Label-free, high-throughput holographic imaging to evaluate mammalian gametes and embryos.

Assisted reproduction is one of the significant tools to treat human infertility. Morphological assessment is the primary method to determine sperm and embryo viability during IVF cycles. It has the advantage of being a quick, convenient, and inexpensive means of assessment. However, visual observation is of limited predictive value for early embryo morphology. It has led many to search for other imaging tools to assess the reproductive potential of a given embryo. The limitations of visual assessment apply to both humans and animals. One recent innovation in ART imaging is interferometric phase microscopy (IPM), also known as holographic microscopy. IPM/QPI is the next likely progression of analytical microscopes for the assisted reproduction laboratory. The IPM system analyzes waves produced by the light as it passes through the specimen observed. The microscope collects the light waves produced and uses the algorithm to create a hologram of the specimen. Recently, IPM has been combined with quantitative phase imaging (QPI), which joins phase contrast microscopy with holographic microscopy. These microscopes collect light waves produced and use the algorithm to create a hologram of the specimen. Unlike other systems, IPM can provide a quantitative digital image, and it can make 2-D and 3-D images of the samples. This review summarizes some newer and more promising QPI microscopy systems for evaluating gametes and embryos. Studies clearly show that QPI is superior to bright field microscopy-based evaluation methods when evaluating sperm and oocytes prior to IVF and embryos prior to transfer. However, further assessment of these systems for efficacy, reproducibility, cost-effectiveness, and embryo/gamete safety must take place before they are widely adopted.

Neuronal innervation regulates the secretion of neurotrophic myokines and exosomes from skeletal muscle.

Myokines and exosomes, originating from skeletal muscle, are shown to play a significant role in maintaining brain homeostasis. While exercise has been reported to promote muscle secretion, little is known about the effects of neuronal innervation and activity on the yield and molecular composition of biologically active molecules from muscle. As neuromuscular diseases and disabilities associated with denervation impact muscle metabolism, we hypothesize that neuronal innervation and firing may play a pivotal role in regulating secretion activities of skeletal muscles. We examined this hypothesis using an engineered neuromuscular tissue model consisting of skeletal muscles innervated by motor neurons. The innervated muscles displayed elevated expression of mRNAs encoding neurotrophic myokines, such as interleukin-6, brain-derived neurotrophic factor, and FDNC5, as well as the mRNA of peroxisome-proliferator-activated receptor γ coactivator 1α, a key regulator of muscle metabolism. Upon glutamate stimulation, the innervated muscles secreted higher levels of irisin and exosomes containing more diverse neurotrophic microRNAs than neuron-free muscles. Consequently, biological factors secreted by innervated muscles enhanced branching, axonal transport, and, ultimately, spontaneous network activities of primary hippocampal neurons in vitro. Overall, these results reveal the importance of neuronal innervation in modulating muscle-derived factors that promote neuronal function and suggest that the engineered neuromuscular tissue model holds significant promise as a platform for producing neurotrophic molecules.

Late Complications after Laparoscopic Longitudinal Gastrectomy - Case Report.

INTRODUCTION: Bariatric surgery is now widely regarded as the most effective treatment for morbid obesity. It aims to enhance patients' health by achieving long-lasting weight loss, reducing associated comorbidities, and improving their quality of life. CASE REPORT: The case involves a 51-year-old female patient who underwent sleeve gastrectomy eight years ago to address morbid obesity (Body Mass Index (BMI) = 43). Subsequently, the patient developed gastric obstructive syndrome, leading to diagnostic investigations including repeated upper digestive endoscopies and native computed tomography. These examinations revealed the presence of a hiatal hernia. In 2021, the patient underwent fundoplication type Dor with anterior hemivalve. However, post-surgery, the patient's condition did not improve, with persistent symptoms including regurgitation, heartburn, difficulty ingesting food, sensation of gastric fullness, and epigastralgia. Further exploratory procedures, including upper digestive endoscopy, abdominal computed tomography with contrast substance, and barium transit with contrast substance, led to the diagnosis of mediogastric stenosis postgastrectomy longitudinal, necessitating surgical intervention. This finding prompted a surgical approach involving distal gastric resection and restoration of digestive tract continuity through Hoffmeister-Finsterer gastro-jejunal anastomosis. Following the surgery, the patient's postoperative symptoms showed improvement. DISCUSSION: Several other studies have demonstrated that the incisura angularis is the most common site of obstruction, as was observed in our study. This particular location appears to be more prone to narrowing, likely attributable to its angular shape. The linear staple line in this area can create a locus minoris resistentiae for kinking, as well as increase the risk of true stenosis if stapling is performed too close to the incisura angularis. CONCLUSIONS: Bariatric surgery should not be considered as the initial treatment option. However, in cases where it becomes necessary, postoperative monitoring is essential to prevent complications or address them promptly.

