the retina, but also increasingly in cardiology, gastroenterology, pulmonology, oncology, and dermatology. The basic properties of OCT, that is, noninvasiveness and low wattage of the used light, have also been appreciated in analytical technology by conservators, who use it to identify the quality and age of paintings, ceramics, or glass. Recently, the OCT technique of visualization is being tested in different fields of dentistry, which is depicted in the article.

Fourier Shell Correlation, Spectral Signal-to-Noise Ratio, Fourier Neighbour Correlation, and Differential Phase Residual are different measures that have been proposed over time to determine the spatial resolution achieved by a certain 3D reconstruction. Estimates of B-factors to describe the reduction in signal-to-noise ratio with increasing resolution is also a useful parameter. All these concepts are interrelated and different thresholds have been given for each one of them. However, the problem of resolution assessment in 3DEM is still far from settled and preferences are normally adopted in order to choose the \"correct\" threshold. In this paper we review the different concepts, their theoretical foundations and the derivation of their statistical distributions (the basis for establishing sensible thresholds). We provide theoretical justifications for some common practices in the field for which a formal justification was missing. We also analyze the relationship between SSNR and B-factors, the electron dose needed for achieving a given contrast and resolution, the number of images required, etc. Finally, we review the consequences for the number of particles needed to achieve a certain resolution and how to analyze the Signal-to-Noise Ratio for a sequence of imaging operations.