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Accurate depiction of waves in temporal and spatial is essential to the investigation of interactions between physical objects and waves. Digital holography (DH) can perform quantitative analysis of wave–matter interactions. Full detector-bandwidth reconstruction can be realized based on in-line DH. But the overlapping of twin images strongly prevents quantitative analysis. For off-axis DH, the object wave and the detector bandwidth need to satisfy certain conditions to perform reconstruction accurately. Here, we present a reliable approach involving a coupled configuration for combining two in-line holograms and one off-axis hologram, using a rapidly converging iterative procedure based on two-plane coupled phase retrieval (TwPCPR) method. It realizes a fast-convergence holographic calculation method. High-resolution and full-field reconstruction by exploiting the full bandwidth are demonstrated for complex-amplitude reconstruction. Off-axis optimization phase provides an effective initial guess to avoid stagnation and minimize the required measurements of multi-plane phase retrieval. The proposed strategy works well for more extended samples without any prior assumptions of the objects including support, non-negative, sparse constraints, etc. It helps to enhance and empower applications in wavefront sensing, computational microscopy and biological tissue analysis.

Quantitative phase imaging has gained popularity in bioimaging because it can avoid the need for cell staining, which, in some cases, is difficult or impossible. However, as a result, quantitative phase imaging does not provide the labelling of various specific intracellular structures. Here we show a novel computational segmentation method based on statistical inference that makes it possible for quantitative phase imaging techniques to identify the cell nucleus. We demonstrate the approach with refractive index tomograms of stain-free cells reconstructed using tomographic phase microscopy in the flow cytometry mode. In particular, by means of numerical simulations and two cancer cell lines, we demonstrate that the nucleus can be accurately distinguished within the stain-free tomograms. We show that our experimental results are consistent with confocal fluorescence microscopy data and microfluidic cyto-fluorimeter outputs. This is a remarkable step towards directly extracting specific three-dimensional intracellular structures from the phase contrast data in a typical flow cytometry configuration.The accurate identification of the three-dimensional quantitative shape of a cell nucleus is now possible without fluorescent staining by applying computational segmentation to refractive index tomograms recorded in the flow cytometry mode.

Digital holography (DH) has emerged as one of the most effective coherent imaging technologies. The technological developments of digital sensors and optical elements have made DH the primary approach in several research fields, from quantitative phase imaging to optical metrology and 3D display technologies, to name a few. Like many other digital imaging techniques, DH must cope with the issue of speckle artifacts, due to the coherent nature of the required light sources. Despite the complexity of the recently proposed de-speckling methods, many have not yet attained the required level of effectiveness. That is, a universal denoising strategy for completely suppressing holographic noise has not yet been established. Thus the removal of speckle noise from holographic images represents a bottleneck for the entire optics and photonics scientific community. This review article provides a broad discussion about the noise issue in DH, with the aim of covering the best-performing noise reduction approaches that have been proposed so far. Quantitative comparisons among these approaches will be presented.

Digital holography is a technique that provides a non-invasive, label-free, quantitative, and high-resolution imaging employable in biological and science of matter fields, but not only. In the last decade, digital holography (DH) has undergone very significant signs of progress that made it one of the most powerful metrology tools. However, one of the most important issues to be afforded and solved for obtaining quantitative phase information about the analyzed specimen is related to phase aberrations. Sources of aberrations can be diverse, and several strategies have been developed and tested to make DH a reliable optical system with submicron resolution. This paper reviews the most effective and robust methods to remove or compensate phase aberrations in retrieved quantitative phase imaging by DH. Different strategies are presented and discussed in detail on how to remove or compensate for such disturbing aberrations. Among the various methods improvements in the optical setups are considered the numerical algorithms, the hybrid methods, and the very recent Artificial Intelligence (AI) approaches to compensate for all aberrations which affect the setups to improve the imaging quality and the accuracy of the reconstruction images’ procedures.

Background Environmental factors have been associated with the outbreak of chronic kidney disease (CKD). We evaluated the association of Cadmium (Cd) exposure with the risk of CKD in U.S. adults who participated in the 1999-2006 National Health and Nutrition Examination Surveys (NHANES). Methods 5426 subjects ≥ 20 years were stratified for values of urinary and blood Cd and a multivariate logistic regression was performed to test the association between blood and urinary Cd, CKD and albuminuria (ALB) after adjustment for age, gender, race/ethnicity, body mass index and smoking habits. Results Subjects with urinary Cd > 1 mcg/g and subjects with blood Cd > 1 mcg/L showed a higher association with ALB (OR 1.63, 95% CI 1.23, 2.16; P = 0.001). Subjects with blood Cd > 1 mcg/L showed a higher association with both CKD (OR 1.48, 95% CI 1.01, 2.17; P = 0.046) and ALB (OR 1.41, 95% CI 1.10, 1.82; P = 0.007). An interaction effect on ALB was found for high levels of urinary and blood Cd ( P = 0.014). Conclusions Moderately high levels of urinary and blood Cd are associated with a higher proportion of CKD and ALB in the United States population.