EVATOM: an optical, label-free, machine learning assisted embryo health assessment tool.

The combination of a good quality embryo and proper maternal health factors promise higher chances of a successful in vitro fertilization (IVF) procedure leading to clinical pregnancy and live birth. Of these two factors, selection of a good embryo is a controllable aspect. The current gold standard in clinical practice is visual assessment of an embryo based on its morphological appearance by trained embryologists. More recently, machine learning has been incorporated into embryo selection "packages". Here, we report EVATOM: a machine-learning assisted embryo health assessment tool utilizing an optical quantitative phase imaging technique called artificial confocal microscopy (ACM). We present a label-free nucleus detection method with, to the best of our knowledge, novel quantitative embryo health biomarkers. Two viability assessment models are presented for grading embryos into two classes: healthy/intermediate (H/I) or sick (S) class. The models achieve a weighted F1 score of 1.0 and 0.99 respectively on the in-distribution test set of 72 fixed embryos and a weighted F1 score of 0.9 and 0.95 respectively on the out-of-distribution test dataset of 19 time-instances from 8 live embryos.

Fusobacterium necrophorum intratonsillar abscess as a source of bacteremia in a patient with a history of substance abuse.

A 22-year-old male, with a history of recreational drug use, was admitted with a 24-hour history of sore throat, bilateral otalgia, fever, chills, sweats, and pain in the upper chest. The blood cultures were positive for Fusobacterium necrophorum. A thoracic and neck soft tissue computed tomography (CT) scan revealed an intratonsillar abscess and pulmonary septic emboli. Initial treatment with Piperacillin-tazobactam and Clindamycin was de-escalated after 5 days. The patient made a complete recovery after 22 days of antibiotic treatment.

First report of Candida auris in Romania: clinical and molecular aspects.

The emerging opportunistic fungal pathogen Candida auris raises significant concerns for public health due to its outbreak potential, the associated high mortality, increased resistance to antifungals, challenging identification to species level, since commonly used diagnostic methods can confuse this fungus with other Candida spp. The present outbreak report describes probably some of the first Candida auris cases in Romania, providing clinical and epidemiological data, and also whole genome sequencing data. The cases were identified in three hospitals in Bucharest during the first eight months of 2022.

Machine learning assisted health viability assay for mouse embryos with artificial confocal microscopy (ACM).

The combination of a good quality embryo and proper maternal health factors promise higher chances of a successful in vitro fertilization (IVF) procedure leading to clinical pregnancy and live birth. Of these two factors, selection of a good embryo is a controllable aspect. The current gold standard in clinical practice is visual assessment of an embryo based on its morphological appearance by trained embryologists. More recently, machine learning has been incorporated into embryo selection "packages". Here, we report a machine-learning assisted embryo health assessment tool utilizing a quantitative phase imaging technique called artificial confocal microscopy (ACM). We present a label-free nucleus detection method with novel quantitative embryo health biomarkers. Two viability assessment models are presented for grading embryos into two classes: healthy/intermediate (H/I) or sick (S) class. The models achieve a weighted F1 score of 1.0 and 0.99 respectively on the in-distribution test set of 72 fixed embryos and a weighted F1 score of 0.9 and 0.95 respectively on the out-of-distribution test dataset of 19 time-instances from 8 live embryos.

Influence of Multiplex PCR in the Management of Antibiotic Treatment in Patients with Bacteremia.

The multiplex PCR assay can be a helpful diagnostic tool for patients with bacteremia. Herein, we assessed the impact of a Blood Culture Identification Panel (BCID) on both the diagnosis and treatment of patients with bacteremia. We performed a retrospective study using laboratory and clinical data to evaluate the impact of syndromic testing using a multiplex PCR testing system (BioFire® FilmArray) for the management of patients with bloodstream infections. BCID detected the pathogen in 102 (87.9%) samples out of the 116 positive blood cultures tested. The average time from the blood culture collection to the communication of the molecular test result was 23.93 h (range: 10.67-69.27 h). The main pathogen detected was Klebsiella pneumoniae (17.6%). The antimicrobial therapy was changed in accordance with the BCID results in 28 (40.6%) out of the 69 cases, wherein the treatment could have been theoretically adjusted. This allowed the adjustment of the therapy to be performed 1305.1 h faster than it would have been possible if conventional diagnostic methods had been used; this was the case for only 35.1% of the time gained if treatment was adjusted for all patients with positive BCID. Thus, although molecular tests can make a difference in the management of bloodstream infections, there is room for improvement in the clinical application of BCID results.

Artificial confocal microscopy for deep label-free imaging.

Widefield microscopy of optically thick specimens typically features reduced contrast due to "spatial crosstalk", in which the signal at each point in the field of view is the result of a superposition from neighbouring points that are simultaneously illuminated. In 1955, Marvin Minsky proposed confocal microscopy as a solution to this problem. Today, laser scanning confocal fluorescence microscopy is broadly used due to its high depth resolution and sensitivity, but comes at the price of photobleaching, chemical, and photo-toxicity. Here, we present artificial confocal microscopy (ACM) to achieve confocal-level depth sectioning, sensitivity, and chemical specificity, on unlabeled specimens, nondestructively. We equipped a commercial laser scanning confocal instrument with a quantitative phase imaging module, which provides optical path-length maps of the specimen in the same field of view as the fluorescence channel. Using pairs of phase and fluorescence images, we trained a convolution neural network to translate the former into the latter. The training to infer a new tag is very practical as the input and ground truth data are intrinsically registered, and the data acquisition is automated. The ACM images present significantly stronger depth sectioning than the input (phase) images, enabling us to recover confocal-like tomographic volumes of microspheres, hippocampal neurons in culture, and 3D liver cancer spheroids. By training on nucleus-specific tags, ACM allows for segmenting individual nuclei within dense spheroids for both cell counting and volume measurements. In summary, ACM can provide quantitative, dynamic data, nondestructively from thick samples, while chemical specificity is recovered computationally.

Antibiotics Used for COVID-19 In-Patients from an Infectious Disease Ward.

Background: although the prevalence of bacterial co-infections for COVID-19 patients is very low, most patients receive empirical antimicrobial therapy. Furthermore, broad spectrum antibiotics are preferred to narrow spectrum antibiotics. Methods: in order to estimate the excess of antibiotic prescriptions for patients with COVID-19, and to identify the factors that were correlated with the unjustified antibiotic usage, we conducted an observational (cohort) prospective study in patients hospitalized with COVID-19 at the National Institute for Infectious Diseases "Prof. Dr. Matei Bals", Bucharest, on an infectious disease ward, from November 2021 to January 2022. To evaluate the prevalence of bacterial co-infection in these patients, all positive microbiology results and concomitant suspected or confirmed bacterial co-infections, as documented by the treating doctor, were recorded. The patients were grouped in two categories: patients who received antibiotics and those who did not receive antibiotics, justified or not. Results: from the 205 patients enrolled in the study, 83 (40.4%) received antibiotics prior to being admitted to the hospital. 84 patients (41.0%) received antibiotics during their hospitalization; however, only 32 patients (15.6%) had signs and symptoms suggestive of an infection, 19 (9.3%) presented pulmonary consolidation on the computed tomography (CT) scan, 20 (9.7%) patients had leukocytosis, 29 (14.1%) had an increased procalcitonin level and only 22 (10.7%) patients had positive microbiological tests. It was observed that patients treated with antibiotics were older [70 (54−76) vs. 65 (52.5−71.5), p = 0.023, r = 0.159], had a higher Charlson index [4 (2−5) vs. 2 (1−4), p = 0.007, r = 0.189], had a severe/critical COVID-19 disease more frequently [61 (72.6%) vs. 38 (31.4%), p < 0.001, df = 3, X2 = 39.563] and required more oxygen [3 (0−6) vs. 0 (0−2), p < 0.001, r = 0.328]. Conclusion: empirical antibiotic treatment recommendation should be reserved for COVID-19 patients that also had other clinical or paraclinical changes, which suggest a bacterial infection. Further research is needed to better identify patients with bacterial co-infection that should receive antibiotic treatment.