Using a single biological element as a photonic component with well-defined features has become a new intriguing paradigm in biophotonics. Here we show that endogenous lipid droplets in the mature adipose cells can behave as fully biocompatible microlenses to strengthen the ability of microscopic imaging as well as detecting intra- and extracellular signals. By the assistance of biolenses made of the lipid droplets, enhanced fluorescence imaging of cytoskeleton, lysosomes, and adenoviruses has been achieved. At the same time, we demonstrated that the required excitation power can be reduced by up to 73%. The lipidic microlenses are finely manipulated by optical tweezers in order to address targets and perform their real-time imaging inside the cells. An efficient detecting of fluorescence signal of cancer cells in extracellular fluid was accomplished due to the focusing effect of incident light by the lipid droplets. The lipid droplets acting as endogenous intracellular microlenses open the intriguing route for a multifunctional biocompatible optics tool for biosensing, endoscopic imaging, and single-cell diagnosis.

In this paper we present the design for a smart-mask to mitigate the impact of an airborne virus such as COVID-19. The design utilises recent results from feedback control theory over a distributed ledger that have been developed to enforce compliance in a pseudo-anonymous manner. The design is based on the use of the IOTA distributed ledger. A hardware-in-the-loop simulation based on indoor positioning, paired with Monte-Carlo simulations, is developed to demonstrate the efficacy of the designed prototype.

Monkeypox (MPX) has been regarded as a neglected tropic disease of Western and Central Africa since the early 70s. However, during May 2022, an unprecedent outbreak of MPX has involved most of European Countries, as well as North and South America. While the actual extent of this outbreak is being assessed by health authorities, we performed a pilot study on specific knowledge, attitudes, and practices (KAP) in a sample of Italian medical professionals (24–30 May 2022; 10,293 potential recipients), focusing on Occupational Physicians (OP), Public Health Professionals (PH), and General Practitioners (GP), i.e., medical professionals more likely involved in the early management of incident cases. More specifically, we inquired into their attitude on the use of variola vaccine in order to prevent MPX infection. From a total of 566 questionnaire (response rate of 5.5%), 163 participants were included in the final analyses. Knowledge status was quite unsatisfying, with substantial knowledge gaps on all aspect of MPX. In turn, analysis of risk perception suggested a substantial overlooking of MPX as a pathogen, particularly when compared to SARS-CoV-2, TB, HIV, and HBV. Overall, 58.6% of respondents were somehow favorable to implement variola vaccination in order to prevent MPX, and the main effectors of this attitude were identified in having been previously vaccinated against seasonal influenza (adjusted Odds Ratio [aOR] 6.443, 95% Confidence Interval [95%CI] 1.798–23.093), and being favorable to receive variola vaccine (aOR 21.416; 95%CI 7.290–62.914). In summary, the significant extent of knowledge gaps and the erratic risk perception, associated collectively stress the importance of appropriate information campaigns among first-line medical professionals.

High-throughput single-cell analysis is a challenging task. Label-free tomographic phase microscopy is an excellent candidate to perform this task. However, in-line tomography is very difficult to implement in practice because it requires a complex set-up for rotating the sample and examining the cell along several directions. We demonstrate that by exploiting the random rolling of cells while they are flowing along a microfluidic channel, it is possible to obtain in-line phase-contrast tomography, if smart strategies for wavefront analysis are adopted. In fact, surprisingly, a priori knowledge of the three-dimensional position and orientation of rotating cells is no longer needed because this information can be completely retrieved through digital holography wavefront numerical analysis. This approach makes continuous-flow cytotomography suitable for practical operation in real-world, single-cell analysis and with a substantial simplification of the optical system; that is, no mechanical scanning or multi-direction probing is required. A demonstration is given for two completely different classes of biosamples: red blood cells and diatom algae. An accurate characterization of both types of cells is reported, despite their very different nature and material content, thus showing that the proposed method can be extended by adopting two alternate strategies of wavefront analysis to many classes of cells. Tomographic microscopy: high-throughput, single-cell analysis Combining digital holographic analysis with numerical wavefront analysis enables the structures of different classes of cells to be imaged in detail. Tomographic phase microscopy is promising for high-throughput, single-cell analysis, but it is difficult to implement as it requires a complex setup for rotating samples. Now, Pietro Ferraro and co-workers in Italy have performed tomographic phase microscopy of red blood cells and diatoms by exploiting their random rolling motion as they flow along a microfluidic channel. Their technique can reconstruct complete three-dimensional images of cell structures from a series of holograms obtained without scanning the laser beam. The scheme can identify morphological abnormalities due to anemia and other medical conditions in red blood cells as well as capture the complex shapes of diatoms. It can also determine important cell biomarkers.

COVID-19 abatement strategies have risks and uncertainties which could lead to repeating waves of infection. We show—as proof of concept grounded on rigorous mathematical evidence—that periodic, high-frequency alternation of into, and out-of, lockdown effectively mitigates second-wave effects, while allowing continued, albeit reduced, economic activity. Periodicity confers (i) predictability, which is essential for economic sustainability, and (ii) robustness, since lockdown periods are not activated by uncertain measurements over short time scales. In turn—while not eliminating the virus—this fast switching policy is sustainable over time, and it mitigates the infection until a vaccine or treatment becomes available, while alleviating the social costs associated with long lockdowns. Typically, the policy might be in the form of 1-day of work followed by 6-days of lockdown every week (or perhaps 2 days working, 5 days off) and it can be modified at a slow-rate based on measurements filtered over longer time scales. Our results highlight the potential efficacy of high frequency switching interventions in post lockdown mitigation. All code is available on Github at https://github.com/V4p1d/FPSP_Covid19 . A software tool has also been developed so that interested parties can explore the proof-of-concept system.