Interferometric imaging with ring-shaped apertures.

We use a scattering model for image formation to demonstrate how to simulate images formed by ring-shaped illumination. The description assumes weakly scattering samples, such as phase objects of broad interest in live cell imaging, which also makes no angular approximations and covers forward and backward scattering, single-angle and angle-averaged illumination, as well as monochromatic and broadband light. The numerical experiments reveal the image formation behavior that is consistent with recent experiments reported in the literature, which shows this model can be applied to different imaging systems that are based on ring-shaped illumination with good performance, by considering the incident as a plane wave incident originating at the ring aperture.

Changes in Use of Blood Cultures in a COVID-19-Dedicated Tertiary Hospital.

Blood cultures should be collected within an hour in the setting of sepsis/septic shock. The contamination rate should be below 3%. Worldwide reports have described an increase in blood contamination rates during the COVID-19 pandemic. We performed a retrospective analysis of the blood cultures collected during a 10-month period (March−December 2020) at NIID "Prof. Dr. Matei Balș". The results were compared with data from the pre-pandemic period (March−December 2016) and with the existing data in the literature. During the pandemic, there was a significant decrease in the number of blood cultures collected (1274 blood cultures in 2020 vs. 5399 in 2016). The contamination rate was higher in 2020 (11.7%) compared to 2016 (8.2%), p < 0.001. The rate of infectious episodes in which the etiological agent was identified was constant: 11% in 2020 versus 11.9% in 2016, p = 0.479, but there were fewer invasive bacterial/fungal infections: 0.95/1000 patient days in 2020 vs. 2.39/1000 patient days in 2016, p < 0.001. We observed a change in the species distribution. The Gram-negative isolate's proportion increased from 50.6% to 63.1% and the gram-positive isolate's proportion decreased from 31.8% to 19%. Collection of a low number of blood cultures and a high contamination rate was identified in our clinic. In order to improve the usefulness of blood cultures as a diagnostic method, at least two sets should be collected in aseptic conditions.

White blood cell detection, classification and analysis using phase imaging with computational specificity (PICS).

Treatment of blood smears with Wright's stain is one of the most helpful tools in detecting white blood cell abnormalities. However, to diagnose leukocyte disorders, a clinical pathologist must perform a tedious, manual process of locating and identifying individual cells. Furthermore, the staining procedure requires considerable preparation time and clinical infrastructure, which is incompatible with point-of-care diagnosis. Thus, rapid and automated evaluations of unlabeled blood smears are highly desirable. In this study, we used color spatial light interference microcopy (cSLIM), a highly sensitive quantitative phase imaging (QPI) technique, coupled with deep learning tools, to localize, classify and segment white blood cells (WBCs) in blood smears. The concept of combining QPI label-free data with AI for the purpose of extracting cellular specificity has recently been introduced in the context of fluorescence imaging as phase imaging with computational specificity (PICS). We employed AI models to first translate SLIM images into brightfield micrographs, then ran parallel tasks of locating and labelling cells using EfficientNet, which is an object detection model. Next, WBC binary masks were created using U-net, a convolutional neural network that performs precise segmentation. After training on digitally stained brightfield images of blood smears with WBCs, we achieved a mean average precision of 75% for localizing and classifying neutrophils, eosinophils, lymphocytes, and monocytes, and an average pixel-wise majority-voting F1 score of 80% for determining the cell class from semantic segmentation maps. Therefore, PICS renders and analyzes synthetically stained blood smears rapidly, at a reduced cost of sample preparation, providing quantitative clinical information.

GANscan: continuous scanning microscopy using deep learning deblurring.

Most whole slide imaging (WSI) systems today rely on the "stop-and-stare" approach, where, at each field of view, the scanning stage is brought to a complete stop before the camera snaps a picture. This procedure ensures that each image is free of motion blur, which comes at the expense of long acquisition times. In order to speed up the acquisition process, especially for large scanning areas, such as pathology slides, we developed an acquisition method in which the data is acquired continuously while the stage is moving at high speeds. Using generative adversarial networks (GANs), we demonstrate this ultra-fast imaging approach, referred to as GANscan, which restores sharp images from motion blurred videos. GANscan allows us to complete image acquisitions at 30x the throughput of stop-and-stare systems. This method is implemented on a Zeiss Axio Observer Z1 microscope, requires no specialized hardware, and accomplishes successful reconstructions at stage speeds of up to 5000 µm/s. We validate the proposed method by imaging H&E stained tissue sections. Our method not only retrieves crisp images from fast, continuous scans, but also adjusts for defocusing that occurs during scanning within +/- 5 µm. Using a consumer GPU, the inference runs at <20 ms/ image.

A Real-World Study to Compare the Safety and Efficacy of Paritaprevir/Ombitasvir/Ritonavir and Dasabuvir, with or without Ribavirin, in 587 Patients with Chronic Hepatitis C at the Fundeni Clinical Institute, Bucharest, Romania.

BACKGROUND In the European Union, a tablet with fixed doses of ombitasvir, paritaprevir, and ritonavir combined with dasabuvir is an authorized treatment for patients with chronic hepatitis C virus (HCV) infection. Ribavirin is a broad-spectrum antiviral used in several treatment regimens for patients with HCV infection. This real-world study aimed to compare the safety and efficacy of ombitasvir, paritaprevir, and ritonavir combined with dasabuvir, with or without ribavirin, in 587 patients with chronic hepatitis C attending the Fundeni Clinical Institute, Bucharest, Romania. MATERIAL AND METHODS This is an observational prospective study including 315 patients with F4 degree of fibrosis and compensated cirrhosis, 185 patients with F3 fibrosis, and 83 patients with F2 fibrosis. Liver fibrosis was evaluated by liver biopsy or Fibromax. Efficacy was defined as undetectable HCV-RNA at 12 weeks after the end of treatment. In terms of safety, we monitored the development of adverse reactions, liver cytolysis, cholestasis, and hematologic disorders. RESULTS Of the 587 patients, 2 patients with B-cell lymphoma died during therapy. In total, 3/585 patients (0.51%) did not achieve sustained virologic response. Common adverse effects were nausea and asthenia (especially in patients with other medical treatments; P=0.03 and P=0.04, respectively) and anemia in patients who received ribavirin (P<0.01). None of the patients discontinued antiviral treatment. Patients with kidney transplant or end-stage kidney disease did not receive or discontinued ribavirin. CONCLUSIONS Ombitasvir, paritaprevir, and ritonavir combined with dasabuvir, with or without ribavirin had an efficacy rate of over 99% in HCV genotype 1b infection. We report no serious adverse reactions.

Circadian Volume Changes in Hippocampal Glia Studied by Label-Free Interferometric Imaging.

Complex brain functions, including learning and memory, arise in part from the modulatory role of astrocytes on neuronal circuits. Functionally, the dentate gyrus (DG) exhibits differences in the acquisition of long-term potentiation (LTP) between day and night. We hypothesize that the dynamic nature of astrocyte morphology plays an important role in the functional circuitry of hippocampal learning and memory, specifically in the DG. Standard microscopy techniques, such as differential interference contrast (DIC), present insufficient contrast for detecting changes in astrocyte structure and function and are unable to inform on the intrinsic structure of the sample in a quantitative manner. Recently, gradient light interference microscopy (GLIM) has been developed to upgrade a DIC microscope with quantitative capabilities such as single-cell dry mass and volume characterization. Here, we present a methodology for combining GLIM and electrophysiology to quantify the astrocyte morphological behavior over the day-night cycle. Colocalized measurements of GLIM and fluorescence allowed us to quantify the dry masses and volumes of hundreds of astrocytes. Our results indicate that, on average, there is a 25% cell volume reduction during the nocturnal cycle. Remarkably, this cell volume change takes place at constant dry mass, which suggests that the volume regulation occurs primarily through aqueous medium exchange with the environment.

Cell Cycle Stage Classification Using Phase Imaging with Computational Specificity.

Traditional methods for cell cycle stage classification rely heavily on fluorescence microscopy to monitor nuclear dynamics. These methods inevitably face the typical phototoxicity and photobleaching limitations of fluorescence imaging. Here, we present a cell cycle detection workflow using the principle of phase imaging with computational specificity (PICS). The proposed method uses neural networks to extract cell cycle-dependent features from quantitative phase imaging (QPI) measurements directly. Our results indicate that this approach attains very good accuracy in classifying live cells into G1, S, and G2/M stages, respectively. We also demonstrate that the proposed method can be applied to study single-cell dynamics within the cell cycle as well as cell population distribution across different stages of the cell cycle. We envision that the proposed method can become a nondestructive tool to analyze cell cycle progression in fields ranging from cell biology to biopharma applications.

The Impact of the COVID-19 Pandemic on Colorectal Cancer Patients in a Tertiary Center in Romania. Single Center Retrospective Study.

Background: The novel coronavirus, SARS-COV-2, was first reported in Wuhan, China in the end of 2019. To curb its spread, social distancing measures and new safety regulations were implemented which led to major disruptions in colorectal cancer care. It is however unknown how it influenced the Romanian colorectal cancer care. Methods and Material: We assessed the demographical, clinical, intraoperative and pathological data of our colorectal cancer patients, 302 in total, between 15.03.2019-14.03.2021. The first year's data was considered as the control group and the second one, the study (pandemic) group. Results: We observed a 12% decrease in colorectal cancer hospitalizations in the first year, 38,6% in the first six months. The rate of emergency admissions, colo/ileostomy formatting procedures, palliative resections, clinical metastasis was higher in the pandemic group. More advanced locoregional invasion, a higher tumor stage, higher rate of vascular, perineural invasion, positive resection margin, and a higher lymph node yield was seen after the restrictions were implemented. Conclusion: The COVID-19 pandemic and the response against it had a major effect on the colorectal cancer care in our country. The outcomes of these worse clinical and pathological findings are unknown, but it is important to do further research in this field. We think colorectal cancer care should have an absolute priority in future pandemics.

Live-dead assay on unlabeled cells using phase imaging with computational specificity.

Existing approaches to evaluate cell viability involve cell staining with chemical reagents. However, the step of exogenous staining makes these methods undesirable for rapid, nondestructive, and long-term investigation. Here, we present an instantaneous viability assessment of unlabeled cells using phase imaging with computation specificity. This concept utilizes deep learning techniques to compute viability markers associated with the specimen measured by label-free quantitative phase imaging. Demonstrated on different live cell cultures, the proposed method reports approximately 95% accuracy in identifying live and dead cells. The evolution of the cell dry mass and nucleus area for the labeled and unlabeled populations reveal that the chemical reagents decrease viability. The nondestructive approach presented here may find a broad range of applications, from monitoring the production of biopharmaceuticals to assessing the effectiveness of cancer treatments.

Automatic Colorectal Cancer Screening Using Deep Learning in Spatial Light Interference Microscopy Data.

The surgical pathology workflow currently adopted by clinics uses staining to reveal tissue architecture within thin sections. A trained pathologist then conducts a visual examination of these slices and, since the investigation is based on an empirical assessment, a certain amount of subjectivity is unavoidable. Furthermore, the reliance on external contrast agents such as hematoxylin and eosin (H&E), albeit being well-established methods, makes it difficult to standardize color balance, staining strength, and imaging conditions, hindering automated computational analysis. In response to these challenges, we applied spatial light interference microscopy (SLIM), a label-free method that generates contrast based on intrinsic tissue refractive index signatures. Thus, we reduce human bias and make imaging data comparable across instruments and clinics. We applied a mask R-CNN deep learning algorithm to the SLIM data to achieve an automated colorectal cancer screening procedure, i.e., classifying normal vs. cancerous specimens. Our results, obtained on a tissue microarray consisting of specimens from 132 patients, resulted in 91% accuracy for gland detection, 99.71% accuracy in gland-level classification, and 97% accuracy in core-level classification. A SLIM tissue scanner accompanied by an application-specific deep learning algorithm may become a valuable clinical tool, enabling faster and more accurate assessments by pathologists.